Managing Knowledge Diversity in Computer-Supported Inquiry-Based Science Education

Abstract

The research area of Technology Enhanced Learning brings together the disciplines of learning sciences, pedagogy, and computer science in order to provide mechanisms and (digital) tools to support learning and teaching. The Go-Lab project aims to promote inquiry-based science education using online laboratories. It serves as a toolbox for teachers to create customized learning spaces for scientific experiments that includes a variety of applications that support the inquiry and knowledge construction processes. Research in the learning sciences has found group learning to be supportive for knowledge (co-) construction in inquiry-based learning. Particularly for group learning approaches, the terms heterogeneity and homogeneity have been stretched out in research and practice. It may be considered as common sense that heterogeneous learning groups have the highest knowledge gain. This leads to problematic policies: First, weaker learners benefit from the skills of the better performing students. Consequently, a heterogeneous grouping is almost only helpful for the weaker learners. Second, a stigmatization of weak learners leads to a less inclusive and unbalanced approach in learning and teaching. Moreover, stigmatizing learners prevents finding the reasons for the problems the learners are facing. Aronson (1978) developed the Jigsaw teaching technique to create a more inclusive learning situation, but with the goal criterion to deal with challenges of mixing ethnicities in the classroom due to the desegregation of public schools in the USA in the late 1950s. However, the formation of groups for Jigsaw relied on creating experts that have a distinct knowledge in a certain field. Managing and facilitating knowledge diversity and complementarity seems to be the key in order to create classrooms that are more inclusive. The work presented in this dissertation aims to create and convey methods that support learning and teaching in inquiry-based science education. Compared to traditional approaches, a more inclusive learning situation can be created by managing learners’ knowledge diversity. In order to create such support tools, computational methods and architectures from the field of learning analytics have been employed to create a technical infrastructure in Go-Lab. Using this learning analytics architecture, an analysis of the first two years of teachers and students using Go-Lab has been conducted. This analysis posed challenges and requirements for the design of support tools, which have to be integrated into the Go-Lab ecosystem. Based on this technical infrastructure, a general approach to support individual and group learning by facilitating knowledge complementarity has been developed and presented in this work. This framework uses automatic semantic extraction of concepts from learner-generated content to create a shared group knowledge model. Two Applications, which facilitate knowledge diversity and complementarity using this approach have been developed and presented. The “concept cloud app” serves as a cognitive scaffold that interactively visualizes the group knowledge as an open learner model. It uses semantic extraction of concepts from learning artifacts in order to create the model. Furthermore, the “semantic group formation” creates and uses such a shared group knowledge model to form groups with an optimal knowledge complementarity. Several empirical studies have been conducted in schools using Go-Lab and the support tools as a part of this work. As a first study, traditional approaches to form heterogeneous and homogeneous groups based on an operationalization of skills have been explored in the context of IBL. It turned out that, similar to other contexts, heterogeneous groups perform better with respect to the group result and the average learning gain. The subsequent studies have been used to explore the opportunities of knowledge-based approaches. In a second experiment, the concept cloud app has been presented to learners. The results have shown that this app is an effective cognitive scaffold, which supports the knowledge construction in conjunction with other production tools such as concept mapping. The final study aimed to evaluate the semantic group formation. In addition to the formation, the model and the results of the group formation have been presented to learners as a cognitive group awareness tool. The results indicate that the semantic group formation creates groups with a high knowledge diversity and a relatively even distribution of scores across the groups. Finally, the presentation of knowledge complementarity as a group awareness tool supports learners in structuring their collaboration and the communication when exchanging knowledge.