With the advent of the era of intelligent education, artificial intelligence and other technologies are being integrated into education, so that more educational data can be collected, processed, and analyzed. However, educational data ethics is an important factor that hinders the application of educational data. Thus, it is important to ensure privacy and security by reasonable use of educational data. As such, this research focuses on analysis of hot-points, trends in development and problems of educational data ethics in existing research using bibliometric analysis. Based on in-depth analysis, this study proposes targeted problem-solving strategies, and future developmental direction for learner-centered educational data ethics in the era of intelligent education. This study found three major problems in the educational data ethics: (a) violation of privacy during data collection, storage, and sharing, (b) the deprivation of the ability of educational subjects to make independent choices by prediction of educational data, (c) and the lack of “forgetting ability” based on data as the evaluation standard, which is one of the restrictions on the development of educational subjects. This research proposes that the corresponding problem-solving strategy in China should be learner-centered, combined with technologies such as blockchain, 5 G technology, and federated learning to form targeted solutions from different levels. Firstly, it is necessary to establish a standard system and related platforms of educational data from the macro level. Second, the research-practice dual channels should make efforts to build a new ecology of educational data. Third, schools and teachers must appropriately apply educational data in evaluation. Finally, this study provides direction and guidance for other countries or regions in researching educational data ethics.
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