The Role of Automation in Instruction

 

Joseph M. Scandura

 

Director of Research, MERGE Research Institute and Emeritus Professor, University of Pennsylvania, USA. (JosephScandura@comcast.net).

 

Manuscript received August 1, 2010.
Manuscript accepted for publication September 12, 2010.

 

Abstract

More and more things that humans used to do can be automated on computer. In each case, complex tasks have been automated – not to the extent that they can be done as well as humans, but better. I will draw and develop parallels to education – showing how and why advances in the Structural Learning Theory (SLT) and the AuthorIT development and TutorIT delivery technologies based thereon make it possible not only to duplicate many of the things that human math tutors can do but to do them better. Specifically, I will show how and why TutorIT can now do a better job than most if not all human tutors in providing more effective and efficient tutoring on essentially any well defined skill. I also will show why this approach has the potential to also match or exceed human tutoring on ill–defined learning in the future.

Key words: Automation, instruction, computer–aided learning.

 

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[47] Scandura, J.M., "How to Cut Development Costs in Half: Comment on Foshay & Preese," Technology, Instruction, Cognition & Learning (TICL), 3, 1–2, pp. 185–190, 2006 (a).         [ Links ]

[48] Scandura, J.M., "Reaction to Foshay & Preese Reaction," Technology, Instruction, Cognition & Learning (TICL), 3, 1–2, PP. 195–197, 2006 (b).         [ Links ]

[49] Scandura, J. M., "AST Infrastructure in Problem Solving Research," Technology, Instruction, Cognition & Learning (TICL), 3, 3–4, pp. 1–13, 2006 (c).         [ Links ]

[50] Scandura, J. M., "Learning Objects: Promise versus Reality," Technology, Instruction, Cognition & Learning (TICL), 3, 3–4, pp. 25–31, 2006 (d).         [ Links ]

[51] Scandura, J. M., "Converting Conceptualizations into Executables: Commentary on Web–based Adaptive Education and Collaborative Problem Solving," Technology, Instruction, Cognition & Learning (TICL), 3, 3–4, pp. 345–354, 2006 (e).         [ Links ]

[52] Scandura, J. M., "Knowledge Representation in Structural Learning Theory and Relationships to Adaptive Learning and Tutoring Systems," Technology, Instruction, Cognition & Learning (TICL), Vol. 5, pp. 169–271, 2007.         [ Links ]

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[54] Scandura, J. M., Koedinger, K, Mitrovic, T, Ohlsson, S. & Paquette, G., "Knowledge Representation, Associated Theories and Implications for instructional Systems: Dialog on Deep Infrastructures," Technology, Instruction, Cognition & Learning (TICL), 6. pp.125–149, 2009.         [ Links ]

Software Engineering Publications:

[55] Scandura, J.M., "Cognitive technology and the PRODOC re/NuSys Workbench^TM: a technical overview," Journal of Structural Learning and Intelligent Systems, 11, pp. 89–126, 1992.         [ Links ]

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[57] Scandura, J.M., "Automating renewal and conversion of legacy code. Software Engineering Strategies," NY: Auerbach Publications, 1994, March/April, pp. 31–43. (Reprinted in Handbook of Systems Management, Development and Support, Auerbach, 1995. Similar version in Scuola estiva: Engineering of existing software. Bari, Italy: Dipartimento di Informatica Universita degli Studi di Bari, 1994, pp. 179–192.)

[58] Scandura, J.M., "Automating renewal and conversion of legacy code into ada: A cognitive approach," IEEE Computer, pp. 5–61, April 1994.         [ Links ]

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[62] Scandura, J.M., "Structural (Cognitive Task) Analysis: An Integrated Approach to Software Design and Programming, " Journal of Structural Learning and Intelligent Systems (a special monograph), 14, 4, pp. 433–458, 2001.         [ Links ]

Key Patent & Pending:

[63] Scandura, J.M., U.S. Patent No. 6,275,976. Automated Methods for Building and Maintaining Software Based on Intuitive (Cognitive) and Efficient Methods for Verifying that Systems are Internally Consistent and Correct Relative to their Specifications. August 14, 2001.         [ Links ]

[64] Scandura, J.M., Method for Building Highly Adaptive Instruction. US Patent pending.         [ Links ]