Collection

2025 Northeast Section Conference

Authors

Elyas Irankhah; Sashank Narain; Kelilah L. Wolkowicz

, strategy, and problem-solving. While Tic-Tac-Toe AI games effectively introduceWhen integrated with AI, it becomes a powerful tool for students to AI principles, their long-term impact on AIteaching computational thinking and decision-making [13]. learning and career development remains uncertain [28].Integrating AI-driven educational tools has transformed Studies suggest that while initial engagement levels are high,learning methodologies, particularly in game-based learning. it is unclear whether this translates into sustained interest in AIOne study by S. Jain and N. Khera highlights that adapting or improved academic performance in advanced AI coursesTic-Tac-Toe into an AI-driven experience

Collection

2025 Northeast Section Conference

Authors

Kristina Riesco; Yuna Ukawa; Pauline Alfreh; Eman Abdelfattah

-intensity ABAtreatment, which focuses on skills like language and social TABLE I. DATASET DESCRIPTIONinteraction, and better outcomes such as higher IQ scores and Feature Name Descriptionsuccess in general education. The research also highlightedkey factors like treatment intensity, supervision, age, andgender in optimizing learning. Neural networks were found A1 S/he often notices small sounds when others do not (score 1 for definitely/slightly agree)to be valuable in predicting mastery of specific learningobjectives and enhancing

Collection

2025 Northeast Section Conference

Authors

Boluwatife E. Faremi; Javier O. Pinzon-Arenas; Amir Mohammad Karimi Forood; Josef Kundrat; Hugo F. Posada-Quintero; Ann Marie Hoyt-Brennan; Wendy A. Henderson

this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.,” IFAC-PapersOnLine, vol. 49, no. 32, pp. 48–53, 2016, doi: 10.1016/j.ifacol.2016.12.188. REFERENCES [6] G. Campagna, D. Chrysostomou, and M. Rehm, “Investigating[1] B. C. Gin et al., “Entrustment and EPAs for Artificial Intelligence Electrodermal Activity for Trust Assessment in Industrial Human-Robot(AI): A Framework to Safeguard the Use of AI in Health

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Yousef Fazea, Marshall University; Yousef Sardahi, Marshall University; Asad Salem

Tagged Topics

Diversity

supportive option for its students.References [1] B. Bygstad, E. Øvrelid, S. Ludvigsen, and M. Dæhlen, "From dual digitalization to digital learning space: Exploring the digital transformation of higher education," Computers & Education, vol. 182, p. 104463, 2022. [2] R. P. Goldenson, L. L. Avery, R. R. Gill, and S. M. Durfee, "The virtual homeroom: Utility and benefits of small group online learning in the COVID-19 era," Current Problems in Diagnostic Radiology, vol. 51, no. 2, pp. 152–154, 2022. [3] V. G. Padaguri and S. A. Pasha, "Synchronous online learning versus asynchronous online learning: A comparative analysis of learning effectiveness," in Proc. AUBH E-Learning Conf., 2021. [4] K. Baba, N

Collection

2025 ASEE -GSW Annual Conference

Authors

Aroudra Syamantak Thakur, The University of Texas at Arlington

Tagged Topics

Diversity

, Abdul Hamid et al. (2018) explored engagement prediction by manpower, including Healthcare, Construction, Entertainment, Computer Conference (EDUCON), Mar. 2022, doi: https://doi.org/10.1109/educon52537.2022.9766690. using AI-assisted facial expression detection. Their model used the Bag of • Ovidiu Andrei Schipor, S. G. Pentiuc, and M. D. Schipor

Collection

2025 Northeast Section Conference

Authors

SUPARSHYA BABU SUKHAVASI; Susrutha Babu Sukhavasi; Mohammad Jaheerabi; Venkata Durga Sunanda Gangula

–318, 2009. [6] H. Thapliyal, S. Kotiyal, and M. B. Srinivas, “Novel BCD adder and5 11.035 58.687 41.198 96.396 carry skip BCD adder using reversible logic,” in Proc. IEEE Conf. Computer Systems and Applications, 2011, pp. 607–610. Table 3: Power Dissipation Data for BJN Gate Models – A [7] M. S. Islam et al., “Efficient approach for designing reversible logictable showing power dissipation for various BJN gate circuits. based sequential circuits,” IET Computers & Digital Techniques, vol. 3

Collection

2025 ASEE -GSW Annual Conference

Authors

Olukayode Emmanuel Apata, Texas A&M University; John O Ajamobe, Texas A&M University; Segun Timothy Ajose; Peter Oluwaseyi Oyewole, Kent State University, Kent; Grace Iyinoluwa Olaitan

/10.55529/jaimlnn.36.23.28Akavova, A., Temirkhanova, Z., & Lorsanova, Z. (2023). Adaptive learning and artificial intelligence inthe educational space. E3S Web of Conferences. https://doi.org/10.1051/e3sconf/202345106011Alsariera, Y., Baashar, Y., Alkawsi, G., Mustafa, A., Alkahtani, A., & Ali, N. (2022). Assessment andevaluation of different machine learning algorithms for predicting student performance. ComputationalIntelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/4151487Altaleb, H., Mouti, S., & Beegom, S. (2023). Enhancing college education: An AI-driven adaptivelearning platform (ALP) for customized course experiences. 2023 9th International Conference onOptimization and Applications (ICOA), 1–5. https://doi.org

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Simon Thomas Ghanat P.E., The Citadel; Scott Curtis, The Citadel

Tagged Topics

Professional Papers

conclusions.Reference[1] Martin, M.J., S.J. Diem, D.M.A. Karwat, E.M. Krieger, C.C. Rittschof, B. Bayon, M.Aghazadeh, O. Asensio, T.J. Zeilkova, and M. Garcia-Cazarin, The climate is changing.Engineering education needs to change as well. Journal of Engineering Education, 111:740-746,2022.[2] Milovanovic, J., T. Shealy, and A. Godwin, Senior engineering students in the USA carrymisconceptions about climate change: Implications for engineering education. Journal ofCleaner Production, 345, 131129, 2022.[3] Sinatra, G.M., and P.R. Pintrich (Eds.), International Conceptual Change. Lawrence Erlbaum,Mahwah, NJ, 2003.[4] P. Molthan-Hill, L. Blaj-Ward, M. F. Mbah, and T. S. Ledley, “Climate Change Education atUniversities: Relevance and Strategies for Every Discipline

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Jundong Liu, Ohio University; Trevor Joseph Bihl, Air Force Research Laboratory; Daniel Masami Nagura, Ohio University

mobile robot motion planning methods: from clas- sical motion planning workflows to reinforcement learning-based architectures,” Journal of Systems Engineering and Electronics, vol. 34, no. 2, pp. 439–459, 2023. [2] E. W. Dijkstra, “A note on two problems in connexion with graphs,” Numerische Mathematik, vol. 1, no. 1, pp. 269–271, 1959. [Online]. Available: https://link.springer.com/article/10.1007/BF01386390 [3] P. E. Hart, N. J. Nilsson, and B. Raphael, “A formal basis for the heuristic determination of minimum cost paths,” IEEE Transactions on Systems Science and Cybernetics, vol. 4, no. 2, pp. 100–107, 1968. [4] S. Koenig and M. Likhachev, “D* lite,” in Proceedings of the AAAI Conference on Artificial Intelli- gence

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Seyed Mohammad Seyed Ardakani P.E., Ohio Northern University; Julia Kamatali, Ohio Northern University

effective. While the game is still in development, the proposed design representsgreat potential to improve learning in a core engineering course.References[1] R. Austin and B. Hunter, “ict policy and implementation in education: Cases in canada, northern ireland and ireland,” European Journal of Education, vol. 48, no. 1, pp. 178– 192, Feb. 2013. doi:10.1111/ejed.12013[2] O. S. Kaya and E. Ercag, “The impact of applying challenge-based Gamification Program on students’ learning outcomes: Academic achievement, motivation and flow,” Education and Information Technologies, vol. 28, no. 8, pp. 10053–10078, Jan. 2023. doi:10.1007/s10639-023-11585-z[3] L. Jaramillo-Mediavilla, A. Basantes-Andrade, M. Cabezas-González

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Trevor Joseph Bihl, Wright State University; Terry Lynn Oroszi, Wright State University; Subhashini Ganapathy, Wright State University; Jeffrey B. Travers, Wright State University

Tagged Topics

Diversity

): Algorithm Details – do the authors name the machine learning method(s) used? Do they cite a quality paper for these method(s)? Do they discuss algorithmic settings? Example 1:“Linear discriminant analysis” has no algorithmic settings and means a specific function Example 2: “discriminant analysis” is unclear (i.e. there are many discriminant variants such as linear and quadratic) Example 3: Artificial neural networks have many settings (number of nodes, number of layers, types of nodes, training methods, architecture variant). All of these must be specified for repeatability Data Details – do the authors describe the source of the data or the collection means? Do they cite a source? Do they describe all data variables? Performance Result

Collection

2025 Northeast Section Conference

Authors

Shalini Jada; Xingguo Xiong; Ahmed El-Sayed; Navarun Gupta

. C¸ etin, K. Dimitropoulos, F. Tsalakanidou, K. Kose, and situational analysis [6]. O. Gunay, B. Gouverneur, D. Torri, E. Kuruoglu, S. Tozzi, et al., • Advanced Visualization Tools: Incorporate additional “A multi-sensor network for the protection of cultural heritage,” in Proceedings of the 19th European Signal Processing Conference, pp. visual analytics features, such as heatmaps and time lapse 889–893, 2011. comparisons, to visually represent wildfire progression [20] I. Bosch, A. Serrano, and L. Vergara, “Multisensor network

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Daron Marshall Weekley, Marshall University; Jace A McPherson-Duckworth, Marshall University; Anastasiia Sukhanova, Marshall Community & Technical College; Ananya Jana, Marshall University

. Xu, Y. Liu, G. Wang, Z. Zhao, S. Li, and Z. Zhang, “3d tooth segmentation and labeling using deep convolutional neural networks,” IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 11, pp. 2603–2615, 2018. [7] Y. Sun, Y. Wang, Y. Wang, Z. Zhang, and Z. Zhao, “Model adaptive tooth segmentation,” in International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, 2020, pp. 442–450. [8] Z. Zhang, Y. Wang, Y. Sun, and Z. Zhao, “Darch: Deep architectures for automated tooth segmentation,” IEEE Access, vol. 7, pp. 118 712–118 721, 2019. [9] Z. Cui, Z. Li, S. Song, Y. Zhou, S. Zhuang, G. Wei, G. Li, and G. Zheng, “Deep multi-scale mesh feature learning for automated

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Saeed Rokooei, Mississippi State University; George D Ford P.E., Mississippi State University; Read Allen Robertson, Mississippi State University

Tagged Topics

Diversity, Professional Papers

Paper ID #45761A Gender-based Comparative Analysis of Motivations and Challenges in ConstructionEducationDr. Saeed Rokooei, Mississippi State University Saeed Rokooei is an associate professor in the Department of Building Construction Science at Mississippi State University. Dr. Rokooei’s primary research interests include community resilience, engineering education, simulation and serious games, project management methodologies, data analytics, creativity and innovation, and emerging technologies.Mr. George D Ford P.E., Mississippi State University Dr. George Ford P.E. is the Director of Mississippi Stateˆa C™s Building

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

James Righter, The Citadel; Nathan John Washuta P.E., The Citadel; Deirdre D Ragan, Pennsylvania State University

Tagged Topics

Professional Papers

studies could also address the impacts of team dynamics such assize, communication and leadership on the application of requirements tools and evolution [18],[19]. These studies would enable further assessment of the impact of QFD on requirementsevolution in capstone product design.References[1] D. G. Ullman, The Mechanical Design Process, 6th ed. Independence, Oregon: David G. Ullman, 2018.[2] G. Pahl and W. Beitz, Engineering Design: A Systematic Approach, 2nd ed. London: Springer, 1995.[3] B. Morkos, S. Joshi, and J. D. Summers, “Investigating the impact of requirements elicitation and evolution on course performance in a pre-capstone design course,” Journal of Engineering Design, vol. 30, no. 4–5, pp. 155–179

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Valmiki Sooklal, Kennesaw State University; Sandip Das, Kennesaw State University

Tagged Topics

Professional Papers

. Pallitt and K. Wolff, "Learning to teach STEM disciplines in higher education: A critical review of the literature," Teaching in Higher Education, vol. 24, no. 8, pp. 930-947, 2019.[2] D. Varas, M. Santana, M. Nussbaum, S. Claro and P. Imbarack, "Teachers’ strategies and challenges in teaching 21st century skills: Little common understanding," Thinking Skills and Creativity, vol. 48, p. 101289, 2023.[3] H. Jang, "Identifying 21st century STEM competencies using workplace data," Journal of Science Education and Technology, vol. 25, no. 2, pp. 284-301, 2016.[4] D. Tan, "The Significance of Integrating Engineering Design-Based Instruction in STEM Education," Science Insights Education Frontiers, vol. 24, no. 1, pp. 3827-3829, 2024

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Sultan Al Shafian, Kennesaw State University; Da Hu, Kennesaw State University; Jayhyun Kwon P.E., Kennesaw State University; Adam Kaplan, Kennesaw State University

Tagged Topics

Professional Papers

a wider range of structural elements and incorporating interactive features likequizzes and feedback would further enhance its educational value. Comparative studies withcontrol groups using traditional learning methods would also help clarify the specific advantagesof AR-based learning in civil engineering education.References[1] ACI, Building code requirements for structural concrete (ACI 318-08) and commentary. American Concrete Institute, 2008. Accessed: Nov. 08, 2024. [Online]. Available: https://books.google.com/books?hl=en&lr=&id=c6yQszMV2- EC&oi=fnd&pg=PT10&dq=Building+Code+Requirements+for+Structural+Concrete+and+ Commentary&ots=nZOlIXZCKL&sig=KMB7MQU6EE9dIpxctdYQvpox8Ws[2] S. A. Sorby

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Fazil T. Najafi, University of Florida; Jack Cuilla, University of Florida

Tagged Topics

Professional Papers

, investment and technology can reduce these expenses over time,while ash byproducts from combustion are repurposed, further minimizing landfill waste.2.4 Byproducts of BiomassWhen wood-based Biomass is burned, fly ash is the primary byproduct, along withemissions like CO₂, CO, CH₄, NOx, VOCs, PM, and trace gases [25]. Fly ash hassignificant potential as a cement substitute in concrete. Rummen et al. demonstrated thatadding 15% wood-based fly ash (WFA) improves concrete durability and compressivestrength due to pozzolanic reactions forming calcium silicate hydrate (C-S-H) gel, a keystrength component [26]. Similarly, John Zachar's study found that replacing 30% ofcement with fly ash in construction reduced material costs by $23,000 and avoided

Collection

2025 Northeast Section Conference

Authors

SUPARSHYA BABU SUKHAVASI; Sriphanindra Perali; Susrutha Babu Sukhavasi; Sneha Gundeboyena; Marisha Rawlins

area utilization compared to A 2-bit multiplexer (MUX) is a fundamental combinationalconventional adder designs. By exploring MUX-based circuit that selects one of two inputs based on a control signal. Themethodologies, this study contributes to advancing low-power VLSI Boolean equation for a 2-bit MUX is:circuit design, offering an efficient and scalable solution for modern 𝑌 = 𝐴 ⋅ 𝑆 + 𝐵 ⋅ 𝑆′digital systems. where: A, B are the input signals, S is the select signal, Y is the output. This simple structure forms the basis for implementing

Conference Session

Track 1: Technical Session 3: Beyond deficits: Developing an elicitation mechanism for engineering practitioners with ADHD to create autoethnographic counterstories

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Hector Enrique Rodríguez-Simmonds, Boston College; Sage Maul, Purdue University at West Lafayette (COE); Levi Xuan Li, Purdue University at West Lafayette (COE); Ruby J Barnett, Boston College

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

Student with ADHD and a Reading Disability,” in Promoting Safe and Effective Transitions to College for Youth with Mental Health Conditions, A. Martel, J. Derenne, and P. K. Leebens, Eds. Cham: Springer International Publishing, 2018, pp. 95–102.[3] M. A. Zapata and F. C. Worrell, “Disability Acceptance and Affirmation Among U.S. Adults With Learning Disabilities and ADHD,” J. Learn. Disabil., vol. 57, no. 2, pp. 79–90, Mar. 2024.[4] S. Maul and R. Figard, “Diminishing the data divide: Interrogating the state of disability data collection and reporting,” presented at the American Society for Engineering Education 2024, Portland, OR, 2024.[5] Learning Disabilities Association of America, “ADHD – Affects focus, attention and

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Leslie Hopkinson, West Virginia University; Lynette Michaluk, West Virginia University; Lizzie Santiago, West Virginia University

by the National Science Foundation under Grant No.2406798. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] A. Godwin and A. Kirn, “Identity-based motivation: Connections between first-year students’ engineering role identities and future-time perspectives,” Journal of Engineering Education, vol. 109, no. 3, pp. 362–383, 2020, doi: 10.1002/jee.20324.[2] S. Liu, S. Xu, Q. Li, H. Xiao, and S. Zhou, “Development and validation of an instrument to assess students’ science, technology, engineering, and mathematics identity,” Phys. Rev. Phys. Educ. Res., vol. 19, no. 1, p

Collection

2025 ASEE -GSW Annual Conference

Authors

Mengqi Monica Zhan, University of Texas at Arlington; Grace Ellen Brannon, The University of Texas at Arlington; Liwei Zhang, The University of Texas at Arlington; Frank K. Lu, The University of Texas at Arlington

Tagged Topics

Diversity

degree plan choices: A qualitative study with engineering and communication students," submitted to the International Communication Association's Annual Conference, 2025.6. E. L. Deci and R. M. Ryan, "Self-determination theory," in Handbook of Theories of Social Psychology, vol. 1, pp. 416-436, 2012.7. M. S. Eickholt, "The effect of superiors' mentoring on subordinates' organizational identification and workplace outcomes," Master’s Thesis, West Virginia University, 2018.8. K. Kricorian, M. Seu, D. Lopez, and others, "Factors influencing participation of underrepresented students in STEM fields: Matched mentors and mindsets," International Journal of STEM Education, vol. 7, no. 16, 2020.9. S. L. Kuchynka, A. E

Collection

2025 ASEE -GSW Annual Conference

Authors

Rojan Shrestha, The University of Texas at Arlington

Tagged Topics

Diversity

Health, Volume 28, 2023, 100395, ISSN 2352-6483, doi: 10.1016/j.smhl.2023.100395 for successful implementation of AI in educational systems. P = (K × U)/2                              (1) C = 5 - (D + R + S + L)/4              (2) educational initiatives aimed at increasing AI literacy could be effective in [6] Z. Xiong, C. Wang, Y. Li, Y. Luo and Y. Cao, "Swin-Pose: Swin Transformer Based Human Pose Estimation," 2022 IEEE where Where improving student perceptions. 5th

Collection

2025 Northeast Section Conference

Authors

Chushun Wang; A. Umit Coskun; Kai-tak Wan

in a fluid flowbalance equation and the Colebrook friction equationsimultaneously, using an iterative method prone to numerical CD: Dimensionless drag coefficient of an object of well-errors. A better way is a graphical method where the equations defined geometryare plotted on a Moody’s chart and the solution derived by A: Planform or frontal area of an immersed body subject tolocating the intersection(s) of relevant curves. This paper fluid flowintroduces a new Matlab app for such purpose and demonstratesits capability to find (i) flow velocity and (ii) pipe diameter, given There are pragmatic engineering problems that requiresall other relevant parameters. The

Conference Session

Track 7: Technical Session 4: Diversity in STEM: Strategies of Professional Engineering Organizations in Recruiting and Retaining Women from Minority-Serving Institutions

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Rebeca Petean, Society of Women Engineers; Roberta Rincon, Society of Women Engineers

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

fields [26].Ultimately, the STEM workforce should reflect the population it serves. However, research bythe National Science Foundation finds “Hispanic, Black, and American Indian or Alaska Nativepersons collectively account for 37% of the U.S. population ages 18–34 years in 2021, and 26%of S&E bachelor’s, 24% of S&E master’s, and 16% of S&E doctoral degrees earned by U.S.citizens and permanent residents in 2020” [27]. In addition, women earned 51% of S&Ebachelor’s, 51% of S&E master’s, and 47% of S&E doctoral degrees in the U.S. in 2020, butdespite women’s high levels of representation in S&E (which includes the life sciences andsocial sciences), women of color earned only 14.9% of all S&E bachelor’s degrees [27

Conference Session

Track 6: Technical Session 3: Breaking Barriers: Unveiling the Journeys and Triumphs of Faculty Women of Color in STEM Academia

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Kemesha Gabbidon, University of South Florida; Saundra Johnson Austin, University of South Florida

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

funding. I need to show that I am being active in seeking funding, I have to be actively applying for grant proposals and it's in my field it's mostly NSF. I need to have publications in peer reviewed journals [and] presentations. You know, all that stuff and then in service. All the etcetera like that that drawer at your home, where you just throw everything else. Everything else goes there. The junk drawer, that[‘s] service everything else. – Mila, Latina, Puerto Rican• Motives – a psychological feature that arouses a person to action to meet a specific goal. In terms of EM, this can be framed as achievement orientation, impact, and value creation.• Achievement orientation - A focus on setting and reaching goals, often

Conference Session

Track 3: Technical Session 1: Bridging Educational Equity Gaps: A Systematic Review of AI-Driven Tools for Students Living with Disabilities in Engineering and STEM Education

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Kevin Zhongyang Shao, University of Washington; Denise Wilson, University of Washington; Eric Kyeong-Min Cho, University of Washington; Sophia Tang, University of Washington; Hanlin Ma, University of Washington; Sep Makhsous, University of Washington

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

methodology. Table 2. Review of technologies being used in STEM education for SLWD.Author(s) Country Technologies Purpose Target Group Education Designedand Year Level Solution/MethodologyIatraki et al., Greece Virtual Investigate the design issues Intellectual Primary Employed a focus group(2021) [21] Reality/Augmented in the development of digital disability (ID) methodology to explore the Reality (VR/AR) learning environments for

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Lionel Hewavitharana, Southern Arkansas University; Mahbub K Ahmed P.E., Southern Arkansas University

Tagged Topics

Professional Papers

phases, integrating industry/engineeringstandards at each design step, paying attention to health and safety of the public, maintainingethical standards, and proper documentation of the capstone design process must be criticalcomponents of any capstone design model. Missing or inadequacy of addressing those criticalcomponents may result in negative evaluation by ABET program evaluators (PEV s). Therefore,it is important for any engineering program to adopt a proper capstone model to satisfy ABETprogram assessment requirements.In view of these contexts, this paper discusses the capstone model used by the engineeringprogram at the Southern Arkansas University (SAU). The model has been developed to providean industry level design experience in

Conference Session

Student Papers

Collection

2025 ASEE Southeast Conference

Authors

Daniel Hernandez, The University of Memphis; Ariadna Mendoza, The University of Memphis; Xiaofeng Tan, The University of Memphis; Kathryn Bridson, The University of Memphis; Pegah Farshadmanesh, The University of Memphis

Tagged Topics

Student Papers

: Create an initial inventory of specific EdTech (e.g., AutoCAD), rather than broad EdTech categories (e.g., “CAD tools”). o Step 2. Define Educator Selection Criteria: Identify the factors relevant to educators when choosing which tool(s) to try among many potential options. o Step 3. Expand the EdTech Dataset: Gather or supplement data for each EdTech based on the selection criteria (established in Step 2 of Phase 1), ensuring all relevant attributes are captured. Augment the dataset to include comprehensive data for a set of tools (i.e., capturing all significant attributes for each EdTech) in at least one specific EdTech

Collection

2025 ASEE -GSW Annual Conference

Authors

Thomas Franklin Hallmark, Texas A&M University

a 28% improvement in persistence throughchallenging coursework.Lave and Wenger's (1991) Situated Learning Theory provides the third theoretical pillar, asemphasized in Brown et al.'s (2017) research showing how AI-supported authentic learningenvironments increased student engagement by 45% and improved transfer of theoreticalknowledge to practical applications by 38%. The integration of these theories creates a robustframework for understanding how AI tools can simultaneously reduce cognitive barriers, buildstudent confidence, and provide authentic learning experiences.Figure 1 illustrates the integration of these theoretical perspectives, demonstrating how theywork together to support comprehensive learning outcomes