articleIEEE Transactions on Knowledge and Data EngineeringJun 25, 2019Closed access

EKT: Exercise-Aware Knowledge Tracing for Student Performance Prediction

University of Science and Technology of China · Rutgers, The State University of New Jersey

Indexed incrossref

Abstract

For offering proactive services (e.g., personalized exercise recommendation) to the students in computer supported intelligent education, one of the fundamental tasks is predicting student performance (e.g., scores) on future exercises, where it is necessary to track the change of each student's knowledge acquisition during her exercising activities. Unfortunately, to the best of our knowledge, existing approaches can only exploit the exercising records of students, and the problem of extracting rich information existed in the materials (e.g., knowledge concepts, exercise content) of exercises to achieve both more precise prediction of student performance and more interpretable analysis of knowledge…

Citation impact

474
total citations
FWCI
51.87
Percentile
100%
References
77
Citations per year

Authors

7

Topics & keywords

Keywords
  • Computer science
  • Tracing
  • TRACE (psycholinguistics)
  • Knowledge acquisition
  • Exploit
  • Artificial neural network
  • Artificial intelligence
  • Task (project management)
UN Sustainable Development Goals
  • Quality Education
No related works found for this paper.

Funding