Theory Name: Algo-Heuristics (see also Landamatics)
Authors: Landa, Lev N.
Associated Learning Theory
Cognitive Learning Theory
Algo-heuristics is a way of prescribing instruction for problem solving.
In algo-heuristics, the learner is encouraged to learn either algorithmic
or heuristic problem solving in a step by step process.
Specification of Theory
(a) Goals and preconditions
Processes – Sets of operations: Operations are transformations
of (or changes to) material objects or mental models.
1. It is more important to teach algo-heuristic processes versus prescriptions.
2. Processes can be taught through prescriptions and demonstrations of
operations. (Operations = changes of mental or material knowledge)
3. Discovery of processes is more valuable than providing formulated
4. Individualize instruction.
(c) Condition of learning
1. Instructional processes are influences directed by a “teacher” and
directed at transformation. (teacher refers to any teaching agent, live
or material, i.e. books, AV, computer)
2. Instructional processes are affected by teacher actions or instructional
3. Instructional processes can be affected by certain conditions.
- external conditions, student psychology, teacher knowledge
4. There are three types of instructional rules: descriptive, prescriptive,
and permissive. Descriptive rules are statements about what occurs. Prescriptive
rules are statements about what should be done. Permissive rules indicate possible
alternatives to prescriptive rules.
(d) Required media
(e) Role of facilitator
Teaching involves solving instructional problems; the teacher has to
determine and perform actions that should be executed in order to meet
(f) Instructional strategies
1. Uncover process underlying expert learners and mastery level performers.
2. Describe the process with a hypothetical descriptive model.
3. Test the correctness of the model.
4. Improve the model if necessary.
5. Optimize the model if possible.
6. Design the final algorithmic or non-algorithmic process to allow the learners
to perform on a mastery level.
7. Identify learning procedures leading to the development of algorithm or
8. Design algo-heuristic teaching procedures.
9. Design algo-heuristic based training materials.
10. If necessary, create a computer-based or other media based programmed
11. Design methods for evaluation.
Instructional Method 1 – The step-by-step approach
1. Present the procedure to the student and demonstrate problem solving.
2. Develop the first operation.
3. Present a problem that requires the first operation and practice that operation.
4. Develop the second operation.
5. Present a problem that requires application of both operation and practice.
6. Develop the third operation.
7. Present a problem that represents all three problems.
8. Proceed until all problems are mastered.
Instructional Method 2 – Developing individual operations
1. Determine whether the student understands the meaning of a direction in
the a prescription and its operations.
2. Present a problem that requires application of the problem.
3. Name the operation (give the learner a self-command) before he/she executes
4. Present the next problem and have the learner give the command internally.
5. Continue practicing the operation until mastery.
2. Explain what the student does not understand.
3. Test the correctness of understanding and allow for practice. Provide extra
explaination and practice.
4. Go to #2 under “yes” above.
(g) Assessment method
Student is able to complete the operation at a mastery level.
Formative Research & Application
(a) Tested context - K-12, College (especially math and language)
(b) Research method
(c) Research description
Landa, L.N. (1983). The algo-heuristic theory of instruction. In Reigeluth,
C.M. (Ed.), Instructional-design theories and: an overview if their current
status. (pp. 163 – 211). Hillsdale, NJ: Lawrence Erlbaum Associates,