參考文獻 |
Abrahamse, E. L., Jiménez, L., Verwey, W. B., & Clegg, B. A. (2010). Representing serial action and perception. Psychonomic bulletin & review, 17, 603-623.
Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE access, 6, 52138-52160.
Akçapinar, G., Chen, M. R. A., Majumdar, R., Flanagan, B., & Ogata, H. (2020, March). Exploring student approaches to learning through sequence analysis of reading logs. In Proceedings of the tenth international conference on learning analytics & knowledge (pp. 106-111).
Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., García, S., Gil-López, S., Molina, D., & Benjamins, R. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information fusion, 58, 82-115.
Atif, A., Richards, D., Liu, D., & Bilgin, A. A. (2020). Perceived benefits and barriers of a prototype early alert system to detect engagement and support ‘at-risk’students: The teacher perspective. Computers & Education, 156, 103954.
Cerezo, R., Bogarín, A., Esteban, M., & Romero, C. (2020). Process mining for self-regulated learning assessment in e-learning. Journal of Computing in Higher Education, 32(1), 74-88.
Dor, L. E., Mass, Y., Halfon, A., Venezian, E., Shnayderman, I., Aharonov, R., & Slonim, N. (2018, July). Learning thematic similarity metric from article sections using triplet networks. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (pp. 49-54).
dos Santos Garcia, C., Meincheim, A., Junior, E. R. F., Dallagassa, M. R., Sato, D. M. V., Carvalho, D. R., Santos, E. A. P., & Scalabrin, E. E. (2019). Process mining techniques and applications–A systematic mapping study. Expert Systems with Applications, 133, 260-295.
Došilović, F. K., Brčić, M., & Hlupić, N. (2018, May). Explainable artificial intelligence: A survey. In 2018 41st International convention on information and communication technology, electronics and microelectronics (MIPRO) (pp. 0210-0215). IEEE.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public interest, 14(1), 4-58.
Fan, Y., Jovanović, J., Saint, J., Jiang, Y., Wang, Q., & Gašević, D. (2022). Revealing the regulation of learning strategies of MOOC retakers: A learning analytic study. Computers & Education, 178, 104404.
Ibrahim, M., Louie, M., Modarres, C., & Paisley, J. (2019, January). Global explanations of neural networks: Mapping the landscape of predictions. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (pp. 279-287).
Jovanović, J., Gašević, D., Dawson, S., Pardo, A., & Mirriahi, N. (2017). Learning analytics to unveil learning strategies in a flipped classroom. The Internet and Higher Education, 33(4), 74-85.
Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2022). Explainable artificial intelligence in education. Computers and Education: Artificial Intelligence, 3, 100074.
Li, L.-Y., & Tsai, C.-C. (2017). Accessing online learning material: Quantitative behavior patterns and their effects on motivation and learning performance. Computers & Education, 114, 286-297.
Mayer, R. E., Mathias, A., & Wetzell, K. (2002). Fostering understanding of multimedia messages through pre-training: Evidence for a two-stage theory of mental model construction. Journal of Experimental Psychology: Applied, 8(3), 147.
Mokoatle, M., Marivate, V., Mapiye, D., Bornman, R., & Hayes, V. (2023). A review and comparative study of cancer detection using machine learning: SBERT and SimCSE application. BMC bioinformatics, 24(1), 1-25.
Moreau, C., Chanson, A., Peralta, V., Devogele, T., & de Runz, C. (2021, March). Clustering sequences of multi-dimensional sets of semantic elements. In Proceedings of the 36th Annual ACM Symposium on Applied Computing (pp. 384-391).
O. H.T. Lua, A. Y.Q. Huang, B. Flanagan, H. Ogata, and S. J.H. Yang, “A Quality Data Set for Data Challenge: Featuring 160 Students’ Learning Behaviors and Learning Strategies in a Programming Course,” Asia-Pacific Society for Computers in Education,
Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).
Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of educational psychology, 82(1), 33.
Ponce, H. R., Mayer, R. E., Loyola, M. S., López, M. J., & Méndez, E. E. (2018). When two computer-supported learning strategies are better than one: An eye-tracking study. Computers & Education, 125, 376-388.
Porter, S. R., Whitcomb, M. E., & Weitzer, W. H. (2004). Multiple surveys of students and survey fatigue. New directions for institutional research, 2004(121), 63-73.
Quadir, B., Chang, M., & Yang, J. C. (2021). Categorizing learning analytics models according to their goals and identifying their relevant components: A review of the learning analytics literature from 2011 to 2019. Computers and Education: Artificial Intelligence, 2, 100034.
Reimers, N., & Gurevych, I. (2019). Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084.
Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). " Why should i trust you?" Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining,
Shapley, L. S. (1953). A value for n-person games.
Tan, T. K., & Samavedham, L. (2022). The learning process matter: A sequence analysis perspective of examining procrastination using learning management system. Computers and Education Open, 3, 100112.
Van der Maaten, L., & Hinton, G. (2008). Visualizing data using t-SNE. Journal of machine learning research, 9(11).
Weinstein, C. E., & Mayer, R. E. (1983, November). The teaching of learning strategies. In Innovation abstracts (Vol. 5, No. 32, p. n32). |