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Ashima Kukkar; Rajni Mohana; Aman Sharma; Anand Nayyar – Education and Information Technologies, 2024
In the profession of education, predicting students' academic success is an essential responsibility. This study introduces a novel methodology for predicting students' pass or fail outcome in certain courses. The system utilises academic, demographic, emotional, and VLE sequence information of students. Traditional prediction methods often…
Descriptors: Predictor Variables, Academic Achievement, Pass Fail Grading, Long Term Memory
Almeda, Ma. Victoria; Zuech, Joshua; Utz, Chris; Higgins, Greg; Reynolds, Rob; Baker, Ryan S. – Online Learning, 2018
Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…
Descriptors: Performance Factors, Online Courses, Electronic Learning, Models
Berthier, Neil E.; Boucher, Kelsea; Weisner, Nina – Infant and Child Development, 2015
Children's performance on cognitive tasks is often described in categorical terms in that a child is described as either passing or failing a test, or knowing or not knowing some concept. We used binomial mixture models to determine whether individual children could be classified as passing or failing two search tasks, the DeLoache model room…
Descriptors: Individual Differences, Toddlers, Investigations, Models
Shulruf, Boaz; Jones, Phil; Turner, Rolf – Higher Education Studies, 2015
The determination of Pass/Fail decisions over Borderline grades, (i.e., grades which do not clearly distinguish between the competent and incompetent examinees) has been an ongoing challenge for academic institutions. This study utilises the Objective Borderline Method (OBM) to determine examinee ability and item difficulty, and from that…
Descriptors: Undergraduate Students, Pass Fail Grading, Decision Making, Probability