Abstract

Business students taking data mining classes are often introduced to artificial neural networks (ANN) through point and click navigation exercises in application software. Even if correct outcomes are obtained, students frequently do not obtain a thorough understanding of ANN processes. This spreadsheet model was created to illuminate the roles of the following ANN parameters: weights, learning rates, threshold functions, and transformation functions. The spreadsheet ANN model project is given early in the semester, just after ANN is introduced. Students can see effects of ANN parameters as they make changes to spreadsheet model inputs, greatly enhancing discussion of ANN processes. After working with the spreadsheet model, students have expressed an appreciation for decisions based on patterns of historic data, and they like the ability to peek "behind the curtain" at processes of predictive software packages.

Citation

Rienzo, T.F. & Athappilly, K.K. (2012). Introducing Artificial Neural Networks through a Spreadsheet Model. Decision Sciences Journal of Innovative Education, 10(4), 515-520. Retrieved August 16, 2024 from https://www.learntechlib.org/p/157666/.

This record was imported from ERIC on November 3, 2015. [Original Record]

ERIC is sponsored by the Institute of Education Sciences (IES) of the U.S. Department of Education.

Copyright for this record is held by the content creator. For more details see ERIC's copyright policy.

Keywords

• artificial intelligence
• College Students
• Computer Networks
• Courseware
• Educational Practices
• Educational Strategies
• Information Processing
• Navigation (Information Systems)
• Spreadsheets
• teaching methods
• Teaching Models
• Technological Literacy