发表机构
Indian Institute of Technology Ropar（印度技术学院罗帕尔分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对自主学习平台动力不足与负载不可预测问题，提出承诺方案，通过预订学习时段对齐承诺与容量，实验显示学习规律性提升且负载可预测。
AI 中文摘要
在线教育使全球学习者能够选修知名院校的课程。然而，自主学习在线课程无法保证学习者在实时课堂中所体验到的动力和参与度。自主访问还使平台负载不可预测，从而推高计算成本。我们提出了一种课程访问的承诺方案，将学习者的承诺与平台容量对齐。学习者提前预订学习时段；教师设定课程可用的学习时长预算；使用完整时段的学习者可获得额外的观看时长。已预订的时段记录了在指定时间学习的意图，而在该时段出现的学习者则实现了该意图。其副产品是平台负载可预测且有界。该研究涉及同一批学习者依次参加的两门课程，仅在第二门课程中启用了时段预订系统。在86.8%的已预订时段中观察到时段内学习，且中位承诺者将95.5%的学习时间置于自我预订的时段内。在课程启动期间进行学习的学习者中，学习规律性从每周1.01个活跃日提高到1.33个活跃日，与同一批学习者之前的课程相比，差异支持为每周+1.37天。与学习时段同日做出的承诺比提前预订更常被履行（88.8%对比提前两天的62.5%），这与经典的意图-行为差距一致。
英文摘要
Online education has enabled learners worldwide to take up courses from reputed institutions. However, a self-paced online course cannot guarantee the motivation and engagement that a learner experiences in a real-time classroom. Self-paced access also makes platform load unpredictable, which drives up the compute cost. We propose a Commitment Scheme for course access that aligns learner commitment with platform capacity. Learners book their study slots in advance; the instructor sets the budget of learning hours available for the course; and learners who use a full window earn additional watch hours. A booked window records an intention to study at a stated time, and a learner who appears in that window implements it. The byproduct is a platform load that can be forecast and bounded. The study involved two courses taken in sequence by the same learners, with the slot booking system activated only in the second. In-window study was observed on 86.8% of booked windows, and the median committer placed 95.5% of all study time inside self-booked windows. Among learners who studied across the launch, study regularity improved from 1.01 to 1.33 active days per week, with a supporting difference of +1.37 days per week against the same learners' preceding course. Commitments made on the same day as the study slot were honoured more often than advance bookings (88.8% against 62.5% two days ahead), which is consistent with the classic intention-behaviour gap.
Comments16 pages, 2 figures, 6 tables. Accepted as a long paper at the International Conference on Technology for Education (T4E 2026). Authors' version, in revision after peer review; not the final published version
