Using Datalog to provide just-in-time feedback during the construction of concept maps

Concept maps have been extensively used in education, especially in science teaching. There is strong evidence that their use is associated with increased knowledge transfer and retention across several instructional conditions, settings and methodological features. However, constructing a concept map is complex and difficult for students, especially newbies. Consequently, there is a necessity to provide feedback to the learners during the authoring of their concept maps. There are several concept-mapping tools that provide feedback but none of them provide immediate or just-in-time (JIT) feedback. This kind of feedback is important for two reasons: First, low achieving or low mastery students benefit greatly from this type of feedback. Second, when students start out badly, with incorrect propositions, they tend to continue with further incorrect propositions until the map is grossly incorrect and JIT feedback could prevent this situation. This paper presents a practical application of Ohlsson's theory of learning from performance errors to provide JIT feedback during the construction of concept maps. It is shown that by creating an Entity-Relationship (E-R) schema that incorporates additional elements into the standard schema for concept maps, the schema can be implemented with Datalog, benefiting from the use of its deductive features to provide immediate feedback to the learner. Finally, some field related examples are provided.