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Planning, Forecasting, and Inventing Your Computers-in-Education Future


This page updated 5/21/07

Planning, Forecasting, and Inventing Your Computers-in-Education Future

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This work is licensed under a
Creative Commons Attribution-NonCommercial 3.0 License.

These materials are Copyright (c) 2004 by David Moursund. Permission is granted to make use of these materials for non-commercial, non-profit educational purposes by schools, school districts, colleges, universities, and other non-profit and for-profit preservice and inservice teacher education organizations and activities

Table of Contents

Preface 2
Chapter 1: An Invitation 4
Chapter 2. Inventing the Future 9
Chapter 3: Some General Background Information 15
Chapter 4: The Art and Science of Planning 24
Chapter 5: Art and Science of Forecasting 33
Chapter 6: The Future, Writ Large 48
Chapter 7: Forecasts for ICT as Content in Non-ICT Disciplines 62
Chapter 8: Forecasts for Computer-Assisted Learning and Distance Learning 75
Chapter 9: Inventing the Future for an Individual Classroom Teacher 85
Chapter 10: Summary and Concluding Remarks 93
Appendix A: Technology 99
Appendix B: Goals of Education in the United States 102
Appendix C: Goals for ICT in Education 105
Appendix D: Miscellaneous Unused Quotations 111
References 113
Index 116

Additional Readings

Pervasive Computing. IEEE holds an annual conference on his topic. See the newspaper article about the fifth conference. http://www.canada.com/nationalpost/story.html?id=42620fdf-6339-40c6-9775-dcad5d623f51&k=8721. Its title is "In future, everything will be a computer." Accessed 5/21/07.

Article on use of robots in medicine. Accessed 7/9/05:


Adler, Robert (2 July 2005). Entering a dark age of innovation. NewScientist.com news service. Accessed 7/9/05: http://www.newscientist.com/article.ns?id=dn7616 Quoting from this article:

"But according to a new analysis, this view couldn't be more wrong: far from being in technological nirvana, we are fast approaching a new dark age. That, at least, is the conclusion of Jonathan Huebner, a physicist working at the Pentagon's Naval Air Warfare Center in China Lake, California. He says the rate of technological innovation reached a peak a century ago and has been declining ever since. And like the lookout on the Titanic who spotted the fateful iceberg, Huebner sees the end of innovation looming dead ahead. His study will be published in Technological Forecasting and Social Change."

The article also contains counter arguments, such as:

"At the Acceleration Studies Foundation, a non-profit think tank in San Pedro, California, John Smart examines why technological change is progressing so fast. Looking at the growth of nanotechnology and artificial intelligence, Smart agrees with Kurzweil that we are rocketing toward a technological "singularity" - a point sometime between 2040 and 2080 where change is so blindingly fast that we just can't predict where it will go."

See also: http://www.accelerating.org/. This organization, and other people, talk about an continuing rapid gowth in invention, and an approaching singularity in which the rate of growth becomes completely overwhelming.

Cole, George (5/17/07). Holographics set to feed a market hungry for data backup. Guardian Unlimited. Retrieved 5/17/07: http://technology.guardian.co.uk/online/
. Quoting from the article:

Could magnetic tapes, hard drives and optical disc formats like Blu-ray be replaced by a data storage format that uses holograms? The world's first commercial holographic storage system is launched this autumn, with the product able to store the equivalent of 64 DVD movies on a disc about the size of a CD.

Whiting, Rick (May 29, 2006). Businesses mine data to predict what happems next. Informaotin Week. retrieved 6/2/06: http://www.informationweek.com/showArticle.jhtml;jsessionid=

So what's next? What's next is what's next--the ability to forecast where events are heading, then make informed decisions based on that assessment. Predictive analytics, the scientific name for using a data warehouse as a crystal ball, is where business intelligence is going. It involves running historical data through mathematical algorithms--neural networks, decision trees, Bayesian networks--to identify trends and patterns and predict future outcomes. Will product demand surge? Will a patient relapse? Will a customer take his business elsewhere? Our ability to make such educated guesses is key to improving service, cutting costs, and exploiting new market opportunities.

Blue Cross Blue Shield of Tennessee now predicts the health care resources postoperative patients will need years down the road. The Federal Aviation Administration is identifying links between pilot health conditions and aviation accidents, with an eye toward avoiding them. FedEx anticipates which customers are most likely to respond to a new service or defect to a competitor.