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A B S T R A C TThis study is focused on how peer feedback in SPOCs (Small Private Online Courses) can effectively lead to deep learning. Promoting deep learning in online courses, such as SPOCs, is often a challenge. We aimed for deep learning by reinforcement of 'feedback dialogue' as scalable intervention.Students provided peer feedback as a dialogue, both individually and as a group. They were instructed to rate each other's feedback, which was aimed at deep learning. Data from questionnaires from 41 students of a master epidemiology course were used to measure for each feedback assignment to what extent deep learning was perceived. The feedback received by students who scored extremely high or low on the questionnaire was analyzed in order to find out which features of the feedback led to deep learning. In addition, students were interviewed to retrieve information about the underlying mechanisms.The results support the view that peer feedback instruction and peer feedback rating lead to peer feedback dialogues that, in turn, promote deep learning in SPOCs. The value of peer feedback appears to predominantly result from the dialogue it triggers, rather than the feedback itself. Especially helpful for students is the constant attention to how one provides peer feedback: by instruction, by having to rate feedback and therefore by repeatedly having to reflect. The dialogue is strengthened because students question feedback from peers in contrast to feedback from their instructor. As a result, they continue to think longer and deeper, which enables deep learning.

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A flipped classroom, an approach abandoning traditional lectures and having students come together to apply acquired knowledge, requires students to come to class well prepared. The nature of this preparation is currently being debated. Watching web lectures as a preparation has typically been recommended, but more recently, a variety of study materials has been considered to serve students personal learning preferences. The aim of this study was to explore in two flipped courses which online study materials stimulate students most to prepare for in-class activities, to find out whether students differ in their use of study materials, and to explore how students use of online study materials relates to their learning strategies. In a basic science and a clinical course, medical students were provided with web lectures, text selections, scientific papers, books, and formative test questions or case studies. Use of these online materials was determined with questionnaires. All students watched web lectures and read text selections to prepare for in-class activities, but students differed in the extent to which they used more challenging materials. Additionally, the use of online study materials was related to students' learning strategies that involved regulation and monitoring of study effort. Our findings suggest that students have similar learning preferences as they all use the same "basic materials" to prepare for in-class activities. We interpret the preferential use of web lectures and text selections as being regarded as sufficient for active in-class participation. The less intensive use of other study materials may reflect students' perception of limited study time.

Several researchers have suggested the importance of being responsive to students' needs in research supervision. Adapting support strategies to students' needs in light of the goals of a task is referred to as adaptivity. In the present study, the practice of adaptivity is explored by interviewing expert thesis supervisors about diagnosing student characteristics in order to determine students' needs and concurrent adaptive support strategies. The findings suggest that next to competence, supervisors also diagnose elements of students' determination and context. With respect to support strategies, it is suggested that supervisors adapt to student needs in terms of explicating standards, quality or consequences, division of responsibilities, providing more/less critical feedback and sympathising. The complexity of the relationship between diagnosing student characteristics and adapting support strategies is illustrated and needs further study.