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Christopher Dann; Petrea Redmond; Melissa Fanshawe; Alice Brown; Seyum Getenet; Thanveer Shaik; Xiaohui Tao; Linda Galligan; Yan Li – Australasian Journal of Educational Technology, 2024
Making sense of student feedback and engagement is important for informing pedagogical decision-making and broader strategies related to student retention and success in higher education courses. Although learning analytics and other strategies are employed within courses to understand student engagement, the interpretation of data for larger data…
Descriptors: Artificial Intelligence, Learner Engagement, Feedback (Response), Decision Making
Zafra, Amelia; Ventura, Sebastian – International Working Group on Educational Data Mining, 2009
The ability to predict a student's performance could be useful in a great number of different ways associated with university-level learning. In this paper, a grammar guided genetic programming algorithm, G3P-MI, has been applied to predict if the student will fail or pass a certain course and identifies activities to promote learning in a…
Descriptors: Foreign Countries, Programming, Academic Achievement, Grades (Scholastic)