Course selection is a crucial activity for students as it directly impacts their workload and performance. It is also time-consuming, prone to subjectivity, and often carried out based on incomplete information. This task can, nevertheless, be assisted with computational tools, for instance, by predicting performance based on historical data. We investigate the effects of showing grade predictions to students through an interactive visualization tool. A qualitative study suggests that in the presence of predictions, students may focus too much on maximizing their performance, to the detriment of other factors such as the workload. A follow-up quantitative study explored whether these effects are mitigated by changing how predictions are conveyed. Our observations suggest the presence of a framing effect that induces students to put more effort into course selection when faced with more specific predictions. We discuss these and other findings and outline considerations for designing better data-driven course selection tools.
Can AI Reduce Acculturative Stress? Exploring the Role of AI-Mediated Speaking Practice in Chinese International Students' Perceived Language Insufficiency, Social Isolation, and Academic Pressure
Xi'an Jiaotong-Liverpool University（西交利物浦大学）；University of Cambridge（剑桥大学）
Leveraging WiFi Network Logs to Infer Student Collocation and its Relationship with Academic Performance
对搭配的全面理解有助于理解绩效结果。对于大学队列，这需要描述长期大群体的数据。利用用户设备来推断这一点虽然诱人，但受到隐私问题、功耗和维护问题的挑战。或者，在环境中嵌入新的传感器受到覆盖整个校园的费用的限制。我们调查利用WiFi关联日志用于此目的的可行性。虽然这些提供了粗略的近似位置，但这些很容易获得，并描述了一个学期内校园内的多个用户。我们探讨这些粗糙的搭配是如何与个人的表现。具体而言，我们检查个人绩效和项目组成员的搭配行为之间的关联。我们研究了163名学生（在54个项目组）超过14周。在描述了我们如何确定搭配的WiFi日志，我们提出了一项研究，分析如何搭配组内涉及到学生的最终成绩。我们发现，搭配行为与绩效表现出显著的相关性（Pearson's r = 0.24），比同伴反馈或个人行为（如出勤）更好。最后，我们将讨论如何重新利用WiFi日志可以促进心理健康和身体健康等领域的应用程序。
The impact of generative artificial intelligence on academic development of Chinese students in humanities and social sciences
Design School, Xi’an Jiaotong-Liverpool University（西安交通大学利物浦大学设计学院）；School of Computer Science and Informatics, University of Liverpool（利物浦大学计算机科学与信息学院）
Measuring How Students Rely on Generative AI in Academic Writing: Development and Multi-Source Validation of the Generative AI Reliance Types Scale (GenAI-RTS)
University of Maryland Baltimore County（马里兰大学巴尔的摩县分校）；University at Buffalo（布法罗大学）
