Equitable Access to Intelligent Tutoring Systems Through Paper-Digital Integration

Conference Paper (2022)
Author(s)

Nirmal Patel (Playpower Labs)

Mithilesh Thakkar (Playpower Labs)

Bansri Rabadiya (Teach for India, Ahmedabad)

Darshan Patel (Playpower Labs)

Shrey Malvi (Playpower Labs)

Aditya Sharma (Playpower Labs)

James Derek Lomas (TU Delft - Form and Experience)

Research Group
Form and Experience
Copyright
© 2022 Nirmal Patel, Mithilesh Thakkar, Bansri Rabadiya, Darshan Patel, Shrey Malvi, Aditya Sharma, J.D. Lomas
DOI related publication
https://doi.org/10.1007/978-3-031-09680-8_24
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Nirmal Patel, Mithilesh Thakkar, Bansri Rabadiya, Darshan Patel, Shrey Malvi, Aditya Sharma, J.D. Lomas
Research Group
Form and Experience
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
255-263
ISBN (print)
9783031096792
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Intelligent Tutoring Systems (ITS) can only respond adaptively to the digital learning activities of the students. If students are learning offline without any digital devices, they have little or no means to receive personalized learning materials with the help of intelligent systems. This paper proposes a Paper-Digital Integration System that can provide offline learners equitable access to ITS capabilities by looking at their work on paper and giving personalized printable feedback. We analyzed data from a paper algebra assessment of N = 17 students and found mistakes that may generalize and help us offer adaptive paper-based recommendations to students. Our analysis showed us some specific algebra mistakes that may help in providing intelligent feedback.

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