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Digital Formative Assessment


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.



When learning in a digital learning environment, learning analytics approaches offer many opportunities to take a differentiated look at learning states and learner performance based on multimodal data in addition to more traditional behavioral psychometric methods (e.g. Di Mitri et al., 2018). In the DiFA project, methodical perspectives from the fields of psychometrics and learning analytics are combined in order to support learners with automated feedback.



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 profile

Project partners
DIPF Leibniz-Institut für Bildungsforschung und Bildungsinformation
Goethe Universität Frankfurt a. Main
Project partners
DIPF Leibniz-Institut für Bildungsforschung und Bildungsinformation
Goethe Universität Frankfurt a. Main