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Direct linkŠaric-Grgic, Ines; Grubišic, Ani; Šeric, Ljiljana; Robinson, Timothy J. – International Journal of Distance Education Technologies, 2020
The idea of clustering students according to their online learning behavior has the potential of providing more adaptive scaffolding by the intelligent tutoring system itself or by a human teacher. With the aim of identifying student groups who would benefit from the same intervention in AC-ware Tutor, this research examined online learning…
Descriptors: Learning Analytics, Intelligent Tutoring Systems, Grouping (Instructional Purposes), Undergraduate Students
Zendler, A.; Spannagel, C.; Klaudt, D. – IEEE Transactions on Education, 2011
Constructivist approaches to computer science education emphasize that as well as knowledge, thinking skills and processes are involved in active knowledge construction. K-12 computer science curricula must not be based on fashions and trends, but on contents and processes that are observable in various domains of computer science, that can be…
Descriptors: Computer Science Education, Elementary Secondary Education, Thinking Skills, Cluster Grouping
Karavirta, Ville; Korhonen, Ari; Malmi, Lauri – Computer Science Education, 2006
Automatic assessment systems generally support immediate grading and response on learners' submissions. They also allow learners to consider the feedback, revise, and resubmit their solutions. Several strategies exist to implement the resubmission policy. The ultimate goal, however, is to improve the learning outcomes, and thus the strategies…
Descriptors: Feedback (Response), Student Evaluation, Computer Managed Instruction, Foreign Countries
