Defining the Ill-Defined: From Abstract Principles to Applied Pedagogy
Abstract
Attempts to define ill-defined domains in intelligent tutoring system (ITS) research has been approached a number of times (Fournier-Viger, Nkambou, and Nguifo, 2010; Lynch, Ashley, Pinkwart, and Aleven, 2009; Mitrovic and Weerasinghe, 2009; Jacovina, Snow, Dai, and McNamara, 2015; Woods, Stensrud, Wray, Haley, and Jones, 2015). Related research has tried to determine levels of ill-definedness for a domain (Le, Loll, and Pinkwart, 2013). Despite such attempts, the field has not yet converged on common guidelines to distinguish between well-defined versus ill-defined domains. We argue that such guidelines struggle to converge because a domain is too large to meaningfully categorize: every domain contains a mixture of well-defined and ill-defined tasks. While the co-existence of well-defined and ill-defined tasks in a single domain is nearly universally-agreed upon by researchers; this key point is often quickly buried by an extensive discussion about what makes certain domain tasks ill-defined (e.g., disagreement about ideal solutions, multiple solution paths).
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2016
- Accession Number
- AD1158376
Entities
People
- Benjamin D Nye
- Michael W. Boyce
- Robert Sottilare
Organizations
- Oak Ridge Associated Universities
- United States Army Research Laboratory
- University of Southern California