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StaffIncremental BloggerVision of Education: Decisive Schools 2010 with Mobile PCs

Vision of Education: Decisive Schools 2010 with Mobile PCs

My vision of education includes that Decisive Schools are possible by 2010. The technology exists. Someone, perhaps in the private sector with a public charter school, will design and organize a prototype. Here are concepts they may use.

The purpose of Decisive Schools 2010 (DS10) is to accelerate student learning rates continuously by using real time databases to calculate the likelihood of instruction and instructional settings yielding rate increases.

Teachers need objective, reliable, empirical data to make decisions that increase learning rates. These data identify risks of failing to learn a specific task that a teacher’s decisions impose on students.

Effective educational decision making now requires in part facility of each educator with subtleties from the increasing complexity and heterogeneity of lesson content and learning, both of which span many disciplines and studies.

Absent learning related databases, educators rely on best judgments to make instruction related decisions and best efforts to increase student learning. Lacking databases to assist in making these decisions, each educator must devise unique constructions of guesses, facts, and philosophies to decide among uncounted permutations of daily instructional choices that affect student learning.

What’s Possible
By 2010, someone can design and operate Decisive Schools, so teachers may use decision oriented databases for organizing student learning activities. Tablet PCs, Ultra Mobile PCs and other advanced technologies exist sufficiently to create dynamic databases that assist teachers to reduce learning risks and thus to accelerate student learning rates.

Decisive Schools
Educators need Decisive Schools to provide a coherent contemporary base for making daily decisions that continuingly accelerate student learning rates.

Teacher pre- and in-service preparation programs provide orientations to the history and presence of schooling. No one has figured out how to assist teachers to stay up with possible impacts on teaching that the robust growth of scholarly and scientific information has on school content and learning processes.

The need for real time learning databases is especially strong because of the heterogeneous nature of education and schooling, both of which span many disciplines.

Decisive Schools use decision theory to organize instruction and thus to increase the likelihood of students consistently increasing their learning rates.

Decision Theory
Decision theory uses “If …, then …” logic to formulate choices to select among alternatives. The theory provides systematic ways to make decisions based on likely consequences of alternative choices.

Conceptually, given a set of alternative procedures and a set of alternative consequences of those procedures, decision theory provides a simple way to make the choice.

For example, a teacher knows that Billy gets nine out of ten items correct when she presents math problems with blue ink and gets six out of ten correct with yellow whiteboard ink. So, she will present problems in blue ink, if she wants him to get more problems correct.

Decision theory addresses the process of making decisions. It does not address the content of decisions.

For example, it does not include formulation of what instructional objectives to address, what criteria to use when any objective is met, or what preferences (biases) a teacher may use in making decisions.

In general, teachers are familiar with decision theory logic and with some related vocabulary. These are inherent in instructional theory, curricula designs, and learning theories.

More technical decision theory vocabulary includes consequences, alternatives, certainty, risks, uncertainty, ordering/prioritizing, ranking, value, utility, trade-offs (MAX-MIN Rule), and probabilities.

Decision School information technology infrastructure handles these technical requirements so teachers follow protocols for making decisions, as do physicians in emergency rooms.

Databases
Decisive Schools use dynamic (real time short term routine refreshing) databases to give priority to instructional strategies, techniques, materials, and settings according to their likelihood of increasing individual student learning rates. These databases provide real time odds (probabilities) of each student learning specific items in a lesson.

Uses of Databases
Educators adjust lessons as data indicate changes will likely increase learning rates for an individual and aggregates of students in each subject.

Authorized educators and overseers, such as local and state board of education members, may monitor these data in real time to assess the appropriateness and adequacy of lessons for individuals as well as aggregates of students.

Rationale
Businesses use strategies and technologies daily to calculate the likelihood of individual events contributing to their profit.

For example, dairy operators know how much of which grains, roughage, and chemicals to give each cow in herds up at least to 25,000 cows in order to increase or decrease milk fat and other components in each cow’s milk.

World class athletes know how much of what nutrition and exercises they must complete in order to compete at peak performance.

Casino operators say they know the likelihood of how much profit they will make when each chip hits a table, when each coin is dropped into a machine, and when each card is given to a player. Among other things, they use laws of large numbers to arrange to receive different percentages from different players that yield on average XX percent to the house of every dollar risked at a game.

Businesses elaborate these principles: If it exists, we can count it. Then, we can compare counts and calculate the likelihood of getting these same or better counts again. They can also calculate the likelihood that they will met their operational objectives, including profit.

Walmart, Costco, and local Mom and Pop stores use this logic. They calculate the cost of a product on a grocery store shelf by location and space, such as lineal inches. They use these data with other information to determine product prices and to adjust costs for a store to carry each product.

Advertising agencies, casinos, airlines, manufacturers among other businesses also know what to count when to count it, and how each count translates to their bottom line profit.

So may school people count and calculate the likelihood of individual students responding correctly to each item in a lesson and to meeting a minimum state learning expectation as identified in a state standard (an education version of a business breaking even without a profit).

Decisions made based on these calculations can decrease school operating costs by increasing learning efficiency. Some prominent school people speculated that efficient learning 120 minutes a day for 72 months can cover all known principles of subjects addressed in schools K20.

Similar, Partial Models
These examples illustrate that similar models and metaphors can contribute to a Decisive School Model. They offer tactics based on a similar linear thinking strategy:
Direct Instruction
Direct Learning
Pinball Machine Metaphor
Precision Teaching
Try Another Way
Two-Choice Visual Discrimination Learning
Walden II

Implications Summary
Decisive Schools have implications for educators, students, and taxpayers. Educators have objective, reliable data to use while creating lessons. Students can have accelerated learning, potentially fast enough to enter college earlier. Taxpayers can potentially see school efficiencies lead to lower costs for a student to learn, for example, to read “A.”

Counterpoint
Several counterpoints commonly heard in school settings and literature appear to reduce the likelihood of Decisive Schools existing.
1. Life’s about fun, not about meeting some arbitrary performance standard.
2. Educators consider ourselves as professionals, not business people. We address lifestyle competencies, not profits, advantages, or satisfactions.
3. Schooling is a meaningful not a mechanical process.
4. Teaching is part art and part technology. Measurement stifles the art and misleads evaluators to wrong conclusions that only measured outcomes matter for schooling.
5. Frequently measured student performance obscures students’ rights to privacy.
6. Ongoing performance measures at least appear that Big Brother is watching teachers’ and students’ behavior unnecessarily and inappropriately.
7. It’s anti-democratic. Everyone has the right to fail just as they have a right to succeed, and no one has the right to interfere with those possible failures and successes.

I think I’ll continue to mull over the idea of Decisive Schools. I wonder if anyone else wants to work explore this idea or knows of someone else developing a similar prototype?

Robert Heiny
Robert Heinyhttp://www.robertheiny.com
Robert W. Heiny, Ph.D. is a retired professor, social scientist, and business partner with previous academic appointments as a public school classroom teacher, senior faculty, or senior research member, and administrator. Appointments included at University of North Carolina at Chapel Hill, Peabody College and the Kennedy Center now of Vanderbilt University; and Brandeis University. Dr. Heiny also served as Director of the Montana Center on Disabilities. His peer reviewed contributions to education include publication in The Encyclopedia of Education (1971), and in professional journals and conferences. He served s an expert reviewer of proposals to USOE, and on a team that wrote plans for 12 state-wide and multistate special education and preschools programs. He currently writes user guides for educators and learners as well as columns for TuxReports.com.

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