Generalizing the Genres for ITS: Authoring Considerations for Representative Learning Tasks
Abstract
Compared to many other learning technologies, intelligent tutoring systems (ITSs) have a distinct challenge: authoring an adaptive inner loop that provides pedagogical support on one or more learning tasks. This coupling of tutoring behavior to student interaction with a learning task means that authoring tools need to reflect both the learning task and the ITS pedagogy. To explore this issue, common learning activities in intelligent tutoring need to be categorized and analyzed for the information that is required to tutor each task. The types of learning activities considered cover a large range: step-by-step problem solving, bug repair, building generative functions (e.g., computer code), structured argumentation, self-reflection, short question answering, essay writing, classification, semantic matching, representation mapping (e.g., graph to equation), concept map revision, choice scenarios, simulated process scenarios, motor skills practice, collaborative discussion, collaborative design, and team coordination tasks. These different tasks imply a need for different authoring tools and processes used to create tutoring systems for each task. In this chapter, we consider three facets of authoring: 1) the minimum information required to create the task, 2) the minimum information needed to implement common pedagogical strategies, 3) the expertise required for each type of information. The goal of this analysis is to present a roadmap of effective practices in authoring tool interfaces for each tutoring task considered.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2015
- Accession Number
- AD1170980
Entities
People
- Benjamin D Nye
- Benjamin M. Goldberg
- Xiangen Hu
Organizations
- University of Southern California