ERIC Number: EJ1127033
Record Type: Journal
Publication Date: 2014
Pages: 3
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-1929-7750
EISSN: N/A
An Adaptive Model of Student Performance Using Inverse Bayes
Lang, Charles
Journal of Learning Analytics, v1 n3 p154-156 2014
This article proposes a coherent framework for the use of Inverse Bayesian estimation to summarize and make predictions about student behaviour in adaptive educational settings. The Inverse Bayes Filter utilizes Bayes theorem to estimate the relative impact of contextual factors and internal student factors on student performance using time series data across a range of possible dimensions. The Inverse Bayesian algorithm treats the student as a Bayesian learner; her partial credit score or confidence is proportional to both her prior knowledge and how she interprets her environment. Once the algorithm has weighted internal and external factors, this information is used to make a prediction about the student's next attempt.
Descriptors: Bayesian Statistics, Academic Achievement, Prediction, Student Behavior, Models, Adolescents
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Massachusetts
Grant or Contract Numbers: N/A