A Multi-dimensional Taxonomy for Automating Hinting

A Framework of Deriving Adaptive Feedback from Educational Ontologies

“…We adopt the learner answer categorization schema proposed in [6], and try to classify responses into these classes. However, for some forms of items, e.g., true/false, if a user submits a wrong answer, this answer does not belongs to any class.…”

“…[3], [6], the adaptive is usually represented by the idea of gradual provision of appropriate information. This approach needs special computing structures to model learners, and classifies users' responses into several categories to produce feedback.…”

Resource-Bounded Modelling and Analysis of Human-Level Interactive Proofs

“…However, in close collaboration with our project, Tsovaltzi and Fiedler have studied hint taxonomies [41,42] and dialogue-adaptive hinting [18].…”

“…Thus, the proof tutor system cannot restrict itself to a repertoire of static hints, associating a student answer with a particular response by the system. [42] defines a multi-dimensional hint taxonomy where each dimension defines a decision point for the associated cognitive function. The domain knowledge can be structured and manipulated for tutoring decision purposes and generation considerations within a tutorial manager.…”

“…The hint taxonomy [42] was derived with regard to the underlying function of a hint that can be common for different NL realisations. This function is mainly responsible for the educational effect of hints.…”