Guided discovery learning

Draft

Definitions

• “Students discover knowledge without guidance, developing their own understanding. The role of instruction is merely to provide a suitable environment, which in software might be a microworld or simulation. Discovery learning, or instructionless learning, involves hypothesis formulation and testing (Goodyear et al. 1991, Shrager and Klahr 1986).” (Stephen Bostock), retrieved, 17:17, 15 September 2006 (MEST).

Features of discovery learning

Guided discovery was developed by Dr. Charles E. Wales at the Center for Guided Design, West Virginia University (Leutner, 1993). Discovery learning is much older and other forms of structuredness have have existed ...

“Guided Discovery, is characterized by convergent thinking. The instructor devises a series of statements or questions that guide the learner, step by logical step, making a series of discoveries that leads to a single predetermined goal. In other words the instructor initiates a stimulus and the learner reacts by engaging in active inquiry thereby discovering the appropriate response. Mosston (1972:117) specifies ten cognitive operations that might take place as the learner engages in active inquiry: recognizing da analysing, synthesizing, comparing and contrasting, drawing conclusions, hypothesizing memorizing, inquiring, inventing, and discovering. By actively doing and consequence discovering facts or concepts, the learner will understand and therefore remember the subject matter. Mosston (1972:122) cautions that "discovery learning cannot take place if t answers are given." He also points out certain drawbacks of this teaching method: it precisely controls and manipulates learning behaviour and could therefore be abused, and is designed for individual rather than group use.” - The Discovery LearningConcept, retrieved, 17:17, 15 September 2006 (MEST)

An example in vocational training

According to Allen (2002), in an example of discovery learning in action, DaimlerChrysler uses guided discovery learning principles for teaching maintenance engineers to troubleshoot automotive electrical systems. Below we summarize its most salient features described in this article.

Determining the source of faults is a very complex task. Maintenance engineers must use diagnostic aids and equipment together with a carefully thought-out strategy to pinpoint and solve the problem. Since workers cannot remember the configurations in all the vehicles, training cannot anymore be specific to any one system. Training focus must be on strategic thinking as well as specific facts, procedures, and concepts. Training must build flexible skills and adaptive thinking to allow for situation-to-situation variations in task sequencing. Therefore the learning systems empowers maintenance engineers to:

• Plot their own course of problem-solving;
• Perform simulated tests on circuits, with simulated diagnostic equipment used to report accurate measures;
• Access reference information;
• Order repairs and test results;
• Proceed with repairs of vehicles returned by customers who have complaints about prior service; and
• Get feedback on efficiency (completion time and completion costs of the job), incorrect assumptions and decisions, and how to approach diagnosis more effectively.

The risk-and-contingent outcome for the DaimlerChrysler discovery learning application gives the exercises a game-like quality. Learners are motivated to try the exercises repeatedly, in order to improve their performance scores. The full simulation makes the learning task realistic, and supports the transfer of learning to real, on-the-job performance.

Links

• [http://snow.utoronto.ca/best/special/discovery/toc.html The Discovery Gallery

Royal Ontario Museum]

• Discovery Learning (1997), Center for positive practices. A larger commented bibliography.

References

• Allen, Michael (2002), Discovery Learning: Repurposing An Old Paradigm, LTI Newsline, HTML, retrieved, 17:17, 15 September 2006 (MEST).

• de Jong, T. & van Joolingen, W. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68(2):179-201, 1998.

• Faryniarz, J. V., & Lockwood, L. G. (1992). Effectiveness of microcomputer simulations in stimulating environmental problem solving by community college students. Journal of Research in Science Teaching, 29(5), 453-470. Abstract and PDF (Access restricted).

• Gokhale, Anu A. (1996), Effectiveness of Computer Simulation for Enhancing Higher Order Thinking, Journal of Industrial Teacher Education, Volume 33, Number 4. HTML.

• Goodyear, P., Njoo, M, Hijne, H & van Berkum, J.J.A. 1991. Learning processes, learner attributes and simulations. Education and Computing (6) 263-304.

• Leutner, Detlev, (1993), Guided Discovery Learning with Computer-Based Simulation Games: Effects of Adaptive and Non-Adaptive Instructional Support, Learning and Instruction, 3 (2) p113-32.

• Mosston, Muska (1972), Teaching: From Command to Discovery. Belmont, California: Wadsworth Publishing.

• Mott Bradford W. , Scott W. McQuiggan, Sunyoung Lee, Seung Y. Lee, and James C. Lester, Narrative-Centered Environments for Guided Exploratory Learning,

PDF

• Shulman, L. and Keisler, E. (1966).Learning by Discovery: A Critical Appraisal. Rand McNally.

• Shrager, J & Klahr, D. 1986. Instructionless learning about a complex device: the paradign and observations. Int. J. Man-Machine Studies. 25, 153-198.