Intelligent tutoring systems (ITS) have become increasingly important in light of the concerns that have arisen regarding public education and technical training. The main objective of an ITS is to provide individualized or adaptive instruction. In order to provide this type of instruction, an ITS must have access to information about a student's problem-solving abilities. The system's representation of this information is referred to as the student model, and the process by which this structure is created and maintained is known as student modelling or diagnosis. / The research presented in this dissertation has led to the development of a diagnostic system which functions as the student modelling component of an ITS. This system addresses three key issues which are necessary to guarantee the satisfactory performance of the diagnostic function. These are: (1) how to assign credit or blame to individual skills, (2) how to handle noise in the diagnostic process, and (3) how to handle the problem of combinatorial explosion common to many AI applications. / Furthermore, this system offers a unique approach for modelling a student's performance abilities through the use of three mechanisms. First, an informal reasoning technique is used for determining the performance levels of individual skills in the student model. Another feature is the use of an assumption-based truth maintenance procedure for maintaining consistent information. The third feature is the inclusion of historical information in the diagnostic process. / Source: Dissertation Abstracts International, Volume: 52-06, Section: B, page: 3148. / Major Professor: Lois W. Hawkes. / Thesis (Ph.D.)--The Florida State University, 1991.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_76440 |
| Contributors | Holmes, Dawn Jay., Florida State University |
| Source Sets | Florida State University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | 188 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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