Publication Type:

Conference Paper


2019 IEEE Tenth International Conference on Technology for Education (T4E) (2019)


Bayes methods, Bayesian knowledge tracing (BKT), Central Board of Secondary Education (CBSE), concept knowledge, concept-knowledge reports, Education, Educational institutions, elementary mathematics, feature-aware knowledge tracing, feature-aware student knowledge tracing, Feature-Aware Student knowledge Tracing (FAST) algorithm, first-grade students, Geometry, India, Indian schools, Intelligent tutoring system, intelligent tutoring system (ITS), intelligent tutoring systems, Length measurement, lesson-specific skills, mathematical model, National Council of Educational Research and Training (NCERT), Shape, student-teacher ratio


<p>In many Indian schools, a high student-teacher ratio makes it an uphill struggle for teachers to assess the knowledge of individual students and deficiencies in the students' understanding. Teachers should have a clear picture on what concepts each student has mastered, and which concepts the teacher needs to review in greater detail. This paper investigates the students' concept knowledge, based on the interaction of the students with an intelligent tutoring system. The Feature-Aware Student knowledge Tracing (FAST) algorithm was used, since the algorithm facilitates the separation of lesson-specific skills from concept knowledge. Data from 2400 first-grade students from 28 schools were used for the analysis. Findings include a moderate fit model and an easy interpretation of the model parameters.</p>

Cite this Research Publication

M. Haridas, Dr. Nirmala Vasudevan, Gayathry, S., Gutjahr, G., Raghu Raman, and Prof. Prema Nedungadi, “Feature-Aware Knowledge Tracing for Generation of Concept-Knowledge Reports in an Intelligent Tutoring System”, in 2019 IEEE Tenth International Conference on Technology for Education (T4E), 2019.