Abstract. Although videos are a highly popular digital medium for learning, video watching can be a passive activity and results in limited learning. This calls for interactive means to support engagement and active video watching. However, there is limited insight into what engagement challenges have to be overcome and what intelligent features are needed. This paper presents an empirical way to elicit requirements for innovative functionality to support constructive video-based learning. We present two user studies with an active video watching system instantiated for soft skill learning (pitch presentations). Based on the studies, we identify whether learning is happening and what kind of interaction contributes to learning, what difficulties participants face and how these can be overcome with additional intelligent support. Our findings show that participants who engaged in constructive learning have improved their conceptual understanding of presentation skills, while those who exhibited more passive ways of learning have not improved as much as constructive learners. Analysis of participants' profiles and experiences led to requirements for intelligent support with active video watching. Based on this, we propose intelligent nudging in the form of signposting and prompts to further promote constructive learning.

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Abstract. There is sufficient evidence to show that allowing students to see their own student model is an effective learning and metacognitive strategy. Different tutors have different representations of these open student models, all varying in complexity and detail. EER-Tutor has a number of open student model representations available to the student at any particular time. These include skill meters, kiviat graphs, tag clouds, concept hierarchies, concept lists, and treemaps. Finding out which representation best helps the student at their level of expertise is a difficult task. Do they really understand the representation they are looking at? This paper looks at a novel way of using eye gaze tracking data to see if such data provides us with any clues as to how students use these representations and if they understand them.

We present a computer-based environment for rehabilitation of prospective memory in stroke survivors. Prospective memory (PM), or remembering to perform actions in the future, is of crucial importance for everyday life. This kind of memory is often impaired in stroke survivors and can interfere with independent living. Fifteen participants were recruited to participate in our study consisting of 10 sessions. The participants were first trained on how to develop visual images in order to remember time-and event-based prospective memory tasks. After the visual imagery training, participants practiced their PM skills using videos, and later in a virtual reality (VR) environment. The results show a significant improvement on PM skills as measured by the CAMPROMPT test, which remained stable 4 weeks after the treatment. VR-based training was well accepted by the participants.

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