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Xiaona Xia; Wanxue Qi – European Journal of Education, 2025
Massive Open Online Courses (MOOCs) effectively support online learning behaviour; while constructing a sustainable learning process, MOOCs have also formed the social network. In addition, learners' burnout state has become a serious obstacle to the development and promotion of MOOCs. This study analyzes the potential social behaviour associated…
Descriptors: MOOCs, Burnout, Social Behavior, Feedback (Response)
Elif Sari – International Journal of Assessment Tools in Education, 2024
Employing G-theory and rater interviews, the study investigated how a high-stakes writing assessment procedure (i.e., a single-task, single-rater, and holistic scoring procedure) impacted the variability and reliability of its scores within the Turkish higher education context. Thirty-two essays written on two different writing tasks (i.e.,…
Descriptors: Foreign Countries, High Stakes Tests, Writing Evaluation, Scores
Ting Yao; Zhongya Qin – Cambridge Journal of Education, 2024
This study aims to assess personal creativity and the development of higher-order thinking skills in improvisation. The authors evaluated higher-order thinking skills in music improvisation and creativity of improvised musical compositions. The results of the t-test showed significant progress in both creativity and thinking skills among students…
Descriptors: Music, Creative Activities, Music Education, Thinking Skills
Mariëtte van Loon; Claudia M. Roebers – Metacognition and Learning, 2024
This study aims to understand individual differences between children in metacognitive monitoring and control processes and the developmental trajectories of metacognition over one year. Three indicators of procedural metacognition were used: monitoring accuracy (discrimination of confidence judgments between correct and incorrect test responses),…
Descriptors: Elementary School Students, Metacognition, Task Analysis, Individual Differences
Erin Conwell; Jesse Snedeker – Language Learning and Development, 2024
Natural languages contain systematic relationships between verb meaning and verb argument structure. Artificial language learning studies typically remove those relationships and instead pair verb meanings randomly with structures. Adult participants in such studies can detect statistical regularities associated with words in these languages and…
Descriptors: Semantics, Cues, Verbs, Adults