Abstract
The ongoing EU project JuxtaLearn aims at facilitating the acquisition of science concepts through the creation and sharing of videos on the part of the learners. For several domains of learning threshold concepts have been specified as key elements of target knowledge. Content analysis techniques are used to extract learners’ concepts manifested in textual artifacts and to contrast these with the anticipated domain concepts (represented as an ontology). Deviations between student concepts and the ontology can indicate problems of understanding and possibly misconceptions. Two studies explore the potential of (semi-) automated analysis of textual artifacts to identify and characterize the students’ comprehension problems around knowledge artifacts. In the first study, protocols from a “flipped classroom” style teacher–student workshop are analyzed. The second study analyses comments to videos from educational video platforms. The “network text analysis” approach was used as a basis for both studies. As an extension of this approach, we have introduced “signal concepts” and their relations to domain concepts as indicators of potential information needs and problems of understanding.
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