Intelligent Tutoring Systems (ITS) aim to deliver personalized learning support to each learner, aligning with the educational aspiration of many countries including China. ITS personalized support is mainly achieved by providing individual prompts to learners when they encounter difficulties in problem-solving. The guiding principles and methods of prompts have been less investigated in previous ITS literatures. Based on relevant learning theories, such as self-regulated learning theory, zone of proximal development, scaffolding and heuristic teaching, we proposed seven guiding principles for designing ITS prompts and designed the guiding and adaptive prompts for the difficult questions in a mathematical ITS, Math Intelligent Assessment and Teaching System (MIATS) V2.0. In order to verify the effectiveness of this ITS with the aforementioned prompts, we conducted a 2x2 quasi-experiment in a high school, where the experimental group followed a process of “pre-test, practice with general prompts and adaptive tutoring, post-test,” while the control group followed a process of “pre-test, practice with only general prompts, post-test”. We collected the pre and post-test scores of both the experimental and control groups, and log data from the student model within the ITS for the experimental group students. The data analysis indicated that although the experimental group scored lower than the control group in the pre-test, they scored higher in the post-test and spent less completion time. The drilled problems and the prompts provided to the experimental group students were personalized. In conclusion, the design principles for guiding and adaptive prompts in the ITS can provide personalized guidance and support for students, thus effectively improve their performance. Those principles are not only valuable for the subject mathematics but also can contribute significantly to the prompt design of other subjects, thereby bolstering the global pursuit of personalized education.

Student-athletes frequently struggle to strike a balance between their academic and athletic responsibilities. Various factors, such as age and competitive level, contribute to differences in their academic motivation and identity, showcasing the multifaceted needs they possess. While self-determination theory (SDT) has been proven effective for explaining student-athletes academic needs, its integration into learning design for this group remains limited. The developing AI technology, especially the Intelligent Tutoring System (ITS), offers the potential for creating personalized learning environments that can cater to the varying levels of motivation among student-athletes within the framework of SDT. Therefore, our paper explored how to build an SDT-based ITS for student-athletes to enhance their academic engagement and motivation. A two-stage experiment was conducted for: (a) identifying academic challenges faced by student-athletes in an online ITS; (b) evaluating the effectiveness of an SDT-based ITS design; and (c) exploring how autonomy, competence, and relatedness design affect their motivation. Results revealed that student-athletes face three challenges in learning in ITS: inflexible technology, identity missing, and mismatched learning difficulty. However, a significant improvement in academic engagement and motivation was shown when student-athletes faced an SDT-based ITS. In the meantime, the athletic motivation, which leads them to higher athletic performance, remains preserved and unaffected, showing a favorable outcome for student-athletes. This paper can provide practical implications for building a more inclusive and diverse learning environment for student-athletes.

The 2022 “Frontier of Educational Technology” summer school was held by the Department of Educational Technology, Graduate School of Education, Peking University from July 4^th 2022 to July 8^th 2022. In order to ensure the learning quality, a small private online course was designed for the first time. A series of learning activities such as ice-breaking trip, expert lectures, group discussions, and group presentation were carried out with the help of the course management system, live broadcast platform and social media groups. We analyzed the data recorded by the course management system and found that more than half of the students participated in all learning activities, and the final completion rate of the summer school is as high as 89.86%. An online questionnaire was used to examine students’ subjective responses to the pedagogy and course performance. The results showed that the average score of almost all the questions in the questionnaire is greater than 4.3 points (out of 5.0), indicating that most students are satisfied or very satisfied with this pedagogy. Suggestions for improvement and future expectations are put forward, and can provide a reference for the full-online SPOC practice and research that are being widely carried out around the world.