Correctness- and confidence-based adaptive feedback of kit-build concept map with confidence tagging

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Abstract

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.

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Pailai, J., Wunnasri, W., Hayashi, Y., & Hirashima, T. (2018). Correctness- and confidence-based adaptive feedback of kit-build concept map with confidence tagging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10947 LNAI, pp. 395–408). Springer Verlag. https://doi.org/10.1007/978-3-319-93843-1_29

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