Developing generative AI chatbots conceptual framework for higher education
Joshua Ebere Chukwuere

TL;DR
This paper develops a comprehensive framework, GAICAM, to understand and facilitate the adoption of generative AI chatbots in higher education, highlighting their benefits and challenges.
Contribution
It introduces the GAICAM framework, synthesizing existing models and variables to guide effective implementation of AI chatbots in higher education.
Findings
AI chatbots enhance student engagement and streamline education.
Challenges include negative student perceptions and trust issues.
AI chatbots support administrative and research tasks.
Abstract
This research explores the quickly changing field of generative artificial intelligence (GAI) chatbots in higher education, an industry that is undergoing major technological changes. AI chatbots, such as ChatGPT, HuggingChat, and Google Bard, are becoming more and more common in a variety of sectors, including education. Their acceptance is still in its early phases, with a variety of prospects and obstacles. However, their potential in higher education is particularly noteworthy, providing lecturers and students with affordable, individualized support. Creating a comprehensive framework to aid the usage of generative AI chatbots in higher education institutions (HEIs) is the aim of this project. The Generative AI Chatbots Acceptance Model (GAICAM) is the result of this study's synthesis of elements from well-known frameworks, including the TAM, UTAUT2, TPB, and others along with…
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Taxonomy
TopicsAI in Service Interactions · Online Learning and Analytics · Engineering Education and Technology
