A study on behavioral intentions of artificial intelligence learning platform: comparing the perspectives of teachers and students

ABSTRACT

Artificial Intelligence Learning Platform (AILP) plays a key role in AI education. However, there are few studies investigating the behavioral intentions of teachers and students on using AILP and the sample size is small. This study examines factors affecting the behavioral intentions of 299 teachers and 347 students from China on using AILP. “Perceived Playfulness” is integrated into the Unified Theory of Acceptance and Use of Technology (UTAUT) model as the theoretical framework. Moreover, this study analyzes the moderating effects of gender, age, experience, voluntariness of use, teachers’ teaching level, teaching experience, and students’ major. The results of research through two structural equation models show that: (1) Students focus more on performance expectancy, whereas teachers are more concerned with perceived playfulness. (2) Students are easily affected by social influence, while teachers are not. (3) Both teachers and students are impacted by effort expectancy and facilitating conditions. This research provides a scientific comparison of affecting factors about behavioral intentions on using AILP between teachers and students, which can be used by researchers and AILP designers to optimize AILP design for better AI education.

KEYWORDS:

• AI learning platform
• AI learning
• UTAUT model
• teachers and students
• technology acceptance model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Informed consent

This study was conducted after informed consent of the participants.

Availability of data

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by Intelligent Education Course Group Virtual Teaching and Research Office and Shenzhen University Programming Cat "Programming Education and Artificial Intelligence Practice Base" school enterprise cooperation project: [Grant Number 014307].

Notes on contributors

Lin Xiaohong

Lin Xiaohong proposed the idea of the study, designed the experiments, and took the lead in drafting the manuscript.

Zhang Jun

Zhan Jun, the corresponding author of the article, also serves as the supervisor for Lin Xiaohong during her master’s education. Zhan Jun played a comprehensive role in the study, offering numerous suggestions throughout the research process, including the conceptualization of the idea, evaluating the experimental design, and identifying areas of improvement in the paper's writing.

Cao Xiaoming

Cao Xiaoming provided many valuable suggestions during the revision phase, which help the improvement of quality for the article.

Zhao Beina

Zhao Beina actively contributed to participating in discussions on the paper’s idea and providing valuable feedback during multiple revisions of the manuscript.