No field is immune from an AI shock. The field of education, which drives human social life by developing intelligence and utilizing intelligence, is directly affected by AI. This is because the educational effect can be multiplied by using AI in teaching and learning processes. Currently, AIED has become a constant rather than a variable. Based on the results confirmed in this study, the future direction of education is explored, while summarizing the impact of AI on education.
Firstly, research on AIED is increasing in quantity, but more research is still needed
[4]. Papers on AIED have been increasing since 2001. Research papers have been increasing exponentially since 2015, as papers published after 2019 accounted for 37% (1872) of the total. This indicates that AIED has been an active research field since 2015. Education is a broad field that has economic, social, and cultural impacts. Various studies that redesign the paradigm of education from the purpose of education to contents and methods, based on AI, are urgently needed. Research on AIED needs to be further accelerated, such that AI-based education can be established early.
Next, international collaboration should be encouraged for research on AIED. The average collaboration rate of the top 40 countries with high international collaboration rates was 34%. Although the United States plays a central role in international collaboration, the proportion of collaborative papers was not high, at 18.83%. Meanwhile, Canada played an important role in international collaboration in the AIED field, as both the number of joint papers and the ratio of joint papers were high. Examining AIED from the perspective of international joint research and collaborative research beyond the national level is more desirable. The Organization for Economic Co-operation and Development highlighted the importance of international collaboration by providing “National AI Policies & Strategies,” an online platform for establishing and sharing AI public policies
[24]. AI is a global issue. This is because AI needs to be viewed from the perspective of humankind to open the door to a sustainable future.
Moreover, research topics related to AIED should be more diverse. Topics emphasizing AI, such as Topic 6 (AI-driven edu-tech) and Topic 8 (machine learning algorithm), emerged and were confirmed to be hot topics, but specific areas of AIED were not highlighted. Of course, traditional fields of education, such as “content of teaching and learning” and “assessment and evaluation,” cannot be disregarded. However, efforts are needed to redesign the educational paradigm from the perspective of AIED. For example, by classifying the learner types of AIED in consideration of the stages and characteristics of education, such as early childhood education, elementary and secondary education, higher education, and lifelong education, customized education, should be carried out. Learning areas, such as mathematics, science, language learning, and music, will need to be restructured based on AI. There is a need to expand research on AIED in fields directly related to AI, such as statistics, mathematics, computational physics, computers, semiconductor design, and neurophysiology. In addition, in terms of the learning method, exploratory learning using AI, writing analysis, mentoring, and learning analysis, should be expanded. Specifically, fields that understand AI, such as AI literacy and AI ethics, and fields that use AI educationally, such as ITS, DBTS, and ELE, along with research on education for fostering AI experts, should be more active areas.
Finally, in-depth research that directly applies AI algorithms and technologies to education should be further promoted. The keywords “artificial intelligence,” “machine learning,” and “deep learning” rarely appear in the keywords and topics presented in this study. Artificial intelligence-essential words, such as “supervised learning,” “unsupervised learning,” “reinforcement learning,” “chatbots,” “artificial neural networks,” “virtual reality,” and “augmented reality”, are not often observed in AIED. This implies that AI algorithms and technologies have not yet been fully utilized in the AIED. For the development of AIED, education-based AI research that examines AI from an educational perspective, beyond simply using AI application services, should be strengthened. This is because we have entered an era in which education without AI cannot exist.