The Journal of Engineering Education (JEE) published our review on interdisciplinarity in engineering education. It is available open access https://bit.ly/cee_review.
Societal challenges that call for a new type of engineer suggest the need for the implementation of interdisciplinary engineering education (IEE). The aim of IEE is to train engineering students to bring together expertise from different disciplines in a single context. This review synthesizes IEE research with a focus on characterizing vision, teaching practices, and support.
We aim to show how IEE is conceptualized, implemented, and facilitated in higher engineering education at the levels of curricula and courses. This aim leads to two research questions:
What aspects of vision, teaching, and support have emerged as topics of interest in empirical studies of IEE?
What points of attention regarding vision, teaching, and support can be identified in empirical studies of IEE as supporting or challenging IEE?
Ninety‐nine studies published between 2005 and 2016 were included in a qualitative analysis across studies. The procedure included formulation of research questions, searching and screening of studies according to inclusion/exclusion criteria, description of study characteristics, appraisal, and synthesis of results.
Challenges exist for identifying clear learning goals and assessments for interdisciplinary education in engineering (vision). Most pedagogy for interdisciplinary learning is designed to promote collaborative teamwork requiring organization and team management. Our review suggests that developing interdisciplinary skills, knowledge, and values needs sound pedagogy and teaming experiences that provide students with authentic ways of engaging in interdisciplinary practice (teaching). Furthermore, there is a limited understanding of what resources hinder the development of engineering programs designed to support interdisciplinarity (support).
Finally our review study on social media in the classroom is available open access via bit.ly/revsocmed. Also the teacher companion (in Dutch) can be downloaded via bit.ly/boeksocmed.
The importance of social media for today’s youth often elicits teachers to explore educational use of these media. However, many teachers appear to struggle with the tension between possible pedagogical use and the tempting distraction of this technology. The current literature review aims to present a synthesis of conditions and outcomes relevant for a well-considered, evidence-based use of social media, and teacher professional development. A conceptual model consisting of intended curriculum (school level), implemented curriculum (teacher level) and attained curriculum (student level) guided the research questions. The review included 271 articles, which were analysed with framework synthesis. Ambiguous results and poor quality of studies often hindered clear statements about conditions and outcomes regarding social media in the classroom. Nonetheless, reported factors include school culture, attitude towards social media, support, teacher professional development, learning goals and a clear position in the curriculum. Considerations and advice for educational practice were formulated.
The International Review of Research in Open and Distributed Learning just published our article in which we combined Process Mining techniques and Clustering to analyse learning behaviour in MOOCs.
The increasing use of digital systems to support learning leads to a growth in data regarding both learning processes and related contexts. Learning Analytics offers critical insights from these data, through an innovative combination of tools and techniques. In this paper, we explore students’ activities in a MOOC from the perspective of personal constructivism, which we operationalized as a combination of learning behaviour and learning progress. This study considers students’ data analyzed as per the MOOC Process Mining: Data Science in Action. We explore the relation between learning behaviour and learning progress in MOOCs, with the purpose to gain insight into how passing and failing students distribute their activities differently along the course weeks, rather than predict students’ grades from their activities. Commonly-studied aggregated counts of activities, specific course item counts, and order of activities were examined with cluster analyses, means analyses, and process mining techniques. We found four meaningful clusters of students, each representing specific behaviour ranging from only starting to fully completing the course. Process mining techniques show that successful students exhibit a more steady learning behaviour. However, this behaviour is much more related to actually watching videos than to the timing of activities. The results offer guidance for teachers.
Van den Beemt, A., Buijs, J., & Van der Aalst, W. (2018). Analysing Structured Learning Behaviour in Massive Open Online Courses (MOOCs): An Approach Based on Process Mining and Clustering. The International Review of Research in Open and Distributed Learning, 19(5). DOI dx.doi.org/10.19173/irrodl.v19i5.3748 (Open Access)