Bibliometric Analyses of the Impact of Pedagogical Agents on Learning

Bibliometric Analyses of the Impact of Pedagogical Agents on Learning

Liyan Liu, Shujuan Yan, Xinjie Deng, Zhonggen Yu
Copyright: © 2024 |Pages: 19
DOI: 10.4018/IJMBL.346976
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Abstract

With the rapid development of artificial intelligence, many applications have emerged, sparking heated discussions across various social sectors, particularly in education. This study aims to delve into the impact of pedagogical agents on learning through a combined use of VOSviewer and CitNetExplorer. Specifically, VOSviewer will facilitate a quantitative analysis, identifying top-cited authors, organizations, countries, co-cited authors, and frequently occurring keywords within the citation network. Meanwhile, CitNetExplorer will undertake a qualitative exploration, anticipated to reveal how visual stereotypes and emotional factors of pedagogical agents substantially impact learners' outcomes. This study lays the groundwork for further investigations into optimizing pedagogical agents' parameters to align with educational goals and promote their integration into instructional practices.
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Introduction

With the rapid development of artificial intelligence, the educational field is undergoing unprecedented changes. The appearance of pedagogical agents has brought many possibilities for education. The integrity of pedagogical agents might have an impact on many aspects of learning and teaching. Therefore, this article will explore the pedagogical agents’ influence on learning. In recent years, pedagogical agents have been used widely in the field of education, with the assumption that pedagogical agents could improve students’ learning abilities. Additionally, studies have shown that pedagogical agents have significant advantages in stimulating students' learning interests and improving their learning efficiency and performance. At the same time, they can also provide teachers with more accurate and personalized teaching aids, to improve the quality of teaching.

However, the application of pedagogical agents in the field of education still faces some challenges, such as the recent rapid development of ChatGPT, which has also aroused widespread concerns among educators around the world (Jiao Jianli, 2023). Researchers have realized the importance of pedagogical agents, so many review articles were published to indicate great impact on various fields, such as education, marketing, and management (Table 1). Tang et al. (2022) conducted a review of 10 studies in English education by case study method. Qi et al. (2020) selected 49 articles from several document databases and explored the effect of chatterbots on digital marketing by case study method. Sikström et al. (2022) conducted a two-phase systematic review of 37 studies by umbrella review method. Dai et al. (2022) used comparative analysis to explore the impact of pedagogical agents on elementary education. However, previous articles conducted content analysis only but neglected quantitative analysis. Table 1 summarizes previous review articles in terms of the total number of included studies, research methods, and keywords.

To give full play to the advantages of pedagogical agents, it is necessary to continuously optimize the algorithm and improve the level of tehcnology to avoid possible problems. Therefore, this study has conducted both qualitative and bibliometric analyses with more than 2,000 articles to explore the impact of pedagogical agents on learning. In the future, the researchers expect to see more research on the application of pedagogical agents in education, as well as practical exploration of how to better leverage their advantages and overcome challenges.

Table 1.
Comparison of review studies
NoAuthorsNumber of included studiesResearch MethodsKeywords
1
Tang et al. (2022)
10
Case study method
Information Technology; Artificial Intelligence; English Education;
2
Qi et al. (2020) al. (2020)
49
Case study method
Chatterbots; digital marketing; literature review; research questions
3
Sikström et al. (2022)
37
Umbrella review method
Student-agent communication
Human-machine communication
4 Dai et al. (2022) 75Comparative analysisAugmented and virtual reality; elementary education; human-computer interface; media in education

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