Examining the applications of intelligent tutoring systems in real educational contexts: A systematic literature review from the social experiment perspective

Abstract

Intelligent Tutoring Systems (ITSs) have a great potential to effectively transform teaching and learning. As more efforts have been put on designing and developing ITSs and integrating them within learning and instruction, mixed types of results about the effectiveness of ITS have been reported. Therefore, it is necessary to investigate how ITSs work in real and natural educational contexts and the associated challenges of ITS application and evaluation. Through a systematic literature review method, this study analyzed 40 qualified studies that applied social experiment methods to examine the effectiveness of ITS during 2011–2022. The obtained results highlighted a complicated landscape regarding the effectiveness of ITS in real educational contexts. Specifically, there was an “intelligent” regional gap regarding the distribution of countries where ITS studies using social experiment methods were conducted. Compared to learning performance, relatively less attention was paid to investigating the impact of ITS on non-cognitive factors, process-oriented factors, and social outcomes, calling for more research in this regard. Considering the complexities and challenges existing in real educational fields, there was a lack of scientific rigor in terms of experimental design and data analysis in some of the studies. Based on these findings, suggestions for future study and implications were proposed.

ChatGPT Needs a Chemistry Tutor Too

“…Intelligent Tutoring Systems (ITSs) describe computers that integrate AI into tutoring practices that know the material, the learner, and how to teach the material. 1 Moreover, ITS has also been described as an early alert system and shows no significant difference between the system and human interventions. 7 Review of the literature highlights implementation of ITSs in most educational contexts.…”

“…7 Review of the literature highlights implementation of ITSs in most educational contexts. 1 Additionally, they describe how it has supported disciplines in STEM, history, and economics. Furthermore, Cognitive Tutors were identified as the primary use of the technology, and 65% of studies reported a positive effect on learning performance.…”

ChatGPT Needs a Chemistry Tutor Too

“…Artificial Intelligence (AI) has been at the center of conversations as a disruptor for many industries 1 . Within the context of education, AI as Natural Language Processing (NLP) Models have been proposed as tools to generate instructional materials, assessment grading, assistance answering questions, and providing feedback to learners [2][3][4][5] .…”

“…Artificial Intelligence (AI) has been at the center of conversations as a disruptor for many industries 1 . Within the context of education, AI as Natural Language Processing (NLP) Models have been proposed as tools to generate instructional materials, assessment grading, assistance answering questions, and providing feedback to learners [2][3][4][5] . Prevalent discussion has focused on ChatGPT, an NLP Model generated by Open AI based on Generative Pre-trained Transformer (GTP) trained by textual data from the internet 2,3,6 .…”

“…Applications of AI related to education and learner engagement is not new. Intelligent Tutoring Systems (ITS) describe computers that integrate AI into tutoring practices that know the material, the learner, and how to teach the material 1 . Moreover, ITS has also been described as an early-alert system and showing no significant difference between the system and human interventions 7 .…”