Case-based reasoning for engineering statistics

George Runger, Sarah Brem, Norma Hubele, Toniann Rotante, Kathryn Kennedy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


In this paper, we report on the formulation and early results of research supported by the National Science Foundation's Experimentation and Laboratory-Oriented Studies Division (DELOS). Using findings from cognitive science, we discuss the design of an intelligent tutoring system (ITS) that utilizes case-based reasoning (CBR) to scaffold undergraduate engineering students in their learning of introductory probability and statistics. Such a system will: Assist students in extracting the underlying common structure from engineering statistics problems that illustrate the full range of engineering disciplines. Allow the students to generate, customize, and change a virtually infinite collection of exercises that can be solved with the assistance of the ITS. The students can explore the effect of changes to solutions. Help students formulate and solve "practical" and "open-ended" problems, a skill stressed by the ABET Engineering Criteria.

Original languageEnglish (US)
Title of host publicationASEE Annual Conference Proceedings
Number of pages10
StatePublished - 2003
Event2003 ASEE Annual Conference and Exposition: Staying in Tune with Engineering Education - Nashville, TN, United States
Duration: Jun 22 2003Jun 25 2003


Other2003 ASEE Annual Conference and Exposition: Staying in Tune with Engineering Education
Country/TerritoryUnited States
CityNashville, TN

ASJC Scopus subject areas

  • Engineering(all)


Dive into the research topics of 'Case-based reasoning for engineering statistics'. Together they form a unique fingerprint.

Cite this