Conference Session

Technical Session 4: Modulus Topics 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Alessio Gaspar, University of South Florida; Dmytro Vitel, University of South Florida; A.T.M. Golam Bari, University of South Florida

Tagged Divisions

Computers in Education

tobetter serve students, but also by adopting a similar perspective including the needs of instructorsand Computing Education researchers. We also introduce a new tool, EvoParsons, and show howit proposes to address some of the limitations and opportunities that were identified.1 IntroductionEvoParsons is a software implementation of Parsons puzzles that was designed to provide accessto students to both instructor-designed and automatically generated puzzles. It is also meant tosupport three distinct categories of users: researchers, students, and instructors.Computing Education researchers, who are interested in applying artificial intelligencetechniques, benefit greatly from open source access to Parsons puzzle software. However, wefound these

Conference Session

COED: Online and Blended Learning Part 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Taylor V. Williams, Purdue University, West Lafayette; Kerrie A. Douglas, Purdue University, West Lafayette; Tarun Yellamraju, Purdue University, West Lafayette; Mireille Boutin, Purdue University, West Lafayette

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Diversity

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Computers in Education

this information by asking students about who they are and what they want from the MOOC they are enrolling in. However, making sense of this survey data is challenging. Machine learning clustering techniques are a standard tool for identifying groups within data; however, two problems exist when trying to cluster survey data: (1) it is often not in a form easily interpreted by clustering algorithms and (2) survey data is frequently high dimensional, which standard clustering techniques cannot handle well. We describe a technique for converting survey data into machine interpretable feature vectors. We then propose analyzing the data using the 𝑛𝑛-TARP clustering technique which is capable of efficiently

Conference Session

COED: Online and Blended Learning Part 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Zelin Zhu; Yuzhong Shen, Old Dominion University; Cheng Y. Lin P.E., Old Dominion University; Shuo Ren, Old Dominion University; Katherine Smith, Old Dominion University; Anthony W. Dean, Old Dominion University

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Computers in Education

graphical interface, as well as a more realistic rendition of the lab environment.Students can now use it to perform circuit wiring for combined electro-pneumatic experiments,just like on-campus students. Classroom use of Virtual Lab has demonstrated good performanceand effectiveness.1. IntroductionEducation and learning have become more accessible thanks to various online resources andtechnologies, such as MIT Open Courseware [1], edX (a Massive Open Online Course (MOOC)learning platform that runs on an open-source software platform (Open edX)) [2], KhanAcademy [3], YouTube [4], and WebEx [5]. While online education provides many newopportunities and resources to students and professionals, one limitation of existing onlineeducation is the absence

Conference Session

COED: Online and Blended Learning Part 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Carole E. Goodson, University of Houston; Susan L. Miertschin, University of Houston; Barbara Louise Stewart, University of Houston

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Computers in Education

are in the areas of (1) information systems applications development and the complementary nature of back-end developer and front-end developer skill sets and (2) managing IT services. Her research interests are program and student as- sessment, the impact of instructional technology on student learning, and the improvement of e-learning environments and experiences.Dr. Barbara Louise Stewart, University of Houston Barbara L. Stewart is a Professor of Retailing and Consumer Science at the University of Houston. Her teaching and research interests are in the application of strategies to improve student learning and life enhancement in online courses. She has served as an academic administrator and in leadership

Conference Session

Technical Session 4: Modulus Topics 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Magesh Chandramouli, Purdue University Northwest

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Diversity

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Computers in Education

reality (VR) and computer graphics (CG) are highly interrelated. The evolution of VRhas been aided by the advancements in 3D graphics, visualization, and interactive user interfaces.Evidently, CG has tools and techniques tremendously influence and impact the capabilities ofVR and also considerably define the limitations as well. However, in this study, multiple modesare used to overcome space and cost limitations. Figure 1: Multiple VR-based modes of Interaction; Clockwise from top-left Using Head Mounted Displays, Using Controllers on Desktop, Using Touchpad, StylusOne of the most important advantages of using VR is the ability to engage students to facilitateactive learning and problem-based learning. Active learning and project-based

Conference Session

Technical Session 4: Modulus Topics 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Afrin Naz, West Virginia University Institute of Technology; Jordan Nicole Bowen; Mardigon Max Toler, West Virginia University Institute of Technology; Mingyu Lu, West Virginia University Institute of Technology

Tagged Divisions

Computers in Education

encouraging evidence demonstrating that project-based learning succeeds inincreasing students’ content knowledge, enabling students to transfer knowledge to practicalimplementation, promoting students’ collaboration skills, and developing students’ positiveattitudes towards math and science [1-5]. When project-based learning is used to supplementinstructions, students are inspired to pursue STEM (science, technology, engineering, andmathematics) careers [4].In the summers of 2015, 2016 and 2017, we organized workshops on the West VirginiaUniversity Institute of Technology (WVU TECH) campus for math and science middle and highschool teachers to learn project-based learning systematically. Workshop instructors are WVUTECH computer science and

Conference Session

Technical Session 4: Modulus Topics 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Magesh Chandramouli, Purdue University Northwest; Emily Hixon, Purdue University Northwest

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Diversity

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Computers in Education

are engaged in activities (e.g., reading, discussing, writing). • Greater emphasis is placed on students' exploration of their own attitudes and values. Figure 1: Team-Quiz Components with Learning OutcomesThe instructional strategy documented in this study provides an active, collaborative approach(Figure.1) for addressing some observations made by the author in CGT courses over the past severalyears: o The graphics production pipeline is inherently teamwork-based and it is important for CGT students to have collaborative skills. o Often times, students who are otherwise proficient in CGT (3D Modeling, Lighting, etc.) are restricted in terms of communicating with teams and

Conference Session

COED: Online and Blended Learning Part 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Swaroop Joshi, Ohio State University; Neelam Soundarajan, Ohio State University; Jeremy Morris, Ohio State University

Tagged Divisions

Computers in Education

to the wiki! Leung and Chu [15] in a course on knowledge management and Juddet al. [13] in a large course on psychology report equally poor results of the use of a wiki. Rickand Guzdial [20] report that although they obtained positive results using wikis in architecture and 1 More commonly, the student will revise her original conception incorporating ideas from other students’ concep-tions rather than simply abandoning her original conception and picking one of the others.english composition classes, the results in STEM classes were “overwhelmingly disappointing”.For example, they report that fully 40% of math students settled for a zero on an assignment ratherthan engage in collaborative learning!In one respect, the work on

Conference Session

Technical Session 4: Modulus Topics 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Raquel Landa, Tecnologico de Monterrey (ITESM); Lorena B. Martinez Elizalde, Tecnologico de Monterrey; Cristina Verónica Gonzalez Cordova, ITESM

Tagged Divisions

Computers in Education

promoting learning through decision-making. As a result of the developmentof the product, students are able to build their own knowledge [1].The RAIS approach also proposes collaborative learning, based on the principle that thecollaboration among pairs significantly increases motivation, stimulates creativity, encouragesand facilitates communication, develops a sense of responsibility and improves the degree ofpersonal satisfaction [2]. Also, it raises the need to relate, contextualize and integrate thecontents of the different disciplines through a set of interdisciplinary modules that have a closeconnection with each other. This proposal facilitates the interconnection of knowledge throughan integrating element: the product to be developed.The

Conference Session

Technical Session 4: Modulus Topics 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Ashwin Satyanarayana, New York City College of Technology; Karen Goodlad, New York City College of Technology, CUNY; Jennifer Sears, New York City College of Technology, CUNY; Philip Kreniske, Columbia University, The HIV Center; Mery F. Diaz, New York City College of Technology; Sandra Cheng, New York City College of Technology

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Diversity

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Computers in Education

the transition experience. The NLP analyzerhelped summarize emotions and concepts, and identified some common concerns of students byidentifying common keywords. The Tone Analyzer tool uses linguistic analysis to detect joy,fear, sadness, anger, analytical, confident and tentative tones found in text. Such summarizationsof student stories provide suggestions to the college on how we can better orient students andprepare them for their first year. In this paper, we present top concerns of students who aretransitioning from high school to college. We will also investigate through the stories if theoverall experience of students gets better or worse through their first year.1. IntroductionEntering college is a major milestone that marks the

Conference Session

Computers in Education 4 - Online and Distributed Learning 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sherif Abdelhamid, Virginia Military Institute; Andrew Katz, Virginia Polytechnic Institute and State University

Tagged Divisions

Computers in Education

fields of human-computer interaction, human-human interaction,video content understanding, and interactive dialog systems.1. Related WorkResearchers from different fields have been using social media to gain insight into their subjectdomains, including marketing [1], healthcare [2][3], design thinking [4], cybersecurity [5],athletics [6], and natural disasters [7]. This trend is also present in engineering education. Forexample, in one study [8], researchers used Twitter to trace the participation and conversationsabout a campaign geared towards promoting STEM learning and engagement among the public.In another study [9], researchers used Twitter to understand different topics, themes, and issuesrelated to engineering education and first-year

Conference Session

Computers in Education 4 - Online and Distributed Learning 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Afrin Naz, West Virginia University Institute of Technology; Mingyu Lu, West Virginia University Institute of Technology; Ryan E. Utzman

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Diversity

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Computers in Education

after the COVERAGEproject was initiated. As a result, almost all the activities had to be changed to an online platform[1], over which the participating students program robots virtually. In Fall 2020 and Spring 2021,online instructions were offered every week via Microsoft Teams, intending to guide theparticipating middle school students to program virtual robots. All the Teams sessions arerecorded and shared with all the participants, such that the middle school students could visitthem anytime. In addition to online instructions, at least one hour was designated every week forthe mentors (who are female undergraduate students) to work with the participating middleschool students on the online assignments under the supervision of middle

Conference Session

Computers in Education 4 - Online and Distributed Learning 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Julian Ly Davis, University of Southern Indiana; Thomas McDonald, University of Southern Indiana; Bradley Lane Kicklighter, University of Southern Indiana

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Computers in Education

of testingin an LMS that could be done much better to suit our individual needs. In this paper, we discusssome of the types of questions that we use in Blackboard Exams and some of the computer toolsthat we use to create them. We discuss some of the successes as well as some tricks of the tradethat we use to address our objectives. Finally, we discuss some additional tools that we use tomitigate cheating. This paper covers subjects such as: 1) Different types of Blackboard questions a. Calculated Formula b. Multiple Choice c. Fill in the Blank d. Fill in Multiple Blanks 2) Software tools to help write questions (e.g.) a. Mathematica b. Excel c. Visio 3

Conference Session

Computers in Education 4 - Online and Distributed Learning 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Juliana Lynn Fuqua, California State Polytechnic University, Pomona; Faye Linda Wachs, California State Polytechnic University, Pomona; Paul Morrow Nissenson, California State Polytechnic University, Pomona; Deanna Miranda Barrios; Cecilia Nguyen, California State Polytechnic University, Pomona

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Diversity

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Computers in Education

open educational resource at the “ME Online”website (www.cpp.edu/meonline), which has accumulated over 8,600,000 views as of March2021. In 2018, a brief survey was administered to 340 mechanical engineering students at CalPoly Pomona as part of a pilot study to investigate the impact of ME Online [1]. The surveyresults were promising – the vast majority of students felt the video library made a positiveimpact on their education and helped their grades in at least one course. However, the survey didnot explore the socio-emotional impact of the video library on students nor obtain specificrecommendations of how the video library could be improved to enhance student success.The current study was designed to gain a deeper understanding of how ME

Conference Session

Computers in Education 4 - Online and Distributed Learning 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sunay Palsole, Texas A&M University; Jeff Chernosky, Texas A&M University; Randy McDonald, Texas A&M University Engineering

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Diversity

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Computers in Education

systems as a face-to-face course. The course may be delivered in a classroom or fromhome using live synchronous lecture capture or asynchronous lectures delivered just-in-time. Thecourse contains student-student, student-content, and student-instructor interactions. Assessmentsmay be delivered fully online or using remote methodologies. I. BACKGROUND Despite all current knowledge around student satisfaction in higher education, researcherspoint out much remains unknown. The effects of the specific course elements, individually andcollectively, when designing a course are not fully understood [1]. The multiple factorssurrounding the achievement of the learning outcomes can be related to several areas

Conference Session

Technical Session 1: Issues Impacting Students Learning How to Program

Collection

2019 ASEE Annual Conference & Exposition

Authors

A.T.M. Golam Bari, University of South Florida; Alessio Gaspar, University of South Florida; R. Paul Wiegand, University of Central Florida, School of Modeling, Simulation, & Training; Dmytro Vitel; Kok Cheng Tan; Stephen John Kozakoff, University of South Florida

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Computers in Education

Tan1 Stephen Kozakoff1 kokcheng@mail.usf.edu kozakoff@mail.usf.edu 1 University of South Florida, Computer Science and Engineering, 4202 E. Fowler Avenue Tampa, FL, 33620, USA 2 Institute for Simulation & Training EECS, University of Central Florida 4000 Central Florida Blvd Orlando, Florida, 32816, USAAbstractOur goal is to investigate whether techniques to automatically generate practice problems

Conference Session

Technical Session 1: Issues Impacting Students Learning How to Program

Collection

2019 ASEE Annual Conference & Exposition

Authors

S. Cyrus Rezvanifar, University of Akron

Tagged Divisions

Computers in Education

instructor for several undergraduate-level courses, and he has conducted educational research on the effect of various learning techniques on improving students’ self-efficacy and overall learning experience. c American Society for Engineering Education, 2019 Programming Without Computer: Revisiting a Traditional Method to Improve Students’ Learning Experience in Computer ProgrammingIntroductionDuring the past three decades, computer programming has been recognized as an essential skilland a necessary element in education. Previous studies have reported numerous cognitiveoutcomes from learning to program [1]. Feurzeig et al. [2] presented an extensive list of cognitivebenefits of learning computer

Conference Session

Technical Session 1: Issues Impacting Students Learning How to Program

Collection

2019 ASEE Annual Conference & Exposition

Authors

Raquel Landa, Tecnologico de Monterrey (ITESM); Yolanda Martinez-Trevino, Tecnológico de Monterrey

Tagged Divisions

Computers in Education

Course María Raquel Landa Cavazos Yolanda Martínez Treviño Computer Science Department Computer Science Department Tecnologico de Monterrey, Tecnologico de Monterrey, Campus Monterrey. Campus Monterrey. Monterrey, México Monterrey, México rlanda@tec.mx yolanda.mar.tre@tec.mxAbstractThis paper presents the results of integrating the use of an auto-grader tool in a ComputerScience 1 course to personalize the learning process of students by allowing them to advance attheir own pace when solving problems in class sessions

Conference Session

Technical Session 1: Issues Impacting Students Learning How to Program

Collection

2019 ASEE Annual Conference & Exposition

Authors

Alex Daniel Edgcomb, Zybooks; Frank Vahid, University of California, Riverside; Roman Lysecky, University of Arizona

Tagged Divisions

Computers in Education

readings and homeworks. Coral has been used byabout 2600 students at 21 universities.1. Introduction: Why a new language?Industry coding languages like Python, Java, and C++ were designed mostly for professionals,not learners. Python is often considered the simplest to learn, but as one long-time instructor putit, “even Python has its ‘Gotchas'”, which is supported by some research where evidence wasfound that students struggle with Python as much as with C++ [1][2][3]. For example, somePython syntax is non-intuitive to learners, like reading integers. Another example is that the lackof static typing in Python can yield hard-to-debug type-related errors. We consideredsubsetting/redefining Python for learners, but knew the needed departures could

Conference Session

Technical Session 1: Issues Impacting Students Learning How to Program

Collection

2019 ASEE Annual Conference & Exposition

Authors

J.w. Bruce, Tennessee Technological University; Bryan A. Jones, Mississippi State University; Mahnas Jean Mohammadi-Aragh, Mississippi State University

Tagged Divisions

Computers in Education

devices toeconomy-critical and life-critical devices. A big reason for the proliferation of digital devicesinto every part of our lives is that digital systems have increasing capabilities at shrinking costs[1]. This seemingly contradictory march has often been characterized by Moore’s Law, namedafter Gordon Moore, co-founder of Fairchild Semiconductor and CEO of Intel.A critical challenge to continue this progress is management of digital circuit complexity. Thedays of hand-tuned digital circuits designed by single engineer are long gone. Modern digitalcircuits are far too complex for a single person to grasp and understand. To aid the moderndigital circuit designer, hardware description languages (HDLs) such as ABEL [2], VHDL (nowdescribed by

Conference Session

Computers in Education Division - General Technical Session 1

Collection

2013 ASEE Annual Conference & Exposition

Authors

Danielle Marie Dowling, Tufts Center for Engineering Education and Outreach; Morgan M Hynes, Arizona State University

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Computers in Education

centrally located screen for subsequent discussion and collaborative attainment of a deeperunderstanding. This paper examines in-class-use cases involving three teachers of diversebackgrounds who participated in our project; the goal of which is to answer the followingquestions: 1) How did our tool change the way the way the teacher engages with studentthinking? 2) How did our technology support the teacher as he interacted with student ideas?3) What are the factors that enable the teacher to or prevent him from capitalizing onopportunities afforded by the tool to probe student reasoning? 4) How does this engagement, aswell as other aspects, affect the student discussions that result from using the tool? In so doing,we hope to inform future

Conference Session

Computers in Education Division - General Technical Session 1

Collection

2013 ASEE Annual Conference & Exposition

Authors

Kellie Grasman, Missouri University of Science & Technology; Dan Cernusca, Missouri University of Science & Technology; Suzanna Long, Missouri University of Science & Technology

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Computers in Education

theredesigned undergraduate engineering economics course that was part of the eFellows program.Instructional ContextTwo large sections of an undergraduate Engineering Economics course were delivered inhybrid/buffet mode during the Fall 2012 semester, following a successful pilot and fullimplementation in earlier semesters. A thorough discussion of the course structure, components,and preliminary implementation results may be found in Grasman et al.13 As previouslydescribed, a variety of course components were utilized. The course components may becategorized as: 1. Online Resources a. WileyPLUS, the online learning environment associated with Principles of Engineering Economic Analysis 5e by White, Case and Pratt3, consisting of a

Conference Session

Computers in Education Division - General Technical Session 1

Collection

2013 ASEE Annual Conference & Exposition

Authors

Jacob P. Moore, Virginia Tech; Michel Paul Pascale; Christopher B. Williams, Virginia Tech; Chris North, Virginia Tech

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Computers in Education

framework for an information visualization arealso presented.1. Background and MotivationTechnology has the potential to aid instruction, but the simple act of using technology to deliverinstruction does not improve the instruction being delivered [1]. In order to have a positiveimpact on student learning, instructional technology developers must draw on what is knownabout how people learn and then use technology to improve the quality of the instructionalmaterials. This often involves collaboration between researchers with backgrounds in educationand those with backgrounds in software, or other technologies. This paper serves as a case studyof one such instructional software development process, the development of the Adaptive Mapdigital textbook

Conference Session

Computers in Education Division - General Technical Session 1

Collection

2013 ASEE Annual Conference & Exposition

Authors

Glenn W Ellis, Smith College; Yanning Yu, Northwestern University

Tagged Divisions

Computers in Education

, watching on-line videos of the tornadoand taking a field trip to neighborhoods impacted by the tornado (see Figure 1). During the fieldtrip they took pictures of the damage (see Figure 2) and recorded their observations andquestions.After the field trip and a short introduction to knowledge building theory, students spent oneweek collaboratively developing knowledge building questions on Knowledge Forum. They didthis by posting their observations (with pictures from the site and other pictures and videos theyfound on the Internet), as well as their initial theories and questions about their own and theirclassmates’ observations. Figure 3 shows part of the Knowledge Forum workspace developedduring the first week and shows how students built upon

Conference Session

Computers in Education Division Technical Session 1: Topics Related to Engineering - Part 2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Burford J. Furman, San Jose State University; Salman Ahsan, San Jose State University; Eric Wertz, self/EduShields

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Diversity

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Computers in Education

, one of the highest in thedepartment, where failure is defined as a student receiving a final grade of less than C-. Failurealso includes ‘unauthorized withdrawal’, which is designated on the transcript as ‘WU’. (A gradeof WU is usually given when a student stops coming to class and turning in assignments). Figure1 below shows the percentage of students who received D, F, or WU grades since 2008: Figure 1. Historical failure rates in ME 30. The average failure rate from fall 2008 to spring 2018 was 19.1%. Data for spring 2017 was not available. Prior to spring 2018, C was the language used to teach procedural programming concepts in ME 30. From fall 2018 to the present, Python is the language used. The boxed numbers correspond to

Conference Session

Computers in Education Division Technical Session 1: Topics Related to Engineering - Part 2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Conrad Tucker, Carnegie Mellon University; Kathy Schmidt Jackson, Pennsylvania State University, University Park; John Jongho Park, Penn State University

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Diversity

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Computers in Education

the power of AI to innovateand retrain its workforce? From an industry perspective, how should degree programs evolve tomeet the needs of the “real world”? Findings from this workshop can serve as a guide toresearchers and decision makers in academia, government and industry on how AI will transformboth STEM education and the workforce.IntroductionGiven today’s advanced technologies and the integration of evidence-based instructionalapproaches, an educational transformation is underway. These changes are also fueled by therecognition of the myriad of challenges facing education and in particular, issues in science,technology, engineering and math (STEM) 1. What and how we teach will directly impact ournation’s success, bringing into question

Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Rahman Adekunle; John Kofi Eshirow Jr., University of Virginia; Jacob Lam Herring, University of Virginia; Sin Lin, University of Virginia; Rider W. Foley, University of Virginia

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Diversity

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Computers in Education

computationalthinking skills needed to excel in the digital economy. One program that was created as part ofthe President’s initiative was the Research-Practitioner Partnership (RPP) grants issued by theNational Science Foundation. The program has four objectives: 1) develop a connectedcommunity of practice; 2) develop and manage a participant-driven and multi-site researchagenda; 3) convene a researcher evaluator working group to develop a process for advancing theshared-research agenda; and 4) collect qualitative and quantitative data about RPP’simplementation and common impact data. However, there has been no detailed reports or studiesof these funded RPP projects thus making their impacts difficult to observe. Thus, this researchentailed a systematic

Conference Session

Computers in Education 5 - Online and Distributed Learning 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Shamsul Arefeen, Texas Tech University; Tim Dallas P.E., Texas Tech University; Heather Greenhalgh-Spencer, Texas Tech University

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Diversity

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Computers in Education

areas ofthe world. As one of the ways to answer that need, we investigated the impact of a solar powerededucation system that is designed to deliver educational contents to less privileged people of thedeveloping world, particularly in rural locations, and mitigate the digital divide in education. Theengineered system is composed of a solar panel, battery, a pico-projector, and digital contentstored in the projector. The system unlocks the opportunity to deliver education at remotelocations where internet and electricity are not commonplace and reliable.introductionThe digital divide has been a well-researched area for decades. The divide is more of a concernwhen it affects the basic necessities, such as education and health [1]. Multiple

Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Anu Aggarwal, University of Illinois Urbana Champaign

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Computers in Education

self-explanatory. Table 1: Comparison of different platforms for administering exams [1],[2]Platform Working Pros ConsGradescope Instructor needs to upload Easy to grade – can grade More time to learn the a pdf and then convert it to each question of all students software – for both an exam by pulling at the same time. instructors and students rectangles around each (around 30 minutes). question and subpart of a Can use same rubrics for question. several

Conference Session

Computers in Education 6: Best of CoED

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sherif Abdelhamid, Virginia Military Institute; Yousef Jalali, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

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Computers in Education

researchers answer (and raise more) importantresearch questions, support administrators in making decisions on funding and institutionalpartnerships, and help faculty members design and develop more effective programs thatfacilitate research collaborations.1. Introduction1.1 Background and MotivationResearch collaboration has become a norm and common practice within and across highereducation institutions [1,2]. Bibliometric analysis of publications over time presents anillustration of growth in faculty collaboration. Jones et al. [2] examined 4.2 million researchpapers from 1975 to 2005, including different fields, science and engineering, social science, andarts and humanity, that involved 662 universities in the U.S. and concluded that there had