Equality in learning outcomes between students from different socio-economic status (SES) backgrounds is a long-standing issue. Although the problem is widespread, not all factors contributing to the gap are known. The compensatory advantage hypothesis posits that benefits of a higher-SES background are greater for students who face early academic difficulties. In other words, the effect of SES is amplified when encountering a challenge. This study examines how poor first assignment outcomes interact with SES to affect success in 22 online university courses. The results show that the relationship between coming from a higher-SES neighbourhood on course success is greater for students who do not submit the first assignment than for those who perform well on it, in line with the compensatory advantage hypothesis. More precisely, students from mid-ranked and high-SES areas were better able to compensate for missing their first assignment than their low-SES counterparts. Despite the robust results, the interaction effect varies considerably across courses, suggesting that contextual course factors might influence the strength, though the factors we analysed did not account for this variation. The implications of these findings for both research and potential strategies to reduce educational inequalities are discussed, emphasizing their significance for theoretical understanding and practical applications.

Procrastination and other forms of irrational delay are widespread among university students, leading to an array of potential negative consequences. While the reasons for this type of behavior are manifold and many facilitating factors have been identified, which of these factors are able to predict dilatory behavior in online/distance education has received comparatively little attention in the literature so far. In this study, we intended to compare the performance of two sets of objective predictors of delay, namely contextual variables based on characteristics of the assignment, and behavioral variables based on log data. Using historical data drawn from our university's learning management system, we calculated Bayesian multilevel models. The strongest and most consistent predictors of dilatory behavior turned out to be interval between the first click on the assignment and its deadline, the interval between the start of a block and the first click on the assignment, the number of clicks on the assignment, and the deadline type. The combination of both sets of predictors slightly improved the model's performance.

Recent research has produced mixed results regarding the effectiveness of learning in VR. It has been suggested that the rich multisensory input in VR may induce cognitive overload that impedes the learning process. Cognitive load is typically measured by administering questionnaires. Although questionnaires are easily used, they imply the need to interrupt students during learning or to assess cognitive load in retrospect. In this work-in-progress paper, we argue that VR motion tracking data has the potential to provide unobtrusive, yet valid measures of cognitive load. We report preliminary results from a user study that aims at predicting cognitive load using the tracking data of a VR headset and two hand controllers. Using a recurrent neural network, we were able to distinguish between different levels of cognitive load with an accuracy of more than 88 percent. Based on this finding, we reflect on future research directions and practical considerations.

Nutritional diseases severely impair the everyday life of affected patients and represent a growing proportion of global disease burden. The diagnosis and treatment of these diseases is mainly provided by trained dietitians. Their profession requires highly developed conversational skills. Immersive virtual reality offers learning environments, which could hardly be delivered by classical teaching methods. Previous research suggests that virtual reality can be successfully used for social skills training. However, we are not aware of existing virtual reality applications that are directed at conversational skills training for dietitians. Therefore, this work-in-progress paper presents the development of an immersive learning environment for dietetics. We have set out to design a multi-user VR environment that enables the training of professional conversations between patients and dietitians in a virtual hospital room. Testing a sample of 30 students, we will evaluate the usability of the learning environment. Furthermore, we are investigating whether subjective feelings of social presence, and cognitive load predict learning satisfaction and task performance. We expect that multi-user virtual reality enables effective conversational skills trainings for dietetics. Consequently, its implementation could benefit curricula that are typically constrained by limited in-situ training opportunities.