Implementation and evaluation of interactive, browser ...

University of Veterinary Medicine Hannover

Implementation and evaluation of interactive, browser-based graphics in veterinary education

INAUGURAL-DISSERTATION

In fulfillment of the requirements of the degree of

Doctor of Veterinary Medicine

-Doctor medicinae veterinariae-

(Dr. med. vet.)

submitted by Pamela Liebig

Herzberg am Harz

Hannover 2021

II

Scientific supervision: Prof. Dr. rer. nat. Klaus Jung Institute for Animal Breeding and Genetics University of Veterinary Medicine Hannover, Foundation, Hannover Germany 1st supervisor: Prof. Dr. rer. nat. Klaus Jung Institute for Animal Breeding and Genetics University of Veterinary Medicine Hannover, Foundation, Hannover Germany 2nd supervisor: Prof. Dr. rer. nat. Heike Pröhl Institute of Zoology University of Veterinary Medicine Hannover, Foundation, Hannover Germany Day of the oral examination: 17.05.2021 This research was funded by the Ministry for Science and Culture of Lower Saxony, Germany within the digitalization project “DigiStep”.

III

To my partner in crime

IV

Results of this dissertation have been presented in a talk at the IBS-DR-

Workshop

• “Statistik lebendig lehren durch Storytelling und forschungsbasiertes

Lernen“

28.-29.11.2019, Berlin

The following manuscripts have been submitted to journals with peer-review

system:

• Pamela Liebig, Heike Pröhl, Nadine Sudhaus-Jörn, Julia Hankel, Christian

Visscher, Klaus Jung (2021). Interactive, browser-based graphics in

veterinary eduction, submitted for publication.

• Pamela Liebig, Viviane Filor, Marina Scheumann, Martina Buchholz, Klaus

Jung (2021). Teaching Academic Staff to Implement Interactive Graphics for

their Courses, submitted for publication.

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TABLE OF CONTENTS

1. GENERAL INTRODUCTION AND LITERATURE SURVEY ......................... 1

1.1 The role of graphics in education ........................................................... 2

1.1.1 Static versus dynamic graphics ......................................................... 3

1.2. Interactive learning modules in higher education ............................... 4

1.3. Technology adoption in education ..................................................... 5

1.4. Introduction to R and Shiny ............................................................... 8

1.4.1 Relevance of shiny apps in research and education .......................... 8

1.5. Aims of this work .............................................................................. 9

2. MATERIAL AND METHODS ..................................................................... 10

2.1 Implementation of interactive graphics in veterinary education ................ 10

2.1.1 Topic identification ........................................................................... 10

2.1.2 App development ............................................................................ 11

2.1.3 App integration ................................................................................ 13

2.1.4 Evaluation study ............................................................................. 13

2.2. Online workshop for faculty members ............................................... 14

3. SUBMITTED MANUSCRIPTS .................................................................. 15

3.1 Interactive, browser-based graphics in veterinary education ................... 15

Abstract ...................................................................................................... 16

1. Introduction ........................................................................................ 17

2. Methods ............................................................................................. 19

3. Results .............................................................................................. 27

4. Discussion ......................................................................................... 34

5. Conclusion ......................................................................................... 36

6. References ........................................................................................ 38

VI

3.2 Teaching Academic Staff to Implement Interactive Graphics for their Courses

.................................................................................................................. 41

Abstract ................................................................................................... 41

1. Introduction ..................................................................................... 43

2. Methods .......................................................................................... 46

3. Results ........................................................................................... 50

4. Discussion ...................................................................................... 61

5. References ..................................................................................... 64

4. GENERAL DISCUSSION ......................................................................... 68

4.1 Students’ perception .............................................................................. 68

4.1.1 Effect on interest ............................................................................. 68

4.1.2 Perceived usefulness and ease of use ............................................. 69

4.1.3 Effect on information processing ...................................................... 70

4.2 Lecturers’ perception ............................................................................. 71

4.2.1 Opinion towards digital media .......................................................... 71

4.2.2 Perceived ease of use and usefulness ............................................. 72

4.2.3 Workshop effect on teachers ........................................................... 73

4.2.4 Age effect ....................................................................................... 75

4.3 LIMITATIONS ........................................................................................ 75

5. ZUSAMMENFASSUNG ............................................................................ 76

6. SUMMARY .............................................................................................. 79

7. REFERENCES ........................................................................................ 82

8. ACKNOWLEDGEMENTS ......................................................................... 92

9. APPENDIX .............................................................................................. 93

9.1. Students‘ questionnaire (English) .......................................................... 93

9.2. Students’ questionnaire (German) ......................................................... 95

VII

9.3. Lecturers’ questionnaire (English) ......................................................... 97

9.4. Lecturers’ questionnaire (German) ........................................................ 99

9.5 Pre-workshop questionnaire (English) .................................................. 101

9.6 Post-workshop questionnaire (English) ................................................ 105

9.7 Pre-workshop questionnaire (German) ................................................. 107

9.8. Post-workshop questionnaire (German) .............................................. 111

VIII

LIST OF FIGURES

Figures in the general part of this work are labelled continuously, while figures in

the manuscripts are labelled as Figure M x.x.

Figure 1 Screenshot of ui.R from an exemplary shiny app................................ 11

Figure 2: Screenshot from the server.R. .......................................................... 12

Figure 3: Screenshot of the exemplary shiny application to visualize the weight of

different dog breeds according to age in month. .............................................. 12

Figure M1.1:Screenshot of the user panel of the interactive teaching tool for the

animal nutrition. ............................................................................................. 21

Figure M1. 2: Screenshot of the bar plot indicating relevant components in struvite

stone formation after selecting the feed components. ...................................... 22

Figure M1.3: Screenshot of the panel with additional information regarding

background information about the taught contents. .......................................... 23

Figure M1.4: Answer distributions for Likert-Scale questions on the interactive

graphic in the zoology course ......................................................................... 29


graphic in the animal nutrition course. ............................................................. 29


graphic in the food science course. ................................................................. 30

Figure M2.1: Comparison of the influence of the invention of letterpress, the

internet or the occurrence of the COVID19 pandemic on the development of

digital teaching in higher education……….………………………………………… 52

Figure M2.2: Overall high agreement to the statements that interactive graphics

are positive for students (left) and lecturer (right) did little change during the

workshop. ...................................................................................................... 54

Figure M2.3: After the workshop, only participants with prior programming skills

agreed to have the intention to program interactive graphics by themselves ..... 55

Figure M2.4: Sketch from a workshop participant for an interactive graphic in a

pharmacology lecture (left) and implementation as interactive graphics with

checkboxes as regulator elements (right). ....................................................... 58

IX

Figure M2.5: Screenshot of interactive graphic for zoology module. ................. 60

Figure 4: Screenshot from the website, where the interactive graphics which have

been implemented within the framework of this project can be accessed. ......... 73

X

GENERAL INTRODUCTION AND LITERATURE SURVEY

1

1. GENERAL INTRODUCTION AND LITERATURE SURVEY

Graphics, such as line charts, boxplots or histograms are frequently used in higher

education to present complex data to students. The intention of presenting data

as a graphic is to ease access to information and improve data readability (Zentner

et al., 2019). However, graphics are mostly shown as static figures depriving

readers from exploring the underlying data (Perkel, 2018). The potential of

interactive graphics in scientific publishing has already been subject of discussion

amongst researchers (Weissgerber et al., 2016; Ellis & Merdian, 2015; Krumholz,

2015). Interactive graphics allow the reader to examine the data and offer

additional information that cannot be presented in a static figure (Weissgerber et

al, 2016). However, in most literature and scientific journals static graphics are

presented. In return, teachers who use these resources for supplementing their

educational material are either forced to stick with the static nature of those

graphics or invest additional time to make them more accessible. In the past,

knowledge of programming languages such as JAVA, HTML or CSS were

necessary to develop dynamic graphics (Ellis & Meridan, 2015). Usually, these

programming languages are not familiar to members of the academic staff in non-

computer-based sciences and in the medical field. In contrast, R, a programming

language for statistical analysis (Team R.C, 2020), is more frequently used in

academic environments. Interactive visualizations can be customized with basic

R skills using the web application framework Shiny (Chang et al., 2018). The

interactive graphics developed within the shiny environment, are also known as

“shiny apps”. These apps have recently gained relevance in research and have

also been employed for statistic education (Fawcett, 2018; Williams & Williams,

2017; Potter et al., 2016). However, up to this date interactive graphics are rarely

used in veterinary education.


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1.1 The role of graphics in education

In the past hundred years oral and written speech has been the dominant form for

conveying instructional information (Li et al., 2019). Historically, the additional use

of pictures draws back on the pioneering work of Comenius (1658). His “Visible

World in Pictures” (lat. Orbis sensualium pictus) is supposed to be one of the first

textbooks especially designed for educational purpose to include illustrations

(Murphy, 2009). Early research on pictorial illustrations revealed that pictures are

“effective interest-getting devices” (Spaulding, 1955), which can facilitate recall

(Alesandrini, 1984) and promote comprehension (Glenberg & Langston, 1992).

Especially in science education, where most of the concepts and phenomena are

explained through models, visual aids frequently support text material (Herrlinger

et al., 2017). Learning from pictures has been analysed from different theoretical

perspectives (Höffler & Leutner, 2007). The idea that “people learn more deeply

from words and pictures than from words alone” (Mayer, 2005) is the rationale

behind the idea of multimedia learning. Multimedia has become prominent in the

academic environment, since several e-learning modalities are based on

multimedia systems (e.g. Zhan & Zhou, 2003; Alsadhan, et al. 2014). While e-

learning can be referred to as learning through electronic devices (Sangrà et al.,

2012), multimedia is defined as the combination of written or spoken words and

pictures. These pictures can be static, such as diagrams and photos, or dynamic,

such as animations and videos (Mayer, 2005). The theoretical basis for designing

effective multimedia in e-learning is represented within the “cognitive theory of

multimedia learning”. The information transmitted through multimedia enters

through an auditory and a visually channel into the information processing system.

Learning occurs when words and images from the presented material is

transferred from the sensory memory to the working memory, where information

is selected and organized into a coherent verbal and pictorial representation

(Mayer, 2017). Finally, the learner activates prior knowledge from long-term

memory for the learning process to be completed (Sorden, 2012). These three

cognitive processes (selection, organization, and integration) must be considered

when designing a multimedia message. The challenge is not to overload the visual

and auditory channel (Mayer & Moreno, 2003; Mayer, 2017).


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1.1.1 Static versus dynamic graphics

The progression of computer graphic technologies made it possible to produce

accurate graphical representations of almost any target content. With this variety

of graphic possibilities, finding the appropriate type of depiction for each top ic,

audience and purpose can be challenging (Lowe, 2017). There are several

reasons for believing that both static as well as animated pictures can benefit

learning (Höffler & Leuter, 2007). Static instructional graphics, such as diagrams

and flowcharts are frequently used in educational print material (McElvany et al.,

2012) to make content more “comprehensible”, “memorable” and “generalizable”

(Lowe, 2017). However, several teaching contents include important dynamic

aspects. Particularly in the medical field several processes have a dynamic nature.

Examples range from pharmacodynamics, where drug availability is visualized

depending on time and administration route (Rowland, 1972), to physiology, where

dynamic cellular process, such as oxygen binding of haemoglobin are studied.

Here students need to understand how changes take place over time. In the past,

due to limited technical means, dynamic processes could only be addressed with

a series of static graphics depicting successive states of the subject of matter

(Lowe, 2017) or with arrows indicating the movement (Hegarty et al., 2003).

However, the spatial and temporal dimension cannot be fully depicted this way.

Another limitation is the narrow space a static graphic can offer, leading to a

restricted amount of information that can be conveyed. Informational overload can

be the consequence, when all or many aspects are illustrated within one static

graphic. The advent of computer capacities gave rise to further visualization

possibilities. Videos, animations, or interactive models have made it possible to

illustrate dynamic processes which include change over time and/or location. For

veterinary education 3D animations have been used to add dimensionality to

anatomic presentations (Clements et al., 2012, Gao et al., 2020, Scherzer et al.,

2010). Instructional videos can provide additional support for learning clinical skills

(Müller et al., 2019), preparing students for laboratory courses (Al-Khalili &

Coppoc, 2014) and reviewing practical techniques (Hawkins et al., 2003).

Animations and videos can offer certain control over the learning pace through

pause-, play- and repeat-functions, but they rarely provide the opportunity to

interact with the teaching content.


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1.2. Interactive learning modules in higher education

Higher education aims to prepare graduates to meet the expectations of their

future working lifes (Chan, 2016). The need to bridge the gap between formal

academic instruction and job training has led to the search for appropriate

teaching methods (Kim et al., 2002). In traditional classroom settings, students

are often taught in frontal teaching in form of lectures and seminars, frequently

accompanied by wall presentations. One mayor issue of this teaching form is the

rather passive engagement of students as mere receiver of information (Craig &

Amernic, 2006). Today several opportunities to actively engage students in the

learning process exist. In large classroom contexts active learning can be

promoted using student response systems (Chan et al., 2015) These systems

work through remote-like devices and transmit students’ response to the

instructor’s computer. Here students get encouraged to participate in classroom

activities, while their level of understanding is captured (Ghilay, Y., & Ghilay, 2015).

Another way to engage students is through interactive learning materials, which

respond dynamically to the learner’s action. Research supports the argument that

meaningful student-content interaction is a critical factor for learning effectiveness

(Dunlap et al., 2007; Nandi et al., 2015, Murray et al., 2012). As stated by

Muirhead & Juwah (2004), interactivity provides diverse functions in the

educational process. It enables students to acquire “higher order knowledge”,

such as problem solving, critical thinking and decision-making skills. For

veterinary education, these features are especially important. The veterinary

profession requires a problem-oriented approach (Lane, 2008) and individual skills

such as decision making (Hodgson et al., 2013). Several universities have

integrated problem-based and case-based learning (CBL) modalities to address

these needs (e.g. Sawras et al., 2020; Crowther & Bailllie, 2016; Newman, 2005).

In CBL students get presented real or realistic case material (Sawras et al, 2020)

and are required to solve the case based on the presented data. It has been

demonstrated that this teaching approach can promote student’s clinical reasoning

(Petterson, 2006) while providing the possibility to apply clinical knowledge

(Sawras et al., 2020). When reviewing the underlying systems, CBL is developed

using a feature which displays content to the user, based on a set of rules provided

by the instructor (Allenspach et al., 2008). Students experience the outcome of


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their decision-making but cannot directly manipulate the content. According to

Schulmeister’s (2003) taxonomy of multimedia component interactivity,

interactivity can be classified in six levels. Starting with the lowest interactivity

form, where users are provided with “pre-fabricated” multimedia components to

the highest being the construction of these objects by users themselves. When

users get the chance to generate own representations of content, so called

“discovery learning” takes place (Schulmeister, 2003). This learning model allows

students to build their own knowledge by discovering rather than by memorizing

what was said by the teacher (Rahman, 2017).

1.3. Technology adoption in education

With institutions’ growing interest in incorporating e-learning into the course

programs, many administrators have expressed concerns regarding faculty

members’ lacking technology skills (Dysart & Weckerle, 2015). Teachers

themselves have identified and experienced the lacking confidence and

competence as an obstacle for technology integration in class (Hutchison &

Reinkind, 2011; Alenezi, 2017, Windiarti et al., 2019). In the past, several theories

tried to explain technology acceptance and usage based on a generational

construct. Prensky (2001) for example popularized the idea of dividing generations

into “digital natives” and “digital immigrants”. He suggested that digital natives

constitute a new generation of students, which were born and raised with

technologies and therefore demand an education adapted to their technology

affinity. Lecturers on the other hand were labelled as “digita l immigrants”, which

were not fully fluent in the digital language and therefore struggle to teach digital

natives. A similar concept had Tapscott (1989) which introduced the term “net

generation” and Howe and Straus (2000) with their “millennials” concept . Even

though these concepts lack empirical evidence, it still resonates with many

academics (Judd, 2018).

The Technology Acceptance Model (TAM) introduced by Davis (1986) in turn

attempts to explain and predict determinants of behavioural intention to make use

of technology. This model has evolved into the key model for studies regarding

information technology acceptance (Lee et al. 2003) and is still widely used to


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understand technology usage in the educational environment (e.g. Scherer et al.

2019; Salloum et al., 2019; Joo et al. 2018). Davis proposed that two specific

beliefs determine the intention to make use of technology: the perceived

usefulness (PU) and the perceived ease of use (PEU). PEU captures the degree

to which a person believes that using a system will be free of effort, while PU is

the degree to which a person believes that using a system will enhance job

performance (Grover, et al. 2019) or offers a “better value over alternative

methods of carrying out the same tasks” (Liu, et al. 2009). When assessing

teachers’ job performances, teaching effectiveness and teacher-student

interaction are important factors to be considered (Cai & Lin, 2006). A common

method used in research to evaluate teaching effectiveness has been through

student ratings. Mart (2017) concluded that “student evaluations cannot only be

used as a feedback to modify teaching practices but also course content and

structure”. The original TAM was expanded by so called “external variables”, which

influence the beliefs of the person towards a system. Training of the user was

recognized as one of those external variable influencing users’ attitudes towards

technology (Burton-Jones & Hubona, 2006). Gold (2011) summarized the

importance of training teachers in using technology in education as follows: “even

though technology may change the way students learn, it will have no impact

without teacher support, and one of the most important reasons for the lack of

faculty support is lack of faculty preparation. Teachers must be trained in using

this new technology”. More recently, Kalonde & Mousa (2016) investigated factors

that influence teachers’ technology decisions. Lack of familiarity and training was

stated by 43% of the respondents to be an obstacle for using technology in the

classroom. In this context, several professional development programs emerged,

aiming to address this problem (e.g.,Watson, 2006, Carlson & Gadio, 2002).

Historically, the principle aim of professional development (PD) is to change

teacher’s practice (Lee et al., 2017). However, the success of PD programs is

frequently measured in terms of participant’s satisfaction (Lee et al., 2017,

Rienties et al., 2013) rather than on evaluating the impact on teacher ’s practice.

One possible way to capture this impact is by using pre- and post-training

questionnaires. Lau & Yuen (2013) for example used this questionnaire format to

investigate the impact of a technology workshop for mathematics teachers,


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yielding that participants showed higher perceived efficiency using information and

communication technologies (ICT) for teaching and learning than before. Similar

did Harsell et al. (2009) and Watson (2006), who affirmed the positive impact of

technology training on teacher’s technology usage in class using pre-and post-

training questionnaires. Most of these professional development programs are

conducted in face-to-face classes. However, the internet has become an important

medium to offer “flexible”, “cost-effective” and “wide-scale” online professional

development programs for teachers (Powell & Bodur, 2019). More recently, in light

of the constraints imposed by the COVID-19 pandemic, online teaching has

become increasingly relevant not only for students’ education, but also for

teachers’ professional development (Hartshorne et al., 2020). Teachers generally

receive training in using educational technologies, but they do not receive

systematic support in designing interactive online learning content (Hartshorne et

al., 2020). One possible way to customize interactive learning content is through

R and shiny.


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1.4. Introduction to R and Shiny

R is a “system for statistical computation and graphics” (Team R.C, 2020), which

is widely used in academic environments. The large amount of user-contributed,

freely available packages has turned R into an extensible, current, up-to-date

software. Packages are collections of related functions and data, which address a

specific problem (Gentleman, 2008). Researchers of almost all fields use different

R packages for diverse tasks, such as machine learning (Molnar et al., 2018),

meta-analysis (Schwarzer, 2007; Owen et al., 2019), model simulations

(Wojciechowski et al., 2015) and others. The shiny package (Chang et al., 2018)

contributes to the multifunctionality of R, by allowing to create interactive graphics,

which can be displayed in a web-browser. The graphic, for example a histogram,

boxplot, or line chart, can be manipulated by the user through different regulator

elements. Results of these adjustments are displayed in real-time. Several design

options such as different colour layouts, font types and the possibility to add texts

and pictures, turn this tool into a visually appealing way to transmit knowledge

embedded in a livid graphic.

1.4.1 Relevance of shiny apps in research and education

In the last years shiny apps have increasingly been used in research, especially

in bioinformatics (Brink et al., 2018, Ekiz et al., 2020; Badgeley et al., 2019), but

also in the biological field (Abhilash & Sheeba; 2019; Cenek et al., 2020;

Cichewicz, & Hirsh; 2018). Despite of their wide distribution in research, shiny

apps are rarely found in education. Fawcett (2018), Williams & Williams (2017)

and Potter et al. (2016) were one of the few to recognize the educational potential

of these web-tools. Fawcett pointed out, that students “seemed more engaged in

lecture when demonstrated techniques via the apps” (Fawcett, 2018). Even though

the authors of these studies commonly agreed for the shiny apps to be beneficial

for teaching and learning, the usage in education have been mostly limited to

statistic courses. More recently, Hanč, et al. (2020) analysed the perception of

physic schoolteachers regarding R Shiny as a digital teaching tool and found a

“very positive acceptation of R Shiny web apps” amongst teachers.


9

1.5. Aims of this work

Although graphics are frequently used in education to ease access to information,

they usually lack the opportunity to explore underlying concepts. For dynamic

processes where spatial and temporal changes are an essential feature of the

learning content, animated graphics have been employed. While students here

get a certain control over the learning pace, active interaction with the content is

generally not provided. In turn, interactive e-learning modalities respond to

students’ actions and allow them to experience the subsequent effects in real-

time. For veterinary education mostly case-based learning have been employed

to promote interaction. To my knowledge, so far, no attention has been paid to

make the underlying scientific data of graphical representations more accessible

to veterinary students. Within the framework of the “DigiStep” project, this work

aims to provide teachers and students of veterinary education an application tool

for interactive data visualization. Other institutes of our universities participated at

this digitalization project, too. Each with own approaches for promoting digitization

in veterinary education and partially collaborating with each other. So far, an

identification tool for poisonous plants of veterinary interest, instructional videos

for animal dissections, graphical physics simulations and case-based e-learning

modalities have been developed. The results of our contribution to this project are

described in two manuscripts, which were submitted for publication and presented

in chapter three of this work. The aim of the paper “Interactive, browser-based

graphics for veterinary education” was to study for the first time the acceptance

and applicability of interactive graphics in veterinary education. In close

collaboration with the course instructors, interactive graphics for two veterinary

medicine lectures and one seminar were developed and evaluated. The second

paper “Teaching Academic Staff to Implement Interactive Graphics for their

Courses” aimed to gain insight into the acceptance and impact of a two-day online

workshop for teachers. Up to this date, no workshop for teaching faculty members

the implementation of own interactive graphics customized on their teaching

needs in veterinary education have been conducted.

MATERIAL AND METHODS

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2. MATERIAL AND METHODS

This work includes two studies, which were conducted in 2019 and 2020 at the

University for Veterinary Medicine in Hannover. For the first study, interactive

graphics were implemented and evaluated amongst course instructors and

students. In the second study, academic staff were taught basic programming

skills to develop those interactive graphics on their own. In the following the

individual work steps will be explained in more detail.

2.1 Implementation of interactive graphics in veterinary education

The implementation of interactive graphics at our university was achieved in four

steps. (1) Topic identification took place, where lecturers and seminars were

scanned for content to be implemented as interactive graphics. (2) App

development was planned in close collaboration with the lectures. (3) App

integration into the lecture and (4) evaluation through questionnaires was

accomplished.

2.1.1 Topic identification

In the first step veterinary medicine lectures and seminars were scanned for

appropriate topics to be implemented as interactive graphics. Therefore, static

graphics were reviewed for limitations, such as lack of clarity and content

overload. Lectures were also scanned for dynamic and complex contents, which

lack graphical representations. In the next step, interactive graphics addressing

these limitations were programmed and introduced to the lecturers. In close

collaboration with the course instructors, layout, appearance, and functional

possibilities were discussed.


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2.1.2 App development

Shiny apps consist of two components, which communicate with each other: a

user interface (ui.R) and a server script (server.R). The ui.R encodes instructions

for the user interface such as layout and design. Here the input objects (user

regulator elements) and the output object (e.g., table, plot, or text) are defined

(Figure 1). The server.R includes instructions for processing user input and

generates output objects (Figure 2). In the following an explementary R script will

be shown to explain the code structure and the resulting app (Figure 3).

Figure 1 Screenshot of ui.R from an exemplary shiny app. The title is specified within the

titlePanel. The code for the user interface must be within the layout function. The

sidebarLayout function containts a mainPanel and a sidebarPanel. The sidebarPanel

contains user input controls (here selectInput and numericInput). The mainPanel contains

outputs (here a plot).


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Figure 2: Screenshot from the server.R. Here the server’s logic is defined in 4 steps: (1)

Data is loaded with a read-function. Several formats of data such as the commonly used

.csv files are supported. (2) Data is filtered according to user’s input. (3) Underlying

mathematical formulas are applied on the filtered data (here an arbitrary formula for

weight calculation is used). (3) The output object (here a histogram) is generated using

the renderPlot function.

Figure 3: Screenshot of the exemplary shiny application to visualize the weight of

different dog breeds according to age in month. The ui.R generates the sidebar panel on

the left, where different user regulator elements can be displayed. Here users can select

different dog breeds and filter the weight according to age. In addition, on the right side

a main panel for the output is generated. The server.R calculates the distribution of weight

according to user provided input parameters and sends the resulting plot to the main

panel.


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2.1.3 App integration

The lecturers were provided a hyperlink which directs them to the app via web

browser. The apps were uploaded to the university servers, so no additional

software or hardware was necessary. Lecturers can access the apps directly from

any computer and/or incorporate them into their slides. In addition, students can

access them from any computer connected to the university servers.

2.1.4 Evaluation study

The acceptance of interactive graphics was evaluated through questionnaires,

which included multiple choice, open field and 5-point Likert scale questions. A

total number of n=327 students in their first and forth study year as well as n=5

lecturers participated. Students and lecturers completed the questionnaires in

absence of the app developers directly after the session with interactive graphics.

Students were asked to estimate user-friendliness and the impact on their learning

experience. Furthermore, students’ use of digital media for education and their

attitude towards digitalization in higher education were asked (see Appendix 9.1-

9.2). The course instructors were asked to rate the user-friendliness, the perceived

impact on students and their previous use of digital media for teaching (see

Appendix 9.3- 9.4). The questionnaire survey was approved by the data security

office of the University for Veterinary Medicine in Hannover. In both questionnaires

no personal identifiable information, except gender and age, was captured and

the data obtained was stored anonymously.


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2.2. Online workshop for faculty members

Faculty members at our university were invited to participate at a two-day online

workshop through MS Teams. This workshop was structured as follows: In the first

workshop session R and shiny were introduced and interactive data visualization

possibilities were explained. Here interactive graphics implemented at our

university were used as examples to describe the layout, functionalities, and the

basic components of shiny apps. At the end participants received templates for

developing three different graphic types (histogram, pie chart and boxplot). These

templates consisted of ready to use R-scripts with explicatory comments.

Additionally, worksheets with step-by-step guide through the code and voluntary

tasks were provided. These tasks were designed to increase in difficulty and base

on each other. Beginning with simple tasks, such as “change the title of the app”,

participants got the chance to understand the syntax. Afterwards, tasks increased

in difficulty up to the point that participants customized ui elements and server

functions. After the first workshop session, participants were encouraged to

develop own ideas for interactive graphics. Several faculty members provided

hand-written drafts or basic R-scripts. These ideas and related implementation

possibilities were discussed amongst all participants and the course instructors in

the second workshop session. Faculty members were asked to complete an online

questionnaire through google forms prior to the workshop and after completing it

(see Appendix 9.5- 9.8). The questionnaire included 5-point Likert scale and open

field questions for additional comments. In both questionnaires, participants were

asked to evaluate the impact of interactive graphics on teaching and learning.

Furthermore, it was asked whether participants could imagine using interactive

graphics in their courses and programming them on their own. Moreover, the

impact of the workshop on participants’ opinion towards digital media usage in

education was asked. Both questionnaire surveys were approved by the data

security office at the University for Veterinary Medicine in Hannover. Again, no

personal identifiable information was captured, excepting gender and age. The

data obtained was stored anonymously.

SUBMITTED MANUSCRIPTS

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3. SUBMITTED MANUSCRIPTS

Following manuscript was submitted on March 2nd, 2021 in the Journal for

Veterinary Medical Education.

3.1 Interactive, browser-based graphics in veterinary education

Pamela Liebig, Heike Pröhl, Nadine Sudhaus-Jörn, Julia Hankel, Christian

Visscher, Klaus Jung*

Pamela Liebig, Veterinarian, is a doctoral student, Institute for Animal Breeding

and Genetics, University of Veterinary Medicine Hannover, Foundation, Hannover

Germany

Heike Pröhl, Dr. rer. nat., is Associate Professor of Zoology, Institute of Zoology,

University of Veterinary Medicine Hannover, Foundation, Hannover Germany

Nadine Sudhaus-Jörn, DVM, is a postdoctoral researcher, Institute of Food

Quality and Food Safety, University of Veterinary Medicine Hannover, Foundation,

Hannover Germany

Julia Hankel, DVM, is a postdoctoral researcher, Institute of Food Quality and

Food Safety, University of Veterinary Medicine Hannover, Foundation, Hannover

Germany

Christian Visscher, DVM, is Professor of Veterinary Medicine and Director of the

Institute of Food Quality and Food Safety, University of Veterinary Medicine

Hannover, Foundation, Hannover Germany

Klaus Jung, Dr. rer. nat., is Professor of Genomics and Bioinformatics, Institute

for Animal Breeding and Genetics, University of Veterinary Medicine Hannover,

Foundation, Hannover Germany

* Corresponding Author

Prof. Dr. Klaus Jung

University of Veterinary Medicine Hannover, Foundation

Institute for Animal Breeding and Genetics

Bünteweg 17p

30559 Hannover

E-Mail: [email protected]

mailto:[email protected]


16

Abstract

The research described here aims to discover how veterinary medicine students

and their lecturers respond to and accept interactive graphics as new digital

teaching tool. In the last decades, technology advances have led to growing usage

of digital teaching media in veterinary education. Interactive graphics, which allow

to dynamically change data and related graphics, however, have rarely been

considered as teaching tool in veterinary education so far. For evaluating such

interactive teaching tools, study contents from three different courses were

implemented as interactive graphics. Therefore, the Shiny environment, a web-

based application framework for the statistic software R was used. In total n=327

students and n=5 lecturers participated in the evaluations study. The

questionnaires revealed an overall high acceptance amongst veterinary medicine

students and lecturers. In total, 71% of the students affirmed that interactive

graphics led to an increased interest for the presented study contents and 76%

expressed the wish to discuss more topics with interactive graphics. All teachers

involved also perceived to have reached more students through teaching with

interactive graphics. Furthermore, most lecturers agreed that the experience of

teaching with interactive graphics had a positive influence on their opinion towards

digital media teaching.

Keywords

interactive graphics, dynamic visualization, R-Shiny, Veterinary education, Web-

based learning


17

1. Introduction

The advances of computational capacities and graphic design technologies have

made it possible to produce animated visualizations of dynamic processes1. Within

the educational context, computer visualizations are increasingly being used as

part of learning material to depict scientific phenomena which include change over

time. Especially in multimedia learning environments, computer visualizations are

becoming prevalent2. Computer-assisted learning has paved the way for

transforming education at universities and has become an important part in

medical education3. The growing integration of web-based applications into

academic environments has converted the internet into an important educational

instrument4. In consequence, universities worldwide have extensively

incorporated e-learning into their curriculum5, offering students time and place

flexibility6. In veterinary education e-learning has also become an integral part of

the curriculum7. This includes lecture recordings and instructional videos as part

of blended learning environments8, where face-to-face teaching is combined with

technology-based modalities. Furthermore, case-based e-learning systems9,

simulations10 and virtual reality tools11 can help veterinary students to overcome

the gap between theorical knowledge and clinical applications. Access and use of

such learning modalities are usually restricted to the own faculty. However, there

has been a growing trend in sharing learning resources as open educational

resources.12

At our university, most study contents are taught in form of frontal teaching using

wall-projected presentations. Although multimedia elements such as videos or

audio material can be included into the presentation, the individual slides usually

remain static. Digital teaching material such as video lectures, a heart sound

library and virtual microscope can provide the opportunity to deepen and

complement the knowledge acquired in the lecture. However, most of those

materials are not modifiable and therefore rarely encourage students to question

or reason the shown information. In contrast, interactive graphics can be

manipulated in several ways and encourage students to actively participate in the

learning process. This is of particular interest, since it is well known that active

inclusion of students is important for learning motivation and long-term retention

of information.13


18

Academic staff has already recognized the potential of this interactive applications

as teaching resource. Since several years, the shiny package, a web-based

framework for the statistics software R, allows to integrate interactive graphics in

a website.14 In veterinary medicine data from experiments and observations are

often displayed as graphs that are used as teaching material for students. These

graphs often have complex underlining formulars and models. Interactive

regulators such as sliders, click boxes or select lists can be used to change

parameters. These changes are displayed in real time and can give the user a

better understanding of how a specific parameter is affecting the outcome. This

interactivity can invite students to explore complex data and dynamic processes.

Fawcett introduced interactive shiny apps to incorporate research-informed

learning and teaching into statistic courses, concluding that the method benefited

the students in terms of their confidence in their understanding.15 In a similar

direction, Williams and Williams and Potter et al. used R shiny apps to enhance

learning experience of statistic students. 16,17 Previously such interactive dynamics

visualisations were done with other programming languages such as HTML or

Flash. These languages are unfortunately not widespread among academic staff

in veterinary medicine. In contrast, R is widely used in science to do a variety of

analysis and thus is much more common among academic staff. With basic R

skills, shiny apps can be customized to specific topics. Due to the web-based

framework these apps can be displayed independently of hardware and software,

which makes them easy to integrate in lectures. However, shiny apps are rarely

used in the context of veterinary education so far. As part of the digitalization

strategy of the State Lower Saxony (Germany) we implemented several teaching

contents from the curriculum of veterinarians as interactive graphics. The aim of

the article is to evaluate the acceptance of interactive graphics amongst veterinary

medicine students and lecturers through a case-study. Three interactive graphics

were implemented into different veterinary medicine lectures. The functionalities

and didactic aims of these graphics as well as the evaluation study design will be

described in the following.


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2. Methods

2.1 Local Setting

The University for Veterinary Medicine in Hannover is one of five institutions of

higher education for veterinary science in Germany. The education consists of a

scientific-theoretical component and a practical component. The teaching and

examination of the scientific-theoretical part is divided into three stages: first and

second preclinical examination, including basic natural science such as physics,

zoology, chemistry. The last stage, the veterinary state examination, consists of

subjects like food science, animal nutrition and pathology. These subjects are

taught in form of compulsory lectures, seminars, laboratory courses and others.

For this study we chose one course from the pre-clinical examination and two

courses from the veterinary state examination taught in form of lectures and

seminars to integrate interactive graphics into the veterinary education of our

university. The first module was integrated in the zoology lecture; the latter two

modules were animal nutrition and food science. We describe the implementation

methods as well as the individual contents of each module in the following. The

three modules were primarily designed to support the lecturer during the course,

but they can also be used by the students for learning after the course within a

web-browser.

2.2. Shiny environment for implementation of interactive graphics

We implemented the interactive graphics using the Shiny environment (Version

1.4.0) (Beeley, 2016) based on the statistic software R (R Core Team, 2019). This

environment converts R scripts into user-friendly, visually appealing Shiny

Applications, which allow to display interactive graphics in the web browser.

Regulator elements can be used to change the data basis behind the graphic.

Besides interactive graphics, interactive tables can be integrated, too.


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2.3. Implemented modules for selected courses

2.3.1 Zoology module: The effect of the pH on the Haemoglobin oxygen

affinity curve

The implemented graphic for this module provides the lecturer an environment to

explain the pH effect on the oxygen affinity of blood haemoglobin step by step

(Supplementary Figure 1). When invoking the interactive graphic, the oxygen-

haemoglobin dissociation curve is displayed for a physiological pH environment.

The lecturer can now choose whether to acidify or alkalize the environment, which

in return leads to changes in the dissociation curve. These changes in

haemoglobin oxygen affinity can now be discussed with the students. For further

interactive teaching, different explanations that clarify the shift of oxygen affinity

are implemented. Thus, the lecturer can first discuss possible answers with the

students and then select the answers from a selection list. Furthermore, users

may obtain additional information about oxygen carriers by clicking on a second

tab located on the top of the application.

2.3.2. Animal nutrition: A tool to design a diet for bladder stone prophylaxis

This web tool allows users to design a specific diet for bladder stone prophylaxis

in dogs. The aim of this interactive graphic is to impart students the influence of

the chemical and mineral composition specific to certain feed materials on the

urine pH level and struvite stone formation. Users of this tool choose out of a

selection of feed materials and one complementary feed as well. They decide

which ingredients to add and the amount in percentage of those components

within the ration. At first, users select a main component, which will be the primary

ingredient in the diet. This main component covers 100 per cent of the dog´s daily

energy requirement. Afterwards, users can decide how many percent of other

ingredients to add to the diet, by activating the sliders (Figure M1.1).


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Figure M1.1:Screenshot of the user panel of the interactive teaching tool for the animal

nutrition. The lecturer can use numeric input, selection list and sliders to demonstrate

the effect of a created diet for dogs on mineral supply. A German version was used in the

evaluation study


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A bar plot immediately displays the chosen components that are essential for a

struvite stone formation. As the formation and dissolution of struvite stones in the

urinary bladder depends on the urine pH, which in turn depends on the cation-

anion balance, the urine pH is estimated and displayed based on the food

composition at hand. Different coloured lines and rectangles, as depicted in

Figure M1.2, indicate whether the maintenances requirements of a dog referred

to its bodyweight and the recommended mineral supply for struvite stone

prophylaxis in the bladder are reached. A second tab located at the top of the

application allows access to additional information (see Figure M 1.3). These

panels provide the student with background information and explanations on how

to read the plot.

Figure M1. 2: Screenshot of the bar plot indicating relevant components in struvite stone

formation after selecting the feed components. Additionally, a table displays the amount

of feed components, the energy content and the estimated urine pH level.


23

Figure M1.3: Screenshot of the panel with additional information regarding background

information about the taught contents. This panel can be accessed by clicking on the

information icon.

2.3.3. Food Science: Thermal destruction of microorganisms in food cans

The interactive graphic for the course food science was designed to simulate a

practical scenario. The lecturer presents a case of an inadequate heating

treatment of a food-can. In cooperation with the lecturer, students can modify the

heating curve by selecting the maximal core temperature and heating duration.

Instantly, the F-value, a sterilization value for food cans (Ohlsson, 1980), is

calculated and displayed beside the heating curve. Afterwards, students have four

possible answers to determine the degree of durability for their theoretical cans.

The durability depends on the F-value the students achieved with their different

temperature and heating duration combinations.


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2.4 Access to interactive graphics

The raw files of all presented interactive graphics are freely available from the

Github repository https://github.com/klausjung-hannover for any person interested

in trying them out. A ReadMe file added to the repository adds information about

the functionalities of the web applications, as well as instructions on how to install

necessary R-packages and to run the R-Scripts. At our own university, the

interactive graphics are hosted within the university server, and students and

lecturers can easily access the web-application via a web browser at a faculty

computer. We are working currently with our IT department to install a virtual

machine so that ready-to-use interactive graphics are online accessible to

everyone. We comment this current limitation in the discussion section.

2.5 Evaluation Study

A paper-based questionnaire was distributed to veterinary students that attended

the three above-described courses in the winter term 2019/2020. The participation

in this study was voluntary and no personally identifiable information except for

gender and age was captured. The data security office of the University of

Veterinary Medicine Hannover approved the evaluation study, and all data were

stored anonymously. The lecturers informed the students about the evaluation

before the lectures and students completed the questionnaires afterwards. In total,

n=327 students returned filled questionnaires. In the zoology course n=89

students participated, all in their first study year. In the animal nutrition and the

food technology course n=215 and n=23 students, respectively, returned the

questionnaires. In addition, n=5 lecturers filled out questionnaires on their

experience while teaching with the interactive tools. Four of these lecturers are

co-authors here (HP, CV, JH and NSJ), however, they were not involved in the

data analysis, which was done by PL and KJ, only. Students and lecturers’

questionnaires are available in the Supplementary Material. In the courses

German version were used but were translated into English here. Their contents

will be described in the following.

https://github.com/klausjung-hannover


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2.5.1. Students’ questionnaire

The student’s questionnaire included two demographic questions (gender and

age) and nine questions regarding categorised into the subtopics:

• B) Interactive graphics in teaching and it´s handling

• C) Effects of the interactive graphic on the learning experience

• D) Digital media usage

Students were asked to rate on an ordinal scale from 1 (strongly disagree) to 5

(strongly agree) following statements:

• B1: I can imagine that the majority of students will handle easily interactive

graphics.

• B2: I´d wish to have more interactive graphics in veterinary school.

• B3: I can image using this tool because it ́s intuitive.

• C4: I was previously familiar with the taught content.

• C5: I understood the teaching contents taught by the interactive graphic.

• C6: The interactivity of the graphic had a positive impact on my interest

about the taught content.

• C7: The interactive graphic had no benefit to the course.

• D9: Digitalization is a chance to improve academic education.

Additionally, students were asked to provide information if and which other digital

media they have been using for learning so far.


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2.5.2 Lecturers questionnaire

We also asked participating lecturers to complete a questionnaire after teaching

with interactive graphics. The questionnaire had a similar design to the student’s

questionnaire. Professors were asked to rate on an ordinal scale from 1 (strongly

disagree) to 5 (strongly agree) the following statements:

• A1: I felt secure handling this teaching tool

• A2: I can imagine that the majority of lecturers will handle easily this teaching

tool

• A3: I wish to have more interactive graphics in my classes

• B4: In my opinion the interactive graphic provided no benefit to the course

• B5: I feel like I could have reached more students by teaching with an

interactive graphic

• C6: I have used digital teaching tools (e.g. CASUS, online lecture etc.) in my

class before

• C8: Digitalization is a chance to improve academic education.

Furthermore, professors were asked (yes/no question) if the usage of interactive

graphic had a positive effect on their opinion towards digital media usage in

academic education. An additional open comment field allowed lecturers to

express improvement wishes, comments or future design ideas.


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2.6. Data Analysis

Answer distributions of all questions were analysed graphically and descriptively,

separately for each course and separated by gender and age. Effects of age and

gender were assessed using the Mann-Whitney U test and the Kendall’s

correlation test, respectively. Correlations between the general usage of digital

learning media (on a nominal scale) and several questions (with ordinal scale of

answers) in the questionnaire were also studied using the Mann-Whitney U test.

The significance level was fixed at alpha=5%, in the case of multiple testing the

method of Bonferroni-Holm was used to adjust p-values. All analyses were

performed using the statistic software R.

3. Results

3.1. Student’s response

In general, we observed similar answer distribution in all three describes courses

(Figures M1.4- M1.6). Absolute and relative frequencies for each answer are

presented in the Supplementary Table S.T1 – S.T3.

3.1.1. Demographic results

In the zoology module, 72/89 (80.9%) participants were female, 16/89 (18%) were

male. One student (1.1%) did not provide gender information. In the animal

nutrition course, 185/215 (86.0%) were female and 26/215 (12.1%) were male,

while 4 (1.9%) students did not answer the gender question. Finally, only women

participated in the food science course (23/23). Thus, there was a similar gender

distribution in the first two courses, but a different distribution in the last one. In

general, large proportions of women is very typical among veterinary students.

Age distribution (mean+/-standard deviation years) was 20.3+/-2.7 (minimum: 17,

maximum: 29) for the zoology module, 24.5+/-4.6 (minimum: 21, maximum: 57)

for the food science module, and 21.9+/-2.8 (minimum: 20, maximum: 29) in the

animal nutrition course. Thus, the food science course was visited by older

students compared to the two other courses.


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3.1.2 Interactive graphics in teaching and it´s handling

In general, we found a high acceptance of interactive graphics as new teaching

tool amongst all students in the three studied courses. Not less than 70% of

students from fourth year agreed or strongly agreed to the statement “I´d wish to

have more interactive graphics in veterinary school”. For students from first year,

we found over 80% agreement to that statement. Regarding the handling of the

web-tool, most students are confident to be able to use easily the interactive tools

themselves and estimate that other students will do so, too (over 70% agreement

or strong agreement to answers of question B1 and B3 in all three courses).

3.1.2 Effects of interactive graphics on learning experience

The previous knowledge about the taught topics was low among students in all

courses. In the zoology course, 62.92% of the students strongly disagreed or

disagreed to the statement “I was previously familiar with the taught topic”. In food

science and animal nutrition lectures 91.3% and 62.5% of the students,

respectively, negated (strongly disagree/disagree) that statement, too. Despite

that the observation, students mainly agreed in all three courses to have

understood the subject taught by this new teaching tool.

Regarding the effect of interactive graphics on the learning experience, the

findings of the questionnaire yielded, that students consider the interactivity of the

graphic to have promoted their interest on the taught contents. In the food science

course 95.6% agreed or strongly agreed to this statement. Zoology and animal

nutrition students agreed to 71.9% and 68.4%, respectively, to that statement. To

correct the acquiesce tendency, we included a negative worded statement. In all

courses students mostly disagreed or strongly disagreed the assertion “The

interactive graphic did no provide benefit to the course”.


29

Figure M1.5: Answer distributions for Likert-Scale questions on the interactive graphic in

the zoology course

Figure M1.4: Answer distributions for Likert-Scale questions on the interactive graphic in

the animal nutrition course.


30


graphic in the food science course.

3.1.3 Digital media usage as learning resource

The student’s questionnaire evidence a positive perception of digitalization in

academic environment amongst veterinary medicine students. Most students

consider digitalization as a chance to improve the academic education. Students

in general seem to have a high acceptance for e-learning offered by the university

and seek for other digital media to support their learning advances (Table 1).

Besides online videos and forums, students use some other digital media, such

as online libraries, multimedia websites and 3D-models. The number of students

which do not use any digital learning material was low. Those students who do not

use other digital learning media as a learning device tended to have a more neutral

attitude regarding digitalization in higher education (Supplementary Tables S.T4-

S.T5). More detailed, 30 (14%) of the students in the animal nutrition course that

stated not to use other digital media, showed a significantly lower agreement to

question D9 (‘Digitalization is a chance to improve academic education’)

compared to 183 (85%) of students who use other digital media for learning

(adjusted p=0.03). Likewise, the 3 (13%) of students in the food science course


31

who stated not to use digital media showed also a significantly lower agreement

to question D9 (adjusted p=0.03).

Course n e-learning at university

videos online-forum

others none

Zoology 89 55 (62%) 51 (57%) 7 (8%) (1%) 16 (17%)

Animal Nutrition

215 101 (47%) 152 (71%)

29 (13%) 27 (13%) 30 (14%)

Food Science

23 18 (78%) 16 (70%) 3 (13%) 3 (13%) 3 (13%)

Table 1: Percentages of students who use other digital media for learning as asked in

the three courses.


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3.2.1 Students response by gender and age

We found no evidence for differences between females and males in their opinion

towards interactive graphics and digital media usage. There was also no evidence

for age effects in the distribution of answers in all three courses. We only observed

a tendency for a difference (adjusted p=0.06) in the negative worded question

asked in the zoology: males found more often no added value by the new teaching

tool (Table 2).

B1 B2 B3 C4 C5 C6 C7

Gender F M F M F M F M F M F M F

1 0 6 0 6 1 6 31 44 1 6 3 12 39

2 1 0 1 6 1 0 29 31 1 0 4 6 34

3 8 6 14 12 14 25 24 19 7 31 21 12 14

4 39 50 40 25 42 44 8 6 43 12 35 38 8

5 51 38 44 50 42 25 8 0 47 50 38 31 4

n 72 16 72 16 72 16 72 16 72 16 72 16 72

p 0.32 0.88 0.13 0.18 0.42 0.51 < 0.0

1

pHolm 1.00 1.00 0.91 1.00 1.00 1.00 0.06

Table 2: Percentage distributions of response (grade of agreement: 1 – 5, ranging from

strongly disagree to strongly agree) for Likert-Scale questions asked in the zoology

course, separately for males and females. For question C7 (“no benefit to the course”)

there is a tendency that males see less benefit of the interactive graphic than females

(50% versus 12% of answers agree or strongly agree).


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3.3. Rating of interactive graphics by the lecturers

Asking the participating lecturers about their option, we found a general

acceptance towards the usage of interactive graphics in teaching (Table 3). All

participating lecturers felt to have reached more students through this new digital

teaching tool. Most lecturers (4/5) claimed to never have used digital media in

their classes before, even though they commonly agreed or strongly agreed to

consider digitalization as a chance to improve academic education. The open field

section in the lecturer’s questionnaire revealed little improvement wishes. One

lecturer rated the interactive graphics to have a high potential and ideal

environment to develop a case-based scenario but criticized the missing

opportunity for students to self-manipulate the graphic in class. Other lecturers

considered a stable internet access and high-quality beamers as important for a

reliable usage of this teaching tool.

Question State of agreement (n=5)

1 2 3 4 5

I felt confident using this teaching tool 2 3

I can imagine that the majority of teachers will handle easily this teaching tool

1 1 1 2

I wish to have more interactive graphic in my clas-ses

2 3

The interactive graphic provided no benefit to the course

3 2

I feel like I could have reached more students by teaching with interactive graphic

2 3

Digitalization is a chance to improve higher school education

2 3

I have used previously digital teaching tools Yes: 1

No 4

The usage of interactive graphic had a positive effect on my opinion towards digital media in higher school education

Yes 4

No 0

NA 1

Table 3: Answer distributions (grade of agreement: 1 – 5, ranging from strongly disagree

to strongly agree) for lecturers involved in teaching with interactive graphics.


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4. Discussion

In this study, interactive graphics were implemented for veterinary medicine

courses. Their impact on students and educators was captured through

questionnaires. Summarizing the results of all three courses, 71% (233/326) of

the students claimed that the interactivity of the graphics led to an increased

interest for the presented study contents. Lecturers also agreed to have reached

more students through teaching with interactive graphic. Researchers in the field

of educational psychology studied the role of interest in the learning process and

revealed that interest is linked to motivation for learning and can also promote a

deeper learning approach18. This is especially important in veterinary education,

where students get instructed in a wide field of disciplines, such as diverse

knowledge of several animal species and their diseases, as well as basic natural

science, food hygiene, animal production and others19. Obviously not all

disciplines can be of particular interest for the individual student and the workload

is known to be quite high. Students facing a high workload, eventually adopt a

surface learning approach,20 where facts are just memorized, and the meaning of

the studied contents may not be entirely understood21. To conduce students into

a deep learning approach a “stimulating learning environment”22 must be

promoted. We believe to have contributed to such a stimulating learning

environment by integrating these interactive teaching tools into the veterinary

medicine lectures. However, studies comparing animated versus static images

reveal inconsistent results regarding their effects on learning23. One common

concern is the possible high informative content, which can lead to an overload.

According to Hegarty (2004) it is unclear whether all students have the

metacognitive skills to effectively learn from interactive media24. Nevertheless, the

here presented graphics were designed to be explored in collaboration with the

professor during the lecture. In class the teacher manipulates certain parameters

through regulator elements while asking students to predict the outcome. This way

students are encouraged to actively participate and think of the fundamental

principles behind the presented graphic. After the class students can manipulate

the interactive graphics at their own pace by accessing a PC connected to the

server of our university or by accessing the shiny apps uploaded on the GitHub

account. Considering that in total 76% of the students wish to discuss more topics


35

with interactive graphics, it is worthwhile to analyse whether teachers in veterinary

education would use interactive graphics for their classes. Even though the

advances in online technology have reached veterinary medicine education and

diverse e-learning options are available25 not all lecturers choose to implement

them into their teaching26. Previous studies revealed that academic staff often

remains attached to traditional ways of teaching, even though new technologies

are fully integrated into the educational system27,28. This matches the findings of

our survey, which affirm that most of the participating professors (4/5) have never

used digital teaching media in their class before. By involving the participating

university professors actively into the development process of these teaching

tools, we believe to have contributed positively not only on their general opinion

towards digital media but also on their confidence in handling interactive graphics.

Past educational studies suggest that students respond positively to digital media

in addition to traditional teaching (Sharpe et al., 2016). Therefore, one further aim

of this work was to provide a positive handling experience and consequently

stimulate digital media usage in class. After using interactive graphics for their

class, 4/5 lecturer strongly agreed to the statement that this experience had a

positive influence on their attitude towards digital teaching. Lecturers nowadays

can currently choose out of a large collection of existing teaching applets and

digital media resources in the web. However, they might not always find an existing

teaching tool, which matches their individual needs15 and consequently might

renounce to digital media for teaching. For this study we cooperated closely with

the lecturers to build a teaching tool adopted to their individual wishes. The Shiny

environment allows to display interactive graphics within a web browser and

therefore can be easily integrated into lecturers’ presentations. Since its handling

doesn´t require any background knowledge in programming nor hardware or

software installation, interactive graphics can be considered as user-friendly

teaching tools. This assumption is confirmed by all lecturers involved (5/5), who

claimed to have felt confident using interactive graphics during the class. When

observing students’ perception towards the ease of use, in total 78% (254/327) of

the students agreed or strongly agreed to the statement that they would feel

confident using interactive graphics by themselves. 86% (279/326) of the students

further believe their fellow students would do so too. This positive attitude can be


36

explained by the high acceptance for digital media and digitalization we yielded

amongst the survey students. Only 49/327 of the students claimed to not use any

digital media for learning. Those who do not support learning with digital resources

also had a more neutral perception towards the effect of digitalization on higher

education. Nevertheless, most students (86%; 280/327) and all lecturers (5/5)

agreed that digitalization can improve higher education. Still a lack of training and

programming skills can be an impediment for lecturers to use and develop further

interactive graphics for their courses. Training teachers basic programming skills

can be one possible way to spread interactive graphics through veterinary schools

and other academic fields. Considering the time-consuming development process

in addition to already high workload amongst teachers, the possibility of

distributing already existing shiny apps through openly available internet hosting

services, such as GitHub, gains special importance. Shiny apps can be shared as

open educational resource which in return reduces the development efforts.

5. Conclusion

The findings of our study revealed a high acceptance for this web-based teaching

tool amongst veterinary students and lecturers. Students commonly agreed for the

interactivity of the graphics to have a positive effect on their interest about the

taught contents. This complies with the lecturer’s perception, to have reached

more students by teaching with an interactive graphic. The lecturer’s positive

perception towards this web-tool is also a promising finding of this study in terms

of promoting digital media usage at our university. Shiny applications facilitate

data visualization and its modification in a user-friendly, visually appealing

environment. We believe to have evidenced the potential of this web tool, to create

an enhanced learning and teaching experience in veterinary medicine education,

where interactive graphics have rarely been integrated so far. Further work must

be done, to examine if the integration of more interactive graphics in this field is

feasible.


37

Conflicts of Interest

The authors declare no conflict of interest.

Acknowledgements

This work was supported by the Ministry of Science and Culture of the State Lower

Saxony, Germany [grant ‘DigiStep’].

Data Accessibility

The data that support the findings of this study are openly available in Mendeley

at https://data.mendeley.com/datasets/6th5cts43p/1

(DOI: 10.17632/6th5cts43p.1).

https://data.mendeley.com/datasets/6th5cts43p/1


38

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41

The following manuscript was submitted 2021, February 2nd in the Journal of

Computing in Higher Education:

3.2 Teaching Academic Staff to Implement Interactive Graphics for their Courses

Pamela Liebig1, Viviane Filor2, Marina Scheumann3, Martina Buchholz4, Klaus

Jung 1*

1) Institute for Animal Breeding and Genetics, University of Veterinary Medicine

Hannover, Foundation, Hannover, Germany

2) Department of Pharmacology, Toxicology and Pharmacy, University of

Veterinary Medicine Hannover, Foundation, Hannover, Germany

3) Institute of Zoology, University of Veterinary Medicine Hannover, Foundation,

Hannover, Germany

4) Institute for Food Toxicology, University of Veterinary Medicine Hannover,

Foundation, Hannover, Germany

* Corresponding Author


University of Veterinary Medicine Hannover, Foundation

Institute for Animal Breeding and Genetics

Bünteweg 17p

30559 Hannover

Phone: +49 511 953-8878

Fax: +49 511 953-8582

E-Mail: [email protected]

Conflicts of Interest

The authors declare no conflict of interest.

Acknowledgements



Abstract


42

This study analyses the respond of academic staff to an online workshop to learn

how to develop interactive graphics as digital teaching device using R-Shiny. The

need for training teachers in the field of educational technologies has gained

increasing relevance in the past decades. More recently, the COVID-19 pandemic

has led to the urgent need of preparing teachers’ for digital education. However,

studies regarding workshops for teachers mostly centre on the learners’

satisfaction rather than the workshops’ impact on the teaching practice. Moreover,

no study regarding teaching academic staff the development interactive graphics

on their own has been conducted before. The n=25 participants were academic

staff from the fields of medicine or natural sciences. Pre- and post workshop

questionnaires were used to identify the impact of the workshop on their opinion

towards digital teaching devices and their willingness to program own interactive

graphics. Furthermore, their opinion towards the role of the corona crisis in

education was asked. The findings indicate that most participants had little

programming skills but showed strong interest in using interactive graphics for

their classes. After the workshop, the intention to program interactive graphics was

only given by participants who had prior programming skills. The workshop had a

positive impact on the participants’ opinion towards digitalization in higher

education. The impact of the COVID- 19 pandemic was rated to be an accelerator

of the digitalization process. No gender or age correlation was observed.

Keywords

COVID-19; Interactive graphics; Workshop; R-shiny; Professional development

Data Accessibility

The data that support the findings of this study are openly available in Mendeley

at http://dx.doi.org/10.17632/4zsggk9swp.1 (DOI: 10.17632/4zsggk9swp.1).

http://dx.doi.org/10.17632/4zsggk9swp.1


43

1. Introduction

Graphics are widely used in education to visualize patterns, correlations, and big

amount of data. Typically, these graphics are presented as a static image.

However, the advances of computer and network technologies have added new

ways for data presentation. Various visualizations tools have emerged, which

allow additional features, such as interactivity (Ali et. al, 2016). This interactivity

enables the user to explore data in more detail (Perkel, 2018). The open-source

software R and the package Shiny allows to program such interactive graphics,

which can be displayed within a web browser. These so-called Shiny apps have

increasingly gained relevance in research (Chiu et al., 2017; Di Filippo et al., 2019;

Ekiz et al., 2020) and have also been employed in education with promising results

(Fawcett, 2018; Potter et al., 2016; Hanč, et al., 2020). According to Wishart

(2019) “a great way to demonstrate data to students […] is by extending use of

the digital learning environment”. He found that interactive graphics build with R-

Shiny can be a way to achieve this. However, to master any digital learning

environment the educational staff needs to get trained in this field. As already

stated by Fulton (1988) training the use of technology is one important factor that

determines whether teachers use technology in class or not. More recently the

COVID-19 pandemic has evidenced the importance of technology trained teachers

and academic staff. When the global lockdown and quarantine policies forced

educational institution worldwide to close, teachers had to move from traditional

face-to-face to online education (Bao, 2020; Murphy, 2020). Under these

circumstances, the focus has been laid on assuring technology-equipment, rather

than on training teachers (Gyimah, 2020). One possibility to provide educators

training can be achieved through workshops. In this paper a workshop for training

academic staff the implementation of interactive graphics for their courses using

the statistical programming environment R and the Shiny package is described.

The impact on teachers’ practice is measured by questionnaires.


44

1.1. Relevance of workshops in teachers’ professional development

The term workshop is used to describe a ‘usually brief intensive educational

program for a relatively small group of people that focuses especially on

techniques and skills in a particular field’ (Merriam-Webster, 2021). Georgina and

Olson (2008) did a survey on more than 1000 faculty members of higher education

regarding their perception towards technology training. They yielded that most

faculty members agreed that learning “new computer-based technologies” could

be achieved the best in small groups instructed by a trainer. According to Chris

Rust (1998) from the Oxford Centre for Staff and Learning Development,

workshops are a common tool for “staff and educational development […] in higher

education around the world”. Workshops do not only serve to transmit knowledge.

As stated by Ørngreen, & Levinsen (2017), a workshop can also be used as a

research methodology, when it’s designed to teach participants something related

to their specific interest and to answer at the same time a research question. Even

though different perspectives exist, all workshops share some basic features, such

as active participation and an expected outcome (Ørngreen, & Levinsen, 2017).

Usually, the expected outcome of teachers’ workshop is the improvement of

teachers’ skills. This can also lead to an improvement of students’ achievement

since it has been suggested that both; teachers’ skills and students’ achievements;

are deeply linked (Darling-Hammond, 2000; Rice, 2003). Literature review

revealed that students in higher education can benefit from teaching technologies

(Concannon & Campbell, 2005), yet some academics remain reluctant to adopt

these (Corard et. al, 2006). A lack of training has been discussed in diverse

educational studies as one of the barriers to the adaption of these technologies

(Brownell & Tanner, 2012; Bingimlas, 2009; Pajo & Wallace, 2001; Abdal-Haqq,

1995; Kurt & Ciftci, 2012). Schneckenberg (2009) further discussed a lack of

interest in technology amongst academic staff as a reason for a slow integration

of learning technologies. In the past years, there have been some studies

regarding workshops to improve teachers’ technology skills. For example, Lai

(2010) discussed the positive reaction of schoolteachers towards an interactive

whiteboard training (IWB). After the workshop, all teachers valued the importance

of IWB training workshops and recognized the potential of using IWB in class.

Furthermore Liu et al. (2011) demonstrated that a computing workshop for


45

teachers can significantly increase their confidence level in computing

technologies. Although the research done in this field has added knowledge to the

teaching literature, most of them centre on the learners’ satisfaction and the

immediate workshop outcome rather than on the impact of those workshops on

the teaching practice (Stet et al., 2010). Watson (2006) for example studied the

long-term effect of a workshop to train the integration of internet in class. He

revealed that after years the workshop still had positive impact on teachers’ self -

efficiency level. These studies have in common that they all analyse the effects of

training educators in already implemented computer-based teaching modalities.

No previous study has been conducted to analyse the effect of teaching academic

staff to develop own interactive graphics.

1.2. Research questions

For the present work, academic staff at our institution were offered to participate

in a workshop to learn how to program interactive graphics as a digital teaching

tool. Those interactive graphics were already employed at our university and found

broad acceptance amongst teachers and students. Previous studies regarding the

usage of this type of interactive graphic in education have also shown a broad

acceptance amongst students (Potter et al., 2016; Fawcett, 2018). Fawcett argued

that a large amount of teaching apps is already available for teachers nowadays.

However, none is specifically designed on the teachers need. Teachers know the

best which topics are difficult for students. A teaching app basing on teachers need

can therefore be beneficial for students’ achievement. Furthermore, the perceived

usefulness of technologies has been identified as one key variable affecting users’

intention to use technology (Davis, 1993). In our study we want to answer the

following questions: 1) Is academic staff willing to learn programming techniques,

in which they are mostly unfamiliar with, to provide digital teaching media for their

students? 2) Does gender, age or previous knowledge in this field have an

influence on the willingness to learn? 3) Does a workshop in teaching technology

influence teachers’ opinion on digital media and promote a further use of the

taught teaching tool. 4) Does the COVID-19 pandemic influence the opinion

towards the digitalization process of higher education?


46

2. Methods

2.1. Local setting and program of the online workshop

Academic staff from different institutes at the University for Veterinary Medicine

Hannover were invited to participate at our workshop. Our University established

in 2005 an e-learning consulting centre to promote the usage of digital teaching

technologies. Additionally, in January 2019, the university launched the project

‘DigiStep’ to advance digitalization at our institution. The departments of physics,

general radiology, chemistry, zoology, botany as well as the institute for genetics

are partners of this project. In addition to online learning modules and case

studies, video material and lectures as well as lecture recordings are used so that

e-learning concepts such as blended learning and inverted classrooms can be

implemented. In addition, the zoological exercises, in which dissections are

carried out on dead animals, will be changed with the project, thereby significantly

reducing the number of animals used. Our working group contributed to this

project by implementing interactive graphics for several lectures in the field of

medicine and natural sciences during the past winter term 2019/2020.

2.2. Program of the online workshop

The workshop was imparted using the online-conference tool Microsoft Teams.

The program of this two-day workshop included, at the first day, a presentation of

previous experiences using interactive graphics as a teaching device at our

university and an introduction to the statistic software R (R Core Team, 2019). The

central part of the workshop consisted of teaching basic programming skills in R

Shiny. The Shiny environment (version 1.4.0) is based on R and allows to convert

R scripts into visually appealing Shiny applications within a web browser. After day

one of the workshop, participants received several R scripts as templates and

study material to create different interactive applications for their classes and self-

study material. Next, participants were given one week to develop idea, concepts,

or sketches for interactive graphics for teaching propose in their own courses. At

the second workshop day, we discussed these ideas and implementation

possibilities.

2.3. Study design


47

Workshop participants were asked to answer an online questionnaire before and

after the workshop. The questionnaires were created using the platform Google

forms and were approved by the data security office of our university. No personal

identifiable information except for gender and age was captured and all data was

stored anonymously. In total, n=25 lecturers and members of the academic staff

completed the first questionnaire and n=15 of them also completed the second

questionnaire. Some participants left some questions unanswered. This is shown

in the result sections through the absolute numbers.

The questionnaires included two demographic questions (gender and age), open

field, multiple choice and 5-point Likert Scale questions ranging from 1 (strongly

disagree) to 5 (strongly agree). Participants were asked before the first workshop

day about their programming skills and their knowledge in R. We also asked

participants about their opinion towards digital media in teaching and especially

interactives graphics as a teaching tool. Furthermore, we included some questions

to evaluate the participant’s perception towards the importance of the corona crisis

in the digitalization process in higher education (Table 1). The second

questionnaire was completed by the participants after the second workshop day.

Lecturers and academic staff were questioned if they can imagine using such

interactive graphics for their teaching purpose and if they feel able to program

such graphics after the workshop session. We also included a question to evaluate

the workshop´s effect on their opinion towards digital teaching media (Table 2).


48

Item Answer options

1. Age Open field

2. Gender female, male, no information

3. Have you already used digital media for your class (video-conferences tools such as Microsoft-Teams and Zoom are not meant)?

Multiple choice: Video/audio-files, smartphone application, CASUS (case-based learning system), virtual microscope, Interactive graphics, podcasts, others, none

4. For how much time (in percent) is it reasonable to use digital teaching tool in higher education?

Open field

5. I find the increasing use of digital teaching media in higher education for students …

5 point-Likert-scale question ranging from 1(negative) to 5 (positive)

6. I find the increasing use of digital teaching media in higher education for lecturers…

7. Interactive graphics facilitate teach-ing

5 point-Likert-scale question ranging from 1(fully disagree) to 5 (fully agree) 8. Interactive graphics facilitate learning

9. I´m experienced in programming. Yes or no If yes, please specify

10. I have knowledge in using R. 5 point-Likert- scale question ranging from 1(fully disagree) to 5 (fully agree)

11. I have already used interactive graphics before.

Multiple choice: on webpages (e.g. online journals) In my class

12. The invention of the letterpress in the 15th century reduced in my opinion the need for traditional face-to-face class

5 point-Likert-scale question ranging from 1(fully disagree) to 5 (fully agree)

13. The invention of the internet in the 20th century will fundamentally pro-mote a permanent shift into digital teaching in higher education.

14. The COVID-19 pandemic will funda-mentally promote a permanent shift into digital teaching in higher educa-tion.

Table 1: Questionnaire distributed to workshop participants before the first

workshop day.


49

Item Answer options

1. Age Open field

2. Gender female, male, no information

3. Interactive graphics facilitate teach-

ing

5 point-Likert-scale question ranging

from1(fully disagree) to 5 (fully agree)

4. Interactive graphics facilitate learn-

ing

5. I can imagine using interactive

graphics in my classes in the future.

6. I can imagine programming interac-

tive graphics for my classes in the

future.

7. The workshop promoted my interest

for using digital teaching media

8. Further comments and ideas Open field

Table 2: Questionnaire distributed to the workshop participants after the second

workshop day.

2.4. Data analysis

Answer distribution of all questions were analysed descriptively, separated by

gender, age groups and groups of prior programming skills. Differences between

groups were further analysed using Fisher’s exact test (categorical answers) or

the Mann-Whitney U test (ordinal answers). Wilcoxon signed-rank test was used

to compare ordinal answers from 1st and 2nd questionnaire. Correlation between

these answers were determined using Kendall’s tau. The significance level was

set to α=0.05. Analyses were performed using again the software R.


50

3. Results

3.1. Workshop participants

Workshop participants were members of the academic staff and lecturers from

natural science and the medical field. 80% (20/25) participants were females and

20% (5/25) were males. Age distribution (mean+/- standard deviation years) was

40.7 years +/- 10.5 (minimum: 26, maximum: 61 years). Most participants (68%,

17/25), had no previous programming skills. Only a few had some knowledge in

HTML (2/25) or Python (1/25). Furthermore, 20% (5/25) participants had prior

experience in R. The statement ‘I am fully experienced in R’ was fully disagreed

by 60% (15/25) workshop participants. Only 3 participants rather or fully agreed

to be experienced in R (Supplementary Table 1).

3.2. Opinion on digital teaching media in class

We found that most members of the participants have already employed digital

teaching media before the workshop. Mostly used media specified by the

participants were video/audio-files (72%; 18/25) and a case-based learning

system, called CASUS (24%; 6/25). Furthermore, 20% (5/25) have never used any

digital teaching media before. Most of the participants (9/25) found that digital

media should take up to 50% of the time in class. The rest of the participants would

rather employ less time in class using digital media. Only 3/25 responders found

it accurate to spent more than half of the time in class using digital devices to

teach. The mean time in percentage to spend with digital teaching technologies

rated by all participants was 41.2%. Analysing these opinions separately by age

we found out, that younger participants (less than 40 years old) rated for slightly

less time using educational technologies in class than the older participants (older

than 40 years old).

Asking about their opinion towards the effect of digital media in teaching, 48%

(12/25) strongly agreed the statement ‘I find the increasing use of digital media in

higher education to be positive’, both for lecturers and students. Comparing their

perception on the benefits of digital media in higher education, we found that

members of the academic staff rated its effect slightly more positive on students


51

than for themselves: 20% (5/25) had a neutral perception on the benefit for

lecturers and 8% (2/24) rather disagreed to the statement digital media would be

positive for lecturers in teaching. In comparison: only 4% (1/25) disagreed the

statement related to students benefits of digital teaching media.

Regarding interactive graphics, 95.8% (23/24) participants found that they

facilitate students to learn study content and 91.7% (22/24) find interactive

graphics to be beneficial for lecturers to teach this content. In total, 40% (10/25)

participants have already used interactive graphics before the workshop, 6 of them

in their own class and 4 on webpages. The remaining 15 participants did not

provide an answer to this question. We found no significant difference in the

opinion towards the usage of digital teaching media between the age groups less

than forty and over forty years old (Supplementary Table 1) nor between female

and male (Supplementary Table 3) or previous programming experience

(Supplementary Table 5).

3.3. Influence of letterpress, internet and COVID19 pandemic on

development of digital teaching

Lecturers and academic staff agreed for the pandemic crisis to promote further

digitalization in higher education (Figure M2.1). In total, 92% (23/25) agreed or

fully agreed to the statement ‘The corona pandemic crisis will lead fundamentally

to a permanent shift into digitisation in higher education’. 72% (18/25) participants

agreed or fully agreed for the invention of the internet to cause a permanent shift

into digitalization in higher education. There was significantly less agreement to

the statement that the invention of letterpress in the 15th century had a strong

effect on the necessity of on-site lectures (letterpress versus internet: p<0.01,

letterpress versus COVID-19: p<0.01). The effect of internet versus the effect of

COVID-19 in digital teaching was rated as significantly different: p=0.04. (Table

3). We found no significant difference towards that opinion regarding age

(Supplementary Table 2), gender (Supplementary Table 4) and previous

programming skills (Supplementary Table 6).


52

Figure M2.1: Comparison of the influence of the invention of letterpress, the

internet or the occurrence of the COVID19 pandemic on the development of digital

teaching in higher education. Levels of agreement are from 1 (no agreement) to

5 (strong agreement).


53

Item Levels All

participants

The invention of the letterpress in the 15th

century reduced in my opinion the need for

traditional face-to-face class

Fully disagree

Rather disagree

Indifferent

Rather agree

Fully agree

3 (12%)

9 (36%)

10 (40%)

2 (8%)

1 (4%)

The invention of the internet in the 20th

century will fundamentally promote a

permanent shift into digital teaching in higher

education.

Fully disagree

Rather disagree

Indifferent

Rather agree

Fully agree

0 (0%)

0 (0%)

7 (28%)

11 (44%)

7 (28%)

The COVID-19 pandemic will fundamentally

promote a permanent shift into digital

teaching in higher education.

Fully disagree

Rather disagree

Indifferent

Rather agree

Fully agree

0 (0%)

1 (4%)

1 (4%)

12 (48%)

11 (44%)

Table 3: Results from first questionnaire regarding the influence of letter press,

internet and COVID19 pandemic on development of digital teaching .


54

3.4 Success of the workshop and responds by the participants

The second questionnaire, distributed at the end of the workshop, revealed that

the positive opinion towards interactives graphics as teaching and learning tool

remained unchanged (Figure M2.2). There was no significant location shift in the

strength of agreement (easier learning for students: p=0.77; easier learning for

lecturers: p=0.42), although answers were only moderately correlated between 1st

and 2nd questionnaire (Kendall’s tau=0.44, p=0.08 and tau=0.57, p=0.02). Most

participants (85.7%, 12/14) affirm to be interested in using interactive graphics in

their course, but only those who had previous programming skills (20%, 3/15) had

intention to program a graphic on their own (Figure M2.3, Table 4). The

significance of the latter effect (p=0.018) would not survive a multiple testing

correction but it shows a tendency. We also asked lecturers and academic staff

about the impact of this online workshop on their opinion towards digital teaching.

According to this, 73.3% (11/15) agreed to the statement ‘the online workshop had

a positive impact on my opinion towards digital teaching’ and 26,7% (4/15) had a

neutral perception to this statement. Again, we found no significant difference in

the opinion of the workshop participants by age (Supplementary Table 7) and

gender (Supplementary Table 8).

Figure M2.2: Overall high agreement to the statements that interactive graphics are

positive for students (left) and lecturer (right) did little change during the workshop. X-

axis shows agreement before workshop, y-axis agreement after workshop.


55

Figure M2.3: After the workshop, only participants with prior programming skills agreed

to have the intention to program interactive graphics by themselves.


56

Item Levels All

participants

(n=15)

No

programming

experience

(n=12)

Programming

experience

(n=3)

p-

value

Age Mean +/- SD

Median (Min,

Max)

38.73 +/-

12.17

34 (26,61)

40.3 +/- 13.14

36 (26, 61)

32.67 +/- 4.16

34 (28,36)

0.47

Gender Female

male

12 (80%)

3 (20%)

10 (83.3%)

2 (16.7%)

2 (66.7%)

1 (33.3%)

0.52

Interactive

graphics

facilitate

learning

Fully disagree

Rather disagree

Indifferent

Rather agree

Fully agree

0 (0%)

0 (0%)

1 (6.7%)

7(46.7%)

7 (46.7%)

0 (0%)

0 (0%)

1 (8.3%)

6 (50%)

5 (41.7%)

0 (0%)

0 (0%)

0 (0%)

1 (33.3%)

2 (66.7%)

0.47

Interactive

graphics

facilitate

teaching

Fully disagree

Rather disagree

Indifferent

Rather agree

Fully agree

0 (0%)

0 (0%)

1 (6.7%)

9 (60%)

5 (33.3%)

0 (0%)

0 (0%)

1 (8.3%)

7 (58.3%)

4 (33.3%)

0 (0%)

0 (0%)

0 (33.3%)

2 (66.7%)

1 (33.3%)

0.93

Use inter-

active

graphics

for course

Fully disagree

Rather disagree

Indifferent

Rather agree

Fully agree

0 (0%)

0 (0%)

2 (14.3%)

5 (35.7%)

7 (50%)

0 (0%)

0 (0%)

2 (18.2%)

4 (36.4%)

5 (45.5%)

0 (0%)

0 (0%)

0 (0%)

1 (33.3%)

2 (66.7%)

0.49

Program

interactive

graphics

for course

Fully disagree

Rather disagree

Indifferent

Rather agree

Fully agree

2 (13.3%)

3(20%)

4 (26.7%)

4 (26.7%)

2 (20%)

2 (16.7%)

3 (25%)

4 (33.3%)

3 (25%)

0 (0%)

0 (0%)

0 (0%)

0 (0%)

1 (33.3%)

2 (66.7%)

0.018


57

Table 4: Results from the second questionnaire, divided according to previous

programming experiences.

3.3 Examples of implemented concepts submitted by the workshop

participants

After the first workshop day, participants were encouraged to send us their own

ideas, drafts or concepts of interactive graphics, they want to employ in their

courses. In total, 7 participants made submissions, which ranged from mere topic

identification, to handwritten sketches and fully programmed Shiny applications.

In the second workshop session, we discussed implementation possibilities with

all participants. In the following the development of two Shiny application for

teaching purpose are described.

3.3.1 Interactive graphic showing bioavailability of drugs for different types

of administration

Figure M2.4 is usually used as static graphic in the lecture of general

pharmacology at our university. It is intended to give an overview of how important

the chosen administration of a drug can be in terms of bioavailability and drug

level (Chausseaud and Taylor, 1974). The message behind this figure is simple,

but fundamental and important for a first understanding of pharmacokinetics. It is

the first figure shown in the lecture and since it can be confusing due to multiple

curves, it was the idea to transform the figure into an interactive graphic. This

should give students a better overview, as the individual curves in the Shiny

application can now be viewed in a more differentiated way by individual selection

and give students the opportunity to try things out in order to consolidate a first

understanding of pharmacokinetics.

Workshop

positive im-

pact on

opinion for

digital

teaching

Fully disagree

Rather disagree

Indifferent

Rather agree

Fully agree

0 (0%)

0 (0%)

4 (26.7%)

3 (20%)

8 (53.3%)

0 (0%)

0 (0%)

5 (41.7%)

2 (16.7%)

5 (41.7%)

0 (0%)

0 (0%)

0 (0%)

1 (33.3%)

2 (66.7%)

0.31


58

Figure M2.4: Sketch from a workshop participant for an interactive graphic in a

pharmacology lecture (left) and implementation as interactive graphics with checkboxes

as regulator elements (right).

The lecturer involved in the development of this application descripted her first

experience using R and Shiny as follows: ‘After the idea was developed and the

first workshop took place, I could implement the idea in small steps. Since the

program always showed you the errors, I was able to convert the basic structures

of my idea into the Shiny app according to the trail-and-error principle.’


59

3.3.1 Interactive graphic showing temperature-dependent sex

determination in reptiles

In some reptiles, the sex of the offspring is triggered by the incubation temperature

during a critical period of the embryonic development (Mitchell et al., 2006).

Thereby, three patterns exist. In the first pattern, males were produced at cooler

temperatures than females (Ia). In the second pattern, females were produced at

lower temperatures than males (Ib). In the third pattern, males were produced at

intermediate temperatures whereas females were produced at both extremes,

below and above the intermediate range (II). Within this study, a static line plot of

a textbook (Gilbert & Sunderland, 2000) was transferred to an interactive graphic.

Here the user can regulate the temperature over a temperature slider and, thereby,

the effect of incubation temperature on the sex ratio of the respective reptile

species will be plotted in a pie chart (Figure M2.5). Moreover, by plotting several

species, the different pattern of sex determination can be additionally visualized.

Since the interactive graphic links simultaneously the movement of the

temperature button to the sex proportion in the pie charts, the user can recognize

on the first look and experience very fast and intuitive the mechanisms without

extensive explanation, which would be necessary by using the static line plot. The

lecturer involved in the development of this application descripted her first

experience with Shiny as follows: ‘After the first day of the workshop, I got

interested to implement an interactive graphic to my lecture. Since I had prior

experience with R and due to the guiding of the workshop organisations it was

quite easy to implement this graphic by myself. But of course, it takes more time

than just using static graphics from the textbook. However, for the visualisation of

dynamic processes interactive graphics are very well suited and can help to

simplify complex relationships.’


60

Figure M2.5: Screenshot of interactive graphic for zoology module. The temperature-

dependent sex determination for different reptile species is illustrated by pie-charts.

Through the slider users can manipulate the incubation temperature. The outcoming

proportion of female (pink) and male animals (blue) is shown by the p ie charts. A grey

coloured pie-chart appears if no information is available or no descendants are hatched

at the given temperature.


61

4. Discussion

The present study investigates the respond of academic staff towards a training

workshop to learn how to program interactive graphics with R-Shiny. As Stes et al.

(2010) emphasized, most studies regarding teachers workshop mostly centre on

participants’ satisfaction, rather than on the workshops’ impact on teacher

practice. To assess the impact of our workshop, we used a pre- and post-workshop

questionnaire design. The results of this work indicates that academic staff were

open-minded towards expanding their programming skills and learn how to employ

a new digital teaching tool. Between the different age groups, we found no

evidence for different perception towards digital teaching tools or the willingness

to use such. Interestingly, older workshop participants had a higher interest in

investing more time using digital teaching devices in class than the younger ones.

This finding contradicts the theory of a ‘digital generation gap’ (Buckingham, 2006;

Kelty, 2002). This term refers to an inter-generational, inequality in the usage of

technology and suggest that older generation have a harder time adapting to new

technologies. The average age of our participants was 40.7 years. Our participants

therefore cannot be categorized as ‘digital natives’ (Jones et al. 2010). A lack of

interest or motivation among academic staff towards technology as stated by

Lazar (2015) or Schneckenberg (2009) was not confirmed in this study. Most of

the lecturers and members of the academic staff, who participated at our

workshop, had no previous programming nor basic R skills, but they got fully

engaged to the topic and had own ideas and drafts of interactive graphics for their

teaching purpose.

We yielded, that most of the participants were interested in using interactive

graphics for their classes after the workshop, but still couldn´t image programming

them. The reason for this can be linked to the short workshop duration and the

consequent low self-efficiency feeling of the participants. In a personal feedback

some participants outlined the need for a second workshop or further support.

These findings are in line with Watsons’ (2006) study results regarding the effects

of a 5-day workshop to train teachers the internet usage in class. He proved that

teachers had a higher level of self-efficiency after attending to online courses in

addition to the workshop, than those who just participated to the workshop.


62

Another reason why participants may remain reluctant to program their own

interactive graphics might be due to the time-consuming development process.

Some studies have already thematized that digital teaching added workload to

lecturers (Bright, 2012; Waycott et al., 2010,;Young et al., 2004). Lai (2010)

further stated that some teachers expressed doubts regarding the time and energy

investment linked to the design of interactive features for lesson. However, there

has been growing evidence for the value of interactivity in enhancing learning

experience (Evans & Gibbons, 2007; Zhang et al., 2006; Teoh & Neo, 2007).

In science and for education graphics are often used to visualize complex facts

and big amount of data. Static graphics are usually limited to visualize just one

aspect of the content. Interactive graphics contain regulator elements which allow

to manipulate the data behind the graphic. The subsequent effects are shown

immediately. This synchronicity has been stated as one important aspect of

interactivity (Liu & Schrum. 2002). Teacher can benefit from using interactive

graphics since they can explain gradually the content of the graphic.

Regarding teachers’ opinion towards the impact of the corona crisis on education,

most participants assigned the corona crisis an important role in advancing

digitalization in higher education. It´s impact was rated by the respondents to be

even higher than the invention of the internet at the end of the 20th century. This

results somehow contradicts educational pre-corona studies, which assign the

internet a crucial role in digitalization in higher education (Cookson, 2000,

Pittinsky, 2003; Stošić, & Stošić, I., 2015; Twigg, 2002). In a ‘future of the Internet’

survey conducted in 2012, digital stakeholders were asked to imagine education

in 2020. 60% agreed with the scenario “By 2020, higher education will be quite

different from the way it is today. There will be mass adoption of teleconferencing

and distance learning […]. There will be a transition to "hybrid" classes that

combine online learning components with less-frequent on-campus, in-person

class meetings.” (Anderson, Boyles & Rainie, 2012). The corona-crisis has

demonstrated that this future vision did not became fully true. In the current

situation universities often simply offer text-file and lecture captures to the

students, providing rather “remote” than online education (Gardner, 2020), raising


63

the question of how online teaching technologies can get promoted and

successfully implemented in the future. The corona crisis has shown the urgent

need for lecturers to get training and coaching in online teaching technologies

(Houlden & Veletsianos, 2020). Garder (2020) went further and declared the

corona crisis as a ‘wake-up call’ for universities to think of a ‘long-term digital

strategy’.

Our survey took place half a year after the corona outbreak and most of the

universities are finding their way to adapt into digital learning and teaching

methods. The aim of this paper was not to provide a solution to the rushed shift

into digital learning under this outstanding circumstance, but rather to reveal the

motivating fact, that lecturers indeed are willing to acquire knowledge in a field

they are still unexperienced in. Although our survey consists of a small sample

size, these participants represent a diverse range of age, institutes and

specialisation. They are all from different academic backgrounds, where

programming is not a common skill. As discussed before, the current

circumstances demand online teaching, but it is common for lecturers to lack

experience in this field. We recommend providing further coaching and support for

teaching staff to get actively involved in the development of digital teaching tools.

Funding




64

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GENERAL DISCUSSION

68

4. GENERAL DISCUSSION

The aim of this work was to provide scientific insights into the acceptance of

interactive graphics amongst teachers and students, and the overall applicability

of such graphics in veterinary education. This was evaluated in two studies

performed at the University for Veterinary Medicine in Hannover. For the first

study, interactive graphics were implemented into the veterinary medicine

lectures. In the second study, a two-day online workshop was conducted, where

members of the academic staff were taught basic programming skills to learn how

to develop interactive graphics. In both studies teachers and students were asked

to participate in voluntary questionnaires. In the following students’ and lecturers’

perception of teaching and learning with interactive graphics and the effect of the

online workshop on faculty members will be discussed.

4.1 Students’ perception

4.1.1 Effect on interest

Overall, 71% (233/326) of the students affirmed that interactive graphics had a

positive impact on their interest for the topic. Lecturers, who delivered class with

interactive graphics, confirmed the apparent positive influence on students’

interest, too. All lecturers involved (5/5) agreed or strongly agreed to have reached

more students while teaching with interactive graphics. Weissgerber et al. (2016)

suggested that integrating interactive graphics in scientific journals can be ‘an

effective strategy for increasing interest in published research’. The here

presented study provides evidence that this positive effect can also be seen when

employing interactive graphics for education. A common belief linked to

interactivity is the idea that it promotes active learning (Anderson, 2002; Muirhead

& Juwah, 200; Draper & Brown, 2004). Prammanee (2003) argued that interaction

can maintain and stimulate students’ motivation and interest. This is of particular

importance, since students’ interest has been recognized as a decisive factor for

learning success (Renninger et al., 2014; Hidi, 1990; Harp & Mayer, 1997). Studies

in this field confirm that interest is strongly related to long term retention and

motivation for learning (Schiefele, & Krapp, 1996). For veterinary education,

maintaining and promoting interest for the taught contents can be challenging.

GENERAL DISCUSSION

69

The curriculum covers a wide range of disciplines, offering students career

possibilities in diverse fields (Pritt & Case, 2018). Consequently, students get

confronted with multiple study contents which at first do not seem relevant for their

future career perspectives (Lane, 2008). In an investigative study amongst first

year veterinary students, Serpell (2005) yielded that more than 90% of the

respondents aimed to work in small-animal practice. A similar finding made

Cornish et al. (2016), who surveyed more than 800 students and revealed an

increased interest on companion animal practice. The three interactive graphics

employed in the presented study were designed for lectures where the link to this

career ambition might not be immediately apparent to students. Integrating

interactive graphics for these courses can possibly provide a way to increase

student engagement in these topics.

4.1.2 Perceived usefulness and ease of use

Simply promoting interest does not ensure students’ acceptance for interactive

graphics as digital teaching tool. The acceptance of web-based learning tools

amongst students has frequently been measured within the Technology

Acceptance Model (TAM) (Tarhini et al., 2013). In this model, perceived ease of

use is one determinant of the intention to make use of technology. When observing

the ease of use, students expressed confidence regarding their own handling

abilities. In total, 78% (254/327) agreed or strongly agreed to be able to use

interactive graphics by themselves and 86% (279/326) could imagine most of their

fellow students would do so too. The other determinant, perceived usefulness, can

be defined as the degree to which a student believes the technology will improve

his or her learning (Park, 2009). When analysing the effect on students’ learning,

82% (267/ 326) of the students claimed to have understood the topics taught with

interactive graphics. In total, 64% (210/326) disagreed or strongly disagreed the

statement “I was previously familiar with the taught content”. Moreover, 95.8%

(23/24) of the faculty members participating at the workshop believe that

interactive graphics facilitate learning. This finding shows a tendency towards the

didactic potential of interactive graphics. Subsequent studies need to be

conducted to evaluate whether integrating this interactive tool leads to mental

processing in the student’s mind and to learning during lecture, as suggested by

GENERAL DISCUSSION

70

Draper & Brown (2004). The promising result that interactive graphics promote

interest in students, can constitute here a solid basis and justification for further

studies.

4.1.3 Effect on information processing

According to the “cognitive theory of multimedia learning” the verbal and visual

information processing systems have limited processing capacities. When

designing instructional material, special attention must be paid to not overload

these systems (Mayer, 2017). When too much content is depicted within one static

graphic it can lose clarity. In consequence, the amount of information conveyed

through a static graphic must be limited or simplified. For concepts, which include

dynamic processes or complex relationships, limiting informational content is not

always the right approach. Animations and videos can be used to visualize such

dynamic processes. One important characteristic is their transience (Ainsworth &

VanLabeke, 2004). As stated by Hegarty (2004) “when one views an animation or

video, one views one frame at a time, and once the animation or video has

advanced beyond a given frame, it is no longer available to the viewer”. According

to the cognitive load theory, this places heavy demands on the working memory,

since information seen in videos and animations must be integrated with previous

and the subsequent shown information (Hegarty, 2004).

Interactive graphics can prevent students from cognitive overload in multiple ways.

Students have the chance to explore information step by step either through

adding, modifying, or removing information at their own pace or being guided

through the content by the teacher. This is made possible through different

regulator elements, which allow to highlight, label, or hide certain aspects or parts

of the graphic. Furthermore, tooltips, that are placed over regulatory elements or

additional tabs can provide further information such as user instructions, guides,

background knowledge about the current topic and references. These possibilities

can be used to construct an app that at first seems minimalistic in regards of

information content. These features can provide students that prefer learning at

their own pace a tool that is self-explanatory and easy to use, where underlying

principles can be explored freely. However, to achieve this positive effect, special

GENERAL DISCUSSION

71

attention must be paid to the user ’s interface design. With the variety of regulator

elements and the possibility to display several plots simultaneously, risk of

cognitive overload is still present.

4.2 Lecturers’ perception

4.2.1 Opinion towards digital media

Participating members of the academic staff had different experience backgrounds

regarding the usage of digital media for educational purpose. While lecturers from

the first study mostly had never used digital media for teaching before (4/5), more

experienced members of the academic staff participated in the second study.

Overall, 80% (20/25) of the workshop participants had already used digital media

in educational context before. A promising result was the positive influence

interactive graphics had on teachers’ opinions towards digital teaching in both

studies. In absolute, 80% (4/5) of the teachers from the first study claimed that

teaching with interactive graphics had a positive impact on their opinion towards

digital media usage for education. In the second study, 73,3% (11/15) of the faculty

members agreed to the statement “the online workshop had a positive impact on

my opinion towards digital teaching”. This finding supports the idea of Mahdizadeh

et al. (2008), who concluded that teachers’ attitude towards e-learning depends

on their first-hand experience using it. They recommend that “any program for

enhancing the actual use of e-learning environments should focus on teachers’

attitude towards e-learning”. Therefore, educators should be “assisted in preparing

useful content for their courses” (Mahdizadeh et al., 2008). In this work, lecturers

were supported actively in preparing useful content for their courses. First, by

implementing interactive graphics for their teaching purpose and second, by

teaching them in an online workshop how to do so on their own.

GENERAL DISCUSSION

72

4.2.2 Perceived ease of use and usefulness

Beside of the forementioned influence on teachers’ opinion towards digital

education, interactive graphics also had an impact on their teaching. In total,

91.7% (22/24) of the academic staff stated that interactive graphics facilitate

teaching and 95.8% (23/24) assessed that interactive graphics can help students

learn content. In the context of the TAM, these findings suggest that teaching with

interactive graphics lead to a positive impact on teachers’ job performance and

thus, can be perceived as useful. When analysing ease of use, the two groups of

involved lecturers had different roles in the development process of the interactive

graphics. While lecturers from the first study received a finished app based on

their functionality and layout wishes, members of the academic staff from the

second study were asked to implement these interactive graphics by themselves.

Since only 20% (5/25) of the workshop participants stated to have used R before,

most had to acquire knowledge in a field they were mostly unexperienced in. This

might explain why most participants did not feel able to program interactive

graphics on their own after the two workshop sessions. Only participants who had

programming skills in R (20%; 3/15) felt they were able to implement further

graphics for their own teachings. Here, the effort put on implementing an

interactive graphics equals an increased difficulty regarding ease of use within the

TAM framework.

GENERAL DISCUSSION

73

4.2.3 Workshop effect on teachers

After the first workshop session, where visualization possibilities and

functionalities of shiny apps and basic programming skills were introduced,

participants showed a high interest in interactive graphics. Several participants

put their newly acquired programming knowledge into practice and developed own

app ideas. In this process they received constant support and feedback from the

instructors and several apps were created (Figure 4).

Figure 4: Screenshot from the website, where the interactive graphics which have been

implemented within the framework of this project can be accessed. The hyperlink directs

the user to the apps. Several interactive graphics were implemented after the workshop.

GENERAL DISCUSSION

74

Active learning, coaching, support, and feedback has been recognized as

important features of effective professional development (Darling-Hammond et al.,

2017). In absolute, 85.7% (12/14) confirmed to be interested in using interactive

graphics for their teaching after the workshop. However, only those who had prior

programming skills (3/15) expressed the intention to implement own interactive

graphics. In a personal feedback several lecturers and members of the academic

staff expressed the wish for additional training and support in implementing

interactive graphics for their courses. Some investigative studies have confirmed

the potential of additional support after a teachers’ workshop. Watson (2006) for

example found out, that teachers who received additional support felt more

confident than those who just participated in the workshop. Carlson & Gadio

(2002) further stated that traditional one-time teacher training is not effective in

helping teachers to feel comfortable using technology without providing ongoing

pedagogical and technical support. It is likely, that given the chance to offer

subsequent workshops with additional coaching, teachers will be able to

implement own interactive graphics in the future. In line with other studies

regarding technology training, a pre- and post-design questionnaire was used to

measure the impact of a workshop on the teachers’ attitude towards interactive

graphics. Participants already had a positive opinion towards interactive graphics

before attending the workshop. This positive attitude remained unchanged after

completing the workshop. This finding is somewhat predictable, since attendance

to the workshop was voluntary and only those who perceived interactive graphics

to be beneficial for teaching would attend a training in this field. Here it is important

to revise the cost-benefit ratio. Acquiring the programming skills necessary to

implement own interactive graphics as well as the development process itself is

time-consuming. However, the effort put on implementing interactive graphics

bears no relation to the actual usefulness. Once an interactive graphic is designed,

it can be incorporated into e-learning modalities, shared with other institutions,

and be used repeatedly. Content or functions can be updated or improved to

accommodate any new insights and needs.

GENERAL DISCUSSION

75

4.2.4 Age effect

In this work no evidence was found that the attitude towards technology usage for

education is influenced by age. Workshop participants were asked to rate how

much time they would like to use digital media in class. Surprisingly, the older

participants (>40 years) voted for more time, than the younger ones. This

contradicts common beliefs that technology adoption is linked to age (Morris &

Venkatesh, 2000; Gilbert et al., 2004; O'bannon, & Thomas, 2014). However,

several educational studies have concluded that teachers’ technology adoption or

attitude is not age-related (e.g. Tweed, 2013; Guo et al, 2008; Mahdi & Al-Dera,

2013; Papadakis, 2018).

4.3 LIMITATIONS

Although a high agreement for interactive graphics amongst veterinary students

and lecturers was evidenced, this work raised some issues that need to be

reflected on. With only 5 participants in the first study and 25 in the second, the

sample size of the academic staff was quite small. Due to the study design, only

educators interested in interactive graphics participated at the survey. When

assessing the extent to which the results presented in this work are generalizable,

it should be kept in mind, that they might only be applicable for similar populations.

It is probable that a different attitude toward interactive graphics would emerge

when asking educators, which were not involved in the development process. One

possibility to strengthen the findings of this work would be through replicating the

study with a randomly selected group of educators. In turn, students’ participation

was not influenced by their interest towards interactive graphics. The integration

of interactive graphics into the classes was not announced previously. Students

attended class without knowing interactive graphics will be used. Therefore, their

participation in the survey was not biased by previous opinions and interests. A

further limitation of the study relates to measurement errors in attitudinal

questionnaire surveys. Several biases, such as the acquiesce and extreme

respond bias can lead to wrong conclusions. In the acquiesce bias, the respondent

tends to agree to all or most statements in the questionnaire. The incorporation of

negative worded items in the questionnaire can force respondents to disagree with

some statements (Qasem & Gul, 2014). This approach was adopted in

ZUSAMMENFASSUNG

76

questionnaires used within this work. However, questionnaires with a mix of

positive and negative worded statements have been critic ized for lowering the

reliability and validity (Qasem & Gul, 2014). The implementation of additional data

collection methods such as in-depth interviews or focus-groups studies could lead

to richer data and greater insights. This work reports on students’ and lecturers’

feedback regarding the use of interactive graphics. It needs to be considered, that

no claims on actual learning outcomes can be made. The here described overall

positive feedback of students and lecturers, however, can justify future studies,

where students’ performance is measured to address whether interactive graphics

have a didactic potential.

5. ZUSAMMENFASSUNG

Pamela Liebig (2021): Implementierung und Evaluierung interaktiver,

browser-basierter Grafiken in der tiermedizinischen Lehre

Im Rahmen des Digitalisierungs-Projekts „DigiStep“ wurden an der tierärztlichen

Hochschule Hannover erstmalig interaktive Grafiken für die tiermedizinische

Lehre implementiert. Ziel dieser Arbeit ist es, Akzeptanz und Anwendbarkeit

interaktiver Grafiken innerhalb der tiermedizinischen Ausbildung zu evaluieren.

Die Ergebnisse dieses Forschungsprojekts wurden in zwei Manuskripten

zusammengefasst und zur Veröffentlichung eingereicht. Grafiken sind häufig

Bestandteil tiermedizinischer Lehrveranstaltung, da sie Zahlendaten und

komplexe wissenschaftliche Zusammenhänge in einer Abbildung

zusammenzufassen. Der Informationsgehalt einer statischen Grafik ist jedoch

meist auf die Darstellung eines Aspekts beschränkt und dynamische Prozesse,

die eine Veränderung über Zeit beinhalten, lassen sich hierdurch nur schwer

darstellen. Heutzutage stehen Videos und Animationen bereit, um dynamischen

Zusammenhänge zu veranschaulichen. Meist fehlt hier jedoch die Interaktion

zwischen Studierenden und Lehrinhalt. Interaktive Grafiken verfügen über

zahlreiche Steuerungselemente, wodurch sich die Datengrundlage hinter einer

Grafik manipulieren lässt. Muster und Beziehungen werden hierdurch leicht

ersichtlich. In Vergangenheit waren zur Programmierung interaktiver Abbildungen

Kenntnisse in Java, HTML oder CSS nötig. Für diese Arbeit wurde jedoch auf die

ZUSAMMENFASSUNG

77

Programmiersprache R zurückgegriffen, die im akademischen Rahmen häufig zur

statistischen Auswertung und graphischen Visualisierung genutzt wird. Mittels der

Erweiterungsbibliothek „Shiny“ lassen sich diese interaktiven Grafiken in einem

Webbrowser darstellen und teilen. Diese so genannten „Shiny Apps“ wurden mit

positivem Ergebnis bereits in Forschung und in der Statistik Lehre eingesetzt,

fanden aber in der tiermedizinischen Lehre bisher noch kaum Anwendung. In

enger Zusammenarbeit mit den hiesigen Hochschuldozenten wurden Lehrinhalte

identifiziert, die mittels einer interaktiven Grafik gelehrt werden können. Dies

waren Themen, die zuvor mit statischen Grafiken gelehrt wurden oder zu denen

es bisher noch keine Abbildung gab. In der ersten Studie wurden drei interaktive

Grafiken für den Einsatz in tiermedizinischen Lehrveranstaltungen entwickelt.

Zwei davon wurden im klinischen Abschnitt (Tierernährung und

Lebensmittelkunde) eingesetzt und eine in der Vorklinik (Zoologie). Insgesamt 327

Studierende und 5 Dozierende wurden zu diesen Grafiken befragt. Die

Fragebögen ergaben eine breite Akzeptanz für interaktive Grafiken. Insgesamt

71.5% (233/326) der Studierenden gab an durch die interaktive Grafik mehr

Interesse für das vorgestellte Thema entwickelt zu haben und 76.1% (249/327)

bestätigten sich mehr interaktive Grafiken in der Lehre zu wünschen. In

Anbetracht des breit gefächerten Curriculums der tiermedizinischen Ausbildung

ist die Möglichkeit das Interesse für einzelne Lehrinhalte zu fördern von

besonderer Bedeutung. Die Tatsache, dass Studierende sich weniger für

Lehrinhalte interessieren, die scheinbar nicht direkt auf die zukünftige berufliche

Praxis vorbereiten, ist ein weit bekanntes Problem. Studierende mehr für diese

Themen zu interessieren, war unter anderen eines der Ziele des

Digitalisierungsprojekts. Die befragten Studierende und Dozenten gaben an,

gegenüber der Digitalisierung der Hochschullehre positiv eingestellt zu sein.

Bezüglich der Einstellung gegenüber interaktiven Grafiken sowie anderen

digitalen Lehrmedien konnte keine Geschlechts- oder Alterskorrelation festgestellt

werden. Studierende zeigten sich zuversichtlich selbst eine interaktive Grafik

bedienen zu können und trauten auch ihren Kommilitonen den Umgang zu.

Bezüglich der Lehreffektivität stimmte die große Mehrheit (81.9%; 276/326) damit

überein, das gelehrte Thema verstanden zu haben. Diese positiven Ergebnisse

können weitere Studien zur Untersuchung des didaktischen Potenzials

ZUSAMMENFASSUNG

78

interaktiver Grafiken rechtfertigen und eine solide Basis darstellen. Dozierende

zeigten sich ebenso positiv eingestellt gegenüber interaktiven Grafiken. Sie

stimmten zu, mehr Studierende durch interaktive Grafiken erreicht zu haben und

sahen einen klaren Vorteil in ihrem Nutzen. Auf diesem Ergebnis aufbauend

wurden Dozierenden und wissenschaftlichen Mitarbeitern ein zweitägiger Online-

Workshop zur Vermittlung grundlegender Programmierkenntnisse in R und Shiny

angeboten. Dozierende erhielten zur Erstellung eigener interaktiver Grafiken

fertige Programmiervorlagen und Arbeitsblätter. Insgesamt nahmen 25 Mitarbeiter

der Hochschule teil. Diese wurden gebeten vor Beginn und nach Ende des

Workshops einen Online-Fragebogen auszufüllen. Die Teilnehmer hatten

mehrheitlich keine bis sehr geringe Programmiererfahrung, hatten jedoch bereits

digitalen Lehrmedien verwendet. Auf die Frage, zu wie viel Prozent digitale

Lehrmedien im Unterricht eingesetzt werden sollten, gaben die Teilnehmer im

Mittel 41.2% an. Im Hinblick auf das Alter der Befragten fiel auf, dass die über 40-

Jährigen mehr Zeit mit digitalen Lehrmedien unterrichten wollen als die unter 40-

Jährigen. Dies widerspricht der landläufigen Meinung, dass der Umgang und

Wunsch nach Technik in der Lehre altersgebunden sei. Bezüglich interaktiver

Grafiken gaben 95.8% (23/24) der Teilnehmer an, dass interaktive Grafiken

Studierenden das Lernen erleichtern und 91.7% (22/24) fanden interaktive

Grafiken zur Vermittlung von Lehrinhalten hilfreich. Nach dem Ende des

Workshops gaben nur diejenigen mit Programmierkenntnisse an sich die

Entwicklung eigener interaktive Grafiken zuzutrauen. Ursächlich hierfür kann die

kurze Dauer des Workshops sein. Trotz der gegenwärtigen Zurückhaltung der

Dozierenden, selbst interaktive Grafiken zu programmieren, kann der Workshop

dennoch als Erfolg angesehen werden. Im Rahmen des Workshops sind bereits

einige interaktive Grafiken entstanden, die als Teil des E-Learning Programms der

hiesigen Hochschule angeboten werden. Hochschuldozenten zeigten ein breites

Interesse am Einsatz interaktiver Grafiken in ihren Lehrveranstaltungen. Seitens

der Studierende konnte auch ein großes Interesse am Einsatz interaktiver

Grafiken festgestellt werden. In Anbetracht dessen, ist anzunehmen, dass die

Implementierung weiterer interaktiver Grafiken durch zusätzliche Workshop

Angebote und technischen Support erreicht werden kann. Von diesem Angebot

könnten sowohl Studierende als auch Dozierende klar profitieren

SUMMARY

79

6. SUMMARY

Pamela Liebig (2021): Implementation and evaluation of interactive, browser-

based graphics in veterinary education

Within the framework of the digitalization project “DigiStep” interactive graphics

were implemented at the University for Veterinary Medicine in Hannover. The aim

of this work is to evaluate for the first time, the applicability and acceptance of

interactive graphics amongst students and lecturers in veterinary education. The

results of this work are described in two manuscripts, which were submitted for

publication. Graphics are frequently used in veterinary education to visualize data

and complex scientific relationships. However, the information content of a static

graphics is limited to depict one certain aspect of the target content. Dynamic

processes, which include change over time, can barely be visualized. Nowadays,

videos and animations can be employed to make dynamic processes more

accessible to students. However, student-content interaction is rarely provided.

Interactive graphics in turn include several regulator elements, which allow to

manipulate the data behind a graphic. Thus, students can explore and recognize

relationships and patterns more easily. In the past programming knowledge in

JAVA, HTML or CSS was necessary to develop interactive graphics. In this work

the programming language R, which is commonly used in academic environment

for statistical analysis and graphical visualizations, is used. With the package

“shiny” these graphics can be displayed and shared within a web browser. The so

called “shiny apps” have found broad acceptance in research and in statistic

education but are rarely used for veterinary education.

In close collaboration with the local lecturers, appropriate learning content was

identified. These topics were previously taught using static graphics or lacked a

graphical visualization. In the first study, three interactive graphics were

implemented. Two were employed in the clinical part (animal nutrition and food

science) and one in the preclinical part (zoology) of the veterinary curriculum. In

total, 327 students and 5 lecturers were asked to evaluate interactive graphics.

The questionnaire revealed a broad acceptance for interactive graphics amongst

students and educators in veterinary education. Overall, 71.5% (233/326) of the

students affirmed to be more interested in the topics taught with interactive

SUMMARY

80

graphics, and 76.1% (249/327), stated to wish to discuss more topics with

interactive graphics. Considering the broad curriculum in veterinary education, the

possibility to promote interest in certain topics is of special importance. The fact

that students are less interested in topics which at first seem to not prepare them

for their future career, is a well-known problem in veterinary education. Promoting

interest in these topics was one of the objectives of this digitalization project.

Students and lecturers were open minded towards digitalization in higher

education. Regarding their attitude towards interactive graphics and other digital

teaching tools, no age or gender correlation was demonstrated. Students

expressed confidence regarding their handling of interactive graphics and

estimated their fellow students would do so, too. Regarding the effect on learning

experience, most students (81.9%; 276/326) affirmed to have understood the

taught contents. These positive findings can constitute a justification and solid

basis for further studies regarding the didactic potential of interactive graphics in

veterinary education.

Lecturers also had a positive attitude towards interactive graphics. They agreed

to have reached more students using interactive graphics and saw a clear benefit

in using interactive graphics. Basing on these results, an online workshop for

teaching basic R and shiny skills was offered to the local faculty members. In total

25 faculty members participated. After first being introduced to R and shiny,

participants received ready to use programming templates and work sheets to

develop own interactive graphics. Participants mostly had no prior programming

skills but had used digital teaching media before. Regarding the question how

much time they would like to spend with digital media in class, the mean time was

41.2%. Surprisingly, older participants (>40 years) wished to discuss more topics

with digital media than the younger ones. This contradicts the popular opinion that

technology acceptance and usage amongst educators is linked to age. Regarding

interactive graphics, 95.8% (23/24) of the participants agreed that interactive

graphics help students understand teaching content and 91.7% (22/24) think they

are helpful in teaching them. After completing the workshop only those with prior

programming experience claimed to feel able to develop own interactive graphics.

The reason for this can be the short duration of the workshop. Even if participants

were reluctant to program interactive graphics on their own, the workshop still was

SUMMARY

81

successful. Within the framework of this workshop, several interactive graphics

were developed and now complement the e-learning selections at our university.

Considering lecturers’ and students’ high interest for interactive graphics, it is

likely that further training and technical support would promote and encourage the

implementation of more interactive graphics. Students and lecturers could clearly

profit from this offer.

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ACKNOWLEDGEMENTS

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8. ACKNOWLEDGEMENTS

First, I would like to thank Prof. Dr. Klaus Jung for the great opportunity to do this

work. I am grateful for the excellent supervision, the continuous support, and the

possibility to acquire knowledge in a new field.

Many thanks go to Prof. Dr. Heike Pröhl, Dr. Nadine Sudhaus-Jörn, Dr. Julia

Hankel and Prof. Dr. Christian Visscher whose collaboration were essential for this

project to be successful. I am thankful for your interest and help in implementing

the interactive graphics in your courses. I also want to express my gratitude to all

the members of the academic staff who participated at the online workshop,

especially to Dr. Viviane Filor, Dr. Marina Scheumann and Dr. Martina Buchholz,

for your helpful feedback and your support.

Additionally, I would like to thank the Ministry for Science and Culture of Lower

Saxony for the financial support of this work.

Thanks to Jörn Wrede for his technical support and to Magdalena Kircher, Moritz

Kohls and Jessica Krepel for the nice working atmosphere. I wish you all the best

and success for the future.

Babak Saremi, there are not enough words to express my gratitude for your

constant help, your infinite patience, and your encouragement. Thanks for being

my stress reliever, my laughter therapist, and my partner in crime. I am deeply

grateful to have meet you through this project.

Un gracias enorme para ti mamá. Estoy agradecida por tú apoyo incondicional,

por siempre creer en mi y por tú amor. Me alegra poder compartir cada momento

importante de mi vida contigo. Sin ti nunca hubiera llegado tan lejos. Me siento

afortunada de tenerte como mi mejor amiga. Gracias!

APPENDIX

93

9. APPENDIX

9.1. Students‘ questionnaire (English)

Stiftung Tierärztliche Hochschule Hannover University of Veterinary Medicine Hannover

Evaluation interactive graphics in veterinary education

Dear Sir or Madam,

Thanks for your participation!


Pamela Liebig, Veterinarian Promoted by:

1/2

Institute for Animal Breeding and Genetics Department of Genomics and

Bioinformatics of Infectious Diseases

Prof. Dr. Klaus Jung Bünteweg 17p 30559 Hannover Tel. +49 511 953-8878

Fax +49 551 953-8582

[email protected]

within the project DigiStep our work group develops interactive graphics for teach-

ing in veterinary education. With this questionnaire we want to evaluate this

new teaching tool and ask for your participation. The information will be used

exclusively for project´s purpose.

APPENDIX

94

A) Demographic questions

Gender: ⃝ male ⃝ female ⃝ not specified Age: ______ years

B) Questions regarding interactive graphics

1. I can imagine that the majority of students will handle easily interactive graphics.

strongly disagree ⃝ ⃝ ⃝ ⃝ ⃝ strongly agree

2. I´d wish to have more interactive graphics in veterinary school.


3. I can image using this tool because it´s intuitive.


C) Effects on learning behaviour

4. I was previously familiar with the taught content.


5. I understood the teaching contents taught by the interactive graphic.


6. The interactivity of the graphic had a positive impact on my interest about the

Taught content.


7. The interactive graphic had no benefit to the course.


D) Digital media usage

8. I also use following digital media (multiple selection possible).

□ e-Learning at university □ online-videos □ forum □ none □else (_____________)

9. Digitalization is a chance to improve academic education.


2/2 www.tiho-hannover.de

http://www.tiho-hannover.de/

APPENDIX

95

9.2. Students’ questionnaire (German)


Evaluierung interaktiver Grafiken

in der tiermedizinischen Lehre

Sehr geehrte Damen und Herren,

Vielen Dank für Ihre Teilnahme!

Prof. Dr. Klaus Jung Pamela Liebig, Tierärztin

1/2

Gefördert durch:

Institut für Tierzucht und

Vererbungsforschung AG Genomics and Bioinformatics

of Infectious Diseases

Prof. Dr. Klaus Jung Bünteweg 17p 30559 Hannover Tel. +49 511 953 8878

Fax +49 551 953-8582

[email protected]

im Rahmen des Projekts DigiStep entwickelt unsere AG interaktive Grafiken zum Einsatz in der tiermedizinischen Lehre. Mit dieser Umfrage möchten wir dieses neue Lehrmedium evaluieren und bitten Sie um Ihre Teilnahme. Selbstverständlich werden Ihre Angaben ausschließlich für Projektzwecke verwendet.

APPENDIX

96

A) Fragen zur Person

B) Fragen zu den interaktiven Grafiken 1. Ich kann mir gut vorstellen, dass der Mehrheit der Studierenden der Umgang mit

interaktiven Grafiken leicht fallen könnte.

2. Ich würde mir mehr interaktive Grafiken in den Lehrveranstaltungen des

Tiermedizinstudiums wünschen.

3. Ich kann mir gut vorstellen selbst dieses Tool zu nutzen, da es intuitiv zu bedienen ist.

C) Auswirkungen auf das Lernverhalten 4. Mit dem dargestellten Sachverhalt in der interaktiven Grafik war ich bereits vor der

Lehrveranstaltung vertraut.

5. Die in der interaktiven Grafik gelehrten Inhalte habe ich verstanden.

6. Durch die Interaktivität der Grafik wurde mein Verständnis für die Thematik positiv

beeinflußt.

7. Ich finde, dass die Integration dieser Grafik in die Lehrveranstaltung keinen

Mehrwert im Hinblick auf die Lehre des dargestellten Sachverhalts mit sich bringt.

D) Nutzung digitaler Medien 8. Ich nutze in meinem Studium noch folgende digitale Lehrmedien (Mehrfachauswahl

möglich)

9. Ich sehe die Digitalisierung als Chance zur Verbesserung der Hochschullehre

2/2 www.tiho-hannover.de

Geschlecht: ⃝ männlich ⃝ weiblich ⃝ keine Angaben Alter: ______ Jahre

trifft gar nicht zu ⃝ ⃝ ⃝ ⃝ ⃝ trifft voll zu

□ E-Learning-Angebote der TiHo □ Online-Videos □ Foren □ keine □sonstige

(___________________)








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97

9.3. Lecturers’ questionnaire (English)


Evaluation interactive graphics in veterinary education

Dear Professors,

A) Question regarding the handling of interactive graphics.

1.I felt secure handling this teaching tool.

strongly disagree ⃝ ⃝ ⃝ ⃝ agree

2. I can imagine that the majority of teachers will handle easily this teaching tool.


3. I wish to have more interactive graphic in my classes.


1/1

Institute for Animal Breeding and Genetics Department of Genomics and


Prof. Dr. Klaus Jung Bünteweg 17p 30559 Hannover Tel. +49 511 953-8878

Fax +49 551 953-8582

[email protected]

you used an interactive graphic in your lecture. With this questionnaire we want

to evaluate this new teaching tool and ask you for your participation. Of course,

your information will be analysed anonymously and exclusively used for project

propose.

APPENDIX

98

B) Effects on teaching

4. In my opinion, the interactive graphic provided no benefit to the course.


5. I feel like I could have reached more students by teaching with interactive graphic.


C) Usage of digital teaching tool

6. I have used digital teaching tools (e.g. CASUS, online lecture) in my classes before.

⃝ Yes, following ________________ ⃝ No

7. The usage of interactive graphic had a positive effect on my opinion towards digital media

in higher school education.

⃝ Yes ⃝ No

8. Digitalization is a chance to improve academic education.

Strongly disagree ⃝ ⃝ ⃝ ⃝ agree

D) Please indicate here your improvement wishes or future design ideas.

2 / 2 www.tiho-hannover.de

APPENDIX

99

9.4. Lecturers’ questionnaire (German)

Stiftung Tierärztliche Hochschule Hannover

University of Veterinary Medicine Hannover

Evaluierung interaktiver Grafiken

in der tiermedizinischen Lehre

A) Fragen zum Umgang mit interaktiven Grafiken

1. Ich habe mich im Umgang mit dem Lehrtool sicher gefühlt.

2. Ich kann mir gut vorstellen, dass der Mehrheit der Dozierenden der Umgang mit diesem Tool leicht fallen wird. 3. Ich würde mir mehr interaktive Grafiken in meinen Lehrveranstaltungen wünschen.

1/1




Institut für Tierzucht und

Vererbungsforschung AG Genomics and


Prof. Dr. Klaus Jung Bünteweg 17p 30559 Hannover Tel. +49 511 953 8878

Fax +49 551 953-8582

[email protected]

Sehr geehrte Damen und Herren,

in Ihrer Lehrveranstaltung haben Sie eine interaktive Grafik eingesetzt. Mit dieser

Umfrage möchten wir dieses neue Lehrmedium evaluieren und bitten Sie um Ihre

Teilnahme. Selbstverständlich werden Ihre Angaben anonym und vertraulich bearbeitet

und ausschließlich für Projektzwecke verwendet.

APPENDIX

100

B) Auswirkungen auf die Lehrtätigkeit 4. Der Einsatz interaktiver Grafiken in meiner Lehrveranstaltung bringt meiner Meinung nach keinen Mehrwert im Hinblick auf die Vermittlung des dargestellten Sachverhalts.

5. Ich habe den Eindruck, dass der gelehrte Inhalt durch den Einsatz interaktiver Grafilken mehr Studierende erreicht haben könnte, als durch den Einsatz statischer Abbildungen. C) Nutzung digitaler Lehrmedien 6. Ich habe bereits früher andere digitale Lehrmedien (z.B. CASUS-Fälle, Vorlesungsaufzeichnungen,) für meine Lehrveranstaltungen eingesetzt. 7. Die Nutzung interaktiver Grafiken hat meine Meinung zu digitalen Lehrmedien positiv beeinflußt. 8. Ich sehe die Digitalisierung als Chance zur Verbessung der Hochschullehre. D) Bitte geben Sie Ihre Verbesserungswünsche zur eingesetzten interaktiven Grafik und ggf. zukünftige Gestaltungsideen an.

2 / 2 www.tiho-hannover.de

⃝ Ja ⃝ Nein



trifft gar nicht zu ⃝ ⃝ ⃝ ⃝ ⃝ tri fft voll zu

⃝ Ja, folgende ________________ ⃝ Nein

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9.5 Pre-workshop questionnaire (English)

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9.6 Post-workshop questionnaire (English)

APPENDIX

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9.7 Pre-workshop questionnaire (German)

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APPENDIX

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9.8. Post-workshop questionnaire (German)

112

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