Navigating the Landscape of Hint Generation Research: From the Past to the Future

Fuente: arXiv
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Main Authors: Jangra, Anubhav, Mozafari, Jamshid, Jatowt, Adam, Muresan, Smaranda
Format: Preprint
Published: 2024
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author Jangra, Anubhav
Mozafari, Jamshid
Jatowt, Adam
Muresan, Smaranda
author_facet Jangra, Anubhav
Mozafari, Jamshid
Jatowt, Adam
Muresan, Smaranda
contents Digital education has gained popularity in the last decade, especially after the COVID-19 pandemic. With the improving capabilities of large language models to reason and communicate with users, envisioning intelligent tutoring systems (ITSs) that can facilitate self-learning is not very far-fetched. One integral component to fulfill this vision is the ability to give accurate and effective feedback via hints to scaffold the learning process. In this survey article, we present a comprehensive review of prior research on hint generation, aiming to bridge the gap between research in education and cognitive science, and research in AI and Natural Language Processing. Informed by our findings, we propose a formal definition of the hint generation task, and discuss the roadmap of building an effective hint generation system aligned with the formal definition, including open challenges, future directions and ethical considerations.
format Preprint
id arxiv_https___arxiv_org_abs_2404_04728
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Navigating the Landscape of Hint Generation Research: From the Past to the Future
Jangra, Anubhav
Mozafari, Jamshid
Jatowt, Adam
Muresan, Smaranda
Computation and Language
Human-Computer Interaction
Digital education has gained popularity in the last decade, especially after the COVID-19 pandemic. With the improving capabilities of large language models to reason and communicate with users, envisioning intelligent tutoring systems (ITSs) that can facilitate self-learning is not very far-fetched. One integral component to fulfill this vision is the ability to give accurate and effective feedback via hints to scaffold the learning process. In this survey article, we present a comprehensive review of prior research on hint generation, aiming to bridge the gap between research in education and cognitive science, and research in AI and Natural Language Processing. Informed by our findings, we propose a formal definition of the hint generation task, and discuss the roadmap of building an effective hint generation system aligned with the formal definition, including open challenges, future directions and ethical considerations.
title Navigating the Landscape of Hint Generation Research: From the Past to the Future
topic Computation and Language
Human-Computer Interaction
url https://arxiv.org/abs/2404.04728