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Okubo, Fumiya; Shiino, Tetsuya; Minematsu, Tsubasa; Taniguchi, Yuta; Shimada, Atsushi – IEEE Transactions on Learning Technologies, 2023
In this study, we propose an integrated system to support learners' reviews. In the proposed system, the review dashboard is used to recommend review contents that are adaptive to the individual learner's level of understanding and to present other information that is useful for review. The pages of the digital learning materials that are…
Descriptors: Learning Management Systems, Student Evaluation, Automation, Artificial Intelligence
Cleon Xavier; Luiz Rodrigues; Newarney Costa; Rodrigues Neto; Gabriel Alves; Taciana Pontual Falcao; Dragan Gasevic; Rafael Ferreira Mello – IEEE Transactions on Learning Technologies, 2025
Providing timely and personalized feedback on open-ended student responses is a challenge in education due to the increased workloads and time constraints educators face. While existing research has explored how learning analytic approaches can support feedback provision, previous studies have not sufficiently investigated educators' perspectives…
Descriptors: Teacher Empowerment, Learning Analytics, Artificial Intelligence, Computer Software
Andriamiseza, Rialy; Silvestre, Franck; Parmentier, Jean-Francois; Broisin, Julien – IEEE Transactions on Learning Technologies, 2023
Formative assessment provides teachers with feedback to help them adapt their behavior. To manage the increasing number of students in higher education, technology-enhanced formative assessment tools can be used to maintain and hopefully improve teaching and learning quality, thanks to the high amount of data that are generated by their usage.…
Descriptors: Learning Analytics, Formative Evaluation, Evidence Based Practice, Peer Evaluation