Development and Evaluation of a Large-scale Agent-based System for Collecting Results of Information Literacy Learning Using Electronic Textbooks

Abstract

We developed and evaluated a system that manages student learning status by executing an agent on multiple lecture PCs to collect the progress status and results of simulated examinations included in electronic textbooks. The agent program constantly monitors the execution status of electronic textbooks on lecture PCs, detects the time when a student finishes the simulated test, and automatically captures the image data of the test result screen. Then, the agent performs template matching of the obtained image data, converts the image into score data, and registers the image and the data in the learning management database over the network. We ran the agent program on more than 800 exercise PCs and used them in a literacy course for 307 students at the university. Our results indicate that the group using our system showed significantly faster test score improvement and obtained a higher average score compared with the control group.