Learning+Theories+Scavenger+Hunt

=Learning Theories Scavenger Hunt =

Behaviorism
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Learning is a hidden process, which is only revealed through observable behaviors. These observable behaviors are affected by operant conditioning.

This math game quizzes the user on basic addition facts using traditional behaviorist learning methods. The learner is scored based directly on the facts they get right or wrong, and incentive is created to get the answer right. The user must select the character with the number corresponding to the addition problem on the screen. If the wrong answer is picked, a red X appears, and the game continues. If the correct answer is chosen, a green checkmark appears, and the next question is posed.

This game encourages the visceral response suggested by the right/wrong paradigm, and reinforces the right answer rather than the guiding concept. The game does not allow for user inquiry or learner-centric apprehension.

Cognitivism
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Learning is shaped by experiences, and is optimized through active participation and ideal learning conditions.

Math Arcade is a good example of cognitivist integration into a traditionally behaviorist subject area. The game begins by informing the learner of the game objective, and allows the user to set the difficulty level to adjust for prior learning. The user is asked to manipulate objects in a learner-centric way to find the answer to a given math problem, then drop it in the correct location. Immediate performance feedback is given in a non-threatening way.

Constructivism
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Learning is defined by the process of instruction and knowledge acquisition, and are active participants in the learning process through inquiry and scaffolding.

Google Earth is an excellent example of constructivist learning on a broad scale. The software allows the user to follow along on preselected "tours" of various places, but at each location the user is able to independently select and follow links to additional textual and visual content to enhance the learning experience. This approach encourages knowledge acquisition through multiple modes of learning, and the learning experience is driven by the learner.

A variety of learning models have been developed within the google earth visualization environment, including earth, sky, and ocean visualization, geotagging of relevant photography and wikipedia entries, and timeline based content showing change over time in a static location.