NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Meta M. Landys – Online Learning, 2025
Student attrition in online courses remains a significant concern, particularly in STEM disciplines. Common pedagogical practices in STEM, such as timed, high-stakes "traditional" exams, may contribute to attrition by adversely affecting cognitive development, student attitudes toward their discipline, and various aspects of motivation.…
Descriptors: STEM Education, Access to Information, Testing, Biology
Peer reviewed Peer reviewed
Direct linkDirect link
Fabrício Domingos Ferreira da Rocha; Bruno Lemos; Pedro Henrique de Brito; Rodrigo Santos; Luiz Rodrigues; Seiji Isotani; Diego Dermeval – Education and Information Technologies, 2024
Self-regulation helps students develop various cognitive, metacognitive, and affective strategies to regulate their learning process and maximize learning gains. However, self-regulation demands i) an encouraging environment and ii) student motivation. First, adding Open Learner Models (OLM) to learning environments encourages self-regulation by…
Descriptors: Gamification, Self Management, Access to Information, Open Education
Peer reviewed Peer reviewed
Direct linkDirect link
Burton, J. Dylan – Language Testing, 2023
In its 40th year, "Language Testing" journal has served as the flagship journal for scholars, researchers, and practitioners in the field of language testing and assessment. This viewpoint piece, written from the perspective of an emerging scholar, discusses two possible future trends based on evidence going back to the very first issue…
Descriptors: Language Tests, Testing, Futures (of Society), Periodicals
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Danielle S. McNamara; Tracy Arner; Elizabeth Reilley; Paul Alvarado; Chani Clark; Thomas Fikes; Annie Hale; Betheny Weigele – Grantee Submission, 2022
Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…
Descriptors: Electronic Learning, Educational Technology, Networks, Learning Analytics