Draft Preliminary note on identifiability and PII review · click to expand

This appendix is being circulated to the committee as a draft. It contains material that has not yet completed a final review for personally identifiable information. Before the appendix is finalized for submission, every mention of a named individual will be reviewed against the taxonomy in §B.6.5: students named in instructor-produced materials will be anonymized unless explicit written consent for educational use is documented; named guest speakers will be retained as public professional identities with their professional context attached; Luma-platform workshop feedback will be reviewed for anonymization; and external journalism is retained as already published and consented.

IndexNext →
§G.1

References

Adler, P. A., & Adler, P. (1987). Membership roles in field research. Qualitative Research Methods Series. Sage Publications.

Anderson, L. (2006). Analytic autoethnography. Journal of Contemporary Ethnography, 35(4).

Baker, R. S., & Hawn, A. (2022). Algorithmic bias in education. International Journal of Artificial Intelligence in Education, 32(4), 1052–1092.

Basgen, B. (2023). A generative AI primer. EDUCAUSE Review (Online).

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21). ACM.

Bommasani, R., Hudson, D. A., Adjeroh, D., Altman, R., Arora, S., von Arx, S., … Zhang, Y. (2021). On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258.

Boyer, E. L. (1990). Scholarship reconsidered: Priorities of the professoriate. Carnegie Foundation for the Advancement of Teaching.

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., … Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901.

Burrows, A. C., Lockwood, M., Borowczak, M., Janak, E., & Barber, B. (2018). An iterative participatory approach to developing an early childhood problem-based STEM curriculum. Journal of Educational Research, 111(3), 256–266.

Chang, H. (2008). Autoethnography as method. Left Coast Press.

Chang, H., Ngunjiri, F. W., & Hernandez, K.-A. C. (2013). Collaborative autoethnography. Left Coast Press.

Christensen, C. M., Grossman, J. H., & Hwang, J. (2009). The innovator's prescription: A disruptive solution for health care. McGraw-Hill.

Cochran-Smith, M., & Lytle, S. L. (2009). Inquiry as stance: Practitioner research for the next generation. Teachers College Press.

Code of Federal Regulations. (2018). Federal Policy for the Protection of Human Subjects (Common Rule), 45 CFR 46.102(l). U.S. Department of Health and Human Services.

Daniel, B. (2014). Big data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 46(5).

Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4).

Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum Press.

Dehouche, N., & Dehouche, K. (2023). What's in a text-to-image prompt? The potential of stable diffusion in visual arts education. Heliyon, 9(6).

Ellis, C., Adams, T. E., & Bochner, A. P. (2011). Autoethnography: An overview. Forum: Qualitative Social Research, 12(1).

U.S. Department of Education. (1974). Family Educational Rights and Privacy Act (FERPA), 20 U.S.C. § 1232g; 34 CFR Part 99. United States Code and Code of Federal Regulations.

Finlay, L. (2002). Negotiating the swamp: The opportunity and challenge of reflexivity in research practice. Qualitative Research, 2(2), 209–230.

Healey, M., & Jenkins, A. (2009). Developing undergraduate research and inquiry. The Higher Education Academy.

Hutchings, P., & Shulman, L. S. (1999). The scholarship of teaching: New elaborations, new developments. Change: The Magazine of Higher Learning, 31(5), 10–15.

Kelly, A., & Sullivan, M. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning and Teaching.

Kemmis, S., McTaggart, R., & Nixon, R. (2014). The action research planner: Doing critical participatory action research. Springer.

Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. UCL Knowledge Lab.

Lungu, M. (2022). The coding manual for qualitative researchers. American Journal of Qualitative Research, 6(1), 232–237.

Marcus, G., & Davis, E. (2020). Rebooting AI: Building artificial intelligence we can trust. Pantheon Books.

McKenney, S., & Reeves, T. C. (2018). Conducting educational design research (2nd ed.). Routledge.

Mishra, P., & Koehler, M. J. (2006). Technological Pedagogical Content Knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.

Mollick, E. R., & Mollick, L. (2023). Assigning AI: Seven approaches for students, with prompts. Working paper.

Office for Human Research Protections. (2014). Guidance on distinguishing quality improvement and research. U.S. Department of Health and Human Services.

OpenAI. (2023). GPT-4 technical report. Retrieved from https://openai.com/research/gpt-4

Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6.

Prince, M. J., & Felder, R. M. (2006). Inductive teaching and learning methods: Definitions, comparisons, and research bases. Journal of Engineering Education, 95(2), 123–138.

Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., & Sutskever, I. (2021). Zero-shot text-to-image generation. Proceedings of the 38th International Conference on Machine Learning, 8821–8831.

Redecker, C., & Punie, Y. (2017). European Framework for the Digital Competence of Educators: DigCompEdu. Publications Office of the European Union.

Reed-Danahay, D. (Ed.). (1997). Auto/Ethnography: Rewriting the self and the social. Berg.

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78.

Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press.

Salmon, G. (2002). E-tivities: The key to active online learning. RoutledgeFalmer.

Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.

Schunk, D. H. (2020). Learning Theories: Educational Perspectives (8th ed.). Pearson.

Selwyn, N. (2021). Education and technology: Key issues and debates. Bloomsbury Publishing.

Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House.

Tedlock, B. (1991). From participant observation to the observation of participation: The emergence of narrative ethnography. Journal of Anthropological Research, 47(1).

Tomlinson, C. A. (2014). The differentiated classroom: Responding to the needs of all learners. ASCD.

Touretzky, D., Gardner-McCune, C., Martin, F., & Seehorn, D. (2019). Envisioning AI for K-12: What should every child know about AI? In Proceedings of the AAAI Conference on Artificial Intelligence, 33.

UNESCO. (2021). Artificial intelligence in education: Challenges and opportunities for sustainable development. United Nations Educational, Scientific and Cultural Organization.

UNESCO. (2021). Equity, inclusion and learner diversity. UNESCO Publishing.

Wendell, K. B., Koehler, C. M., Fanucchi, A. K., & Baral, K. (2021). Designing biomimetic robots: Iterative development of an integrated technology design curriculum. Educational Technology Research and Development, 69(6), 3141–3164.

Wobbrock, J. O., & Kientz, J. A. (2016). Research contributions in human-computer interaction. Interactions, 23(3).

Yin, R. (2014). Case study research: Design and methods (5th ed.). Sage.

IndexNext →