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Wongvorachan, Tarid; Lai, Ka Wing; Bulut, Okan; Tsai, Yi-Shan; Chen, Guanliang – Journal of Applied Testing Technology, 2022
Feedback is a crucial component of student learning. As advancements in technology have enabled the adoption of digital learning environments with assessment capabilities, the frequency, delivery format, and timeliness of feedback derived from educational assessments have also changed progressively. Advanced technologies powered by Artificial…
Descriptors: Artificial Intelligence, Feedback (Response), Learning Analytics, Natural Language Processing
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Tong Li; Sarah D. Creer; Tracy Arner; Rod D. Roscoe; Laura K. Allen; Danielle S. McNamara – Grantee Submission, 2022
Automated writing evaluation (AWE) tools can facilitate teachers' analysis of and feedback on students' writing. However, increasing evidence indicates that writing instructors experience challenges in implementing AWE tools successfully. For this reason, our development of the Writing Analytics Tool (WAT) has employed a participatory approach…
Descriptors: Automation, Writing Evaluation, Learning Analytics, Participatory Research
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Worsley, Marcelo; Martinez-Maldonado, Roberto; D'Angelo, Cynthia – Journal of Learning Analytics, 2021
Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12…
Descriptors: Learning Analytics, Artificial Intelligence, Data Collection, Statistical Inference
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Zhang, Ling; Jackson, Haidee A.; Hunt, Tiffany L.; Carter, Richard Allen; Yang, Sohyun; Emerling, Christopher R. – TEACHING Exceptional Children, 2022
Mathematical problem solving is a complex cognitive activity, which poses difficulties for students with and without disabilities in inclusive learning environments. With a variety of functions, Learning Management Systems (LMSs) have the potential to enhance personalized learning to meet the diverse needs of all students. This paper provides…
Descriptors: Integrated Learning Systems, Mathematics Skills, Problem Solving, Evidence Based Practice
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Leu, Katherine – RTI International, 2020
Postsecondary education is awash in data. Postsecondary institutions track data on students' demographics, academic performance, course-taking, and financial aid, and have put these data to use, applying data analytics and data science to issues in college completion. Meanwhile, an extensive amount of higher education data are being collected…
Descriptors: Learning Analytics, Postsecondary Education, Academic Achievement, Graduation Rate
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Lam, Paul; Lau, Carmen K. M.; Chan, Chi Him – International Association for Development of the Information Society, 2019
A successful flipped classroom relies heavily on student engagement in pre-class learning and their active participation in classroom activities. However, much to students' disappointment, their efforts in the learning process often go unnoticed in traditional assessment approaches (such as term papers and final examinations) that are more…
Descriptors: Flipped Classroom, Homework, Student Attitudes, Learning Processes
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Hershkovitz, Arnon – Technology, Instruction, Cognition and Learning, 2015
Data-driven instruction is still a huge scope and has many shades. One promising way of adding learning analytics to traditional teaching is to offer teachers accessible, data-driven information, either in a dashboard style or with a UI with which they could perform their own analysis on student data (e.g., Ben-Naim, Bain, & Marcus, 2009;…
Descriptors: Data Use, Learning Analytics, Computer Interfaces, Reflection