A priori evaluation & refinement of curricula by data mining over storyboards

In university studies, there is a flexible but complicated learning system of subject offers, enrollment rules for particular subject combinations, and prerequisites to meet for taking particular subjects, which need to be matched with students' needs and desires. Students need assistance in the jungle of such learning opportunities and limitations at today's universities. To face this problem, we employed our formerly developed storyboard concept and used it to develop, maintain, and evaluate curricula. Storyboarding is based on the idea of formally representing, processing, evaluating and refining didactic knowledge. This concept is utilized to supplement an educational system called Dynamic Learning Needs Reflection System (DLNRS) of the School of Information Environment of Tokyo Denki University, Japan. Didactic knowledge of DLNRS can be represented by storyboarding and used for supporting dynamic learning activities of students. Here, we introduce an additional benefit of storyboarding. By using data mining-like methods to evaluate storyboard paths, we are able to estimate success chances of storyboard paths. Based on this evaluation we will be able to rate planned (future) paths and thus, to prevent students from failing by non-appropriate curricula. Moreover, besides the evaluation, the estimation can be used for computer enforced suggestions to complete a path towards optimal success chances

Using storyboarding and data mining to estimate success chances of curricula

In university studies, there is a flexible but complicated learning system of subject offers, enrollment rules for particular subject combinations, and prerequisites to meet for taking particular subjects, which need to be matched with students' needs and desires. Students need assistance in the jungle of such learning opportunities and limitations at today's universities. To face this problem, we employed our formerly developed storyboard concept and used it to develop, maintain, and evaluate curricula. Storyboarding is based on the idea of formally representing, processing, evaluating and refining didactic knowledge. This concept is utilized to supplement an educational system called Dynamic Learning Needs Reflection System (DLNRS) of the School of Information Environment of Tokyo Denki University, Japan. Concretely speaking, didactic knowledge of DLNRS can be represented by storyboarding and used for supporting dynamic learning activities of students. Here, we introduce an additional benefit of the storyboard concept. By using data mining - like methods to evaluate storyboard paths, we are able to estimate success chances of storyboard paths. Based on such an evaluation we will be able to rate planned (future) paths and thus, to prevent students from failing by non-appropriate curricula. Moreover, besides the evaluation, the estimation can be used for computer enforced suggestions to complete a path towards optimal success chances

Applying knowledge engineering methods to didactic knowledge: first steps towards an ultimate goal

Generally, learning systems suffer from a lack of an explicit and adaptable didactic design. Since E-Learning systems are digital by their very nature, their introduction rises the issue of modeling the didactic design in a way that implies the chance to apply Knowledge Engineering Techniques (like Machine Learning and Data Mining). A modeling approach called storyboarding, is outlined here. Storyboarding is setting the stage to apply Knowledge Engineering Technologies to verify and validate the didactics behind a learning process. Moreover, didactics can be refined according to revealed weaknesses and proven excellence and successful didactic patterns can be inductively inferred by analyzing the particular knowledge processing and its alleged contribution to learning success

Theorizing teaching: current status and open issues

Presents practical implications for teaching and educating teachers. Examines systematically the issue of theorizing teaching. Enables collective thinking about issues that are of paramount importance in the field. This book is open access, which means that you have free and unlimited access

Design revolutions: IASDR 2019 Conference Proceedings. Volume 4: Learning, Technology, Thinking

In September 2019 Manchester School of Art at Manchester Metropolitan University was honoured to host the bi-annual conference of the International Association of Societies of Design Research (IASDR) under the unifying theme of DESIGN REVOLUTIONS. This was the first time the conference had been held in the UK. Through key research themes across nine conference tracks – Change, Learning, Living, Making, People, Technology, Thinking, Value and Voices – the conference opened up compelling, meaningful and radical dialogue of the role of design in addressing societal and organisational challenges. This Volume 4 includes papers from Learning, Technology and Thinking tracks of the conference

By hand and by computer – a video-ethnographic study of engineering students’ representational practices in a design project

In engineering education there has been a growing interest that the curriculum should include collaborative design projects. However, students’ collaborative learning processes in design projects have, with a few exceptions, not been studied in earlier research. Most previous studies have been performed in artificial settings with individual students using verbal protocol analysis or through interviews.  The context of this study is a design project in the fifth semester of the PBL-based Architecture and Design programme at Aalborg University. The students had the task to design a real office building in collaborative groups of 5–6 students. The preparation for an upcoming status seminar was video recorded in situ. Video ethnography, conversation analysis and embodied interaction analysis were used to explore what interactional work the student teams did and what kind of resources they used to collaborate and complete the design task. Complete six hours sessions of five groups were recorded using multiple video cameras (2 – 5 cameras per group). The different collaborative groups did not only produce and reach an agreement on a design proposal during the session – in their design practice they used, and produced, a wealth of tools and bodily-material resources for representational and modelling purposes. As an integral and seamless part of students’ interactional and representational work and the group’s collaborative thinking bodily resources such as “gestured drawings” and gestures, concrete materials such as 3D-foam and papers models, “low-tech” representations such as sketches and drawings by hand on paper and “high-tech” representations as CAD-drawings were used. These findings highlight the cognitive importance of tools and the use of bodily and material resources in students’ collaborative interactional work in a design setting. Furthermore, our study demonstrates that a focus primarily on digital technologies, as is often the case in the recent drive towards “digital learning”, would be highly problematic