ASEE Gulf Southwest 2025


Integrating Artificial Intelligence in Engineering Education:

A Work-in-Progress Systematic Review of Applications and Challenges


References (APA-7 Format)

  1. Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
  2. Chang, L., & Peterson, M. (2020). Implementing AI tools in resource-constrained institutions. International Journal of Engineering Education, 36(4), 1205-1220.
  3. Davidson, R., Martinez, J., & Kumar, S. (2019). Longitudinal analysis of engineering student retention. Journal of Engineering Education Research, 28(2), 178-195.
  4. de Jong, T., Linn, M. C., & Zacharia, Z. C. (2013). Physical and virtual laboratories in science and engineering education. Science, 340(6130), 305-308.
  5. Freeman, S., Eddy, S. L., McDonough, M., et al. (2014). Active learning increases student performance in science, engineering, and mathematics. PNAS, 111(23), 8410-8415.
  6. Haddaway, N. R., Page, M. J., Pritchard, C. C., & McGuinness, L. A. (2022). PRISMA2020: An R package and Shiny app for producing PRISMA 2020-compliant flow diagrams. Campbell Systematic Reviews, 18, e1230. https://doi.org/10.1002/cl2.1230
  7. Heffernan, N. T., & Heffernan, C. L. (2014). The ASSISTments ecosystem: Building a platform that brings scientists and teachers together for minimally invasive research on human learning and teaching. International Journal of Artificial Intelligence in Education, 24(4), 470-497.
  8. Holstein, K., McLaren, B. M., & Aleven, V. (2019). Co-designing a real-time classroom orchestration tool to support teacher–AI complementarity. Journal of Learning Analytics, 6(2), 27-52.
  9. Johnson, R. T., & Smith, K. A. (2018). Cooperative learning and AI integration in engineering education. Journal of Engineering Education, 107(1), 123-142.
  10. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press.
  11. Mayer, R. E. (2019). Thirty years of research on online learning. Applied Cognitive Psychology, 33(2), 152-159.
  12. Mitchell, J. E., & Lee, K. (2020). Faculty development for AI integration in engineering courses. International Journal of Engineering Education, 36(2), 645-657.
  13. Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097.
  14. Potkonjak, V., Gardner, M., Callaghan, V., Mattila, P., Guetl, C., Petrović, V. M., & Jovanović, K. (2016). Virtual laboratories for education in science, technology, and engineering: A review. Computers & Education, 95, 309-327.
  15. Rodriguez, M. A., Thompson, S. E., & Wilson, K. R. (2018). Phased implementation of AI tools in large public universities. Journal of Computing in Higher Education, 30(3), 478-493.
  16. Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582-599.
  17. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285.
  18. VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221.
  19. Washington, K. E., & Lee, M. J. (2020). Implementing equitable access in AI-enhanced engineering education. Journal of Engineering Education, 109(3), 424-442.