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Welcome to the Cognitive Models MCQs Page

Dive deep into the fascinating world of Cognitive Models with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Cognitive Models, a crucial aspect of Human Computer Interaction. In this section, you will encounter a diverse range of MCQs that cover various aspects of Cognitive Models, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Human Computer Interaction.

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Check out the MCQs below to embark on an enriching journey through Cognitive Models. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Human Computer Interaction.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Cognitive Models. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Cognitive Models MCQs | Page 1 of 13

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Answer: (b).Competence models predict legal behavior sequences, while performance models describe necessary behavior sequences and how they are executed. Explanation:Competence models predict legal behavior sequences without reference to actual execution, while performance models describe necessary behavior sequences and how they are executed.
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Answer: (d).To build the cognitive models effectively Explanation:Architectural assumptions about the user are needed to build and understand cognitive models effectively.
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Answer: (c).Encouragement of a mechanistic view of the user Explanation:There is a danger that using computational analogies could encourage a mechanistic view of the user.
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Answer: (c).Users solve subgoals in a divide-and-conquer manner. Explanation:Many models represent the achievement of goals by solving subgoals in a divide-and-conquer fashion.
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Answer: (d).They involve breaking down goals into subgoals. Explanation:A central feature shared by GOMS, CCT, TAG, and task analysis techniques is breaking down goals into subgoals.
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Answer: (a).The level of detail to which a task is decomposed Explanation:Granularity refers to the level of detail to which a task is decomposed.
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Answer: (b).Abstract concepts without specific goals Explanation:Task analysis can start at different points in the hierarchy of goals, including an extreme point where it starts with abstract concepts without specific goals.
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Answer: (a).It represents the simplest goal achievable by users. Explanation:Unit task represents the most abstract task that does not require problem-solving skills on the part of the user.
Q9.
How does cognitive complexity theory (CCT) differ from other hierarchical modeling techniques regarding error behavior?
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Answer: (a).CCT can predict error behavior accurately. Explanation:Cognitive complexity theory (CCT) can represent error behavior, although other hierarchical modeling techniques generally have poor prediction of error behavior.
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Answer: (c).Representing how users select between competing solutions Explanation:Users often have more than one way to achieve a goal, and there must be a way to represent how they select between competing solutions.

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