Work

Understanding chatbot-assisted collaborative learning among female undergraduate students

Year: 2026

Type: article

Abstract: Computer programming can be daunting for beginners due to complex concepts and syntax. Traditional teaching methods, while engaging through gamification and active learning, often lack personalized approaches. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), present new possibilities for personalized and interactive learning environments. This study introduces a chatbot-assisted collaborative learning environment (CCLE) that leverages an LLM (GPT-4) to enhance collaborative programming education. The CCLE enables real-time guidance and collaboration through natural language interactions, allowing students to work together on programming tasks, edit code collaboratively, and engage with both peers and the educational chatbot. We conducted an empirical study with 102 female students using the CCLE for programming exercises, followed by a survey assessing factors impacting the intention to use the environment. The results indicated that perceived collaboration support by the tool and participants’ personal innovativeness were strong drivers of the intention to use the tool. This study demonstrates the CCLE’s potential to improve collaborative education by fostering a more interactive and supportive learning environment.

Source: Discover Artificial Intelligence

DOI: 10.1007/s44163-026-01416-8

Authors: Mohammad Amin Kuhail, Ahmed Shuhaiber, Sinan Salman, Nazik Alturki

Institutions: Zayed University, Princess Nourah bint Abdulrahman University

Language: English

Topic: Teaching and Learning Programming

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,590