Exploring Factors Influencing Teachers' Acceptance of AI Tools for Creating Animated Educational Videos With Pedagogical Agents

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2025-06-16 DOI:10.1111/jcal.70083

Sivakorn Malakul

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引用次数: 0

Abstract

Background

Artificial intelligence (AI) tools have been increasingly utilised in the production of educational media, including animated educational videos (AEVs) incorporating pedagogical agents (PAs). These tools support the efficient creation of multimedia content and reduce teachers' technical workload.

Objectives

This study investigates the relationships among factors influencing teachers' acceptance of AI-assisted tools for creating AEVs, based on the technology acceptance model (TAM).

Methods

A mixed-methods approach was employed, combining quantitative analysis using the AI Technology Acceptance Scale (AITAS) based on the TAM and qualitative insights from thematic analysis of open-ended responses from 1569 teachers. Structural equation modelling was applied for the quantitative analysis, confirmed an excellent model fit (CFI = 0.97, GFI = 0.95, RMSEA = 0.06, SRMR = 0.03). Sentiment analysis further supported the qualitative findings.

Results and Conclusions

The results show that perceived usefulness and ease of use significantly influence teachers' attitudes towards adopting AI tools for AEV production. These tools improve content quality and student engagement. While 77.44% of teachers expressed positive attitudes toward using AI, technical challenges were also reported, particularly in relation to limited skills, inadequate hardware, and poor internet connectivity. These issues were more prevalent in less-resourced areas. To support successful integration, it is essential to provide targeted training and ensure broader access to AI tools.

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探索影响教师接受人工智能工具与教学代理一起制作动画教育视频的因素

人工智能（AI）工具越来越多地用于制作教育媒体，包括包含教学代理（PAs）的动画教育视频（aev）。这些工具支持多媒体内容的高效创建，并减少教师的技术工作量。本研究基于技术接受模型（TAM），探讨影响教师接受人工智能辅助工具创建aev的因素之间的关系。方法采用混合方法，采用基于TAM的人工智能技术接受度量表（AITAS）进行定量分析，并通过对1569名教师开放式回答的主题分析获得定性见解。采用结构方程模型进行定量分析，证实模型拟合良好（CFI = 0.97, GFI = 0.95, RMSEA = 0.06, SRMR = 0.03）。情绪分析进一步支持了定性研究结果。结果与结论结果表明，感知有用性和易用性显著影响教师对采用人工智能工具进行AEV制作的态度。这些工具提高了内容质量和学生参与度。虽然77.44%的教师对使用人工智能持积极态度，但也报告了技术挑战，特别是与技能有限，硬件不足和互联网连接不良有关。这些问题在资源较少的地区更为普遍。为了支持成功的整合，提供有针对性的培训并确保更广泛地使用人工智能工具至关重要。

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来源期刊

Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

9.70

自引率

6.00%

发文量

116

期刊介绍： The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope