Challenges and Future Directions of Big Data and Artificial Intelligence in Education

Abstract

We discuss the new challenges and directions facing the use of big data and artificial intelligence (AI) in education research, policy-making, and industry. In recent years, applications of big data and AI in education have made significant headways. This highlights a novel trend in leading-edge educational research. The convenience and embeddedness of data collection within educational technologies, paired with computational techniques have made the analyses of big data a reality. We are moving beyond proof-of-concept demonstrations and applications of techniques, and are beginning to see substantial adoption in many areas of education. The key research trends in the domains of big data and AI are associated with assessment, individualized learning, and precision education. Model-driven data analytics approaches will grow quickly to guide the development, interpretation, and validation of the algorithms. However, conclusions from educational analytics should, of course, be applied with caution. At the education policy level, the government should be devoted to supporting lifelong learning, offering teacher education programs, and protecting personal data. With regard to the education industry, reciprocal and mutually beneficial relationships should be developed in order to enhance academia-industry collaboration. Furthermore, it is important to make sure that technologies are guided by relevant theoretical frameworks and are empirically tested. Lastly, in this paper we advocate an in-depth dialog between supporters of "cold" technology and "warm" humanity so that it can lead to greater understanding among teachers and students about how technology, and specifically, the big data explosion and AI revolution can bring new opportunities (and challenges) that can be best leveraged for pedagogical practices and learning.

Determining middle school students' perceptions of the concept of artificial intelligence: A metaphor analysis

“…Participants used positive metaphors to explain AI, demonstrating that they had positive views of AI. This situation is very important, so they must be ready for the future of AIsupported education (Luan et al, 2020). Some of the students had negative connotations, such as danger, threat, virus, and evil, as in some literature studies (UNICEF, 2020).…”

“…It is mentioned that students must be ready for the future of AI-supported education (Luan et al, 2020). Growing interest in big data and machine learning has accelerated the evolution of AI in education.…”

Analysis of AI Precision Education Strategy for Small Private Online Courses

“…This is consistent with the study of Lu et al ( 2018 ), which found that precision education aims to identify high-risk students as early as possible and intervene in a timely manner based on teaching experience. Similarly, Luan et al ( 2020 ) stated that AI has the potential to realize individualized learning and precision education. This is because a smart education system powered by AI technology is capable of collecting precise and comprehensive personal data, which can then be analyzed to reveal students' learning patterns and determine their specific needs.…”

The Teaching Design Methods Under Educational Psychology Based on Deep Learning and Artificial Intelligence

“…Some experts also put forward the initial content and implementation plan of relevant teaching courses in view of the application of deep learning theory in higher fields under the background of AI (Chong et al, 2020 ). Lei studied the application of open-source AI systems in education and discussed the existing problems and future development space in the process of research and practice (Lei et al, 2020 ). In a word, the specific practical effect needs further research.…”