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

Tagged Divisions

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

Programming Education 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sunjae Park, Wentworth Institute of Technology

Tagged Divisions

Computers in Education Division (COED)

problem for sufficiently large numbers, for most introductory C programming this is not aproblem. For example, strlen returns an unsigned integer. This means the following code can leadto a compiler warning.f o r ( i n t i = 0 ; i < s t r l e n ( ” H e l l o ” ) ; i ++)Some other issues were the sluggishness of every operation. Running Ubuntu inside a virtualmachine is taxing on the graphics card, and the slow build times of catch2 was a frequent complaint.Novice students tend to write relatively small programs, so the additional compile time can slowdown their development cycle.In subsequent iterations, students running Windows were instructed to use Windows Subsystem forLinux (WSL) instead of a hypervisor. Visual Studio Code (and CLion) both

Conference Session

Spotlight on Diverse Learners

Collection

2024 ASEE Annual Conference & Exposition

Authors

Minkyung Lee, Pennsylvania State University; Stephanie Cutler, Pennsylvania State University; Sarah E Zappe, Pennsylvania State University; Sam Spiegel, Colorado School of Mines; Ibukun Samuel Osunbunmi, Pennsylvania State University

Tagged Divisions

Computers in Education Division (COED)

variety of instructional modes. Future studies could benefit from a designwhere students experience each mode of instruction for different subjects to provide a moreaccurate measure of preference and performance. Such research would offer a deeperunderstanding of how different instructional modes influence learning outcomes and couldpotentially inform more effective educational practices. References[1] Freeman, S., et al. 2014. Active learning increases student performance in science,engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23),8410-8415.[2] Prince, M. 2004. Does active learning work? A review of the research. Journal ofEngineering Education, 93(3), 223-231.[3

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

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Zoe Wood, California Polytechnic State University, San Luis Obispo; Miguel Manoah Refugio Greenberg

Tagged Divisions

Computers in Education Division (COED)

important for people to learn how to code because we need to understand whatChatGPT is doing. Also, no matter how advanced ChatGPT gets, it is still only getting itsinformation from the internet, yet the internet does not contain equal amounts of informationfrom every part of the world. Teachers should continue to teach coding and include ways thatChatGPT can improve learning instead of replace learning.5 AcknowledgmentsThank you to Ms. Ashley Ong, AP-CS high school teacher for teaching me CS and to our papereditor.References [1] N. Forman, J. Udvaros, and M. S. Avornicului, “Chatgpt: A new study tool shaping the future for high school students,” International Journal of Advanced Natural Sciences and Engineering Researches, vol. 7, no. 4, p

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Trini Balart, Texas A&M University; Kristi J. Shryock, Texas A&M University

Tagged Divisions

Computers in Education Division (COED)

. Haleem, R. P. Singh, S. Khan, and I. H. Khan, “Unlocking the opportunities through ChatGPT Tool towards ameliorating the education system,” BenchCouncil Transactions on Benchmarks, Standards and Evaluations, vol. 3, no. 2, p. 100115, Jun. 2023, doi: 10.1016/j.tbench.2023.100115.[6] D. Eke, «ChatGPT and the rise of generative AI: threat to academic integrity?», Journal of Responsible Technology, vol. 13, p. 100060, abr. 2023, doi: 10.1016/j.jrt.2023.100060.[7] S. Nikolic et al., “ChatGPT versus engineering education assessment: a multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity,” European Journal of Engineering Education, vol. 48

Conference Session

Computer-Supported Pedagogy and Assessment

Collection

2024 ASEE Annual Conference & Exposition

Authors

Keith Hekman, California Baptist University

Tagged Divisions

Computers in Education Division (COED)

volume, center ofmass, and moment of inertia to a reference file. Such a comparison is similar to the CertifiedSOLIDWORKS Associate in Mechanical Design exam [7], where students generateSOLIDWORKS files and input a geometric property, such as mass or center of mass, todetermine if their drawing is correct. Bojcetic et al.’s method allows for more refined gradingcriteria, grading features, and sketches in addition to the basic geometry [8]. Overall, thedeveloped automated grading systems speed up the grading time for faculty, allowing for morehomework. Still, they do not provide quick feedback, allowing students to learn by correctingtheir mistakes. Having rapid feedback was the motivation for developing an email-based gradingsystem.Program

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Carsten Monrad Thue-Bludworth, University of Florida; Jeremiah J Blanchard, University of Florida

Tagged Divisions

Computers in Education Division (COED)

matures, we intend to introduce it to the community at large in a variety of ways,including publishing via social media, forums, maker communities on the internet, conferenceson engineering education, as well as through outreach with some of the vendors whose hardwareand software inspired Iron Coder’s conception.References [1] L. Fried, “Introducing adafruit feather.” https://learn.adafruit.com/adafruit-feather/overview. Accessed: 2024-01-20. [2] Sparkfun, “What is micromod?.” https://www.sparkfun.com/micromod. Accessed: 2024-01-20. [3] “Raspberry pi.” https://www.raspberrypi.com/. Accessed: 2024-01-20. [4] “The easiest way to program microcontrollers.” https://circuitpython.org/. Accessed: 2024-01-20. [5] S. Hodges, S. Sentance, J. Finney

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

Tagged Divisions

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

Computer Engineering Topics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Timothy Sellers, Mississippi State University; Tingjun Lei, Mississippi State University; Chaomin Luo, Mississippi State University; Gene Eu Jan; Zhuming Bi, Purdue University, Fort Wayne

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

(TALE). IEEE, 2015, pp. 72–76. [7] K. W. Van Treuren, “Applying active learning to an introductory aeronautics class,” in 2018 ASEE Annual Conference & Exposition, 2018. [8] C. R. Compeau, A. Talley, and P. Q. Tran, “Active learning in electrical engineering: Measuring the difference,” in 2019 ASEE Annual Conference & Exposition, 2019. [9] F. Portela, “A new and interactive teaching approach with gamification for motivating students in computer science classrooms,” in First International Computer Programming Education Conference (ICPEC 2020). Schloss Dagstuhl-Leibniz-Zentrum f¨ur Informatik, 2020.[10] G. S. Tewolde, “Effective active learning tools for an embedded systems course,” in 2017 IEEE Frontiers in Education

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Arnav Ketineni, Portland State University; Hrithik Ketineni; Kyle Liu, Portland State University; Marek Perkowski, Portland State University

Tagged Divisions

Computers in Education Division (COED)

. The GameThe method by which this paper teaches SOP minimization is a game with which students competeto capture the maximum number of true minterms. Upon capture by either player, a true minterm’ssquare or cell is highlighted with the player’s corresponding color. Once all true minterms arecaptured by either Player One or Player Two, the game is over and the player with a greater numberof true minterms covered wins. The player(s) can also capture true minterms occupied by the otherplayer to both reduce their opponents score and increase their own. However, if a player capturesa false minterm through any one of their moves via an incorrect Sum-of-Products, then the playerforfeits the game. As such, the game encourages students to naturally

Conference Session

Programming Education 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Edward Dillon, Morgan State University; Krystal L. Williams, University of Georgia; Ashley Simone Pryor, Morgan State University; Theodore Wimberly Jr., Morgan State University; Mariah McMichael, Morgan State University; Abisola Mercy Arowolaju; Donald Bernard Davis, Morgan State University; Toluwanimi Ayodele, Morgan State University

Tagged Divisions

Computers in Education Division (COED)

programming tool. Only 41% of the CS2 students, whowere instructed to use a command line tool, completed Task 1. This percentage was much higherfor the CS2 students using this tool to complete Task 2. For both Tasks 1 and 2 most of the OOPstudents, who were instructed to use a command line tool, were able to complete them. Table 5. Assigned Tool/Editor(s) to Complete the Two Assigned Tasks (Fall 2020 - Spring 2023) Assigned Tool(s) - Command Line vs. IDE N Task 1 Task 2 CS2 77 Command Line: 41% Command Line: 71% IDE

Conference Session

Robotics and Circuits

Collection

2024 ASEE Annual Conference & Exposition

Authors

Carl Joseph Murzynski, Pennsylvania State University, Behrend College; Hussein - Abdeltawab, Wake Forest University; Omar Ashour, Pennsylvania State University, Behrend College; Ahmed Sammoud, Pennsylvania State University, Behrend College

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

result of the experiment performed in a Computer Science course. The lastsection provides the conclusions and future work.2. The Overall Robotic Arm PlatformThe main component of the robotic arm platform is the Dobot M1 Pro [6]. This robotic arm weighs15.7kg, can carry a maximum load of 1.5kg, has a maximum reach of 400mm, and has industrial-level repeatability of ±0.02mm. Its power supply uses 00~240 VAC at 50/60Hz, and the arm hasa rated voltage of 48 volts DC. Each joint can turn 180°/s, the end effector can turn 1000°/s, andit can move up and down 1000mm/s. The first joint can move ±85°, the second joint can move J2±135°, the vertical moves 5mm～245mm, and the end effector can move ±360°. An air pump,suction cup, and gripper are sold in a

Conference Session

Programming Education 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tyler James Stump, The Ohio State University; Abbey Darya Kashani Motlagh, The Ohio State University; Krista M Kecskemety, The Ohio State University

Tagged Divisions

Computers in Education Division (COED)

Parsons Problems. The eleven features of interest for this transferabilityconsideration includes the following: Accessibility, Assessment, Classroom Dynamics,Difficulty, Distractors, Format, Group Dynamics, Length, Preparation, Time, and Utility Valuewere all identified as unique elements impacted student experiences. The definitions for each canbe described in Table 1. Table 1: Finalized Codebook for Parsons Problems Features Impacting Student Experiences Feature Definitions Example(s) Student Experiences regarding access to tools & Click and drag, full team seeing Accessibility resources to support the demonstration of a student's

Conference Session

Computer-Supported Pedagogy and Assessment

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jim Sosnowski, University of Illinois Urbana-Champaign; Julie M Baker, University of Illinois Urbana-Champaign; Olivia Arnold, University of Illinois Urbana-Champaign; Mariana Silva, University of Illinois Urbana-Champaign; David Mussulman, University of Illinois Urbana-Champaign; Craig Zilles, University of Illinois Urbana-Champaign; Matthew West, University of Illinois Urbana-Champaign

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

atscale is conducted in the College of Engineering, facilitating the implementation ofresearch-based pedagogical assessment practices that are improving student outcomes [10, 11].We believe the lessons shared in this paper can serve as a template for other engineering programsabout how to effectively provide CBT at scale in a manner that positively impacts students andfaculty.References [1] S. Shadle, A. Marker, and B. Earl, “Faculty drivers and barriers: Laying the groundwork for undergraduate stem education reform in academic departments.” International Journal of STEM Education, vol. 4, 2017. [Online]. Available: https://proxy2.library.illinois.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true& amp;db=eric&

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

Tagged Divisions

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

Tagged Divisions

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

Simulations and Virtual Learning

Collection

2024 ASEE Annual Conference & Exposition

Authors

David M. Feinauer P.E., Virginia Military Institute; James C. Squire P.E., Virginia Military Institute; Gerald Sullivan, Virginia Military Institute

Tagged Divisions

Computers in Education Division (COED)

questions, the mean confidence in the response on a scale from 1 to5, with 1 indicating highest confidence, and the standard deviation of the confidence responses.The delta or difference between each performance metric computed by subtracting the discreteresults from the continuous results is perhaps the most illustrative lens for exploring the results.Table 2 - Table of objective performance results from users of the simulation tools. Question Percent Mean Median Std Dev Mean Std Dev Performance Correct [%] Time [s] Time [s] Time [s] Confidence Confidence Q1 Cont. 86.67 66.05 42.26 60.58 1.63 0.93 Q1 Discrete 71.88 81.35

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Alexander Hicks, Virginia Polytechnic Institute and State University; Cliff Shaffer, Virginia Polytechnic Institute and State University

Tagged Divisions

Computers in Education Division (COED)

from additional scaffolding in office hours.References [1] M. Ball, J. Hsia, H. Pon-Barry, A. DeOrio, and A. Blank, “Teaching TAs To Teach: Strategies for TA Training,” in Proceedings of the 51st ACM Technical Symposium on Computer Science Education, (Portland OR USA), pp. 477–478, ACM, Feb. 2020. [2] E. McDonald, G. Arevalo, S. Ahmed, I. Akhmetov, and C. Demmans Epp, “Managing TAs at Scale: Investigating the Experiences of Teaching Assistants in Introductory Computer Science,” in Proceedings of the Tenth ACM Conference on Learning @ Scale, (Copenhagen Denmark), pp. 120–131, ACM, July 2023. [3] S.-H. Ko and K. Stephens-Martinez, “What Drives Students to Office Hours: Individual Differences and Similarities,” in Proceedings

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

Tagged Topics

Diversity

Tagged Divisions

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

Tagged Topics

Diversity

Tagged Divisions

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

Tagged Topics

Diversity

Tagged Divisions

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

Conference Session

COED: Spotlight on Diverse Learners

Collection

2023 ASEE Annual Conference & Exposition

Authors

Heidi Huang, University of Michigan, Ann Arbor; Kevin Yan, University of Michigan, Ann Arbor; Andrew Deorio, University of Michigan, Ann Arbor

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

results support the generalizability of Doebling et al.’s findings. We too observed that womenstudents attended office hours more frequently than men. Similarly, we observed that URM statusdid not have a statistically significant association with office hours usage.5.2 LimitationsOne limitation of our study is that we cannot disentangle remote learning from the pandemic. Asa result, the pandemic could have caused interesting student behaviors without affecting usagepatterns. Because remote learning was immediately adopted following the onset of the pandemic,we cannot separate how remote learning and pandemic onset interacted in our final results.An example of possible interference would be if pandemic onset caused widespread mental

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Gerry A Pedraza, Texas A&M University; Sunay Palsole, Texas A&M University

Tagged Divisions

Computers in Education Division (COED)

require careful calibration of new algorithms created withinTranscriptto and other AI APIs that would allow us to perform that complex functionality.References[1] F. Martin, A. Ritzhaupt, S. Kumar, and K. Budhrani, “Award-winning faculty online teaching practices: Course design, assessment and evaluation, and facilitation,” Internet High. Educ., vol. 42, pp. 34–43, Jul. 2019, doi: 10.1016/j.iheduc.2019.04.001.[2] M. Kebritchi, A. Lipschuetz, and L. Santiague, “Issues and Challenges for Teaching Successful Online Courses in Higher Education: A Literature Review,” J. Educ. Technol. Syst., vol. 46, no. 1, pp. 4–29, Sep. 2017, doi: 10.1177/0047239516661713.[3] C.-S. Li and B. Irby, “An Overview of Online Education: Attractiveness

Conference Session

Simulations and Virtual Learning

Collection

2024 ASEE Annual Conference & Exposition

Authors

J Cecil, Oklahoma State University

Tagged Divisions

Computers in Education Division (COED)

Laboratories,Los Alamos National Laboratory and the Mozilla Foundation.REFERENCES [1] Forcael, E., Glagola, C., and González, V. (2012). ”Incorporation of Computer Simulations into Teaching Linear Scheduling Techniques.” J. Prof. Issues Eng. Educ. Pract., 138(1), 21–30 [2] Adams, W.K., Reid, S., LeMaster, R., McKagan, S.B., Perkins, K.K., Dubson, M., and Wieman. C.E. (2008a). A study of educational simulations part I—Engagement and learning. Journal of Interactive Learning Research, 19(3), 397-419.[3] Adams, W.K., Reid, S., LeMaster, R., McKagan, S.B., Perkins, K.K., Dubson, M., and Wieman, C.E. (2008b). A study of educational simulations part II—Interface design. Journal of Interactive Learning