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Direct linkGabriela Trindade Perry; Marlise Bock Santos – Journal of Computer Assisted Learning, 2024
Background: Instances of academic dishonesty are common in online learning environments because difficulties in their detection result in considerably low degrees of risks. However, if not identified, the noise introduced by dishonest learners in MOOCs' clickstream data could lead to biased results and conclusions in scientific research.…
Descriptors: Foreign Countries, MOOCs, Distance Education, Electronic Learning
Saman Rizvi; Bart Rienties; Jekaterina Rogaten; René F. Kizilcec – Journal of Computer Assisted Learning, 2024
Background: Extensive research on massive open online courses (MOOCs) has focused on analysing learners' behavioural trace data to understand navigation and activity patterns, which are known to vary systematically across geo-cultural contexts. However, the perception of learners regarding the role of different learning design elements in…
Descriptors: MOOCs, Inclusion, Instructional Design, Participant Characteristics
Jaramillo-Morillo, Daniel; Ruipérez-Valiente, José A.; Burbano Astaiza, Claudia Patricia; Solarte, Mario; Ramirez-Gonzalez, Gustavo; Alexandron, Giora – Journal of Computer Assisted Learning, 2022
Background: Small private online courses (SPOCs) are one of the strategies to introduce the massive open online courses (MOOCs) within the university environment and to have these courses validates for academic credit. However, numerous researchers have highlighted that academic dishonesty is greatly facilitated by the online context in which…
Descriptors: Learning Analytics, Cheating, Integrated Learning Systems, Intervention
