Objective
In the DiFA project, methodological perspectives from the fields of psychometrics and learning analytics will be combined to support learners through automated feedback. By using digital trace data in online courses, DiFA will develop new forms of non-invasive measurement (so-called "stealth assessment") and investigate the possibilities of automated feedback that supports learning. The results of this research are highly relevant for a better understanding of learning behavior and outcomes, as well as for the automated provision of individualized feedback to learners in digital environments.
Approach and Methods
In order to be able to collect and evaluate the above mentioned trace data in a real learning situation, the DiFA project will develop an online course on "Digital Education" for student teachers, which will be available as an Open Educational Resource after the end of the project. On the basis oft he data thus obtained, automated learning support feedback will be developed in the course of the project. In the second phase of the project, it will be verified whether this feedback has a positive effect on the learning progress of the students.
1) Pilot Phase
In the pilot phase, indicators about learning behavior will be formed from trace data generated in the online course and validated using standardized psychometric measurement procedures. Trace data can be understood as a digital footprint. For example, time management can be a useful indicator of engagement in learning, or learning progression (e.g., the coherence of selected texts or learning steps) an indicator of self-regulation. Thus, the indicators aim to capture learners' skills and characteristics that are relevant in the use of digital learning environments in higher education. To this end, the pedagogical concept and the design of the interactive learning environment of the online course must be closely coordinated. This will set the stage for gaining meaningful indicators about learning behavior.
2) Evaluation Phase
In the evaluation phase, a second cohort of students will go through the online course. One half of this cohort will receive automated learning support feedback on their own learning behavior based on the validated behavioral indicators. The other half will serve as a control group. A pre-post measurement on the learning objectives of the course will be used to verify whether the feedback has a positive impact on the students' learning progress.
Project Duration
April 2020 -– June 2024
Funding source
DiFA is funded as a third-party funded project under the Leibniz 2020 competition.
Projektpartner
Prof. Dr. Hendrik Drachsler, Prof. Dr. Frank Goldhammer (DIPF | Leibniz Institute for Research and Information in Education)
Prof. Dr. Cordula Artelt (LIfBi)
Prof. Dr. Holger Horz (Goethe University Frankfurt a. M.)
Projektleitung am LIfBi
Prof. Dr. Cordula Artelt
Prof. Dr. Ilka Wolter