Modelling and Maintenance of log Data – the Example of a Multimedia Textbook

Project Description

In this project, we look at a multimedia history book for lower secondary schools (a so-called mBook) to investigate how the concrete use of a multimedia textbook in both institutional and home learning environments, which can be described by log data, can explain individual developments of competence. Added value of a co-operation between histtorical didactics, empirical educational research and computer science consists in analysing user data, i.e. log data from the use of the mBook, by means of complex statistical procedures from Machine Learning, making statements on probable user conduct, establishing a correlation between usage and achievement in learning and thus optimising the service regarding its usability and enhancement of competencies. Hence, the project will deliver an innovative contribution to investigating in how far multimedia textbooks – perhaps depending on student characteristics – might foster a competence-oriented learning of students.

Objectives

Subject to the DIPF 2015 proposal for the mBook project, we aim to pursue four objectives:

• We aim to conduct preliminary work to submitting a proposal to the German Research Foundation (DFG) or Federal Ministry of Education and Research (BMBF), together with our co-operation partners, Catholic University Eichstätt and Tübingen University.
• The developed modelling procedures from Machine Learning shall be applicable in the context of learner-oriented process data.
• Co-operations of the research and development units and groups involved at DIPF will be intensified.
• The mBook infrastructure will be located at DIPF, to collect experience in the use of new types of data (log data) and their indexing for educational research.

Prospectively, experience gained from the project will enable an assessment of whether log data can be integrated into the research data centre for education (FDZ Bildung). In this regard, DIPF would add another national and international “unique selling point“ in the research data landscape to its profile.

Project Team

Project Details