Artificial Intelligence-based Robotic Technology in Vocational Education, A Literature Review: A Promising Strategy for Enhancing Student Performance?

Artificial Intelligence-based Robotic Education (AIRE) has emerged as a transformative approach applied across various disciplines, merging the realms of Arts and Science. Central to AIRE research is the learning performance of students, which remains a primary focus (Chen, Park, & Breazeal, 2020; Raj & Seamans, 2019; Timms, 2016). Additionally, valuable aspects explored in connection with student performance include learners' attitudes, perceptions, and behaviors regarding their educational experiences. As artificial intelligence technology advances rapidly, its integration into robotics—facilitating more interactive educational tools—has been notably significant.

Traditionally, conventional robots, like LEGO models, were primarily designed to assist students in assembling tasks and programming commands. In contrast, AI-integrated robots possess advanced capabilities, enabling them to interact seamlessly with learners through voice and image recognition, as well as natural language processing. These sophisticated interactions diversify learning scenarios, allowing for personalized guidance, immediate feedback (Chan & Zary, 2019), and engaging interactions with students (Papadopoulos et al., 2020). They serve as intelligent tutoring systems, fostering an environment where learners can acquire knowledge and skills independently (Yang & Zhang, 2019), reshaping the traditional educational framework.

Numerous studies attest to the effectiveness of AI in enhancing educational outcomes in various fields, such as in the areas of engineering (García et al., 2007), mathematics (Tang et al., 2021, pp. 1–19), languages (Liu et al., 2021), online learning (Hwang et al., 2022), and nursing education (Chang et al., 2022). As AI and robotics continue to evolve within educational contexts, it becomes crucial for vocational education researchers and educators to identify trends and applications of AI-robots.

The objective of this study is to assess the effectiveness of robotic technology on enhancing the learning process for vocational school students. The methodology employed is a review and analysis by using 49 studies and taken from Google Scholar, ScienceDirect, and Proquest databases from 2014 to 2023. The effect size data analysis technique was used to find the impact on each study. The study’s conclusions showed that there was no publication bias in the random effects hedging model. At a 95% confidence level, the average effect size of incorporating robotic technology into the learning process was > 0.90, findings illustrate a robust correlation between the incorporation of robotic technology into educational practices and improved student outcomes. The use of robotic technology in vocational education not only enriches learning experiences but also develops essential skills such as computational thinking, creativity, and teamwork. These competencies are foundational as students navigate the complexities of the fourth stage of industrialization, emphasizing the urgent relevance and potential impact of AI-based robotic technologies in modern education.


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