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Download full textShimmei, Machi; Matsuda, Noboru – International Educational Data Mining Society, 2020
One of the most challenging issues for online courseware engineering is to maintain the quality of instructional components, such as written text, video, and assessments. Learning engineers would like to know how individual instructional components contributed to students' learning. However, it is a hard task because it requires significant…
Descriptors: Teaching Methods, Engineering, Outcomes of Education, Courseware
Almond, Russell G. – ETS Research Report Series, 2007
Over the course of instruction, instructors generally collect a great deal of information about each student. Integrating that information intelligently requires models for how a student's proficiency changes over time. Armed with such models, instructors can "filter" the data--more accurately estimate the student's current proficiency…
Descriptors: Markov Processes, Decision Making, Student Evaluation, Learning Processes
Direct linkBurns, Bruce D. – Cognitive Psychology, 2004
Gigerenzer (2000) and Anderson (1990) analyzed reasoning by asking: what are the reasoner's goals? This emphasizes the adaptiveness of behavior rather than whether a belief is normative. Belief in the ''hot hand'' in basketball suggests that players experiencing streaks should be given more shots, but this has been seen as a fallacy due to…
Descriptors: Heuristics, Beliefs, Adjustment (to Environment), Markov Processes
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
