Key points are not available for this paper at this time.
Affective computing techniques have become increasingly important as advanced education technologies. By applying these techniques to education, this work designs and evaluates a novel Affective Tutoring System for the Digital Arts (ATSDAs). By semantically analysing a text with ontological references, the emotions induced by a text when input by a user are identified. Inference of emotions is accomplished using OMCSNet and WordNet, two engines commonly used in computational linguistics research. The proposed system has a visual agent that provides text feedback based on inferred emotions from textual analysis. The proposed system has a conscientious design flow that includes concept modelling, prototype design, expert-based evaluation (which consists of a cognitive walkthrough and heuristic evaluation), final system design and a series of evaluations from a learner's perspective. The System Usability Scale (SUS) evaluation results show that this system achieves positive usability and learners enjoy interacting with the proposed system.
Lin et al. (Thu,) studied this question.