Collaborative Problem-Solving Behavior of 15-Year-Old Taiwanese Students in Science Education

Abstract Collaborative problem solving can be successful or counterproductive. The performance of collaborative teams depends not only on team members’ abilities, but also on their cognitive styles. Cognitive style measures differences in problem-solving behavior: how people generate solutions, manage structure, and interact. While teamwork and problem solving have been studied separately, their interactions are less understood. This paper introduces the KAI Agent-Based Organizational Optimization Model (KABOOM), the first model to simulate cognitive style in collaborative problem solving. KABOOM simulates the performance of teams of agents with heterogeneous cognitive styles on two contextualized design problems. Results demonstrate that, depending on the problem, certain cognitive styles may be more effective than others. Also, intentionally aligning agents’ cognitive styles with their roles can improve team performance. These experiments demonstrate that KABOOM is a useful tool for studying the effects of cognitive style on collaborative problem solving.

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Relationships between Collaborative Problem Solving, Learning Performance and Learning Behavior in Science Education

2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) ◽

10.1109/tale.2018.8615254 ◽

2018 ◽

Cited By ~ 3

Author(s):

Li Chen ◽

Hirokazu Uemura ◽

Hao Hao ◽

Yoshiko Goda ◽

Fumiya Okubo ◽

...

Keyword(s):

Science Education ◽

Problem Solving ◽

Collaborative Problem Solving ◽

Learning Performance ◽

Learning Behavior ◽

Collaborative Problem

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Fantastic four! Problem-solving processes of a professional string quartet

Psychology of Music ◽

10.1177/0305735621998746 ◽

2021 ◽

pp. 030573562199874

Author(s):

Rebecca A Roesler

Keyword(s):

Problem Solving ◽

String Quartet ◽

Domain Knowledge ◽

Collaborative Problem Solving ◽

Future Research ◽

Leadership Roles ◽

Collaborative Problem ◽

Problem Solving Process ◽

Musical Context ◽

Problem Solving Behavior

The purpose of this study was to provide a rich multi-dimensional view of expert musical collaborative problem-solving processes. I analyzed the collaborative problem-solving process during three subsequent rehearsals by a professional string quartet, applying Roesler’s (2016) model of musical problem-solving components. As Roesler observed with shared problem solving during one-to-one instruction, problem-solving components were enacted by and distributed among members of the quartet in any combination. In addition, quartet members prompted problem-solving behavior from one another in a similar way that teachers prompted problem-solving behavior from students (Roesler, 2017). Leadership roles shifted fluidly among quartet members from moment to moment. Domain knowledge and musical context were a critical component of their decision-making process. Additional observed rehearsal strategies are outlined. Suggestions for future research and applications of these findings are discussed, including the learning of collaborative problem-solving skill through participation in small musical ensembles.

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Collaborating with Style: Using an Agent-Based Model to Simulate Cognitive Style Diversity in Problem Solving Teams

10.31224/osf.io/pfys6 ◽

2019 ◽

Author(s):

Christopher McComb ◽

Kathryn Jablokow ◽

Samuel Lapp

Keyword(s):

Problem Solving ◽

Cognitive Style ◽

Cognitive Styles ◽

Collaborative Problem Solving ◽

Design Problems ◽

Team Members ◽

Agent Based ◽

Collaborative Problem ◽

Problem Solving Teams ◽

Problem Solving Behavior

Collaborative problem solving can be successful or counterproductive. The performance of collaborative teams depends not only on team members' abilities, but also on their cognitive styles. Cognitive style measures differences in problem-solving behavior: how people generate solutions, manage structure, and interact. While teamwork and problem solving have been studied separately, their interactions are less understood. This paper introduces the KAI Agent-Based Organizational Optimization Model (KABOOM), the first model to simulate cognitive style in collaborative problem solving. KABOOM simulates the performance of teams of agents with heterogeneous cognitive styles on two contextualized design problems. Results demonstrate that, depending on the problem, certain cognitive styles may be more effective than others. Also, intentionally aligning agents' cognitive styles with their roles can improve team performance. These experiments demonstrate that KABOOM is a useful tool for studying the effects of cognitive style on collaborative problem solving.

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Application of Real-World Problems in Computer Science Education

International Journal of Information and Communication Technology Education ◽

10.4018/ijicte.2018070102 ◽

2018 ◽

Vol 14 (3) ◽

pp. 15-28

Author(s):

Deller James Ferreira ◽

Ana Paula Laboissière Ambrósio ◽

Tatiane F. N. Melo

Keyword(s):

Science Education ◽

Problem Solving ◽

Computer Science ◽

Real World ◽

Daily Life ◽

Collaborative Problem Solving ◽

Motivational Orientations ◽

Beliefs And Practices ◽

Collaborative Problem ◽

Real World Problems

This article describes how it is due to the fact that computer science is present in many activities of daily life, students need to develop skills to solve problems to improve the lives of people in general. This article investigates correlations between teachers' motivational orientations, beliefs and practices with respect to the application of real-world problems in undergraduate courses. A questionnaire was applied to twenty-eight teachers of an undergraduate computer science course. Data from the questionnaire was analyzed using statistical methods. The results show that the majority of the teachers, especially those who interact with companies, believe that the insertion of real-world problems in the classroom is important. However, some teachers are not willing to adopt this practice. This is linked to reasons such as the need for more flexible curricula and a better teaching qualification with respect to collaborative problem solving.

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