Integrating Science and Technology: Using TechnologicalPedagogical Content Knowledge as a Framework to Studythe Practices of Science Teachers
Rose M. Pringle • Kara Dawson • Albert D. Ritzhaupt
Published online: 13 March 2015
� Springer Science+Business Media New York 2015
Abstract In this study, we examined how teachers in-
volved in a yearlong technology integration initiative
planned to enact technological, pedagogical, and content
practices in science lessons. These science teachers, en-
gaged in an initiative to integrate educational technology in
inquiry-based science lessons, provided a total of 525 les-
son plans for this study. While our findings indicated an
increase in technology-related practices, including the use
of sophisticated hardware, very little improvements oc-
curred with fostering inquiry-based science and effective
science-specific pedagogy. In addition, our conceptual
framework, technological pedagogical content knowledge,
as a lens to examine teachers’ intentions as documented in
their lesson plans, provided an additional platform from
which to investigate technology integration practices
within the ambit of reform science teaching practices. This
study, therefore, contributes knowledge about the structure
and agenda of professional development initiatives that
involve educational technology and integration into content
knowledge disciplines such as science.
Keywords Integrating science and technology �Technological pedagogical content knowledge � Sciencelesson plans
Introduction
The National Education Technology Plan 2010 (NETP)
developed by the United States Department of Education’s
Office of Educational Technology signals a strong com-
mitment to the integration of technology in all levels of the
educational system. This plan recognizes the integral role
of technology in every aspect of daily lives and as such
calls for educators to leverage technology-based learning in
order to ensure that students are provided with authentic,
engaging, and meaningful learning experiences (NETP
2010). Likewise, other science educational reform docu-
ments [e.g., American Association for the Advancement of
Science (AAAS) 1989; 1993; and National Research
Council (NRC) 1996] have recommended the use of
technology to promote students’ participation in learning
experiences that allow them to adopt the attitudes and
dispositions typical of scientists (McNeill and Pimentel
2010; Slykhuis and Krall 2011). In response to these
mandates, science educators and school leaders have re-
newed their efforts to promote the integration of learning
technologies and inquiry-based practices into their in-
struction in order to improve students’ understanding of
science and also to better prepare them for the twenty-first
century workforce. Technologies, from probes to comput-
ers and digital whiteboards to smartphones, have the po-
tential to enhance students’ understanding of natural
phenomena (Hug et al. 2005; NRC National 1996) and to
successfully engage them in the learning process (Blu-
menfeld et al. 2000). With increased accessibility to tech-
nologies, more science teachers have begun to embrace
their use as essential for illustrating and reinforcing science
concepts, promoting student learning, and enhancing
problem solving and data analysis (Guzey and Roehrig
2009; Slykhuis and Krall 2011).
R. M. Pringle � K. Dawson � A. D. Ritzhaupt (&)
School of Teaching and Learning, College of Education,
University of Florida, 2423 Norman Hall,
PO Box 117048, Gainesville, FL 32611, USA
e-mail: [email protected]
123
J Sci Educ Technol (2015) 24:648–662
DOI 10.1007/s10956-015-9553-9
Context
Since 2002, state education agencies have awarded mil-
lions of dollars in Enhancing Education through Tech-
nology (EETT) funding to support technology-rich
classroom environments and professional development
experiences that increase effective technology integration
practices and student learning across the USA [State
Educational Technology Directors Association (SETDA)
2011]. This study is situated within one such statewide
initiative in Florida designed to accomplish the following
goals: (1) improve the technology integration practices of
math and science teachers, (2) increase access to techno-
logical tools and infrastructure, (3) strengthen teacher and
administrator ICT skills, (4) strength student ICT skills,
and (5) improve student achievement (Dawson et al. 2012).
This particular study is focused on the technology inte-
gration practices of science teachers (i.e., Goal 1) par-
ticipating in this yearlong initiative.
The technology integration initiative involved 28 funded
projects within 24 school districts. These districts represent
the diversity of the state with a mix of urban and rural
districts. Student numbers in these districts vary from ap-
proximately 1000 students in the district to nearly 200,000
students. Likewise, teacher population varies from less
than 100 teachers to more than 13,000. Economic condi-
tions in the districts also vary, with the number of students
on free or reduced lunches ranging from 36 to 100 %, the
number of students living in poverty ranging from 10 to
29 %, and the unemployment rates ranging from 8 to 16 %.
During the initiative, teachers were engaged in a four-
day statewide professional development program. This
professional development provided a forum for educators
to collaborate and engage in learning experiences for
themselves and their students, using digital tools. Teachers
funded through this initiative as well as teachers from non-
funded districts participated in the professional develop-
ment program. The program was led by educational tech-
nology specialists and focused on technologies that could
be used across content areas such as digital audio, digital
video, and presentation tools. It was neither focused on
science nor led by science educators.
This statewide professional development was comple-
mented by local efforts throughout the grant period. These
localized activities allowed individual school districts to
make decisions regarding professional development based
on their own needs, but the mechanisms by which districts
reported this professional development make it impossible
to richly describe the professional development within or
across projects. Required self-reports from district leaders
suggest that exemplary professional development features
such as access to support and resources, opportunities for
collaboration with peers, and opportunities to plan for
technology use within the context of science content
knowledge were present in many of the local professional
development efforts (Dawson et al. 2012).
Research Questions
Our study contributes to the literature base by examining
the way science teachers participating in a yearlong tech-
nology integration initiative used technology in their sci-
ence lesson plans. While these uses cannot be directly
linked to particular components of the initiative such as
professional development or the acquisition of particular
technology tools, understanding how teachers use tech-
nology is important in and of itself (Lei 2007; Darling-
Hammond 2000). Specifically, the following research
questions guided the study:
1. In what ways do science teachers involved in a
yearlong technology integration initiative enact tech-
nological, pedagogical and content practices in
lessons?
2. In what ways, if any, do these practices change during
a yearlong technology integration initiative?
Conceptual Framework
Technological pedagogical content knowledge (TPACK)
was used to frame this study and capture insights into
science teachers’ practices with technology. TPACK was
selected because it organizes the types of knowledge
needed in order to integrate technology in K-12 teaching
and learning based on technology, pedagogy, and content
knowledge (Mishra and Koehler 2006). TPACK builds on
pedagogical content knowledge (PCK) literature first pro-
posed by Shulman (1986). Shulman conceptualized PCK as
specialized knowledge distinguishing the teacher from the
content specialist and included, ‘‘an understanding of how
particular topics, problems, or issues are organized, pre-
sented, and adapted to the diverse interests and abilities of
learners, and presented for instruction’’ (Shulman 1986,
p. 8). While PCK has two primary components—pedagogy
and content—TPACK adds a third component—tech-
nology. Within the TPACK framework are a total of seven
constructs visually represented in the three-circle Venn
diagram shown in Fig. 1.
The three major constructs include the following: (1)
technological knowledge (TK) which refers to knowledge
about technologies for use in teaching and learning; (2)
pedagogical knowledge (PK) which refers to the processes
and methods of teaching and learning; and (3) content
knowledge (CK) which refers to the subject area
J Sci Educ Technol (2015) 24:648–662 649
123
understandings. These three major constructs intersect to
form three additional constructs: (4) technological peda-
gogical knowledge (TPK); (5) pedagogical content
knowledge (PCK); and (6) technological content knowl-
edge (TCK). Each construct refers to the merger of two
types of knowledge. For example, technological pedago-
gical content knowledge refers to uniting knowledge
of teaching and learning pedagogy with knowledge of
technology. TPACK lies within the center triadic inter-
section and represents a merger of all three types of
knowledge.
Previously, TPACK has been used as a framework to
support research on technology integration including case
studies of mathematics teachers involved in a learner-cen-
tered professional development project (Polly 2011) and
mathematics and science preservice teachers enrolled in
methods courses (Neiss 2005); survey research to ascertain
K-12 online teachers perceptions of their TPACK knowl-
edge (Archambault and Crippen 2009); studying TPACK
development in faculty and students in a learning technology
by design seminar (Koehler and Mishra 2005); interpretive
research examining growth of TPACK knowledge exhibited
by inservice teachers enrolled in an online graduate course
(Niess et al. 2010); and design-based research to support
TPACK development in preservice teachers (Mishra and
Koehler 2006). In each case, TPACK constructs were de-
fined within the context of the study.
However, some have questioned the practicality of
measuring TPACK as a multi-dimensional construct (Ar-
chambault and Barnett 2010; Brantley-Dias and Ertmer
2013). For instance, Brantley-Dias and Ertmer (2013)
criticize the TPACK framework for not clearly gauging
what types of pedagogy or curricula provide a ‘‘best fit’’ for
technology integration. Further, Archambault and Barnett
(2010) call into question the theoretical foundations of
TPACK by stating that Shulman’s PCK operated with
difficult to define domains that make the overall construct
unclear. Brantley-Dias and Ertmer (2013) state that
TPACK possesses a critical flaw of being both too large
(seven distinct knowledge types) and too small (compart-
mentalized) for practical use or measure.
In this study, the TPACK constructs were defined using
literature from teaching and learning, science education,
and educational technology. For example, technological
content knowledge (TCK), or the merger of technology and
content knowledge, was represented by the types of sci-
ence-specific technologies teachers used in their lesson
plans, and the pedagogical content knowledge was repre-
sented by evidence of inquiry-based science teaching
(Michaels et al. 2008). These definitions are further de-
scribed later in the paper.
Method
Study Design
There is a precedent for using lesson plans and other class-
room artifacts as proxies for teacher practices (Darling-
Hammond 2010; Jacobs et al. 2008; Silk et al. 2009; Silver
et al. 2009). Examining lesson plans can provide insight into
teachers’ approaches to science teaching and learning.
Furthermore, lesson plans ‘‘allow for evaluation of longer
‘chunks’ of planned instruction, allowing insight into the
teachers’ decisions about sequence of and relationships be-
tween activities and topics as well as their assessment
strategies, neither of which are commonly evident when
observing a single class period’’ (Jacobs et al. 2008, p. 1098).
Lesson plans provide a better idea, compared to a snapshot
observation of the enacted curriculum, of teachers’ beliefs
about teaching science with technology and reflect how
teachers envision the integration of their preferred tech-
nology into contemporary science teaching practices
(Brown 1998). In this study, we used lesson plans as proxies
for teacher practice. We embraced the process of lesson
planning as a crucial component of teachers’ practices.
The TPACK framework provided us with a way to or-
ganize the types of knowledge needed in order to integrate
technology in science teaching and learning. It also al-
lowed us to develop coding criteria for the lesson plans.
While the TPACK framework is inherently complex and
contextually bound (Mishra and Koehler 2006), this study
separated the components in order to explore science and
technology integration practices in a way that is consistent
Fig. 1 Technological pedagogical content knowledge framework
650 J Sci Educ Technol (2015) 24:648–662
123
and reliable across multiple lesson plans and multiple re-
viewers. We recognized that knowledge and practice are
related but not synonymous. While we used a knowledge
framework (i.e., TPACK) to guide our study of teacher
practice, we understood that in many cases, we were cod-
ing information about practice that might not represent the
complex nature of teacher knowledge.
We also recognized our results were limited by the in-
formation on which we chose to focus and on the quality
and level of detail provided in the lessons plans. We ad-
dressed these limitations in several ways. First, we defined
our criteria based on literature in science education and
educational technology. Second, our research team in-
cluded both science educators and educational tech-
nologists. Third, we conducted extensive reviewer training
and inter-rater agreement work. Finally, we provided an
online template to collect consistent information from the
teachers and the review process from the reviewers.
Sample
Participating science teachers were asked to submit their
best science lesson using technology at the beginning of the
technology integration initiative and then again at the end.
Teachers submitted their lessons through an online system
that required information such as lesson title, grade level,
content area, estimated time, objectives/standards, proce-
dures, and assessments (see Fig. 2). All submissions were
time stamped to determine whether they were submitted at
the beginning or end of the initiative. The system was
closed in the middle of the initiative to easily identify pre-
and post-submissions. Each lesson plan was reviewed for
completeness and to ensure a science focus. The research
team analyzed a total of 525 lesson plans. Of the 525 lesson
plans, 306 were pre-lessons and 219 were post-lessons.
Coding Criteria
Teacher practices were identified using literature-based
indicators related to six constructs identified in the TPACK
framework and described earlier. Table 1 overviews these
literature-based indicators and each TPACK component.
Technological Knowledge
TK was represented by the general software and hardware
used in the lesson plans. Lists of possible software (see
Table 2) and hardware (see Table 3) were modified from two
valid and reliable instruments used in previous studies of
technology use (Hogarty et al. 2003; Lowther andRoss 2001).
Pedagogical Knowledge
PK was represented by the attributes of meaningful learn-
ing as defined by (Jonassen et al. 2003) and identified in the
Fig. 2 Lesson plan submission
tool
J Sci Educ Technol (2015) 24:648–662 651
123
lesson plans. Specifically, reviewers looked for evidence of
four attributes of meaningful learning: (a) active; evidence
of students developing knowledge and skills by interacting
with their environment (i.e., manipulating objects, ob-
serving phenomena, debating, and role-playing), (b) con-
structive; students representing their learning in the
creation of artifacts, (c) authentic; learning situated in a
meaningful real-world context, and (d) cooperative; stu-
dents engage in negotiations leading to the construction of
new knowledge (Jonassen et al. 2003). These attributes are
not mutually exclusive and reviewers selected as many
attributes as were evident in the lesson (Morrison et al.
2007; Wiggins 1990). PK was also represented by the
assessment methods articulated in the lesson plan. Re-
viewers retrieved this information from the assessment
section of the lesson plan only.
Content Knowledge
CK was retrieved from the objectives and standards sec-
tions of the lesson plan and not inferred from other areas of
the lesson plan. The list of science topics came from
Florida’s Next Generation Sunshine State Standards
(FDLOE 2010).
Technological Pedagogical Knowledge
Technological pedagogical knowledge (TPK) was repre-
sented using the five-level continuum for technology inte-
gration initially developed during the Apple Classrooms of
Tomorrow (ACOT) study (Sandholtz et al. 1996). These
five levels were (a) entry, (b) adoption, (c) adaptation,
(d) infusion, and (e) transformation. The level of
Table 1 Coding criteria in TPACK framework
TPACK construct Review criteria Supporting literature
Content knowledge (CK) Science topics FLDOE (2010)
Pedagogical knowledge (PK) Attributes of meaningful learning
environments, and assessment practices
Jonassen et al. (2003), Morrison et al. (2007),
Wiggins (1990)
Pedagogical content knowledge (PCK) Science practices & cognitive demand for
content area learning
Michaels et al. (2008), Silver et al. (2009)
Technological pedagogical knowledge
(TPK)
Level of integration Sanholtz et al. (1997)
Technological knowledge (TK) General hardware & software Hogarty et al. (2003), Lowther and Ross (2001)
Technological content knowledge (TCK) Science software Kersaint (2003)
Table 2 Software tools in
lesson plansSoftware Pre-lessons (%) Post-lessons (%) v2 p value
Internet browser 45.75 63.93 16.228 0.0001
Presentation 34.64 42.92 3.368 0.0665
Web 2.0 tools 5.56 20.09 24.843 \0.0001
Digital video software 9.80 17.81 6.49 0.0108
Word processing/desktop publishing 8.82 9.59 0.022 0.8821
Digital audio software 7.19 7.76 0.0059 0.9388
Digital imaging software 2.29 7.31 6.523 0.0106
Other 1.63 5.02 3.888 0.0486
Testing software 2.29 4.57 1.451 0.2283
Communication tools 0.65 3.65 4.656 0.031
Spreadsheet 7.84 2.74 5.253 0.0219
Concept mapping 2.61 1.83 0.0862 0.7691
Online textbooks 0.33 1.83 1.656 0.1981
Database 0.33 1.37 0.708 0.4002
Draw/paint/graphics 0.33 0.91 0.0796 0.7779
Authoring 0.98 0.91 0.14 0.708
Digital animation 0.00 0.46 0.0311 0.8601
CD reference 0.65 0.46 0.0915 0.7623
Planning 0.00 0.00 – –
Programming 0.00 0.00 – –
652 J Sci Educ Technol (2015) 24:648–662
123
technology integration was determined using descriptions
from the Technology Integration Matrix, a nationally rec-
ognized tool for identifying technology integration prac-
tices (Allsopp et al. 2007). For example, the following
technology integration descriptors show how entry and
transformational levels were defined in the manual created
for reviewers (Dawson et al. 2011). Details about the re-
viewer training are discussed later.
Entry Level: Typically the teacher uses technology to
deliver curriculum content to students. Entry level
activities may include listening to or watching con-
tent delivered through technology or working on ac-
tivities designed to build fluency with basic facts or
skills, such as drill-and-practice exercises. In a lesson
that includes technology use at the Entry level, the
students may not have direct access to the technology
they may use technology with no stated purpose (i.e.,
taking digital pictures but not doing anything with
them). Decisions about how and when to use tech-
nology tools as well as which tools to use are made
by the teacher. Students solving problems or ma-
nipulating items on an interactive whiteboard usually
occur at this level as well.
Transformational Level: Students use technology
tools flexibly to achieve specific learning outcomes.
They are encouraged to use technology tools in un-
conventional ways and are self-directed in combining
the use of various tools. The teacher serves as a
guide, mentor, and model in the use of technology. A
key distinguishing feature between Infusion and
Transformation is that technology tools are often used
to facilitate higher order learning activities that would
not otherwise have been possible, or would have been
difficult to accomplish without the use of technology.
Pedagogical Content Knowledge
Pedagogical content knowledge (PCK) was represented by
the cognitive demand of the lesson in terms of content area
learning. Cognitive demand is the kind and level of
thinking required of students during a learning experience.
Criteria for low- and high-demand tasks aligned with an-
other study using lesson plans as proxies for teacher
practices (Silver et al. 2009). Low-demand tasks were
identified as those involving skills such as recalling, re-
membering, or applying facts/procedures, while high-de-
mand tasks were identified as those involving skills such as
analyzing, creating, evaluating, and being metacognitive.
Pedagogical content knowledge (PCK) was also repre-
sented by the science practices articulated in the lesson plan.
These science practices were based on the following
practices often associated with inquiry-based science: Les-
son involves a scientifically oriented question or problem;
students collect evidence; students make claims; and stu-
dents engage in reasoning (Michaels et al. 2008; NRC 2000).
Technological Content Knowledge
Technological content knowledge (TCK) was represented
by the content-specific software included in the lesson plan
with reference to its usage by both teacher and students.
Inputs from previous work with math-specific content
specialists (Kersaint 2003) and science educators on the
research team resulted in a list of TCK software. These
include function probe, virtual fieldtrips, and simulations.
Procedures
A cohort of trained reviewers analyzed the lesson plans in
four dyads. A dyad consisted of a science education doc-
toral student and an educational technology doctoral stu-
dent. The reviewers were at various points in their doctoral
studies and had an average of over 6 years of experience
teaching in K-12 environments.
All reviewers attended a 6-h training session conducted
by members of the research team. The training session
served several purposes. First, it allowed the reviewers to
be introduced to each other and the project in a formal
setting and allowed the reviewers to select their dyad
partner based on scheduling preferences. Second, the
training session allowed the research team to formally
prepare the reviewers to identify teacher practices in the
lesson plans following a 14-page manual that was also
developed by the research team. Third, during the training
session, the research team collected data for calculating the
inter-rater agreement across the dyads.
The reviewer training was executed in three iterations
using a gradual release of responsibility model (Pearson
and Gallagher 1983) in which strong scaffolds were
steadily decreased to the point at which reviewers were
independently analyzing the lesson plans. These iterations
were: (a) independent staged walkthrough, (b) dyad staged
walkthrough, and (c) coding simulation. During each stage,
the reviewers either independently or in their dyads re-
viewed a variety of lesson plans that were previously coded
using the manual by members of the research team to
provide a level of consistency in the coding procedures.
Finally, the reviewers were provided a sample of five
science lesson plans drawn from the population lesson plans.
The dyads reviewed all five of the lesson plans indepen-
dently. Inter-rater agreement was calculated for each item,
and scoring differences for inter-rater agreement below
80 % were resolved through dialogue among reviewers and
researchers. The cumulative inter-rater agreement for the
J Sci Educ Technol (2015) 24:648–662 653
123
dyads was 0.94. The dyads coded each lesson plan within
3 weeks of the training session. Reviewers used a web-based
system with a hyperlink to each lesson plan and a rubric with
the codes to identify teacher practices within the lessons.
Each dyad received no more than 130 lessons to review, and
reviewers were compensated for their time.
Data Analysis
Data from the online rubric were exported into IBM SPSS
Statistics 19. Descriptive statistics analysis was conducted
including percentages such as the percentage of science
topics. The percentage of certain level of technology in-
tegration and the percentage of specific technologies uti-
lized in the lesson plans were calculated. Chi-square was
used to compare the proportions of different categories
between pre- and post-lesson plans.
Results
While data analysis occurred around the six constructs of
the TPACK framework, we present our findings organized
around the three questions that guided the research: (1) In
what ways do science teachers involved in a yearlong
technology integration initiative enact technological, ped-
agogical and content practices in lessons? (2) In what ways,
if any, do these practices change during a yearlong tech-
nology integration initiative?
Technological Knowledge
Technological knowledge (TK) was represented based on
the generic types of software and hardware (Hogarty et al.
2003; Lowther and Ross 2001) used within the lessons. In
term of software (see Table 2), the most commonly used
software in the lessons was presentation software (i.e., MS
PowerPoint, Keynote) and Internet browsers (i.e., Internet
Explorer, Firefox). Notable increases were detected in the
use of digital video software (v2 = 6.49, p = 0.0108), In-
ternet browsers (v2 = 16.228, p = 0.0001), Web 2.0 tools
(v2 = 24.843, p\ 0.0001), and digital imaging software
(v2 = 6.523, p = 0.0106). Another notable finding was the
significant decrease in the use of spreadsheets (v2 = 5.253,
p = 0.0219) from pre-lesson to post-lesson.
In terms of hardware, Table 3 shows that the most com-
mon tool employed was a computer (including laptops). In
fact, a significant increase was detected from pre-lesson to
post-lesson in the use of computers (v2 = 13.576,
p = 0.0002). Significant increases also were detected in the
use of tablet technologies (v2 = 13.375, p = 0.0003),
classroom response units (v2 = 6.494, p = 0.0108), digital
microscopes (v2 = 9.2, p = 0.0024), data collectors
(v2 = 4.71, p = 0.03), and handheld devices (v2 = 12.973,
p = 0.0003) from pre-lesson to post-lesson. No significant
decreases were detected from pre-lesson to post-lesson.
Technological Content Knowledge
Technological content knowledge (TCK) was manifested
by the types of science-specific software (Kersaint 2003)
employed within the lessons. As shown in Table 4, very
little science-specific software was employed within the
lesson plans with the exception of web-based science re-
sources. All of the categories of science-specific software
were below 35 %. More importantly, no significant chan-
ges were detected from pre-lesson to post-lesson (Table 4).
Table 3 Hardware tools in
lesson plansHardware Pre-lessons (%) Post-lessons (%) v2 p value
Computers (including laptops) 67.97 82.65 13.576 0.0002
Digital camcorder 9.48 12.33 0.809 0.3683
Digital camera 6.54 8.68 0.567 0.4514
Handheld devices/PDAs/cell phones 1.63 8.68 12.973 0.0003
Other 12.42 6.85 3.771 0.0522
Tablet technologies (iPad, tablets) 0.33 5.94 13.375 0.0003
Data collectors/probes/CBL, CBR, MLB 1.96 5.94 4.71 0.03
Interactive whiteboards 5.88 4.57 0.213 0.6443
Digital microscope 0.33 4.57 9.2 0.0024
Classroom response units (clickers) 0.33 3.65 6.494 0.0108
Document cameras 1.63 2.28 0.0457 0.8308
Microphones/headsets 1.96 2.28 0.0032 0.9549
Graphing calculators 0.00 0.00 – –
Networked calculators 0.00 0.00 – –
654 J Sci Educ Technol (2015) 24:648–662
123
Pedagogical Knowledge
Pedagogical knowledge (PK) was documented in two ways
within the lesson plans: (1) the attributes of meaningful
learning environments (Jonassen et al. 2003) and (2) the
assessment practices employed (Morrison et al. 2007;
Wiggins 1990). In terms of the attributes of meaningful
learning environments (see Table 5), most lesson plans were
active as opposed to passive within these data. Further, more
than 60 % of the pre- and post-submissions were construc-
tive in nature, indicating that students were involved with
the creation of some artifact to demonstrate their knowledge,
skills, and dispositions. We observed significant increases in
the frequency of active (v2 = 9.42, p = 0.0021) and con-
structive (v2 = 18.706, p\ 0.0001) characteristics as ex-
hibited within the lessons. The authenticity of the lessons
was the least well-represented characteristic.
With respect to the assessment practices employed
within the lessons, Table 6 shows an extensive variety.
The most common assessment practices were perfor-
mance-based assessments and short response tests, which
include items like multiple-choice, true/false, fill in the
blank, chapter tests, and unit tests. We observed a significant
decrease in the use of extended response tests (v2 = 4.602,
p = 0.0319) from pre-lesson to post-lesson. Further, we
observed a significant increase in the use of performance-
based assessments (v2 = 10.057, p = 0.0015) and rubrics
(v2 = 4.15, p = 0.0416) from pre-submission to post-sub-
mission. There was also a decrease in the use of short re-
sponse tests from pre-submission to post-submission;
however, this change was not statistically significant.
Content Knowledge
Content knowledge (CK) was represented in the lesson plans
via standards and objectives addressed within the lesson
plans themselves. Again, the list of science topics came from
Florida’s Next Generation Sunshine State Standards
(FDLOE 2010). Teachers focused on an array of content in
their lesson plans as illustrated in Table 7. The content most
frequently addressed within the lessons included the
Table 4 Science-specific
software in lesson plansScience software Pre-lessons (%) Post-lessons (%) v2 p value
Web-based science resources 26.14 30.14 0.828 0.3629
Science content via online services 9.48 9.59 0.0118 0.9137
Virtual simulations 8.17 8.22 0.0198 0.888
Science-specific software 1.96 5.48 3.773 0.0521
Science games 1.63 1.37 0.0148 0.9032
Online data sets for explorations 0.33 0.46 0.228 0.6327
Virtual fieldtrips 0.00 0.00 – –
Table 5 Attributes of
meaningful learning
environments
Attribute Pre-lessons (%) Post-lessons (%) v2 p value
Active 93.14 99.09 9.42 0.0021
Constructive 62.42 80.37 18.706 \0.0001
Cooperative 37.91 45.21 2.519 0.1125
Authentic 9.15 13.70 2.246 0.134
Table 6 Assessment practices
in lesson plansAssessment practices Pre-lessons (%) Post-lessons v2 p value
Performance-based assessment 51.96 66.21 10.057 0.0015
Short response tests 40.85 34.25 2.086 0.1486
Rubrics 20.26 28.31 4.15 0.0416
Extended response tests 15.36 8.68 4.592 0.0321
Teacher observation 11.11 6.85 2.257 0.133
Peer assessment 1.96 2.28 0.0032 0.9549
Group assessment 2.61 1.83 0.0862 0.7691
Student self-assessment 0.65 1.37 0.146 0.7022
No assessment practices specified 0.65 0.00 0.226 0.6348
J Sci Educ Technol (2015) 24:648–662 655
123
following lesson topics as stipulated in the state’s science
standards: the practice of science, matter, interdependence,
organization and development of living organisms, and en-
ergy. We observed a significant increase in organization and
development of living organisms (v2 = 4.535, p = 0.0332)
and interdependence (v2 = 5.663, p = 0.0173) from pre-
submission to post-submission.
Technological Pedagogical Knowledge
Technological pedagogical knowledge (TPK) was repre-
sented using the five-level continuum for technology inte-
gration (Sandholtz et al. 1996): entry, adoption, adaptation,
infusion, and transformation. As shown in Table 8, more
than 95 % of the lesson plans were found on the first three
levels of the ACOT continuum: entry, adoption, and adap-
tation. However, there were significant differences detected
from pre-lesson to post-lesson. In particular, we observed a
significant decrease in the entry-level lesson plans
(v2 = 18.903, p = 0.0003) from pre-submission to post-
submission. Conversely, we observed a significant increase
in the adaptation lesson plans (v2 = 30.258, p\ 0.0001)
and infusion lesson plans (v2 = 5.213, p = 0.0224).
Pedagogical Content Knowledge
Pedagogical content knowledge (PCK) was revealed in two
ways within the lesson plans: (1) science practices
(Michaels et al. 2008) and (2) cognitive demand for content
area learning (Silver et al. 2009). Science practices aligned
to inquiry-based teaching methods as shown in Table 9.
During the post-lessons, students engaged in collecting
data or evidence and making claims at comparable levels.
A notable positive trend was observed in students engaging
in reasoning within the lessons; however, this change was
not statistically significant.
Cognitive demand for content area learning was classified
as either high demand or low demand based on a previous
study (Silver et al. 2009). As can be gleaned in Table 10,
most lesson plans were classified as low-cognitive demand,
meaning the tasks required students to recall, define,
remember, implement, or apply facts to science. However,
we did observe a significant increase in the proportion of
lessons exhibiting a high-cognitive demand (v2 = 10.126,
p = 0.0015) from pre-lesson to post-lesson, meaning stu-
dents more frequently had to justify, compare, assess, ana-
lyze, or evaluate facts related to mathematics or science
Table 7 Science topics in lesson plans
Science topics Pre-lessons (%) Post-lessons (%) v2 p value
The practice of science 21.57 20.09 0.0913 0.7626
Interdependence 12.09 20.09 5.663 0.0173
Organization and development of living organisms 9.80 16.44 4.535 0.0332
Matter 16.99 15.07 0.22 0.6392
Energy 12.09 10.96 0.0678 0.7946
Diversity and evolution of living organisms 5.88 10.05 2.589 0.1076
Heredity and reproduction 6.21 9.13 1.187 0.276
Earth in space and time 6.21 8.68 0.821 0.3649
Earth systems and patterns 6.21 8.22 0.51 0.475
Earth structures 7.19 6.39 0.0333 0.8552
The characteristics of scientific knowledge 6.21 5.94 0.0033 0.9542
Science and society 2.29 4.57 1.451 0.2283
Motion 6.86 4.11 1.318 0.251
Matter and energy transformations 3.92 3.65 0.0052 0.9427
The role of theories, laws, hypotheses, and models 1.63 1.83 0.0279 0.8674
Table 8 Level of Integration
(ACOT continuum) in lesson
plans
Level of integration Pre-lessons (%) Post-lessons (%) v2 p value
Adaptation 28.43 52.51 30.258 \0.0001
Adoption 21.90 26.48 12.34 0.2666
Entry 26.80 10.96 18.903 \0.0001
Infusion 0.33 3.20 5.213 0.0224
Transformation 0.33 0.00 0.0253 0.8736
656 J Sci Educ Technol (2015) 24:648–662
123
content areas. Conversely, a significant decrease in the les-
sons that exhibited a low-cognitive demand (v2 = 5.45,
p = 0.0196) from pre-lesson to post-lesson was detected.
Discussion
In this study, we used TPACK as a theoretical lens to
examine how teachers integrated educational technology as
evidenced through their science lesson plans submitted at
the beginning and end of a one-year technology integration
effort. Though our results show an increase in the overall
sophistication of technologies used, the use of reform-
based science practices was not observed as frequently in
the lesson plans. In the following sections, we discuss our
findings in detail.
Technological Knowledge
Educators agree that when educational technology is suc-
cessfully integrated into teaching, students become en-
gaged with tools that afford them opportunities to analyze
and manipulate systems and processes in the construction
of science knowledge and in problem solving (Hew and
Brush 2007; Neiss 2005). A variety of technologies both
hardware and software tools are easily accessible to many
students. Thus, students enter the science learning envi-
ronment with much familiarity and technological knowl-
edge about the uses and applicability of computers and
related current hardware and software. In this study, TK
was represented by both generic software and hardware.
Teachers used Internet browser software and computers in
their lessons. While these were the most common educa-
tional technology tools, there were significant increases in
other devices such as digital microscopes, tablets, and
handheld devices from pre- to post-lesson plan submis-
sions. We suspect the use of more sophisticated devices
was related to new technologies purchased through the
initiative. Mobile computing devices such as tablet and
handheld devices were the most commonly purchased
items, while probe and peripherals were purchased in large
quantities across the projects (Dawson et al. 2012).
The findings from teachers’ use of the hardware were
complementary to the general software with levels of in-
crease from pre- to post-lessons. Many of the lesson plans
required students to seek information on the Internet and,
in developing their presentation, employed such tools as
digital video and imaging software. However, we were
alarmed at the significant decrease in the use of spread-
sheets from pre- to post-lessons. Spreadsheets have much
utility in inquiry-based science teaching and learning in
constructing graphs and tables, and in analyzing large
amount of data—an important science practice in the use of
evidence to support conclusions.
Pedagogical Knowledge
Attributes of Meaningful Learning
Teachers have the authority to plan and teach what they
deem as necessary for students’ learning. Yet, too often,
high-stakes tests with their punitive consequences are the
deciding factor on what is taught. In support, Haney and
McArthur (2002) posited that the choice of instructional
strategies is influenced by constraints such as adherence to
the local curriculum and high-stakes testing. As a result,
much of K-12 science teaching still revolves around tra-
ditional science teaching dominated by reading compre-
hension and a search for science as a body of knowledge.
Such curricular constraints do affect instructional decisions
and ultimately students’ learning of science.
Research and development in science education and an
understanding of how learning occurs all point to the need
for learners to be actively engaged in science practices
supported by educational technologies and communication
among peers (Michaels et al. 2008). The teachers’ lesson
Table 9 Science practices in
lesson plansScience practices Pre-lessons (%) Post-lessons (%) v2 p value
Students collect data/evidence 39.87 46.12 1.793 0.1806
Students make claims 37.91 42.47 0.926 0.336
Scientifically oriented question or problem 30.39 37.44 2.547 0.1105
Students engage in reasoning 13.07 19.63 3.649 0.0561
Table 10 Cognitive demand for content area learning in lesson plans
Cognitive demand Pre-lessons (%) Post-lessons (%) v2 p value
Low-cognitive demand 68.30 57.99 5.45 0.0196
High-cognitive demand 27.45 41.10 10.126 0.0015
J Sci Educ Technol (2015) 24:648–662 657
123
plans revealed significant increase in both active and con-
structive attributes of a meaningful learning environment
and sought to engage students in strategies that included
manipulation and required the creation and production of
artifacts supporting students’ learning. We posit that the
significant increase in the frequency of both active and
constructive characteristics could be attributed to the
yearlong technology integration initiative. The initiative
offered support in educational technology and may have
fostered the teachers’ realization of the role of these tools
in facilitating the active engagement of students in learning
science. That is, during science instruction, these tools
presented opportunities for students to access science
content knowledge during web-based research.
Authentic, real-world learning experiences and coop-
erative learning environments are important for science
learning. This certainly is consistent with how scientists do
science as advocated by science education reform efforts.
However, the authentic and cooperative attributes were not
well represented in the lesson plans. One plausible expla-
nation is that teachers possibly viewed authentic as related
to immediate, hands-on, in-class activities and not related
to the wide range of real-time science data and other ex-
periences accessible through the use of computer tech-
nology. A lack of such inclusion possibly indicates a lack
of experience or failure on the part of the teachers to rec-
ognize the possibilities of accessing real-world data and
exemplars from sites such as the National Oceanic and
Atmospheric Administration (NOAA), National Aeronau-
tics and Space Administration (NASA), and others. In
addition, we concluded also that the support offered by the
availability of more educational technologies resulted in
the teachers’ planning for individual student access and use
of the devices. Thus, with increasing availability of com-
puters and other educational technologies, the cooperative
attribute of a meaningful learning environment was not
promoted as indicated in the findings.
Assessment Practices
Assessment as a tool to gather information about teaching
and learning is important in learning environments. Current
lesson planning and curricular processes are guided by
students’ responses to formative assessment prompts, while
summative assessment tasks indicate the extent to which
learning in relation to deliberate objectives has been
achieved. In general, lesson plans usually reveal assess-
ment opportunities to determine the extent to which
learning has occurred. The teachers’ pre- and post-sub-
mission lesson plans included a range of common assess-
ment practices requiring both teacher and student
involvement. Noticeably, however, were the significant
increases in both performance-based assessment and the
use of rubrics and the decrease in the use of extended
response tests. We suspect that these practices as repre-
sented in the pre- and post-lesson plans were related to
each other and to the infusion of technology.
Content Knowledge
Science teaching in Florida is mostly guided by the science
topics indicated in the state’s science standards (FLDOE
2010). However, on the national level, standards are not
mandates (NRC 2000) but represent the minimum students
should learn within grade-level bands in public school.
Such guidance is particularly important in a time when
there is a national reform effort to improve students’ sci-
ence learning and embrace science as a cornerstone in
twenty-first century education. Both state and national
standards stress the notion that science teaching and
learning should be consistent with how scientists do sci-
ence. The national standards therefore state the following:
Scientific inquiry refers to the diverse ways in which
scientists study the natural world and propose ex-
planations based on the evidence derived from their
work. Inquiry also refers to the activities of students
in which they develop knowledge and understanding
of scientific ideas, as well as an understanding of how
scientists study the natural world (NRC 2006, p. 23).
This emphasis on inquiry as practice and as a way of
understanding the world has implications for the integration
of classroom strategies that can support effective science
learning. An examination of the frequency of the science
content knowledge topics that emerged in the teachers’ pre-
and post-lesson plan submissions was revealing. The three
content knowledge topics that occurred most frequently—
the practice of science, matter, and energy—are considered
major themes across science disciplinary areas related to
biology, chemistry, and physics. One plausible reason for
the observed frequency of the practice of science could be
attributed to the focus on inquiry-based science (NRC, 1996)
and current efforts to involve learners in science practices
(Michaels et al. 2008). Ironically, other content knowledge
topics related to the nature of science (characteristics of
scientific knowledge and the role of theories, laws, hy-
potheses, and models) did not incur the level of frequency as
the practice of science. This might suggest that teachers
were more comfortable with or more inclined to treat the
practice of science in a generic manner with less emphasis
on the specific related content knowledge of characteristics
of science knowledge, role of theories, laws, hypotheses, and
models. This finding signaled the need for research to ex-
plore how science teachers’ understandings of the tenets of
the nature of science impact their decisions on choice of
science content knowledge topics.
658 J Sci Educ Technol (2015) 24:648–662
123
Only two content topics emerged with significant in-
creases in their representation in the lesson plans from pre-
to post-submission. These biological science topics were
organization and development of living organisms, and
interdependence. This finding might be interpreted in re-
lation to the recent high school graduation requirement and
also is reflective of the time teachers were required to
submit their lesson plans. Students in Florida are required
to pass the state-mandated end-of-course biology ex-
amination. While this finding might suggest a delay in
teaching the topic until closer to the examination date
where students are more likely to exhibit greater perfor-
mance, it also indicates weaknesses in the planned treat-
ment and delivery of science content.
Technological Pedagogical Knowledge
In our exploration of TPK, we embraced the notion that
technology integration may take many forms and is usually
captured along a variety of continuums (Hooper and Rieber
1995; Itzkan 1994; Knenek and Christensen 2000). Fur-
thermore, multiple levels of integration from entry through
to transformation can be observed in any one lesson. More
than 95 % of the lesson plans ascribed to the first three
levels of the ACOT continuum; thus, only 5 % of the
lessons sought to allow students autonomous use of the
technology. We observed a significant decrease in the
frequency of plans that were at the entry levels from pre- to
post-lessons indicating a reduction in the teachers’ use of
technology to deliver science information. At the same
time, there was a significant increase in adaptation lessons
in which teachers incorporated technology tools as integral
components in the development of lesson plans. While
many of these lessons involved students’ independent use
of the technology tools to create particular digital projects,
the lessons lacked students’ use at the infusion and trans-
formative levels. That is, teachers were limited in the ways
they planned to use technology in affording variety and in
supporting the development and use of higher-level skills.
Pedagogical Content Knowledge
Inquiry-Based Science Teaching
Within the category of PCK is the consideration of how
science content knowledge is formulated in ways that are
accessible for learners. While there is no one single pow-
erful representation (Shulman 1986) of science content
knowledge, lesson plans should at least include the teach-
ers’ intent for developing such knowledge. This intent
should include strategies or approaches for shaping and
reshaping students’ understanding of the proposed science
content knowledge and practices per the curriculum.
Furthermore, the plan of action should be derived from the
wisdom of the teachers’ own practices or from knowledge
garnered in previous methods courses or professional de-
velopment experiences.
The focus of the one-year technology integration ini-
tiative was to provide support for integrating educational
technology in science classrooms. On the national level,
inquiry-based science teaching is given much priority in
science curriculum as a way of allowing learners to expe-
rience how scientists do science and science knowledge is
developed (NRC 1996). Inquiry-based science instruction
has also been recommended as a way for teachers to pro-
mote student understanding of the nature of science
(Bianchini and Colburn 2000; Forbes and Davis 2010)
combining science practices, student-designed explo-
rations, and experimentation within the context of the
state’s curriculum.
Science educators contend that engagement in these sci-
ence practices over time will lead to a more scientifically
literate population with a greater appreciation and under-
standing of the nature of science. Our analysis revealed a fair
consistency in how teachers planned to involve students in
scientifically oriented questions, collect data, make claims
substantiated by the evidence collected, and engage in sci-
entific reasoning. Each of these essential features was in-
cluded in the pre- and post-lesson plans. This consistency
could be attributed to the fact that although the focus of the
one-year initiative was on technology integration, little or no
emphasis was placed on PCK within the construct of in-
quiry-based lessons. A plausible explanation for the change
in student reasoning though statistically insignificant could
be that while the other features of inquiry require levels of
individual student engagement, teachers may plan to involve
students in other activities such as structured small- and
whole-group discussions and, with the use of question
prompts, provide opportunities for reasoning and the pos-
sibility of deepening students’ learning.
Cognitive Demand
We embraced cognitive demand as the kind and level of
thinking required of students during a learning experience.
As a critical feature of ensuring depth of understanding,
Silver et al. (2009) described low-demand tasks as those
relating to recall of information such as facts and proce-
dures. For these authors, high-demand tasks included skills
such as analyzing, evaluating, and being metacognitive in
nature. Our findings of high incidences of low-cognitive
demand in both pre- and post-lesson plan submissions
support much of the criticisms directed at science teaching
and facilitated by the nature of high-stakes tests. Too often,
these tests—tied to teachers and school accountability
processes—favor the recall of snippets of science
J Sci Educ Technol (2015) 24:648–662 659
123
information. Similarly, teachers may not have had the
knowledge or experience to use technology to support
higher levels of cognitive demand. Further, technology is
often used as a tool for students to present information,
recite procedures, or memorize facts. While there was a
significant decrease in the low-cognitive demand between
pre- and post-test lesson plans, if the reform efforts of
science teaching are to be realized, there is still the need for
lessons to incorporate more of the skills consistent with
high-cognitive demand.
Technological Content Knowledge
We found a paucity of science-specific software in the
lesson plans. Two possible reasons for this deficiency could
be a lack of awareness of the existence of this type of
software among the teachers. We suspected that during the
year, more emphasis was placed on generic educational
technology hardware tools and software than science-
specific software. Furthermore, teachers seemed unaware
of the great science teaching potentials that exist in uti-
lizing this type of software or in accessing Web sites such
as NOAA and NASA.
Implications
This study was one component of a large Florida tech-
nology integration initiative. Our analysis of pre- and post-
lesson plans identified and documented teachers’ practices
with educational technologies. The implementation of the
initiative offered no guarantee that teachers were posi-
tioned to interpret the goals as intended by policymakers
(Brown and Campione 1996). The findings, therefore, can
be attributed to the extent to which lead administrators and
teachers understood and translated the goals into practice.
A number of misalignments occurred between the goals
of the technology integration initiative and teachers’ in-
tended practices as documented in their lesson plans. In an
era of loud calls for reforms in science teaching, our study
revealed deficiencies in science technological, pedagogical,
and content knowledge and practices in the pre- and post-
lesson plans. We recognized that a gap existed between the
goals of the state’s initiative and the actual implementation
by teachers. According to Lincoln and Guba (1986), this
difference between the stated goals of the initiative and
actual implementation may be attributed to the fact that
interpretation of policies is usually dependent on the lens
through which the policies are viewed. The policy inter-
pretation became a major weakness in the technology in-
tegration initiative, as it did not have a commonly
expressed framework guiding the activities of the stake-
holders involved such as policymakers, district personnel,
and teachers. We posit that TPACK may be a useful
framework to use when educational technology policy
initiatives are to be implemented.
Our findings revealed the occurrence of more positive
and frequent changes in technology practices than science
pedagogical and content practices. Notably, the initiative
provided teachers with technology tools, which could ac-
count for the increases in areas such as general software
and hardware. There is a risk, however, that schools may
invest in an abundance of new technologies faster than the
teachers’ readiness for effective integration to promote
science learning.
Advances in educational technology—focused on inquiry-
based science reform efforts and refinement in instructional
practices—all present challenges and opportunities for sci-
ence teaching. It follows that a one-year initiative with a
focus on technology integration may not have done enough
to engage teachers in related pedagogical and content pro-
fessional development experiences to afford the necessary
change in science teaching practices. Morrison et al. (2007),
in giving credence to collaboration among content fields in
professional development, suggested that the inclusion of
content experts in design and implementation in much the
same way subject area experts are engaged with instructional
design teams. To further effect changes in science pedago-
gical and content knowledge, we offer that science teachers
should be explicitly engaged in content-specific technology
integration efforts simultaneously conducted by the team of
experts from the other related fields. This shared experience
would aptly fit at the intersection of science pedagogical
knowledge, content knowledge, and education technology. In
such a structure, TPACK becomes a viable framework for
technology integration into science lessons.
References
Allsopp MM, Hohlfeld T, Kemker K (2007) The technology
integration matrix: the development and field-test of an internet
based multi-media assessment tool for the implementation of
instructional technology in the classroom. Paper Presented at the
Florida Educational Research Association, Tampa
American Association for the Advancement of Science (AAAS)
(1989) Project 2061: Science for All Americans
American Association for the Advancement of Science (AAAS)
(1993) Benchmarks for science literacy. http://www.project2061.
org/
Archambault LM, Barnett JH (2010) Revisiting technological
pedagogical content knowledge: exploring the TPACK frame-
work. Comput Educ 55(4):1656–1662
Archambault L, Crippen K (2009) Examining TPACK among K-12
online distance educators in the united states. Contemp Issue
Tech Teach Educ 9(1):71
Bianchini J, Colburn A (2000) Teaching the nature of science through
inquiry to prospective elementary teachers: a tale of two
researchers. J Res Sci Teach 37(2):177–209
660 J Sci Educ Technol (2015) 24:648–662
123
Blumenfeld PC, Fishman BJ, Krajcik JS, Marx RW (2000) Creating
usable innovations in systemic reform: scaling up technology-
embedded project-based science in urban schools. Educ Psychol
35(3):149–164
Brantley-Dias L, Ertmer PA (2013) Goldilocks and TPACK: is the
construct ‘‘Just Right?’’. J Res Technol Educ 46(2), 103–128
Brown SD (1998) Twelve middle-school teachers’ planning. Elem
Sch J 89(1):69–87
Brown AL, Campione JC (1996) Psychological theory and the design
of innovative learning environments: on procedures, principles
and systems. In: Schauble L, Glaser R (eds) Innovations in
learning: new environments for education. Erbaulm, Hillsdale,
pp 289–325
Darling-Hammond LL (2000) How teacher education matters.
J Teach Educ 51(3):166–173
Darling-Hammond LL (2010) Evaluating teacher effectiveness: How
teacher performance assessments can measure and improve
teaching. Washington, D.C.: Center for American Progress
Dawson K, Ritzhaupt A, Pringle R, Kersaint G (2011) Manual for
EETT lesson plan reviewers. Unpublished document,
Gainesville
Dawson K, Drexler W, Ritzhaupt AD, Liu F, Barron A, Kersaint G,
Cavanaugh C, Harmes C, Welsh J (2012) Charting a course for
the digital science, technology, engineering, and mathematics
(STEM) classroom interim research and evaluation report. Final
report to the Florida Department of Education. Title II-D/
Enhancing Education Through Technology (EETT) grant
program
Florida Department of Education (2010) Florida next generation
sunshine state standards. FLDOE, Tallahassee
Forbes CT, Davis EA (2010) Curriculum design for inquiry:
preservice elementary teachers’ mobilization and adaptation of
science curriculum materials. J Res Sci Teach 47(7):820–839
Guzey SS, Roehrig GH (2009) Teaching science with technology: case
studies of science teachers’ development of technology, pedagogy,
and content knowledge. Contemp Issues Technol Teach Educ 9(1).
http://www.citejournal.org/vol9/iss1/science/article1.cfm
Haney J, McArthur J (2002) Four case studies of prospective science
teachers’ beliefs concerning constructivist teaching practices. Sci
Educ 86:783–802
Hew KF, Brush T (2007) Integrating technology into K-12 teaching
and learning: current knowledge gaps and recommendations for
future research. Educ Tech Res Dev 55(3):223–252
Hogarty KY, Lang TR, Kromrey JD (2003) Another look at
technology use in classrooms: the development and validation
of an instrument to measure teachers’ perceptions. Educ Psychol
Meas 63(1):137–160
Hooper S, Rieber LP (1995) Teaching with technology. In: Ornstein
A (ed) Teaching: theory into practice. Allyn & Bacon, Neeham
Heights, pp 154–170
Hug B, Krajcik JS, Marx RW (2005) Using innovative technologies to
promote learning and engagement in an urban science classroom.
Urban Educ 40(4):446–472
Itzkan S (1994) Assessing the future of telecomputing environments:
implications for instruction and administration. Comput Teach
4(22):60–64
Jacobs CL, Martin SN, Otieno TC (2008) A science lesson plan
analysis instrument for formative and summative program
evaluation of a teacher education program. Sci Educ
92(6):1096–1126. doi:10.1002/sce.20277
Jonassen D, Howland J, Moore J, Marra R (2003) Learning to solve
problems with technology: a constructivist perspective, 2nd edn.
Merrill Prentice Hall, Upper Saddle River
Kersaint G (2003) Technology beliefs and practices of mathematics
education faculty. J Technol Teach Educ 11(4):549–577
Knenek G, Christensen R (2000) Refining best teaching practices for
technology integration key instructional design strategies
(KIDS). http://www.iittl.unt.edu/KIDS2000/
Koehler MJ, Mishra P (2005) What happens when teachers design
educational technology? The development of technological peda-
gogical content knowledge. J Educ Comput Res 32(2):131–152
Lei J (2007) Technology uses and student achievement: a longitudinal
study. Comput Educ 49(2):284
Lincoln YS, Guba EE (1986) Research, evaluation, and policy
analysis: heuristics for disciplined inquiry. Rev Policy Res
5(3):546–565. doi:10.1111/j.1541-1338.1986.tb00429.x
Lowther DL, Ross SM (2001) Observation of computer use:
reliability analysis. Center for Research in Educational Policy,
The University of Memphis, Memphis
McNeill KL, Pimentel DS (2010) Scientific discourse in three urban
classrooms: the role of the teacher in engaging high school
teachers in high school argumentation. Sci Educ 94:203–229
Michaels S, Shouse AW, Schweingruber HA (2008) Ready, set,
science: putting research to work in K-8 science classrooms.
National Academy, Washington
Mishra P, Koehler MJ (2006) Technological pedagogical content
knowledge: a framework for teacher knowledge. Teach Coll Rec
108(6):1017–1054
Morrison GR, Kemp JE, Ross SM (2007) Designing effective
instruction (5th edn). In: Hoboken NJ (ed), National Education
Technology Plan (2010) Transforming American education:
learning powered by technology, Wiley. http://www.ed.gov/
technology/netp-2010
National Educational Technology Plan (NETP) (2010) Transforming
American education: Learning powered by technology. Wash-
ington, DC. Retrieved from http://www.ed.gov/technology/netp-
2010
National Research Council (1996) National science education stan-
dards. National Academy Press, Washington
National Research Council (2000) Inquiry and the national science
education standards: a guide for teaching and learning. National
Academy, Washington
National Research Council (2006) Research on Future Skill Demands.
Washington, DC.: National Academy Press
Neiss ML (2005) Preparing teachers to teach science and mathematics
with technology: developing a technology pedagogical content
knowledge. Teach Teach Educ 21(5):509–523
Pearson PD, Gallagher MC (1983) The instruction of reading
comprehension. Contemp Educ Psychol 8(3):317–344
Polly D (2011) Examining teachers’ enactment of technological
pedagogical and content knowledge (TPACK) in their
mathematics teaching after technology integration professional
development. J Comput Math Sci Teach 30(1):37–59
Sandholtz JH, Ringstaff C, Dwyer DC (1996) Teaching with
technology: creating student-centered classrooms. Teachers
College Press, New York
Shulman LS (1986) Those who understand: knowledge growth in
teaching. Educ Res 15(2):4–14
Silk Y, Silver D, Amerian S, Nishimura C, Boscardin CK (2009)
Using classroom artifacts to measure the efficacy of professional
development, No. 761. Los Angeles: National Center for
Research on Evaluation, Standards and Student Testing
Silver EA, Mesa VM, Morris KA, Star JR, Benken BM (2009)
Teaching mathematics for understanding: an analysis of lessons
submitted by teachers seeking NBPTS certification. Am Educ
Res J 46(2):501–531
J Sci Educ Technol (2015) 24:648–662 661
123
Slykhuis D, Krall R (2011) Teaching science with technology: a
decade of research. In: Koehler M, Mishra P (eds),Proceedings
of Society for Information Technology & Teacher Education
International Conference 2011). AACE, Chesapeake,
pp 4142–4151. http://www.editlib.org/p/36982
State Educational Technology Directors Association (SETDA) (2011)
national trends. http://www.setda.org/web/guest/2011national
trends. Accessed 15 July 2011
Wiggins, G. (1990). The case for authentic assessment. Practical
Assessment, Research and Evaluation, 2(2). http://PAREonline.
net/getvn.asp?v=2&n=2
662 J Sci Educ Technol (2015) 24:648–662
123