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From a human-centred computing perspective, supporting the interpretation of educational dashboards and visualizations by the people intended to use them exposes critical design challenges that may often be trivialized. Empirical evidence already shows that "usable" visualizations are not necessarily effective from an educational perspective. Since an educator's interpretation of visualized data is essentially the construction of a narrative about student progress, in this paper, we propose the concept of "Educational Data Storytelling" as an approach for explaining student data by aligning educational visualizations with the intended learning design. We present a pilot study that explores the effectiveness of these data storytelling elements based on educator responses to prototypes by analyzing the kinds of stories they articulate, their eye-tracking behaviour, and their preferences after inspecting a series of student data visualizations. The dual purpose is to understand the contribution of each visual element for data storytelling, as well as the effectiveness of the enhancements when combined. 1 Notes for Practice  The learning analytics field, to effectively support teaching and learning visually, needs to move on from visual analytics that invite users to explore the data, to visualizations that explain insights.  In this paper, we propose the concept of "Educational Data Storytelling" as an approach to designing visual learning analytics interfaces that explain student data by aligning educational visualizations with the learning design intended by the teacher.  We see the potential of learning-design-driven data storytelling elements to support sensemaking by guiding students and teachers to "one learning story per visualization," given that learning is a complex task.

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The present study describes a proposed multitabletop system for supporting collaborative database design activities in the classroom. Additionally, two experiments were conducted to evaluate students' and teachers' perceptions of the proposed system potential on aspects of group work assessment such as: ease of grading individuals as well as groups; equality of students' participation; and, capability to accurately reflect individual contributions. Ten educators and 22 students from a Computer Science program participated in the experiments. The findings of this work show that the use of the proposed system impacted positively on the educators' perception about the ease of grading individuals and groups. In addition, distinguishing users in collaborative group work is key for decreasing social-loafing. The results suggest that the proposed system does have potential to support a better group work assessment.

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