Examining and Visualizing the Effects of Pedagogical Agents on Learning Outcomes

Introduction

Pedagogical agents are computer-based characters or avatars designed to simulate human teachers for the purpose of delivering educational content and guidance (Zhao et al., 2023). They are often used in online and distance learning settings to provide personalized instruction and support. Pedagogical agents can be classified into interactive, animated, and embodied pedagogical agents based on their level of autonomy, interaction capabilities, and the type of content they deliver (Zhao et al., 2023). Animated pedagogical agents are computer-generated characters used in educational contexts to engage learners. They are designed to simulate human behavior and interact with learners through digital media, enhancing the learning experience (Hong et al., 2014). Embodied pedagogical agents, on the other hand, are physical robots or figurines that possess movement and interactivity, simulating human movement and speech. They aim to create a more immersive and engaging learning environment, particularly in areas like physical skills and spatial reasoning (Swiecki et al., 2019). Interactive agents engage students in conversation and provide immediate responses (Zhang et al., 2023). The design and implementation of pedagogical agents require a combination of educational theory, artificial intelligence techniques, and user-centered design principles to create effective and engaging learning experiences.

The study on the effects of animated and interactive pedagogical agents on learning outcomes is a groundbreaking exploration into the intersection of technology and education. It is crucial in our understanding of how to maximize the potential of digital tools in enhancing teaching and learning. The findings of this study have far-reaching implications for education systems worldwide, suggesting that the integration of animated and interactive agents can significantly improve student engagement and learning outcomes (Wei et al., 2024). This research also highlights the need for ongoing investigation into the most effective uses of these agents in various educational contexts, allowing for more personalized and impactful learning experiences. The study on animated and interactive pedagogical agents serves as a valuable resource for informing educational practices and policies, ultimately leading to more effective teaching and learning methods (Hong et al., 2014).

The research gap in the field of visualization and systematic analysis study on the effects of animated and interactive pedagogical agents on learning outcomes is wide and significant. While there has been a growing interest in the use of these agents in education, there is a lack of comprehensive understanding of their impact on learning outcomes (Gu et al., 2023). To date, much of the research in this area has focused on exploring the acceptability and engagement of students with these agents. However, there is a dearth of evidence regarding the type of pedagogical agents, such as animated, interactive and embodied pedagogical agents (Davis et al., 2021). Furthermore, it remains unclear whether ethnicity and prior knowledge, as well as pedagogical agents integrated with image, audios, visuals, and narration, influence learning outcomes (Zhao et al., 2023). Research should aim to bridge this gap by conducting rigorous visualization and systematic analyses to synthesize the existing evidence on the effects of animated and interactive pedagogical agents on learning outcomes. This will require a comprehensive search and analysis of publications using systematic and visualization methods.

This visualization and systematic analysis study, utilizing VOSviewer and CitNetExplorer, aims to explore the impact of pedagogical agents on learning outcomes. Through visualization capabilities of VOSviewer, we will create knowledge maps to identify key clusters and patterns within the research field (Huang et al., 2024). This will give us a comprehensive understanding of the field and highlight potential research gaps. CitNetExplorer, with its network analysis abilities, will help us trace the influence of individual studies and identify the most influential works (Yu & Yu, 2023). By combining both tools, we aim to gain a deeper understanding of the topic and its development over time. The results of this study will inform educators and researchers about effective uses of pedagogical agents in enhancing learning outcomes, leading to improved teaching practices and student learning experiences.