Analyzing Learner Affect in a Scenario-Based Intelligent Tutoring System
نویسندگان
چکیده
Scenario-based tutoring systems influence affective states due to two distinct mechanisms during learning: 1) reactions to performance feedback and 2) responses to the scenario context or events. To explore the role of affect and engagement, a scenario-based ITS was instrumented to support unobtrusive facial affect detection. Results from a sample of university students showed relatively few traditional academic affective states such as confusion or frustration, even at decision points and after poor performance (e.g., incorrect responses). This may show evidence of “over-flow,” with a high level of engagement and interest but insufficient confusion/disequilibrium for optimal learning.
منابع مشابه
Analyzing Learner Language: Towards A Flexible NLP Architecture for Intelligent Language Tutors
Intelligent Language Tutoring Systems (ILTS) typically focus on analyzing learner input to diagnose learner errors and provide individualized feedback. Despite a long history of ILTS research (cf. Heift & Schulze, 2007), such systems are virtually absent from real-life foreign language teaching (FLT). Arguably, one reason for this state of affairs is that FLT activity design and its impact on t...
متن کاملFacial Expression Analysis for Estimating Learner?s Emotional State in Intelligent Tutoring Systems
Intelligent tutoring systems (ITS) provide individualized instruction. They offer many advantages over the traditional classroom scenario: they are always available, non-judgmental and provide tailored feedback resulting in increased and effective learning. However, they are still not as effective as one-on-one human tutoring. The next generation of intelligent tutors is expected to be able to ...
متن کاملIntegrating Learner Help Requests Using a POMDP in an Adaptive Training System
This paper describes the development and empirical testing of an intelligent tutoring system (ITS) with two emerging methodologies: (1) a partially observable Markov decision process (POMDP) for representing the learner model and (2) inquiry modeling, which informs the learner model with questions learners ask during instruction. POMDPs have been successfully applied to non-ITS domains but, unt...
متن کاملPedagogically-Driven Courseware Content Generation for Intelligent Tutoring Systems
This paper describes a novel approach to adaptive courseware generation. This approach adopts its structure from existing intelligent tutoring systems and introduces a new component called pedagogical scenario model to support pedagogical flexibility in the adaptation process of courseware generation system. The adaptation is carried out using Dynamic Constraint Satisfaction Problem framework, ...
متن کاملAutomated Scenario Adaptation in Support of Intelligent Tutoring Systems
Learners may develop expertise by experiencing numerous different but relevant situations. Computer games and virtual simulations can facilitate these training opportunities, however, because of the relative difficulty in authoring new scenarios, the increasing need for new and different scenarios becomes a bottleneck in the learning process. Furthermore, a one-size-fits-all scenario may not ad...
متن کامل