Conference Session

Computers in Education Division (COED) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Shirley Qin, University of Toronto; Jiawei Tian, University of Toronto; Yuqi Yang; Qian Guo, University of Toronto; Junhao Liao, University of Toronto; Hamid S. Timorabadi, University of Toronto

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Computers in Education Division (COED)

interested in software programming and User Experience designs. He is proficient with C, C++ and Python and familiar with JavaScript, PSQL, Intel FPGA Verilog and ARM Assembly(ARMv7-A). Personal Website: https://junhao.caDr. Hamid S. Timorabadi, University of Toronto Hamid Timorabadi received his B.Sc, M.A.Sc, and Ph.D. degrees in Electrical Engineering from the University of Toronto. He has worked as a project, design, and test engineer as well as a consultant to industry. His research interests include the applicati ©American Society for Engineering Education, 2023 WIP - A Face Recognition Application to Improve In-Person LearningAbstractA face recognition application that enables instructors

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Yu Sheng Pan, University of Toronto; Aniruddha Redkar, University of Toronto; Sowrov Talukder, University of Toronto; Parth Sindhu, University of Toronto; Hamid S. Timorabadi, University of Toronto

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Computers in Education Division (COED)

, University of Toronto Sowrov Talukder is a Computer Engineering student at the University of Toronto helping to improve programming labs in education.Mr. Parth Sindhu, University of TorontoDr. Hamid S. Timorabadi, University of Toronto Hamid Timorabadi received his B.Sc, M.A.Sc, and Ph.D. degrees in Electrical Engineering from the University of Toronto. He has worked as a project, design, and test engineer as well as a consultant to industry. His research interests include the applicati ©American Society for Engineering Education, 2023 WIP: Lab Container: An environment to manage a student’s time to complete programming labs while providing effective

Conference Session

COED: Computing in K-12 / Early Childhood Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

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

Tagged Divisions

Computers in Education Division (COED)

students.Limitations and Future WorkThe frameworks must be validated through qualitative research, and the work should beexpanded to include integration pathways.AcknowledgementThis work was funded by the National Science Foundation (NSF) with Grant No DRLGEGI008182. However, the authors alone are responsible for the opinions expressed in thiswork and do not reflect the views of the NSF.References[1] B. Vittrup, S. Snider, K. K. Rose, and J. Rippy, "Parental perceptions of the role of media and technology in their young children’s lives," Journal of Early Childhood Research, vol. 14, no. 1, pp. 43-54, 2016.[2] A. Sullivan, M. Bers, and A. Pugnali, "The impact of user interface on young children’s computational thinking," Journal of Information

Conference Session

The Best of Computers in Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Yiqiu Zhou, University of Illinois, Urbana-Champaign ; Qianhui Liu, University of Illinois, Urbana-Champaign ; Sophia Yang, University of Illinois, Urbana-Champaign ; Abdussalam Alawini, University of Illinois, Urbana-Champaign

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Diversity

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Computers in Education Division (COED)

design their class.Among the multiple ways to reveal collaborative problem-solving processes, temporal submissionpatterns is one that is more scalable and generalizable in Computer Science education. In thispaper, we provide a temporal analysis of a large dataset of students’ submissions to collaborativelearning assignments in an upper-level database course offered at a large public university. Thelog data was collected from an online assessment and learning system, containing the timestampsof each student’s submissions to a problem on the collaborative assignment. Each submission waslabeled as quick (Q), medium (M), or slow (S) based on its duration and whether it was shorter orlonger than the 25th and 75th percentile. Sequential compacting and

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Ryan L. Solnosky P.E., Pennsylvania State University; Rebecca Napolitano; Wesley F. Reinhart, Pennsylvania State University

Tagged Divisions

Computers in Education Division (COED)

) creating examples and projectsis one delivery mechanism but there could be a steep learning curve student will encounter [27], 6) currentdemands from larger employers who may not all use these techniques, and lastly [28]; 7) Creating newtracks is possible but requires new resources and faculty to teach them. Given these benefits and challenges,many engineering students are still often pushed to take computer science course(s) to compensate for theirlack of in-department offerings. This research looks to help overcome several aspects of these barriers inthe discipline specific domains of architectural engineering (AE) and material science and engineering(MATSE). Both fields were selected given their renewed emphasis and need for more data skills as

Conference Session

COED: Spotlight on Diverse Learners

Collection

2023 ASEE Annual Conference & Exposition

Authors

Edward Dillon, Morgan State University; Theodore Wimberly Jr.; Mariah McMichael; Lauren Brown, Morgan State University; Abigail Dina; Krystal L. Williams, University of Georgia

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Diversity

Tagged Divisions

Computers in Education Division (COED)

classified below as subtopics: 1. Established identity in CS with themselves and others. 2. Personal experiences and challenges in CS that are gender and/or race related. 3. Psycho-social characteristics experienced. 4. Personal feedback/recommendations for promoting equity, inclusion, and representation of black women in CS.Each subtopic and corresponding findings are discussed below.4.1 Established Identity in CS with Themselves & OthersFindings for this classification were based on five key questions that were asked during the focusgroup sessions: Q1: Do the participant(s) exhibit an identity towards computer science? Q2: Do the participant(s) consider themselves as computer scientists? Q3: Are they proud to be

Conference Session

COED: Skills for Moving from Computing Student to Professional

Collection

2023 ASEE Annual Conference & Exposition

Authors

Edward Dillon, Morgan State University; Abigail Dina; Mariah McMichael; Theodore Wimberly Jr.; Lauren Brown; Krystal L. Williams, University of Georgia

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Diversity

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Computers in Education Division (COED)

noted as one persistent attribute that students exhibit during theseexperiences. For instance, one aspect of Behroozi et al.’s work [7] compared anxiety levels thattheir participants exhibited while conducting mock technical interviews either in a public settingor in a private setting. It was determined that participants who conducted technical interviews ina public setting exhibited higher levels of anxiety than their counterparts who were in a privatesetting. Similarly, Hall and Gosha [23] conducted a study that measured the correlation ofanxiety and preparation in a technical interview that targeted junior and senior CS majors at aSoutheastern Historically Black College/University (HBCU) in the United States. Keyinformation collected during

Conference Session

COED Modulus Topics

Collection

2023 ASEE Annual Conference & Exposition

Authors

Adam Steven Weaver, Utah State University; Jack Elliott, Utah State University

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Computers in Education Division (COED)

engineering educators to research more holisticstudent networks than previously studied. Results of these future studies may yield moregeneralizable and accurate conclusions about which social practices help students succeed.Acknowledgements This material is based upon work supported by the second author's National ScienceFoundation Graduate Research Fellowship under Grant No. DGE1745048. Any opinions,findings, and conclusions or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation. References[1] A. Kozulin, Vygotsky’s Psychology: A biography of ideas. Cambridge, MA: Harvard University Press, 1990.[2

Conference Session

COED: Spotlight on Diverse Learners

Collection

2023 ASEE Annual Conference & Exposition

Authors

Daniel A. Tillman, University of Texas, El Paso; Wei Yan, Texas A&M University; Song An, University of Texas, El Paso; Jeffrey Liew, Texas A&M University; Kien H. Lim; Lisa Garbrecht, University of Texas, Austin; Philip B. Yasskin

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Diversity

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Computers in Education Division (COED)

institution.” Journal of Hispanic Higher Education, vol. 20, no. 3, pp. 297-312, 2021.[4] M. F. Rogers-Chapman. "Accessing STEM-focused education." Education and Urban Society, vol. 46, no. 6, pp. 716-737, 2014.[5] J. L. Petersen and J. S. Hyde. "Trajectories of self-perceived math ability, utility value and interest across middle school.” Ed. Psych., vol. 37, no. 4, pp. 438-456, 2017.[6] D. L. and Z. Lavicza, “Dissecting a Cube as a Teaching Strategy for Enhancing Students’ Spatial Reasoning,” Proceedings of Bridges 2019, pp. 319–326,[7] u/diegolieban, “GeoGebra and 3D printing: Mathematics as a creative practice,” GeoGebra, Feb. 03, 2020. www.geogebra.org/m/pkfzccjw (accessed Jan. 16, 2021).[8] Y. Gao, S. Liu, M. M. Atia, and A

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Ahmed Ashraf Butt, Purdue University at West Lafayette (COE); Saira Anwar, Texas A&M University; Muhsin Menekse, Purdue University at West Lafayette (COE)

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Computers in Education Division (COED)

.[6] K. Mite-Baidal, C. Delgado-Vera, E. Solís-Avilés, A. H. Espinoza, J. Ortiz-Zambrano, and E. Varela-Tapia, “Sentiment analysis in education Domain: A systematic literature review,” in Technologies and Innovation, R. Valencia-García, G. Alcaraz-Mármol, J. Del Cioppo- Morstadt, N. Vera-Lucio, and M. Bucaram-Leverone, Eds., Cham: Springer International Publishing, 2018, pp. 285–297.[7] Y. Sun, Z. Ming, Z. Ball, S. Peng, J. K. Allen, and F. Mistree, “Assessment of Student Learning Through Reflection on Doing Using the Latent Dirichlet Algorithm,” J. Mech. Des., vol. 144, no. 12, Sep. 2022, doi: 10.1115/1.4055376.[8] U. Naseem, I. Razzak, K. Musial, and M. Imran, “Transformer based Deep Intelligent

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Matthew Norris, Virginia Tech; Hamidreza Taimoory, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University; Jacob R Grohs, Virginia Polytechnic Institute and State University

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Computers in Education Division (COED)

students inthe college of engineering and college of arts and sciences. Student responses to open-endedquestions were scored manually by two trained raters in accordance with Grohs et al.’s publishedscoring guide [15]. Scores for each response were assigned and rationales recorded. An initialsample of 20% of the responses were scored individually by each rater. These scores were thencompared across raters to develop a consensus for interpreting student-generated text [16] andscoring guidelines normalized across raters. The remaining 80% of responses were split evenlybetween the two raters. This process required 50 human hours of work.Facilitated ScoringUsing the RStudio and the R Shiny package we import a spreadsheet of the raw text

Conference Session

COED: Computing in K-12 / Early Childhood Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Safia A. Malallah, Kansas State University; Lior Shamir, Kansas State University; William Henry Hsu, Kansas State University; Joshua Levi Weese, Kansas State University; Salah Alfailakawi, Kansas State University

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Diversity

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Computers in Education Division (COED)

Practices and Processes,” Hollylynne S. Lee etel. developed a framework using the work of statistics educators and researchers to investigatehow data science practices can inform work in K–12 education. Their framework buildsfundamental practices and processes from data science [19]. The math field has contributed to data science research via the Common Core StateStandards Initiative (CCSSI), which is a joint project to develop common K–12 reading andmath standards designed to prepare students for college and careers. The CCSSI includes a datascience section for elementary students that focuses on data collection, data type, function,analysis type, and sample [20]. Similarly, the Launch Years Data Science Course Frameworkprovides broad

Conference Session

COED: Online and Remote Learning

Collection

2023 ASEE Annual Conference & Exposition

Authors

Rishi Sunny Gulati; Matthew West, University of Illinois, Urbana-Champaign; Craig Zilles, University of Illinois, Urbana-Champaign; Mariana Silva, University of Illinois, Urbana-Champaign

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Diversity

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Computers in Education Division (COED)

offering online sections of courses to students that want the flexibilitythat they facilitate, if their primary concern is student performance. We found no statistically sig-nificant difference in the overall performance of students that elect to take a course online relativeto those that elect to take it in person. Taking courses online may, however, have a substantialnegative impact on a student’s sense of belonging. This effect is particularly pronounced for un-derrepresented minority students and first generation students, but not present in women.References [1] B. Bizot and S. Zweben, “Generation cs, three years later,” On the Internet at https://cra. org/generation-cs- three-years-later/(visited August 2019), 2019. [2] T. Camp, W. R

Conference Session

COED: Skills for Moving from Computing Student to Professional

Collection

2023 ASEE Annual Conference & Exposition

Authors

Rachel Field, Morgan State University; Steven J. Fuller; Edward Dillon, Morgan State University

Tagged Divisions

Computers in Education Division (COED)

institutions are beginning toimplement technical interview practices into the classroom as assignments, group projects,warm-ups, class exercises, and dedicating a class to the topic. For instance, literature shows thatexposing students to technical interview exercises in their Data Structure course(s) is one of themost effective methods. One reason being that students are exposed to the process early on but itbecomes natural for them to think as interviewees based on the construct of these particularcourses. Likewise, literature suggests that introducing the technical interview process early in astudent’s computational development could better gauge the overall effectiveness of thisemployed initiative. Yet, the number of studies that reflect such

Conference Session

COED: Computing in K-12 / Early Childhood Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Safia Malallah, Kansas State University; Lior Shamir, Kansas State University; William Henry Hsu, Kansas State University; Joshua Levi Weese, Kansas State University; Salah Alfailakawi, Kansas State University

Tagged Divisions

Computers in Education Division (COED)

forearly childhood. As a future work, the models and framework developed could be branched intoseveral qualitative research studies for validation. Additionally, AI inclusion for early childhoodlearning could be studied.AcknowledgementsThis work was funded by the National Science Foundation (NSF) with Grant No DRLGEGI008182. However, the authors alone are responsible for the opinions expressed in thiswork and do not reflect the views of the NSF.References[1] A. Strawhacker and M. U. Bers, "Promoting positive technological development in a Kindergarten makerspace: A qualitative case study," European Journal of STEM Education, vol. 3, no. 3, p. 9, 2018.[2] B. Vittrup, S. Snider, K. K. Rose, and J. Rippy, "Parental perceptions of the

Conference Session

COED: AI and ML Topics

Collection

2023 ASEE Annual Conference & Exposition

Authors

Nebojsa I. Jaksic, Colorado State University, Pueblo; Bahaa Ansaf, Colorado State University, Pueblo

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Diversity

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Computers in Education Division (COED)

of applications that were introduced in the workshop.Upon completion of the workshop, the participants were given an eight-question exit post-trainingsurvey shown in Figure 2. There were six quantitative questions using a five point or a three-pointLikert scale as well as two qualitative questions. The two qualitative questions were also used aspedagogical tools based on experiential learning best practices. Question 7’s goal was to elicit apositive self-reflection while Question 8 reinforced learning through internalization andsummarization. 1. Exiting this workshop, I learned something new about AI concepts, applications, and ethics (1 - strongly disagree to 5 - strongly agree). 2. I have a better understanding of AI and how to

Conference Session

COED: Online and Remote Learning

Collection

2023 ASEE Annual Conference & Exposition

Authors

Janardhanan Gangathulasi, National Institute of Technical Teachers Training and Research, Chennai, India; Shanmuganeethi Velu, P.E.; P. Malliga; Dinesh Kumar K.S.A.

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Computers in Education Division (COED)

University, India. He extensively traveled within and abroad for technical lectures viz., USA, Germany, Belarus, China, Hong Kong, Thailand, Malaysia, Singapore.Dr. Shanmuganeethi Velu, P.E., Dr. V.Shanmuganeethi, Professor, Department of Computer Science and Engineering. He has been work- ing in the domain of Education Learning Analytics, web technologies, programming Paradigm, Instruc- tional technologies and Teaching aˆ C” Learning PraDr. P. MalligaDr. Dinesh Kumar K.S.A. Dr. K S A Dineshkumar, Assistant Professor, Department of Civil Engineering. He has been working in the domain of Structural Engineering, Geographical Information System, Sustainable development, Smart City, Instructional technologies and Teaching

Conference Session

COED: AI and ML Topics

Collection

2023 ASEE Annual Conference & Exposition

Authors

Shatha Jawad, National University; Ronald P. Uhlig, National University; Pradip Peter Dey; Mohammad N. Amin, National University; Bhaskar Sinha, National University

Tagged Divisions

Computers in Education Division (COED)

back on trackfaster by alerting teachers to potential problems. This paper proposes a Deep Learning NeuralNetworks approach that helps students select their best-fit specialization in a specific category.Deep learning is a subset of machine learning, but it can determine whether a prediction isaccurate through its own neural network- no human help is required [1]. The proposed systemwill use a dataset that contains student data that is related to the general education coursesrequired for their program, such as grades, the number of hours spent on each course's materials,the opinion of the student about the content of each course, and the course(s) that the studentenjoyed the most. Additional data will be included in the dataset such as the

Conference Session

The Best of Computers in Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Sarah L. Harris, University of Nevada, Las Vegas; Daniel Chaver Martinez, University Complutense of Madrid, Spain; Luis Piñuel; Olof Kindgren; Robert C.W. Owen

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Computers in Education Division (COED)

, Thong Doan, Oliver Rew, NikoNikolay, and Guanyang He. We also acknowledge the support of projects PID2021-123041OB-I00, funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”,and by the CM under grant S2018/TCS-4423.References[1] RISC-V International: https://riscv.org/. Accessed February 21, 2023.[2] VeeR (SweRV) Cores: https://github.com/chipsalliance/Cores-VeeR-EH1, https://github.com/chipsalliance/Cores-VeeR-EL2, https://github.com/chipsalliance/Cores- VeeR-EH2. Accessed February 21, 2023.[3] Arm Introduction to Computer Architecture: https://www.arm.com/resources/education/education-kits/computer-architecture. Accessed February 21, 2023.[4] S. Harris, D. Harris, D. Chaver, R. Owen, Z. Kakakhel, E

Conference Session

The Best of Computers in Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Andrew Rukangu, University of Georgia; John Ray Morelock, University of Georgia; Kyle Johnsen, University of Georgia

Tagged Divisions

Computers in Education Division (COED)

extent to which students be- Self-determination theory (Deci and Ryan, 2000), par- lieve they have meaningful control ticularly the importance of autonomy to intrinsic mo- over their learning. tivation (Reeve and Jang, 2006). (U)sefulness The extent to which students be- Future time perspective theory (Simons et al., 2004) lieve the material will be useful to and the utility value construct of expectancy-value them. theory (Wigfield and Eccles, 2000). (S)uccess The extent to which students be- Ability beliefs, including self-efficacy and com

Conference Session

COED: Grading Systems

Collection

2023 ASEE Annual Conference & Exposition

Authors

Marko V. Lubarda, University of California, San Diego; Alex M. Phan, University of California, San Diego; Aidan Daniel Carrigg; Karthik Srinivasan; Josephine Relaford-Doyle, University of California, San Diego

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Diversity

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Computers in Education Division (COED)

Conference Session

COED: Skills for Moving from Computing Student to Professional

Collection

2023 ASEE Annual Conference & Exposition

Authors

Mary Kay Camarillo, University of the Pacific; Elizabeth Basha, University of the Pacific

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Computers in Education Division (COED)

instruction in multiple STEM disciplines,”presented at the ASEE Annual Conference, Virtual Conference, Jul 26-9, 2021. Available:https://peer.asee.org/37955.[2] C. Torres-Machi, A. Bielefeldt, and Q. Lv, “Work in progress: The strategic importanceof data science in civil engineering: Encouraging interest in the next generation,” presented at theASEE Annual Conference, Minneapolis, MN, Jun 26-9, 2022. Available:https://peer.asee.org/40713.[3] S. Grajdura and D. Niemeier, "State of programming and data science preparation in civilengineering undergraduate curricula," Journal of Civil Engineering Education, vol. 149, no. 2, p.04022010, 2023, doi: doi:10.1061/(ASCE)EI.2643-9115.0000076.[4] J. G. Hering, "From slide rule to big data: How data

Conference Session

COED: Skills for Moving from Computing Student to Professional

Collection

2023 ASEE Annual Conference & Exposition

Authors

Stephanie Jill Lunn, Florida International University; Veon Brewster, Florida International University

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Computers in Education Division (COED)

Conference Session

COED Programming Education 1: Students, Motivation, and Mastery

Collection

2023 ASEE Annual Conference & Exposition

Authors

James E. Lewis, University of Louisville; Nicholas Hawkins, University of Louisville; Brian Scott Robinson, University of Louisville

Tagged Divisions

Computers in Education Division (COED)

thesimilarities and differences of the APL to Python. Upon completion of the “Programminglessons”, there is a series of activities designed to help the students create circuit(s) andprogram(s) that interact with each other.The programming and circuitry scaffolded modules prepare students for an end-of-semesterCornerstone Project. ENGR 111 currently has two different Cornerstone Projects. TheCornerstone Project is determined by the semester and year that the course is taken. The firstCornerstone Project (Project 1) is comprised of a windmill power generation system. Project 1has students constructing a windmill and using Arduino programming to interpret sensor dataand calculate system performance. The second Cornerstone Project (Project 2) is comprised of

Conference Session

COED: All about That Math

Collection

2023 ASEE Annual Conference & Exposition

Authors

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Computers in Education Division (COED)

a better understanding of the subject and the ability to use and apply it [11].A Survey conducted by Poçan, S., Altay, B. & Yaşaroğlu, C [1] showed the effects of using appson the success and motivation of 73 students in a high school algebra class. The findingsrevealed that mobile technology applications positively impact the learning process. Fabian,Topping, and Barron [2] explored the effects of mobile technology on the attitudes andachievements of 52 elementary school students. They found that mobile technology results inpositive student responses, improving their performance. Yussop, Annamalai, and Salam [3]investigated to find out the effectiveness of a particular mobile application. They found that byusing the app, students

Conference Session

COED Programming Education 1: Students, Motivation, and Mastery

Collection

2023 ASEE Annual Conference & Exposition

Authors

Thomas Rossi, Penn State Behrend; Paul C. Lynch, Penn State Behrend

Tagged Divisions

Computers in Education Division (COED)

Learning Methods: Definitions, Comparisons, and Research Bases," Journal of College Teaching, vol. 36, no. 5, pp. 14-20, 2007.[5] T. Ruutman and H. Kipper, "Teaching Strategies for Direct and Indirect Instruciton in Teaching Engineering," in Proceedings of 14th International Conference on Interactive Collaborative Learning, Slovakia, 2011.[6] A. Poulsen, K. Lam, S. Cisneros and T. Treust, "ARCS Model of Mtivational Design," November 2008. [Online]. [Accessed December 2014].[7] S. Bjorklund, J. Parente and D. Sathianathan, "Effects of Faculty Interaction and Feedback on Gains in Student Skills," Journal of Engieering Education, vol. 93, no. 2, pp. 153-160, 2004.[8] P. Hsieh, J. R. Sullivan and N. S. Guerra, "A Closer

Conference Session

COED: Grading Systems

Collection

2023 ASEE Annual Conference & Exposition

Authors

Chenyan Zhao, University of Illinois, Urbana-Champaign; Matthew West, University of Illinois, Urbana-Champaign; Mariana Silva, University of Illinois, Urbana-Champaign

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Diversity

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Computers in Education Division (COED)

: https://doi.org/10.1111/j.1540-4609.2012.00366.x [3] C. A. Shaffer and S. H. Edwards, “Scheduling and student performance,” in Proceedings of the 16th Annual Joint Conference on Innovation and Technology in Computer Science Education, ser. ITiCSE ’11. New York, NY, USA: Association for Computing Machinery, 2011, p. 331. [Online]. Available: https://doi.org/10.1145/1999747.1999842 [4] S. Willman, R. Lindén, E. Kaila, T. Rajala, M.-J. Laakso, and T. Salakoski, “On study habits on an introductory course on programming,” Computer Science Education, vol. 25, no. 3, pp. 276–291, 2015. [5] G. Schraw, T. Wadkins, and L. Olafson, “Doing the things we do: A grounded theory of academic procrastination,” US, pp. 12–25, 2007. [Online

Conference Session

The Best of Computers in Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Jayma Koval, Georgia Institute of Technology; Diley Hernandez, Georgia Institute of Technology; Tom McKlin; Douglas Edwards, Georgia Institute of Technology; Rafael A. Arce-Nazario; Joseph Carroll-Miranda; Isaris Rebeca Quinones Perez, University of Puerto Rico, Rio Piedras; Lilliana Marrero-Solis; Jason Freeman, Georgia Institute of Technology; Taneisha Lee Brown; Pascua Padro; Stephen Garrett; Analia E. Rao; Marion Usselman, Georgia Institute of Technology

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Diversity

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Computers in Education Division (COED)

theCollective Self-Esteem Scale [35] and included three of the original MIBI-T seven subscales(centrality, private regard, and public regard). We used this scale with the purpose of exploringstudents’ ethnic identity identification [36]. Because Latinx ethnic identity can be complex andvaried, we developed an initial question to allow the students to self-identify ethnically(Latin/Hispanic, Puerto Rican/Boricua, etc.), they then answered follow-up questions related tothat identity such as “I have a strong sense of belonging to other _____ people,” and “Mostpeople think that ______(s) are as smart as people of other groups.”Sense of Belongingness in Computer Science: Items were selected from the Sense of Social andAcademic Fit (in STEM) instrument [37

Conference Session

COED: Spotlight on Diverse Learners

Collection

2023 ASEE Annual Conference & Exposition

Authors

Vijesh J. Bhute, Imperial College London; Ellen Player; Deesha Chadha, Imperial College London

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Diversity

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Computers in Education Division (COED)

virtual learning environment in a university class,” Comput. Educ., vol. 56, no. 2, pp. 495–504, 2011, doi: 10.1016/j.compedu.2010.09.012.[2] J. Barker and P. Gossman, “The learning impact of a virtual learning environment : students’ views,” Teach. Educ., vol. 5, no. 2, pp. 19–38, 2013.[3] H. Waheed, S. U. Hassan, N. R. Aljohani, J. Hardman, S. Alelyani, and R. Nawaz, “Predicting academic performance of students from VLE big data using deep learning models,” Comput. Human Behav., vol. 104, no. November 2018, p. 106189, 2020, doi: 10.1016/j.chb.2019.106189.[4] J. Kuzilek, J. Vaclavek, Z. Zdrahal, and V. Fuglik, “Analysing Student VLE Behaviour Intensity and Performance.,” in Transforming Learning with

Conference Session

COED: Cybersecurity Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Sai Sushmitha Sudha; SaiSuma Sudha; Ahmad Y. Javaid, The University of Toledo; Xiaoli Yang

Tagged Divisions

Computers in Education Division (COED)

comprehension of the subjects in cybersecurity. Following the lecturesessions, the students appeared to have improved their knowledge and understanding of thesubject, as evidenced by the rise in the average value of each question in the post-surveycompared to the pre-survey. This may be ascribed to the thorough lecture materials and practicallab exercises that were made available to the students, which helped to reinforce the ideas andprovide them with hands-on experience using the knowledge acquired. The findings support theidea that providing cybersecurity education to undergrad students can significantly affect theircomprehension of and readiness for the sector. Table 2 Questions of Quiz Survey S. No. Questions of