PROVOST’S LEARNING INNOVATIONS GRANTS 2015 APPLICATION · 2015-03-11 · 2 Kudithipudi_PLIG_2015.docx III. PLIG TYPES Exploration Grants (approximately 30% of the funding pool for

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Kudithipudi_PLIG_2015.docx

PROVOST’S LEARNING INNOVATIONS GRANTS

2015 APPLICATION I. INSTRUCTIONS

Complete this form in its entirety and email it to [email protected] no later than January 26, 2015. Please note to save and rename this document substituting your name (in place of “NAME”) in the file name.

Ask your Department Head complete to complete the Department Head certification on page 12 and send a digitally-signed or printed, signed, and scanned copy with this application.

If you have any questions about completing this application, please email them to [email protected] or call Michael Starenko at 585-475-5035.

II. APPLICANT INFORMATION

Name: Dhireesha Kudithipudi Email: [email protected] Phone: X5085

College: KGCOE Department: Computer Engineering

Faculty rank: (full-time faculty only): Associate Professor

Department head name: Shanchieh Jay Yang

Proposed project name: Use of educational design patterns and flipped classroom models in a new computer engineering course

Total funds requested: (requests of $1,000 to $5,000 will be considered): $ 4,880

Administrative use: ❏ Focus Grant ❏ Exploration Grant

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III. PLIG TYPES

Exploration Grants (approximately 30% of the funding pool for this cycle)

These grants provide seed funds for faculty to investigate an innovative mode or model of teaching and learning in terms of its potential to positively impact student outcomes and the student experience at RIT. These are funds for "proof of concept" investigations into the development, adaptation, or application of a new or different teaching approach, practice, or procedure.

Focus Grants (approximately 70% of the funding pool for this cycle)

Focus Grants provide funds for faculty to develop, apply, and/or research an innovative mode or model of teaching and learning that directly supports an RIT priority. These are funds for the development, adaptation, application, and/or research into a new or different teaching approach, practice, or procedure in the priority areas of focus.

The two focus areas for this cycle are:

Flipped Classroom

The flipped classroom model (sometimes called the inverted classroom) is one in which traditional in-class activity—the lecture—is delivered outside of class via recorded lectures and other web-based materials. In-class time is used for collaborative project work, small group problem-solving, and other such activities that allow students to engage at a deep level with the content they viewed outside of (and before) class. To learn more about the model, visit the Teaching and Learning Services webpage at rit.edu/tls/course-design/flipped-classroom.

Learning Analytics

According to the 2014 NMC Horizon Report, (http://www.nmc.org/publications/2014-horizon-report-higher-ed), “Learning analytics research uses data analysis to inform decisions made on every tier of the education system, leveraging student data to deliver personalized learning, enable adaptive pedagogies and practices, and identify learning issues in time for them to be solved.”

Simon Buckingham Shum notes: "Micro-level [learner-level] analytics support the tracking and interpretation of process-level data for individual learners. This data is of primary interest to learners themselves, and those responsible for their success, since it can provide the finest level of detail, ideally as rapidly as possible. Researchers are adapting techniques from fields including serious gaming, automated marking, educational data mining, computer-supported collaborative learning, recommender systems, intelligent tutoring systems/adaptive hypermedia, information visualization, computational linguistics and argumentation, and social network analysis." (http://iite.unesco.org/pics/publications/en/files/3214711.pdf).

Smaller sets of data are permitted in this PLIG focus area. The scope of a proposal may be on the order of a single course or a few courses.

For further background about learning analytics, please see: https://net.educause.edu/ir/library/pdf/ELI7059.pdf.

This application is for a: ❏ Focus Grant ❏ Exploration Grant

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IV. BUDGET SUMMARY

There is a Microsoft Excel worksheet to calculate your budget

The total shown in this worksheet must match the “Total funds requested” on the first page of this application form.

• The worksheet will automatically calculate the appropriate benefit rate based on the salaries entered.

• This figure must be included in the total award request when any salary dollars are requested. Lastly, please do not override any formulas in the worksheet.

You can download the worksheet at https://www.rit.edu/academicaffairs/plig/index.php.

Note that any equipment or other materials purchased with grant funds are the property of your department and revert to the department after your project is completed.

V. TIMELINE

Please indicate any variances to the planned PLIG schedule and your reasons. If you do not intend to deviate from the schedule, you may leave this section blank.

Task Date Proposed variance and reason

Full project plan submitted Aug. 24, 2015

Preliminary findings submitted Jan. 25, 2016

Summary of final findings submitted Aug. 22, 2016

Final budget accounting submitted Aug. 22, 2016

Faculty Teaching and Learning Commons posting (a summary of findings, examples of teaching designs or materials, etc.) due

On or before Oct. 2, 2016

Participation in Teaching and Learning Services PLIG dissemination event

On or before Nov. 21,

2016

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VI. STATEMENT OF UTILITY (two pages maximum)

Using the proposal evaluation criteria provided in Evaluation section of the Call for Proposals document, provide an overview of the project you are proposing, including: • Project objectives • An explanation of the teaching/learning problem(s) it is designed to address • An explanation of the significance of the project to student outcomes and/or the student

experience.

• A brief description of how the project integrates with activity already underway at RIT in the priority area and/or how this approach has been successfully used at RIT already.

Project Main Objective: To develop a new course on Brain-inspired Computing (BIC) using educational design patterns and flipped classroom models, for enhanced student learning. Teaching/Learning Problems: Brain-Inspired Computing is a special topics course offered for the first time in the Spring’2015 in the Department of Computer Engineering with 24 students (from Electrical and Microelectronics Engineering and Computer Engineering). Although few institutes offer variants of Brain-Inspired Computing, none of them cover the material at the same breadth and depth. The interdisciplinary nature of this course (typically any special topics/research based courses) entails learning modules from different disciplines, some of which are unexplored terrain for the students. Moreover, learning modules also intersect with more than one discipline that is vital to understanding the aggregate concept. For example, the neuroanatomy and neurophysiology modules of this course are not part of a typical engineering curriculum. Within this field there are atleast 100 different neuron and synapse designs that are available, depending on which aspect of the brain we are focusing on. Students typically have minimal exposure to these concepts from their high-school curriculum, which is a distant memory for most. For such topics, it is vital to contact domain-experts who can provide guidance to Dr. Kudithipudi in developing focused content or generate digital content themselves for specialty topics. Therefore, it is critical to identify recurring design patterns that integrate systematic, interdisciplinary scientific research into flexible and scalable learning modules that can be applied in classroom. Another important challenge is to present the topics from different disciplines at varying granularities, depending on the correlation to the overall course outcomes. For example, the alternative computing architectures (non-VonNeumann) topic is a motivating lecture to the Brain-Inspired Computing paradigm. However, due to the wide range of advanced computing paradigms (e.g.: stochastic, chaos, approximate, and analog) it is not feasible to go over them in-depth during the class-time. In such instances, we plan to use flipped classroom approach where students will be referred to expert digital media content populated by instructor and/or auxiliary videos (e.g: TED Talks, Coursera modules). The objective of the proposed study is thus to develop a teaching approach that integrates educational design patterns and facets of a flipped classroom for an enhanced student learning.

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STATEMENT OF UTILITY (continued)

Significance of the project to Student Outcomes/Experience: The course is currently divided into five modules and each module has a culminating assignment and a team-based research topic presentation. By identifying design patterns to teach these modules, we can develop more advanced exercises for in-class room and provide agility in learning medium and inquiry[1]. In fact, by identifying the right patterns, students would be motivated to go back to the scientific theory in order to better understand the applied problems. Dr. Kudithipudi has persistently observed that students struggle with abstract/theoretical concepts in her Digital Integrated Circuit Design course (a core Computer Engineering course offered every semester and cross-listed for graduate and senior undergraduates) and uses “Pitfall diagnosis and Prevention” design pattern to improve the understanding and engagement. Usage of actual video viewing in class coupled with current industry adoption of this topic showed highly positive response rate for these topics. This also avails additional instructor-student time in the classroom and considerably improves the quality of their team-based projects. By utilizing portions of flipped classroom approach to generate explanatory models for specialty topics outside the classroom, in class time can be spent with the instructor guiding group exercises that integrate and apply the specialty topic to an overarching applied concept. Integration with existing activity underway at RIT: Firstly, the use of educational design patterns is growing significantly over the last decade in several domains including Cognitive neuroscience, Computer Science, Software Engineering, e-learning, and networked learning [2,3]. The prototype design patterns developed in this course can be applied to courses across multiple disciplines at RIT. Flipped classrooms with student-centered learning experiences have shown to provide personalized assistance, guidance and inspiration to students at large (inside and outside RIT). The proposed study integrates both of these complementary approaches to teaching that pave a new delivery mechanism for education at RIT. This project addresses three among five key priority areas of importance to the office of the provost, student success (by providing enriched and personalized learning experiences for different learning types), academic excellence (access to novel learning content), research and innovation (by bringing latest research developments into classroom education and also drive RIT to the forefront of Brain-Inspired Computing Research). The collection of flipped video modules will also be used in other advanced courses in Computer Engineering: Advanced Digital IC Design, Low Power Design, and Machine Intelligence courses. The repertoire of design patterns will be scalable and applicable to several other courses in engineering and sciences. Since Brain-Inspired Computing is a highly interdisciplinary field, the methods developed for this course could be applied to any interdisciplinary/special-topics/research-based courses at RIT that require the presentation of a breadth of topics, with varying depth of knowledge. 1. Connell, W.M, Stein,Z., H.Gardner.(2012). Bridging between brain science and educational

practice. Current Conjectures in Neuroscience education, 267-285. 2. Goodyear, P. (2005). Educational design and networked learning: Patterns, pattern languages and

design practice. Australasian Journal of Educational Technology, 21(1). 3. Fischer, K. W. (2009). Mind, Brain, and Education: Building a Scientific Groundwork for Learning

and Teaching1. Mind, Brain, and Education, 3(1), 3-16.

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VII. STATEMENT OF CREATIVITY (three paragraphs maximum)

Provide a brief description of how this is a novel approach, or a new application of an existing mode or model of teaching and learning, and/or research about teaching and learning represents an entirely new paradigm. (Please note that special consideration will be given to proposals that demonstrate a new use/application of a model, system, or technology already in use at RIT.)

Design patterns were initially proposed in 1977 by architects and more recently experimented by software engineering educators and educational technologists for identifying pedagogical patterns [1,3,4]. In parallel, the field of brain inspired (a.k.a neuromorphic) computing is rapidly evolving along with the neuroscience research. As identified by the Department of Education, National Science Foundation, and Department of Defense in 2014, there is a substantial need to offer such new interdisciplinary courses related to Brain that will enrich the collaboration and innovation experience for students and educators. To the best of our knowledge there is no other comprehensive brain-inspired computing course, which covers the disciplines of machine learning, circuit design, computer architecture, computational neuroscience, and neurophysiology, that has been reported in the engineering education literature. The concept of educational design patterns is gaining traction in networked learning paradigms[1] and cognitive neuroscience[4], due to the flexibility and reusability of the patterns. However, there is no demonstrated application of this model in Computer, Electrical, and Microelectronic Engineering disciplines.

Specifically in this Brain-Inspired Computing course it is critical for students to understand the abstract theoretical concepts and apply them to different design facets in neuromorphic systems. Traditional PowerPoint and white-board based teaching models alone will not be sufficient for the students to synthesize all the learning material and for the instructor to deliver the content in an engaging way. By creating tactile and independent modules using flipped model, we also support students in building good analytical reasoning for big-picture problems that overlaps across multiple disciplines. Since RIT has an excellent support system for flipped classroom approaches, we will seek support from Wallace Center early-on in the development. Additionally we will reach out to faculty utilizing flipped classroom approaches within and outside RIT to identify best practices.

1. Goodyear, P. (2005). Educational design and networked learning: Patterns, pattern languages and

design practice. Australasian Journal of Educational Technology, 21(1). 2. Bruer J.T (1997), Education and the brain: A bridge too far, Educational researcher, 26(8),4-16 3. Anthony D. et.al. (1996), Patterns for classroom education, Pattern languages of program design 2. 4. Blake et.al. (2007), A first course in Mind, Brain, and Education, Mind, Brain, and Education,1,61-65

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VIII. STATEMENT OF EFFICACY (two pages maximum)

Provide a brief description of the experiment/research design, methodology, and methods of data collection you will use to gauge efficacy.

In 2012, Dr. Howard Gardner a world-renowned developmental psychologist (who pioneered multiple intelligences framework) has published a research article, which addresses an important question on “How can research in the special sciences (neuroscience) and insights from educational practice both inform a science of education?” [1]. He proposed the use of educational design patterns to overcome the obstacles in developing sustainable interdisciplinary science of education, along with explanatory models by educators and domain-experts. Design pattern is a description of a recurring problem and a general solution to the problem in such a way that you can employ this solution flexibly over several contexts . The figure below demonstrates the overarching design pattern template for the different learning modules, based on [1], that we will be using for the Brain-Inspired Computing Course.

We will seek experts in the field (e.g: Neuroscientists from Univ. of Rochester and Graz) to generate the explanatory models for topics not common to the Computer Engineering discipline. These explanatory models also can be flipped learning modules in certain scenarios, in a way that they are either in digital-media, textual, or tangible mediums. We have identified the following design patterns for immediate development: Pattern 1: Perceptual Accessibility (separate the delivery modality from educational content; to engage students comprehend interdisciplinary modules inspite of different learning modalities). Pattern2: Scalable Adapter (integration of independent learning modules into one collaborative learning experience; to address the connectivity between different discipline topics), and Pattern 3: Quiz Games modeled on TV game shows (For testing comprehension and absorption of material using games such as Jeopardy for brain-inspired machine learning algorithms). We understand that the first offering of the course might not enable us to implement all the patterns or some of the patterns might deem not as attractive in practice. We will adopt and improve these in the second iteration of the course in Spring 2016.

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STATEMENT OF EFFICACY (continued)

Each class will start with a discussion of the flipped module/explanatory model for 15 minutes. During this time Camtasia software will not be enabled for free expression of thought. Once the educator begins delivery of content, Camtasia software will be enabled and used for the rest of the classroom activities. All the recorded notes will be posted/synced to mycourses for immediate access. Data Collection: On the first day of the course, students are asked to fill out a survey on their learning preferences and topics where they typically stumble. These will serve as a guidance to generate the explanatory models and flipped modules for the first offering, along with topics identified by us based on our experience in this research field. We have already reached out to experts in the field (e.g: Dr. Mahon for detailed presentation on visual pathway in the brain and its implications on cognitive processing). Supplementary material will be created for specific modules, based on the design patterns. During the duration of this course, a graduate student will be assisting Dr. Kudithipudi in populating the digital-media content, assessing needs for design-templates, and filling the proposed design templates. Student’s formative feedback will be collected mid-semester to identify any pitfalls and improve. Final assignment will include a focused thought experiment question to see how well the design patterns and flipped modules aided in the fundamental knowledge building and application. We will be cognizant of portability to different platforms when developing the digital media content. 1. Connell, W.M, Stein,Z., H.Gardner.(2012). Bridging between brain science and educational

practice. Current Conjectures in Neuroscience education, 267-285.

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IX. DISSEMINATION PLAN (optional)

Provide details about the journal, conference, show, other external vehicle with strong potential for dissemination of your results. Include supporting documentation such as preliminary interest or acceptance with your application, if available. (Please note that special consideration will be given to proposals that have a defined opportunity for external dissemination, such as an academic journal or professional conference.)

Teaching and Learning Services will arrange channels for disseminating results within RIT.

The design patterns developed through this course will be made accessible to a broad audience through professional conferences such as ASEE conferences, ACM/IEEE educational conferences (e.g.: Frontiers in Education conference 2015), and the RIT event hosted by the online learning community. Dr. Kudithipudi will also demonstrate the initial design patterns at a workshop in IEEE-INNS 2015 conference in SanFrancisco from 8-10 August 2015. The workshop proposal is already accepted. Given the exploratory nature of this course development, we are confident that the work will lead to a full journal article, which we plan to submit to IEEE Transactions on Education in 2016. Moreover, students from this course might plan (committed by two teams in the Spring 2015 offering) to publish review and project assignment articles to appropriate conferences (e.g.: IEEE IJCNN). The flipped learning modules, examples, and other supporting materials developed will provide initial scaffolds that will be available for educator repertoires through open-source (using creative commons licenses). From our experience with organizing several professional and pedagogical outreach activities within and outside RIT, it is important to provide access to online-repositories for immediate use by other educators. All the material will be posted on Dr. Kudithipudi’s website along with mycourses. We will also disseminate specific flipped learning modules and design patterns to our collaborating partners in academia (e.g: Univ. of Rochester, Indian Institute of Technology, and CNSE-Albany) and government organizations for formative feedback and cross-fertilization of ideas.

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X. ADDITIONAL CONSIDERATIONS

Please address these questions, if needed. • Will your project require assistance for extensive or unusual media, multimedia, simulation,

and/or software development? If so, please explain?

• All courses offered by RIT must be accessible to students with disabilities, according to

Section 504 of the Rehabilitation Act of 1973 and Title II of the Americans with Disabilities Act of 1990 (rit.edu/studentaffairs/disabilityservices/info). Is your proposed teaching approach accessible to all students, with reasonable accommodation? If not, please explain.

• RIT abides by the Family Educational Rights and Privacy Act of 1974 (FERPA), which

prohibits instructors from making students' identities, course work, and educational records public without their consent (rit.edu/xVzNE). Will any data gathering or sharing for your project raise any FERPA issues? If so, please explain.

For the development of flipped learning modules and explanatory models, digital media content, we will use the Camtasia software. Currently Dr. Kudithipudi is using a trial version of the software and plans to purchase this software. There is already support system and studio availability for Camtasia software existing at RIT TLS center, which was the primary reason to choose this tool. Some of the large-scale brain simulations will be demonstrated using Matlab, Verilo-AMS, and Python toolsets, which are already available in the Computer Engineering department. Students will also develop short-video content as part of their group activities using tools like Masher (freely available).

The proposed model is inclusive and accessible to students with diverse learning needs. All the digital media generated will be easily portable for creating content with captioning. Caution will be taken during media creation to address different learning needs.

There will not be any data gathering that will release student’s identities in the proposed project. Any content developed by the students through assignments or learning activities will be shared (if at all) with their consent only.

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XI. DISSEMINATION AGREEMENT

By completing this grant application, I agree to provide the materials described here, in support of disseminating what is learned from this project to other faculty at RIT.

I also agree to return all/a portion of the funds that I receive for this project to RIT if I fail to complete or provide the materials described here. • Full project plan (including roles and responsibilities, milestone dates, and pertinent project

details)

• Overview of preliminary findings (may include experiment/study design, lessons learned, initial data collection, and/or literature review summary)

• Final project summary (including data collection, lessons learned, implications for further study, and which may be in the form of an article abstract, conference presentation outline, or short report)

• Faculty Teaching & Learning Commons posting (a summary of findings, examples of teaching designs or materials)

• Participation in a faculty dissemination event • Final budget accounting (reconciliation of budget provided with your application and the

actual project expenses)

By submitting this application, I accept this agreement.

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XII. DEPARTMENT HEAD CERTIFICATION

I support this PLIG application and budget, and verify that __Dr. Dhireesha Kudithipudi____ is a full-time faculty member in good standing in my department.

Department head name: Dr. Shanchieh Jay Yang Date: 2/2/15

Department head signature:

Phone: 585-475-2987 Email: [email protected]

PLIG 2015 Budget WorksheetApplicant's Name:

Personnel Purpose/JustificationFull time Faculty/Staff

123Adjuncts/Part time Faculty/Staff

1 Graduate Student Assistantship Populating the design pattern and flipped module software maintainance by two students at $15/hr for 5 hours a week (over two semesters).23

T Personnel Total

T Benefits -‐ Calculated Automatically

Equipment Purpose/Justification123

T Equipment Total

Licenses Purpose/Justification1 Camtasia Software To generate the video learning modules23

T Licenses Total

Travel Purpose/Justification1 ASEE Regional Conference Dissemination at an ASEE Regional Conference(Travel)2 IEEE INNS Conference Dissemination at a workshop in IEEE INNS Conference (Airfare+Hotel to SFO in August 8-‐10,2015)3

T Travel Total

Other (Specify) Purpose/Justification123

T Other Expenses Total

Total Award Request

PLIG 2015 Budget Worksheet

Amount

-‐$ -‐$

3,500$

-‐$

3,500$

280$

Amount-‐$ -‐$ -‐$

-‐$

Amount100$ -‐$ -‐$

100$

Amount500$ 500$ -‐$

1,000$

Amount-‐$ -‐$ -‐$

-‐$

4,880$

PROVOST’S LEARNING INNOVATIONS GRANTS 2015 APPLICATION · 2015-03-11 · 2 Kudithipudi_PLIG_2015.docx III. PLIG TYPES Exploration Grants (approximately 30% of the funding pool for

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