Πηγές

Buckingham Shum, S., Ferguson, R., & Martinez-Maldonado, R. (2019). Human-centred learning analytics. Journal of Learning Analytics, 6(2), 1–17. https://doi.org/10.18608/jla.2019.62.1

Buckingham Shum, S., & Ferguson, R. (2012, April 29-May 2). Social learning analytics: Five approaches. LAK 2012: Second International Conference on Learning Analytics and Knowledge, Canada. https://doi.org/10.1145/2330601.2330616

Echeverria, V., Yang K, Lawrence, L, Rummel, N., & Aleven, V. (2023). Designing hybrid human–AI orchestration tools for individual and collaborative activities. IEEE Transactions on Learning Technologies. 16(2), 191-205. https://doi.org/10.1109/TLT.2023.3248155

Ekstrom, S., & Pareto, L. (2022). The dual role of humanoid robots in education: As didactic tools and social actors. Education and Information Technologies, 27,12609-12644. https://doi.org/10.1007/s10639-022-11132-2

Elias, T. (2011). Learning analytics: Definitions, processes and potential. Learning Analytics Research Network. https://landing.athabascau.ca/file/download/43713

Gresham, F. M., Elliott, S. N., Vance, M. J., & Cook, C. R. (2011). Comparability of the Social Skills Rating System to the Social Skills Improvement System: Content and psychometric comparisons across elementary and secondary age levels. School Psychology Quarterly, 26(1), 27–44. http://dx.doi.org/10.1037/a0022662

Lallé, S., Taub, M., Mudrick, N.V., Conati, C., & Azevedo, R. (2017). The Impact of Student Individual Differences and Visual Attention to Pedagogical Agents During Learning with MetaTutor. In: André, E., Baker, R., Hu, X., Rodrigo, M., du Boulay, B. (eds) Artificial Intelligence in Education. AIED 2017. Lecture Notes in Computer Science(), vol 10331. Springer, Cham. https://doi.org/10.1007/978-3-319-61425-0_13

Lawrence, L., Echeverria, V., Yang, K., Aleven, V., & Rummel, N. (2023). How teachers conceptualise shared control with an AI co-orchestration tool: A multiyear teachercentred design process. British Journal of Educational Technology, 00, 1-22. https://doi.org/10.1111/bjet.13372

Nazaretsky, T., Bar, C., Walter, M., & Alexandron, G. (2022). Empowering teachers with AI: Co-designing a learning analytics tool for personalized instruction in the science classroom. LAK22: 12th International Learning Analytics and Knowledge Conference. In ACM international conference proceeding series (pp. 1–12). https://doi.org/10.1145/3506860.3506861

Ochoa, X., & Dominguez, F. (2020). Controlled evaluation of a multimodal system to improve oral presentation skills in a real learning setting. British Journal of Educational Technology, 51(5), 1615–1630. https://doi.org/10.1111/bjet.12987

Rodrigues, L., Palomino, P., Toda, A., Klock, A., Pessoa, M., Pereira, F., Oliveira, E., Oliveira, D., Cristea, A., Gasparini, I., & Isotani, S. (2023). How personalization affects motivation in gamified review assessments. Journal of Artificial Intelligence in Education, 34(2), 147-184.  https://doi.org/10.1007/s40593-022-00326-x

Tsai, Y. S., Perrotta, C., &  Gašević, D. (2019). Empowering learners with personalized learning approaches: Agency, equity and transparency in the context of learning analytics. Assessment & Evaluation in Higher Education, 45(4), 554–567. https://doi.org/10.1080/02602938.2019.1676396

Wang, Q., Jing, S., & Goel, A. K. (2022). Co-designing AI agents to support social connectedness among online learners: Functionalities, social characteristics, and ethical challenges. In DIS ’22: Designing Interactive Systems Conference, Virtual Event. https://doi.org/10.1145/3532106.3533534