Study Guide for Human Information Processing (eBook, PDF)
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Study Guide for Human Information Processing is designed to accompany Lindsay and Norman's Human Information Processing (HIP). Problems and questions range from ones that are relatively easy to several that are somewhat difficult. This variation is intentional; the easy exercises explain and demonstrate the principles introduced in HIP, and the harder problems challenge students to apply those principles to new areas. Much of this study guide relies on the process of model building to review and expand on the principles in the text. Models will be proposed to explain experimental results. By u...
Study Guide for Human Information Processing is designed to accompany Lindsay and Norman's Human Information Processing (HIP). Problems and questions range from ones that are relatively easy to several that are somewhat difficult. This variation is intentional; the easy exercises explain and demonstrate the principles introduced in HIP, and the harder problems challenge students to apply those principles to new areas.
Much of this study guide relies on the process of model building to review and expand on the principles in the text. Models will be proposed to explain experimental results. By using models the goal is to help students develop the ability to find truly significant patterns of results. This ability involves a critical attitude toward any experiment. For many of the models proposed, a joint search is conducted with students to discover the fatal flaws in the models. Students are also encouraged to propose models of their own, and to design experiments to test them
Much of this study guide relies on the process of model building to review and expand on the principles in the text. Models will be proposed to explain experimental results. By using models the goal is to help students develop the ability to find truly significant patterns of results. This ability involves a critical attitude toward any experiment. For many of the models proposed, a joint search is conducted with students to discover the fatal flaws in the models. Students are also encouraged to propose models of their own, and to design experiments to test them
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