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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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Acknowledgement
This work was supported by JSPS KAKENHI Grant Number 17H0183901.
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Authors and Affiliations
Graduate School of Engineering, Hiroshima University, Higashihiroshima, Japan
Jaruwat Pailai, Warunya Wunnasri, Yusuke Hayashi & Tsukasa Hirashima
- Jaruwat Pailai
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- Warunya Wunnasri
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- Yusuke Hayashi
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- Tsukasa Hirashima
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Correspondence toJaruwat Pailai.
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Carnegie Mellon University, Pittsburgh, PA, USA
Carolyn Penstein Rosé
University of Technology, Sydney, NSW, Australia
Roberto Martínez-Maldonado
University of Duisburg-Essen, Duisburg, Germany
H. Ulrich Hoppe
UCL Institute of Education, London, UK
Rose Luckin
UCL Institute of Education, London, UK
Manolis Mavrikis
UCL Institute of Education, London, UK
Kaska Porayska-Pomsta
Carnegie Mellon University, Pittsburgh, PA, USA
Bruce McLaren
University of Sussex, Brighton, UK
Benedict du Boulay
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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: Penstein Rosé, C.,et al. Artificial Intelligence in Education. AIED 2018. Lecture Notes in Computer Science(), vol 10947. Springer, Cham. https://doi.org/10.1007/978-3-319-93843-1_29
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