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Several studies have shown that complex nonlinear learning analytics (LA) techniques outperform the traditional ones. However, the actual integration of these techniques in automatic LA systems remains rare because they are generally presumed to be opaque. At the same time, the current reviews on LA in higher education point out that LA should be more grounded to the learning science with actual linkage to teachers and pedagogical planning. In this study, we aim to address these two challenges. First, we discuss different techniques that open up the decision-making process of complex techniques and how they can be integrated in LA tools. More precisely, we present various global and local explainable techniques with an example of an automatic LA process that provides information about different resources that can support student agency in higher education institutes. Second, we exemplify these techniques and the LA process through recently collected student agency data in four courses of the same content taught by four different teachers. Altogether, we demonstrate how this process-which we call explainable student agency analytics-can contribute to teachers' pedagogical planning through the LA cycle.

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In this paper, we use student agency analytics to examine how university students who assessed to have low agency resources describe their study experiences. Students (n = 292) completed the Agency of University Students (AUS) questionnaire. Furthermore, they reported what kinds of restrictions they experienced during the university course they attended. Four different agency profiles were identified using robust clustering. We then conducted a thematic analysis of the open-ended answers of students who assessed to have low agency resources. Issues relating to competence beliefs, self-efficacy, student-teacher relations, time as a resource, student well-being, and course contents seemed to be restrictive factors among the students in the low agency profile. The results could provide guidelines for designing systems for smart education.

Lay DescriptionWhat is currently known about the subject matter The advantages of VR training systems are clear in the safety‐critical fields. Cognitive load (CL) theory may help design of VR training. CL management is part of the professional competence in these fields. What this paper adds The pilots performed well in CL management in VR flight training. The work experience of the pilot was not associated with the performance. The physiological data improved the explanatory level of the performance. The implications of study findings for practitioners Pilots need time to get used to the immersive learning environment. Typical 1–2‐hour intensive VR flight training is not too demanding. The physiological data could complement CL management assessment.

Making in education is an emergent practice focusing on learners as creators of things in a collaborative fashion while promoting knowledge construction through technology, design, and creative selfexpression. Teachers' (n = 33) opinions about making were studied using an online questionnaire after they had attended an online course for professional development about making in education. The results suggest that there exists a group of educators who consider making as a promising approach in education and want to promote its use in schools.