Algo-Hueristic is an instructional
theory that involves the to use two different types of teaching. One type is an Algorithmic approach that
relies on the student’s cognitive ability and the teacher building on previous
concepts the student understands. The
other aspect to this model is a Heuristic approach. The Heuristic aspect of the model involves
teaching skills the students need to know and submerging them with that
skill. One way to think of the
difference is Algorithms are taught patterns that stack together while Heuristic
lessons teach through experience. The
cognitive strategy teaches at least one of the three outcomes: knowledge,
skills and activities. The instructional
strategy comes from the overarching theoretic school of cognitivism/pragmatism.
The Algorithmic part of the theory
is set procedures that are taught and built on each other. An example of an Algorithmic lesson is
teaching students to get to school each day.
- · Wake up and walk to shower
- · Take off clothes, turn on water
- · Shower
- · Try off
- · Brush Teeth
- · Etc.
This example
shows that sequencing is a major form of learning. Sequencing is most evident in math, which is
why math uses Algorithms. This method
also uses elementary processes and uses building blocks to learn one concept
then review the other concepts leading up to the new one. The term of building concepts is often
referred to as the snowball effect.
Heuristic methods of instruction are
becoming more and more evident in schools today. The new standards focus on experiences and
explanations. Heuristic instruction
provides in-depth analysis and critical thinking to real problem solving. An example of a Heuristic lesson would be assigning
students in a Chemistry class to build a boat only using recyclables. Students performing this assignment are going
to need two plans. First they will need
a procedure to figuring out how to float a boat with only recyclables. Second, they would have to determine a method
for executing this plan. This lesson is
Heuristic because it places students in an environment in which they have to
determine a plan and a mode of action for solving the overarching question.
Algorithmic and Heuristic approaches
are similar because they both use different amounts of elementary
scaffolding. Algorithms constantly use
build in other concepts and are limited to that repetition. Heuristic approaches use a small amount of elementary
concept instruction and jump straight to a bigger concept. For the Biology lesson, the teacher did not
go back and review why things float. The
teacher simply gave them the challenge and they figured it out. If the teacher would have gone all the way
back to lessons on floating bottles and build lessons from that, then the
lesson would be Algorithmic. The two can
provide great structure for lessons and both need to be used to keep students
understanding smaller concepts (Algorithmic) and using large concepts to
overarch the smaller ones (Heuristic).
In the end, the two types of
instruction used in one model provide at least one of the following outcomes:
knowledge, skills and/or activities. As
seen at the bottom of figure 1, Algorithmic models provide students with great
knowledge. However, it fails to provide
skills and activities for the students. Heuristic
models include knowledge through investigation, skills through experience, and
activities to reinforce knowledge. The
constant reinforcement of skills makes Algorithmic models provide knowledge to
students but Heuristic processes use critical thinking to produce skills. The Algo-Heruistic Theory of teaching is
supported by the theory of cognitivism/pragmatism. The overarching theory of
cognitive/pragmatism includes efficiently understanding knowledge and
organizing it efficiently. The
Algo-Heuristic theory can be very beneficial by students when teachers use Algorithmic
methods to reinforce knowledge and Heuristic methods to build skills and
activities.
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