Correctness- and Confidence-based Adaptive Feedback of Kit-Build Concept Map with Confidence Tagging

In this paper, we present an adaptive feedback of Kit-Build concept map with confidence tagging (KB map-CT) for improving the understanding of learners in a reading situation. KB map-CT is a digital tool that supports the concept maps strategy where learners can construct concept maps for representing their understanding as learner maps and can identify their confidence in each proposition of the learner maps as a degree of their understanding. Kit-Build concept map (KB map) has been already realized the propositional level automatic diagnosis of the learner maps. Therefore, KB map-CT can utilize both correctness and confidence information for each proposition to design and distinguish feedback, that is, (1) correct and confident, (2) correct and unconfident, (3) incorrect and confident, and (4) incorrect and unconfident. An experiment was conducted to investigate the effectiveness of the adaptive feedback. The results suggest that learners can revise their maps after receiving feedback appropriately. In “correct and unconfident” case, adaptive feedback is useful to improve the confidence. In the case of “incorrect and confident,” improvement of the propositions was the same ratio with the case of “incorrect and unconfident.” The results of the delay test demonstrate that learners can retain their understanding and confidence one week later.This work was supported by JSPS KAKENHI Grant Number 17H0183901.'Artificial Intelligence in Education' 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part

再構成型概念マップの妥当性の検証と理解共有のための協調的利用に関する研究

広島大学(Hiroshima University)博士(工学)Doctor of Engineeringdoctora

概念マップと確信度情報に基づく適応的フィードバックに関する研究

広島大学(Hiroshima University)博士(工学)Doctor of Engineeringdoctora