Mental models and problem solving in using a calculator

1983 ◽  
Author(s):  
Frank G. Halasz ◽  
Thomas P. Moran
Keyword(s):  
Problem Solving ◽  
Mental Models

Neurophysiologic Collaboration Patterns during Team Problem Solving

2009 ◽  
Vol 53 (12) ◽  
pp. 804-808 ◽  
Author(s):  
Ron Stevens ◽  
Chris Berka ◽  
Marcia Sprang
Keyword(s):  
Problem Solving ◽  
Mental Models ◽  
Real World ◽  
Mental Workload ◽  
Team Work ◽  
Team Members ◽  
Collaboration Patterns ◽  
Random Patterns ◽  
Time Critical

We have explored using neurophysiologic collaboration patterns as an approach for developing a deeper understanding of how teams collaborate when solving time-critical, complex real-world problems. Teams of three students solved substance abuse management simulations using IMMEX software while measures of mental workload (WL) and engagement (E) were generated by electroencephalography (EEG). Levels of high and low workload and engagement were identified for each member at each epoch statistically and the vectors consisting of these measures were clustered by self organizing artificial neural networks. The resulting cognitive teamwork patterns, termed neural synchronies, were different across six different teams. When the neural synchronies were compared across the team members of individual teams segments were identified where different synchronies were preferentially expressed. Some were expressed early in the collaboration when the team members were forming mental models of the problem, others were expressed later in the collaboration when the team members were sharing their mental models and converging on a solution. These studies indicate that non-random patterns of neurophysiologic synchronies can be observed across teams and members of a team when they are engaged in problem solving. This approach may provide an approach for monitoring the quality of team work during complex, real-world and possible one of a kind problem solving.

scholarly journals Cognitive psychology and problem solving in the physical sciences

2016 ◽  
pp. 21-25
Author(s):  
David Sands ◽  
Tina Overton
Keyword(s):  
Working Memory ◽  
Cognitive Psychology ◽  
Problem Solving ◽  
Mental Models ◽  
Cognitive Style ◽  
Field Dependence ◽  
Physical Sciences

This paper provides and introduction to the literature on cognitive psychology and problem solving in physical sciences. We consider the working memory and its three different components, two of which hold and record information and are controlled by an executive that controls attention. Working memory alone cannot explain problem solving ability and we review the influence of schemata, the construction of mental models, visual reasoning and the cognitive style of field dependence.

scholarly journals Novice programmer’s misconception of programming reflected on problem-solving plans

2017 ◽  
Vol 1 (4) ◽  
pp. 14-24 ◽  
Author(s):  
Kyungbin Kwon
Keyword(s):  
Problem Solving ◽  
Natural Language ◽  
Mental Models ◽  
Strategic Knowledge ◽  
Introductory Programming ◽  
Instructional Supports ◽  
Different Types ◽  
Conditional Statements ◽  
Novice Students ◽  
The Way

Understanding the misconception of students is critical in that it identifies the reasons of errors students make and allows instructors to design instructions accordingly. This study investigated the mental models of programming concepts held by pre-service teachers who were novice in programming. In an introductory programming course, students were asked to solve problems that could be solved by utilizing conditional statements. They developed solution plans pseudo-code including a simplified natural language, symbols, diagrams, and so on. Sixteen solution plans of three different types of problems were analyzed. As a result, the students’ egocentric and insufficient programming concepts were identified in terms of the misuse of variables, redundancy of codes, and weak strategic knowledge. The results revealed that the students had difficulty designing solution plans that could be executed by computers. They needed instructional supports to master how to express their solution plans in the way computers run. Problem driven instructional designs for novice students were discussed.

Thinking About Applications: Effects on Mental Models and Creative Problem-Solving

2013 ◽  
Vol 25 (2) ◽  
pp. 199-212 ◽  
Author(s):  
Jamie D. Barrett ◽  
David R. Peterson ◽  
Kimberly S. Hester ◽  
Issac C. Robledo ◽  
Eric A. Day ◽  
...  
Keyword(s):  
Problem Solving ◽  
Mental Models ◽  
Creative Problem Solving ◽  
Creative Problem

Problem Solving in Naive Users

1989 ◽  
Vol 33 (5) ◽  
pp. 418-422
Author(s):  
C. Michael Lewis ◽  
Wesley Jamison
Keyword(s):  
Operating System ◽  
Problem Solving ◽  
Mental Models ◽  
University Of Pittsburgh ◽  
The University ◽  
Good Support

Unix Tutor is a menu interface to UNIX being developed at the University of Pittsburgh as a training aid for new users. This paper compares mental models currently supported by the interface and those used by novices by examining subject logs from experiments. The paper concludes that Unix Tutor provides good support for consistent aspects of the operating system but fails to support models novices need to deal with inconsistencies. Design enhancements are suggested for resolving this problem.

Mental Models and Creative Problem Solving: The Relationship of Objective and Subjective Model Attributes

2011 ◽  
Author(s):  
Jamie D. Barrett ◽  
Michael D. Mumford ◽  
Kimberly S. Hester ◽  
Issac C. Robledo ◽  
David R. Peterson ◽  
...  
Keyword(s):  
Problem Solving ◽  
Mental Models ◽  
Creative Problem Solving ◽  
Creative Problem ◽  
Relationship Of ◽  
The Relationship

System Failures

2019 ◽  
pp. 91-112
Author(s):  
William B. Rouse
Keyword(s):  
Pattern Recognition ◽  
Problem Solving ◽  
Complex Systems ◽  
Mental Models ◽  
Social Phenomena ◽  
Team Coordination ◽  
System Failures ◽  
Operations And Maintenance ◽  
Problem Solving Strategies ◽  
Human Problem

This chapter focuses on the operations and maintenance of new product and service offerings once they have been deployed; in particular, it addresses dealing with system failures. Addressing system failures is an important aspect of operating and maintaining complex systems, particularly when laced with behavioral and social phenomena. Despite advances in technology and automation, humans will inevitably have roles in addressing failures when detection, diagnosis, and compensation cannot be automated. Human problem-solving involves a mix of pattern recognition and structural sleuthing based on mental models for taskwork and teamwork. Training and aiding can enhance human problem-solving performance by fostering problem-solving strategies and tactics, as well as team coordination.

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