Preliminary analysis of IRT on question bank of General Physics

Ming-Huey Huang^1*

¹Dept. of Energy Engineering, National United University, Miao-Li city, Taiwan

* Presenter:Ming-Huey Huang, email:mahuang@nuu.edu.tw

General physics is a required course for freshman in many science or engineering majors, and its learning outcome influence to the study of future professional courses. To improve the learning problems of general physics, a mechanism that can adjust the content of teaching and evaluation is necessary. In our university, two comprehensive exams were conducted in each semester for the last 8 years. Approximately 200 ~ 250 students participate in the exams. A large number of questions and students’ answer were collected. Such big data can be used to construct a question banks to students' assignment or formal instructional evaluation. Using the item response theory, such big data can be analyzed for the difficulty and discrimination indexes, and forming a database of questions. A subset of data will be analyzed and reported in the annual conference. Complete data will be analyzed in the coming year and extended to an on-line system with Artificial Intelligent for adaptive learning.

Keywords: instructional evaluation, item response theory, general physics teaching, general physics teaching, adaptive learning