Sandbox University: Estimating Influence of Institutional Action

The approach presented in this article represents a generalizable and adaptable methodology for identifying complex interactions in educational systems and for investigating how manipulation of these systems may affect educational outcomes of interest. Multilayer Minimum Spanning Tree and Monte-Carlo methods are used. A virtual Sandbox University is created in order to facilitate effective identification of successful and stable initiatives within higher education, which can affect students' credits and student retention – something that has been lacking up until now. The results highlight the importance of teacher feedback and teacher-student rapport, which is congruent with current educational findings, illustrating the methodology's potential to provide a new basis for further empirical studies of issues in higher education from a complex systems perspective.

本文提出的方法，是一种兼具可推广性与适配性的方法论，可用于识别教育系统中的复杂交互关系，并探究对该系统实施干预可能对目标教育结果产生的影响。本研究采用了多层最小生成树（Multilayer Minimum Spanning Tree）与蒙特卡洛（Monte-Carlo）方法。为有效识别高等教育领域中可影响学生学分与学生留存率的成功且稳定的实践方案，本研究构建了虚拟沙盒大学（Sandbox University）——这正是此前相关研究中存在的空白环节。研究结果凸显了教师反馈与师生融洽关系的重要性，这与当前教育领域的研究发现相契合，同时也印证了本方法论能够从复杂系统视角，为高等教育相关问题的后续实证研究提供全新研究基础的潜力。