Enhancing Programming eTextbooks with ChatGPT Generated Counterfactual-Thinking-Inspired Questions

Autor:	Narayanan, Arun Balajiee Lekshmi, Hendrawan, Rully Agus, V, Venktesh
Rok vydání:	2023
Předmět:	Computer Science - Computation and Language Computer Science - Human-Computer Interaction
Druh dokumentu:	Working Paper
Popis:	Digital textbooks have become an integral part of everyday learning tasks. In this work, we consider the use of digital textbooks for programming classes. Generally, students struggle with utilizing textbooks on programming to the maximum, with a possible reason being that the example programs provided as illustration of concepts in these textbooks don't offer sufficient interactivity for students, and thereby not sufficiently motivating to explore or understand these programming examples better. In our work, we explore the idea of enhancing the navigability of intelligent textbooks with the use of ``counterfactual'' questions, to make students think critically about these programs and enhance possible program comprehension. Inspired from previous works on nudging students on counter factual thinking, we present the possibility to enhance digital textbooks with questions generated using GPT. Comment: Paper Under Review
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.00551 Zobrazit plný text záznamu View this record from Arxiv