Conference Session

Computers in Education 2 - Programming 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Safia Malallah, Kansas State University; Khaled Nasser Alsalmi, The Public Authority for Applied Education and Training; Joshua Levi Weese, Kansas State University

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Computers in Education

bring CT into classrooms. This study sought to identify CT awareness in different educational roles to suggest a plan to promote CT in Kuwait education institutes. The promoted plan employs the CT Systemic Change Model, developed by ISTE. We utilize the model with the outcome of our CT awareness surveys to recommend a plan that fits the regulations and roles in Kuwait education. The survey derived from the technological pedagogical content knowledge framework; It investigated CT awareness of content knowledge (knowledge of CT concepts), pedagogical knowledge (knowledge of CT purposes, values, and aims), and technological knowledge (knowledge of the technologies and resources that support CT

Conference Session

Computers in Education 1 - Programming 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Pat Ko, Mississippi State University; Mahnas Jean Mohammadi-Aragh, Mississippi State University; Jonathan G. Harris, Northern Gulf Institute; Jamie Lee Dyer, Mississippi State University; Yan Sun, Mississippi State University

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Computers in Education

classroom, we are using a“teach the teacher” model. We provide a two-week summer professional development for middleschool teachers in the state. During the program, the teachers are taught introductory weather science,the IDV visualization software basics, and how to obtain free weather data from the National Oceanicand Atmospheric Administration (NOAA). Restrictions due to the COVID19 pandemic requiredmodifications to our planned initial year activities, but we were able to pilot and obtain feedback toimprove the program. Our plans for the 2021-2022 school year include offering our full summerprofessional development workshop, observing teachers in their classrooms while they implementmeteorology lessons with computational thinking, and

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Thad B. Welch, Boise State University; Cameron H. G. Wright P.E., University of Wyoming; Michael G. Morrow, University of Wisconsin - Madison

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Computers in Education

Engineering Education, 2021 Lemons into Lemonade!AbstractThis paper discusses a trial of offering two senior/first-year graduate classes in a 7-week format,one following the other. Thus, a student could complete two courses (6-credits), dealing with twoclosely related topics, in one semester. In this case, the courses were Digital CommunicationSystems and Wireless Communications.During the first week of the first 7-week course, all of the in-class demonstrations and hands-onexperiences needed to be shifted to online/remote delivery. This was primarily accomplishedusing the Amazon Web Services (AWS) AppStream, cloud computing system.The planned real-world signal capture and analysis project changed to an optional

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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c Society for Engineering Education, 2021Online COVERAGE (Competition Of VEX Educational Robotics to Advance Girls Education) (Research-to-Practice, Strand: Other)IntroductionThe major objective of the COVERAGE (Competition Of VEX Educational Robotics toAdvance Girls Education) project is to increase female West Virginia middle school students’interest in Computer Science and STEM. As the original plan of the COVERAGE project, GirlsRobotics Clubs would be organized in three counties of West Virginia, including Kanawha,Fayette, and Lincoln Counties, to prepare female middle school students for a regional roboticscompetition at the end of 2020. The Covid-19 pandemic started soon

Conference Session

Computers in Education 1 - Programming 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Astrid K. Northrup P.E., Northwest College; Raymond Edward Floyd, Northwest College; S. Renee Dechert, Northwest College; Andrea Carneal Burrows Borowczak, University of Wyoming

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Computers in Education

theclassroom. Discussion forums and sharing of computational artifacts (lesson plans anddemonstrations) were central to the structure of this class to address Practice 1 (Fostering anInclusive Computing Culture in an exploration of cyber citizenship), Practice 2 (CollaboratingAround Computing in the creation and sharing of computer artifacts), and Practice 7(Communicating About Computing). Application Development reinforces computationalthinking and traditional programming skills (Practices 5 & 6) in the development of artifacts thathave immediate classroom applications. To summarize, with the directive issues by former Governor Mead, and the Practicesoutlined in the Wyoming Computer Science Standards, it became clear that COSC 1010

Conference Session

Computers in Education 1 - Programming 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Ben Tribelhorn, University of Portland; Heather Dillon, University of Washington Tacoma; Andrew M. Nuxoll, University of Portland; Nicole C. Ralston, University of Portland

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Computers in Education

of a course.Specifically Scrum specifies that in each iteration of work, a sprint, should include planning, dailystand-ups, reviews, and retrospectives. It also specifies how to keep the requirements backlogorganized along with roles to manage the process.Figure 1: Summary of the EM modules (purple) discussed in this paper, in the context of the coursetimeline.The modules developed had several learning objectives focused on the entrepreneurialmindset: • Students will identify and describe links between course knowledge and real world systems. [connections] • Students will improve their ability to self-reflect and evaluate preconceived ideas, thoughts, and accepted solutions to recognize opportunities. [curiosity

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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Computers in Education

in the development of online programs for academic credit and workforce development. Prior to coming to Texas A&M, Randy worked at Stephen F. Austin State University for twenty-five years in a variety of roles including technology specialist for the Center for Professional Development and Technology, tenured faculty member in the College of Education, director of instructional technology and distance education, director of the university’s Quality Enhancement Plan, and director of the Center for Teaching and Learning. Randy holds a B.B.A. in Information Systems and Quantitative Studies from Abilene Christian University, an M.Ed. in Secondary Education from Stephen F. Austin State University, an M.S. in

Conference Session

Computers in Education 6: Best of CoED

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Nabeel Alzahrani, University of California, Riverside; Frank Vahid, University of California, Riverside

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Computers in Education

desired a way to see the progression of a student's coding. The auto-grader’s web interfacedoes provide links to all submitted code, but that was insufficient -- manually examining each code rundidn't provide a quick or easy way to gain insight on what the student changed in the code.This paper describes a tool we developed to automatically highlight differences between each run, and toprovide statistical data for those runs, forming the main part of our contribution. The current toolimplementation is language independent. We plan to make the tool freely available on the web (both theroster/statistics and the progression highlighting), to serve CS educators who may wish to gain insightson their students and/or to conduct research on programming

Conference Session

Computers in Education 5 - Online and Distributed Learning 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sunay Palsole, Texas A&M University; Jaskirat Singh Batra, Texas A&M University; Xi Zhao, Texas A&M University

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Computers in Education

information exchange. These informal exchanges are important to engender in technology-enhanced learning to ensure that the students have opportunities for developing informal engagement and space.Purpose of StudyGiven the rapid transition to remote and online learning formats, we developed a study toinvestigate the tools (technologies and platforms), and methods used by faculty to engage withstudents in asynchronous and synchronous learning. In addition, we planned to gain anunderstanding of how students adopt technological tools to keep some continuity in theirinformal and social learning networks, so we also surveyed the students to identify thetechnology, platforms, and methods they use to communicate with each other outside of classhours

Conference Session

Computers in Education 1 - Programming 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Frank Vahid, zyBooks; University of California, Riverside; Roman Lysecky, University of Arizona; zyBooks; Bailey Alan Miller, University of California, Riverside; Lyssa Vanderbeek, zyBooks

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Computers in Education

scattered throughout. We thusabandoned efforts to show when students worked, at least for now.Total time spent is also something teachers would like to see. We tried putting time spent at the end ofeach day, plus a total at the end of the coding trail. We found though that teachers were most interestedin the total time; the detailed breakdown was interesting but not so important as to clutter the codingtrail. Thus, we plan to put the time info at the end of the coding trail, like below where the student spenta total of 42 minutes: 7/13 M----0 S---2|4--10 42minLikewise, teachers indicated wanting to know code size each day. Like time-of-day and time spent, suchinfo can quickly clutter the coding trail. Thus, we plan to just put the code

Conference Session

Computers in Education 2 - Programming 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Nabeel Alzahrani, University of California, Riverside; Frank Vahid, University of California, Riverside

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Computers in Education

43 Lack of plan 11 Miscellaneous 4 Typos Total no. of errors 166Table 1: 11 error categories for the 166 errors in the 47 publications from 1985 to 2018 with an example of the most common error in each category.Obviously, we cannot provide explanations and examples for all 166 logic errors. Instead, wehighlighted in bold errors reported in multiple publications, and highlighted with an asterisk errors that[7, 8] found to be the most time-consuming, yielding 43 highlighted errors. References are included forall 211 errors, however, so that a reader can find details in previous publications of any error of interest.Common errorsTable 1

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Arinjoy Basak, Virginia Polytechnic Institute and State University; Todd Patrick Shuba, Virginia Polytechnic Institute and State University; Jianqiang Zhang, Virginia Polytechnic Institute and State University; Sneha Patel Davison, Virginia Polytechnic Institute and State University; David A. Dillard, Virginia Polytechnic Institute and State University; Jacob R. Grohs, Virginia Polytechnic Institute and State University; Nicole P. Pitterson, Virginia Polytechnic Institute and State University; Clifford A. Shaffer, Virginia Polytechnic Institute and State University

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Computers in Education

workflow, and describesupport for targeted feedback and analysis for the instructors. We present our plans to evaluatethe system, and discuss the results of a preliminary usability study.1. IntroductionRecent studies show problem-solving ability is being increasingly prioritized as a core aspect ofengineering curriculum and a fundamental competency demanded by employers. However, notonly are problem-solving activities time consuming for students, they are also often difficult toassess beyond simply checking for correctness of the final answer. In addition, it is difficult in aclassroom setting to deliver useful feedback [1]. While popular online tutoring frameworks exist[2], [3] that support structures for mathematical problem solving and some

Conference Session

Computers in Education 9 - Technology 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Mahgol Nowparvar, Pennsylvania State University ; Xing Chen, Pennsylvania State University ; Omar Ashour, Pennsylvania State University ; Sabahattin Gokhan Ozden, Pennsylvania State University Abington; Ashkan Negahban, Pennsylvania State University

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Computers in Education

issues and understand howinterdisciplinary instruction affects students’ ability to identify, formulate, and solve problems,communicate effectively, appreciate the impact of planning and engineering solutions, anddevelop understanding of ethics-related factors. The effectiveness of integration of PBL andimmersive technologies is measured with pre/post surveys related to the above outcomes and theresults indicate increased technical and collaborative skills in students.The authors in [42] work with graduate and undergraduate students to develop a web-based 3Dvisualization and cluster computing system for disaster data management, resource distributionand communication between local authorities and disadvantaged populations affected by adisaster

Conference Session

Computers in Education 9 - Technology 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Emre Tokgoz, Quinnipiac University; Samantha Eddi Scarpinella, Quinnipiac University; Michael Giannone, Quinnipiac University

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Computers in Education

since 2011. His other research interests include nonlinear optimization, financial engineering, facility alloca- tion problem, vehicle routing problem, solar energy systems, machine learning, system design, network analysis, inventory systems, and Riemannian geometry.Samantha Eddi Scarpinella , Quinnipiac University Samantha Scarpinella is a Senior Industrial Engineering major at Quinnipiac University with additionally pursuing mathematics and business minors. Her research interests include healthcare, human factors and engineering education. She is planning to be an engineering professor as her profession.Mr. Michael Giannone, Quinnipiac University Michael Giannone is currently a Senior at Quinnipiac University

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

James Kretzschmar, University of Wyoming; Robert F. Kubichek, University of Wyoming; Cameron H. G. Wright P.E., University of Wyoming; Steven F. Barrett, University of Wyoming; Jeffrey R. Anderson, University of Wyoming

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Computers in Education

pandemic. Engineering education is not immune to thesenew dynamics, and institutions need to plan and prepare to embrace new modalities of instruction.Historically, electrical engineering courses have had lab requirements that have involved physicalpresence in a laboratory with several pieces of test equipment available for testing circuits. Inrecent years, computer-based laboratory equipment has become available that can provide thesame robustness needed to facilitate learning for online electrical engineering courses. A pilotstudy was conducted at our institution using a home-based laboratory for two electrical engineeringcourses (Microcontrollers and Electric Circuit Analysis). Presented will be the development ofthe labs, implementation of the

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Roxanne Moore, Georgia Institute of Technology; Sunni Haag Newton, Georgia Institute of Technology; Meltem Alemdar, Georgia Institute of Technology; Sabrina Grossman, Georgia Institute of Technology; Jason Freeman, Georgia Institute of Technology; Jason Brent Smith, Georgia Institute of Technology; Tom Berry, Amazon Future Engineer

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Computers in Education

educational evaluation, including K-12 educational curricula, K-12 STEM programs after-school programs, and comprehensive school reform initiatives. Across these evaluations, she has used a variety of evaluation methods, ranging from a multi-level evalua- tion plan designed to assess program impact to methods such as program monitoring designed to facilitate program improvement. She received her Ph.D. in Research, Measurement and Statistics from the Depart- ment of Education Policy at Georgia State University (GSU).Sabrina Grossman, Georgia Institute of Technology Sabrina Grossman, Program Director in Science Education at Georgia Tech’s Center for Education In- tegrating Science, Mathematics, and Computing (CEISMC), who

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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Computers in Education

areplacement for professors and peers when they needed help. Nearly all students (96%) providedfavorable ratings about the trustworthiness of the video library and most students trusted the MEOnline videos more than other videos available online. They were particularly happy whenfinding videos by their favorite instructors who were clear, engaging, and knowledgeable. Moststudents plan on using ME Online as alumni for both professional and personal reasons – 88% ofthe students reported they expect to use ME Online to study for licensing exams, graduate schoolwork, professional work, and/or just to learn new things.The study also explores the potential for video libraries like ME Online to help addressachievement gaps among historically disadvantaged

Conference Session

Computers in Education 5 - Online and Distributed Learning 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Tiffanie R. Smith, Lincoln University; Susan Ellen Safford, Lincoln University; Chidera Iguwe; Mofoluwasho Akinlade

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Computers in Education

difficultto navigate through the app and complained about designs and other minor issues. Ultimately, theproject was temporarily halted and a new application is currently being designed and developedwith the same objectives. It will only have a different framework and personnel on theproject.The new path for the project includes switching to React Native for cross-platform mobiledevelopment and a goal to create a functional product for evaluation for final exam review.Thischange also follows best practices in app development as described by Wardynski1 and wouldserve all students with a mobile phone 1 . Future plans would include creating a Professorfunctionality that helps the professor see the efforts made by the students and assign grades basedon

Conference Session

Computers in Education 6: Best of CoED

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Molly Rebecca Domino, Virginia Polytechnic Institute and State University; Margaret O'Neil Ellis; Dennis Kafura

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primarily done for the interviewer to get a better understanding of the student population.After a brief introduction from the interviewer about the study, students were directed to sign uponline for a 45 minute time slot if interested. A scheduling conflict caused this presentation to begiven on different class days in the Fall and Spring semesters. However, all interviews occurredafter students had been exposed to the iteration module and before the post-quiz wasadministered.In the fall semester, all time slots were filled before the second section had a chance to sign up. Tomitigate this in the spring semester, a different plan was implemented. Two different sign-upsheets were created: one for each section of the class. In the case students from

Conference Session

Computers in Education 10 - Technology 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Jeffrey Todd McDonald, University of South Alabama; Dawn McKinney, University of South Alabama; Todd R. Andel, University of South Alabama

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Computers in Education

ofminterms (1-producing input terms) and maxterms (0-producing input terms). PETGUI providesa view of the minterms and maxterms of the function in a traditional KMAP view, howeverreduction steps of the KMAP are not integrated directly into the interface currently (planned forfuture work). Figure 3 shows the KMAP of the circuit function in Figure 1 as an example andillustrates how the minterm information (010, 100, 101) could be reduced into smaller forms(prime and essential prime implicants) with don’t care conditions (010, 10X). In practice,students could use the KMAP view as a basis to apply reductions and then check work usingessential prime implicants. Through third-party tool integration such as ABC and Espresso,PETGUI can also produce several

Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Gulustan Dogan, University of North Carolina Wilmington; Yang Song, University of North Carolina Wilmington; Damla Surek, Yildiz Technical University

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Computers in Education

challenge junior students to learn CT as a newset of concepts , and help senior students to revisit the CT-related concepts they have alreadylearned.The limitation of this project is that this project only used students’ time-on-task informationfrom different courses. In the future, the authors plan to get students’ feedback toward theirexperience and the perceived usefulness of CT concepts from student survey(s).To download the CT course module we have designed, please visit:https://bit.ly/3bfxohR.6 AcknowledgementWe would like to thank all the students and teachers who participated in this project. Thismaterial is based upon work supported by the Center of Teaching Excellence Summer PedagogyDevelopment Award of University of North Carolina

Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Joseph Maloba Makokha, Stanford University

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Computers in Education

, augmenting humans, or unsuitable forthe task). BASIS OF THEIR PROPOSAL RELATIONSHIP AUTHORS TO HUMANS Exhibit intuition, insight and learning. Machines that think, that REPLACE NEWELL, SHAW, learn, that create … the range of problems which they can SIMON[16] handle will be coexistive with the range to which the human mind has been applied. Programming a robot with an integrated suite comprising REPLACE Nilsson, N. J.[17] planning systems, models of the world and sensory processing systems enables it to successfully accomplish tasks in the real world settings. Role of AI cased

Conference Session

Computers in Education 8 - Video Technology

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Markus Iseli, University of California, Los Angeles; Tianying Feng, University of California, Los Angeles; Gregory Chung, University of California, Los Angeles; Ziyue Ruan; Joe Shochet, codeSpark; Amy Strachman, codeSpark

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Computers in Education

such as NAEP or PISA that would allow those programs to offer assessments ofcomputational thinking.In future research we plan to: a) Extract new, visualization-informed measures derived from thetime series used in these visualizations. E.g., first and second order derivatives, means andvariances to infer CT constructs can be used. b) Use the newly extracted measures to providereal-time feedback to students and/or teachers. c) Explore the use of the newly extractedmeasures as new features for inputs to machine learning models and algorithms.References[1] H. M. Madill, R. G. Campbell, D. M. Cullen, A. A. Einsiedel, A.-L. Ciccocioppo, and M.- A. Armour, “Developing Career Commitment in STEM-related Fields: Myths versus Reality,” in Women

Conference Session

Computers in Education 10 - Technology 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Valerie Varney, TH Cologne; Dominik May, University of Georgia

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Computers in Education

reality technologies for learningcontexts. Therefore the authors have identified two exemplary use cases, which will beexamined by using the framework. The first use case is set at [university 1]. In this use case,groups of Bachelor students are asked to plan a shop floor of a robotics manufacturer via anaugmented reality application and afterwards maintain it in a fully immersive virtual realityenvironment. During the process of maintenance several problems occur that the studentsneed to solve. The key to success is a combination of effective communication, skilfulteamwork and a sensible division of labour. The mixed reality game was developed in 2019and 2020 and applied for the first time in 2020 in a class of 460 engineering students. Theother

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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Computers in Education

and content knowledge. This is an important consideration for CS education, asteachers must understand how to integrate computer science skills and competencies into theirlesson plans. Pilot projects and localized programs have shown success in developing thiscapacity within teachers. For example, a researcher group from University of SouthernCalifornia collaborated with nine teachers in three elementary schools in the Latino communityof Boyle Heights in Los Angeles and created the Building Opportunities with Teachers inSchools (BOTS) program [11]. The focus of this program is to use robotics and other non-computer-based activities to teach CS concepts in a physical form. One of the long-term goals ofthe BOTS program is to provide a low-cost

Conference Session

Computers in Education 2 - Programming 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Xueyi Bao, Notre Dame University; Jun Han, University of Notre Dame; Chaoli Wang, University of Notre Dame

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Computers in Education

techniques applied tothe same volumetric data set in two side-by-side display panels, allowing students to make an easy comparison byadjusting parameters such as cutting planes, lighting, and viewing. The two display panels also react synchronicallyto interactions when parameters are changed. This is more helpful for students to understand the respective strengthsand weaknesses of these rendering techniques rather than solely relying on instructors in explaining the differences.P4: Modular and web-friendly. We design VolumeVisual with possible future expansion in mind. Therefore, we fol-low a modular design, making it easy to include other additions not yet planned. WebGL is used for easy deployment,which is based on the widely-adopted Internet