ReviewFrontiers in psychology2020
Challenges and Future Directions of Big Data and Artificial Intelligence in Education.
Review in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
31 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effectiveness of AI-assisted medical education for Chinese undergraduate medical students: a meta-analysis.BMC medical education · 2025Pooled it
- Systematic bibliographic analysis of heavy metal remediation.Water science and technology : a journal of the International Association on Water Pollution Research · 2025Pooled it
- Article
- Fueling AI literacy through school support: unveiling the mediating role of basic psychological need satisfaction in Chinese university English teachers.BMC psychology · 2026Article
- Nursing Educators' Perceptions of AI in Research: Risks and Benefits.Nursing research and practice · 2026Article
- AI-supported teaching and student engagement: the mediating role of perceived competence in vocational education.Frontiers in psychology · 2026Article
- The dark side of AI in education: AI dependency as a mediator linking academic self-efficacy and teacher support to learning burnout among university students.Frontiers in psychology · 2026Article
- Application of DeepSeek-assisted problem-based learning in hematology residency training.BMC medical education · 2025Article
- Unpacking the ethics of using AI in primary and secondary education: a systematic literature review.AI and ethics · 2025Article
- A hybrid model combining environmental analysis and machine learning for predicting AI education quality.Scientific reports · 2025Article
- Psychometric properties and Turkish adaptation of the artificial intelligence attitude scale (AIAS-4): evidence for construct validity.BMC psychology · 2025Article
- Technology challenges in a higher education institution: Student nurse experience.Health SA = SA Gesondheid · 2025Article
- Influence of theoretical and practical artificial intelligence knowledge on the primary school teachers' sustainable AI integration ability: mediating effects of beliefs and attitudes.Frontiers in psychology · 2025Article
- Research perspectives and trends in Artificial Intelligence-enhanced language education: A review.Heliyon · 2024Review
- Assessing AI adoption in developing country academia: A trust and privacy-augmented UTAUT framework.Heliyon · 2024Article
- Demand Forecasting of Nurse Talents in China Based on the Gray GM (1,1) Model: Model Development Study.Asian/Pacific Island nursing journal · 2024Article
- Comparative Analysis of Mixed Reality and PowerPoint in Education: Tailoring Learning Approaches to Cognitive Profiles.Sensors (Basel, Switzerland) · 2024Article
- Artificial Intelligence Readiness, Perceptions, and Educational Needs Among Dental Students: A Cross-Sectional Study.Clinical and experimental dental research · 2024Article
- Onscreen presence of instructors in video lectures affects learners' neural synchrony and visual attention during multimedia learning.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning.Frontiers in psychology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.