Development and validation of the perceived interactivity of learner-AI interaction scale

Feifei Wang, Alan C.K. Cheung*, Ching Sing Chai, Jin Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

As learners are able to perceive interactivity when interacting with instructors or peer learners in traditional learning environments, learners are similarly able to perceive interactivity when interacting with artificial intelligence (AI) in AI-supported learning environments. Advancements in AI, such as generative AI including ChatGPT and Midjourney, enhance learners’ perceived interactivity, thereby facilitating learning through AI-enabled interaction. However, there is no scale in education for measuring perceived interactivity of learner-AI interaction. This study develops a 17-item scale to assess the extent to which a learner perceives interactivity with AI from four dimensions: responsiveness, personalization, learner control, and learning engagement. The sample group included 422 Chinese university students for the first application and 306 university students for the second application. Both the exploratory factor analysis and the confirmatory factor analysis verified the factor structure of the scale. The Cronbach’s alpha value for the whole scale was 0.948, whereas the Cronbach’s alpha values for the four dimensions ranged between 0.820 and 0.915. Results suggested that this scale was a reliable and valid instrument. This study also found that perceived interactivity of learner-AI interaction was significantly associated with AI tools, learners’ behavioral intentions to use AI in learning, months of using AI in learning, and average duration of using AI in learning each time, and not associated with ages, genders, education levels, and fields of education. Finally, theoretical and practical implications are discussed.

Original languageEnglish
JournalEducation and Information Technologies
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • Artificial intelligence
  • Perceived interactivity
  • Reliability
  • Scale development
  • Validity

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