The primary objective of this paper is to explore how the intersection of Positive Psychology and Artificial Intelligence in Education can be harnessed to promote both learning and well-being. The authors argue that while AI has made significant strides in addressing various aspects of the learning process, it is equally crucial to focus on the emotional and psychological well-being of students and educators.
Key takeaways:
1. The need for a new approach
The authors highlight that the global shift towards technological solutions in education during the Covid-19 pandemic was not sufficient to address the emotional and psychological challenges faced by students and educators. There is a need to go beyond simply improving academic performance and to also consider the emotional well-being of everyone involved in the educational process.
2. Positive psychology in education
Positive psychology, as proposed by Martin Seligman and Mihaly Csikszentmihalyi, emphasizes building on the strengths of individuals rather than just focusing on alleviating their weaknesses. In the educational context, this means fostering a learning environment that promotes positive emotions, engagement, and well-being.
3. The concept of positive artificial intelligence in education (P-AIED)
The paper introduces the concept of P-AIED, which aims to apply AI not only to enhance learning outcomes but also to promote well-being. This involves developing intelligent tutoring systems that care about the student’s emotional state and using AI to foster a positive learning environment.
4. Research findings
Through a bibliometric analysis, the authors identified 256 studies that align with the principles of P-AIED. The analysis revealed a growing interest in this field, with significant contributions from institutions worldwide. The primary constructs identified were Positive Emotion and Engagement, highlighting the importance of these factors in educational settings.
5. Opportunities for further research
The study points out the lack of well-grounded theories in Positive Psychology within the context of AI in education, presenting an excellent opportunity for future research. Areas like Positive Learning Analytics (P-LA), Positive Educational Data Mining (P-EDM), and Positive Intelligent Tutoring Systems (P-ITS) are identified as hot topics that warrant further exploration.
6. A Roadmap for the future
The authors propose a roadmap for future research and development in P-AIED, emphasizing the need for intelligent systems that genuinely care about the student’s success. This involves a broader understanding of caring, which includes not only what the student knows but also how they feel and how their emotional state affects their learning process.
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