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Schmitz, Marcel; Scheffel, Maren; Bemelmans, Roger; Drachsler, Hendrik – Journal of Learning Analytics, 2022
Learning activities are at the core of every educational design effort. Designing learning activities is a process that benefits from reflecting on previous runs of those activities. One way to measure the behaviour and effects of design choices is to use learning analytics (LA). The challenge, however, lies in the unavailability of an…
Descriptors: Learning Analytics, Instructional Design, Learning Activities, Decision Making
Scanlon, Eileen – Journal of Interactive Media in Education, 2021
This paper explores the development of educational technology research over the last 50 years. This is done by considering what has influenced this development and what are current trends. The issue is further explored by considering what influence these trends have had on the development of distance learning pedagogy, especially for the education…
Descriptors: Educational Technology, Educational Research, Educational History, Educational Trends
Bozkurt, Aras; Sharma, Ramesh C. – Asian Journal of Distance Education, 2022
Humans have always been lured by the idea that they can use data to understand a phenomenon and make predictions about it. Learning analytics, in this sense, promise to understand and optimize learning and the environments in which it occurs by collecting data from learners and learning contexts. In this regard, this study systematically examines…
Descriptors: Learning Analytics, Teaching Methods, Learning Processes, Prediction
Luckin, Rosemary; Cukurova, Mutlu – British Journal of Educational Technology, 2019
Interdisciplinary research from the learning sciences has helped us understand a great deal about the way that humans learn, and as a result we now have an improved understanding about how best to teach and train people. This same body of research must now be used to better inform the development of Artificial Intelligence (AI) technologies for…
Descriptors: Instructional Design, Educational Technology, Artificial Intelligence, Mathematics
Rosé, Carolyn P.; McLaughlin, Elizabeth A.; Liu, Ran; Koedinger, Kenneth R. – British Journal of Educational Technology, 2019
Using data to understand learning and improve education has great promise. However, the promise will not be achieved simply by AI and Machine Learning researchers developing innovative models that more accurately predict labeled data. As AI advances, modeling techniques and the models they produce are getting increasingly complex, often involving…
Descriptors: Discovery Learning, Man Machine Systems, Artificial Intelligence, Models