Predicting Assessment Item Difficulty Levels Using a Gaussian Mixture Model

• Published in: 2018 International Conference on Data Science and Engineering (ICDSE) pp. 1 - 6
• Main Authors: Narayanan, Sankaran, Saj, Fensa Merry, Soumya, M.D., Bijlani, Kamal
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2018
• Subjects: Adaptation models; adaptive learning systems; Calibration; Data models; Electronic learning; evaluation methodologies; Gaussian mixture model; intelligent tutoring systems; Manuals; personalized learning

The difficulty level of an assessment item plays an important role in ensuring well qualified evaluation process as well as helping in the generation of appropriate assessments for personalized learning. AMrita Personalized Learning and Evaluation (AMPLE) platform adopts an automatic calibration met...