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Related Concept Videos

Problem-Solving01:29

Problem-Solving

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Effective problem-solving consists of two steps: 1. identifying the problem and 2. selecting the appropriate problem-solving strategy (i.e., a plan of action used to find a solution). Humans use four problem-solving strategies:
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Cognitive Learning01:21

Cognitive Learning

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
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Principle of Moments: Problem Solving01:30

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The principle of moments is a fundamental concept in physics and engineering. It refers to the balancing of forces and moments around a point or axis, also known as the pivot. This principle is used in many real-life scenarios, including construction, sports, and daily activities like opening doors and pushing objects.
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Principle of Virtual Work: Problem Solving01:13

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The principle of virtual work is an essential concept in the field of mechanics and engineering. This is used to solve problems related to the equilibrium of a structure or system. It is based on the assumption that if a system is in equilibrium, the work done by all the forces during a virtual displacement is zero. This principle is applied by considering virtual displacements of the system and the corresponding work done by internal and external forces.
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Method of Sections: Problem Solving I01:27

Method of Sections: Problem Solving I

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Consider a symmetrical roof truss structure, composed of vertical, diagonal, and horizontal members. The length of each horizontal member is 4 m. The lengths of the vertical members FB and HD are 4 m, while the length of member GC is 6 m. The loads acting at joints F, G, and H are 2 kN, while those at joints A and E are 1 kN.
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Method of Sections: Problem Solving II01:30

Method of Sections: Problem Solving II

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Consider an arbitrary truss structure composed of diagonal, vertical, and horizontal members fixed to the wall. To calculate the force acting on members CB, GB, and GH, method of sections can be used. The loads and lengths of the horizontal and vertical members are known parameters, as shown in the figure.
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Updated: Dec 6, 2025

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QLens: Visual Analytics of MUlti-step Problem-solving Behaviors for Improving Question Design.

Meng Xia, Reshika Palaniyappan Velumani, Yong Wang

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    |October 13, 2020
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    Summary

    QLens visualizes student problem-solving data to help educators improve online learning materials. This system analyzes complex interaction data, offering insights into student logic and engagement for better educational design.

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    Area of Science:

    • Educational Technology
    • Human-Computer Interaction
    • Data Visualization

    Background:

    • Online education platforms increasingly use multi-step questions to develop student problem-solving skills.
    • Assessing the quality of these materials requires understanding student problem-solving processes and comparing group behaviors.
    • High-dimensional interaction data, like mouse trajectories, offers potential for analysis but is challenging to interpret.

    Purpose of the Study:

    • To introduce QLens, a visual analytics system designed for educational question designers.
    • To enable detailed inspection of student problem-solving trajectories and comparison between different student groups.
    • To distill insights for improving online learning materials and question design.

    Main Methods:

    • Modeling student problem-solving behavior as a hybrid state transition graph.
    • Visualizing these behaviors using a novel glyph-embedded Sankey diagram.
    • Conducting case studies and expert interviews with real-world datasets of thousands of problem-solving traces.

    Main Results:

    • QLens effectively models and visualizes complex student problem-solving sequences.
    • The system reveals students' problem-solving logic, engagement levels, and difficulties encountered.
    • Case studies and interviews confirm the utility of QLens for educational designers.

    Conclusions:

    • QLens provides a valuable tool for analyzing fine-grained student interaction data in online education.
    • The system aids in evaluating and refining educational content by offering interpretable insights into student behavior.
    • Visual analytics, through systems like QLens, can significantly enhance the design and effectiveness of online learning platforms.