scholarly journals Using Positioning Theory to Study the Role of Emotions in Engineering Problem Solving: Methodological Issues and Recommendations for Future Research

2021 ◽  
Vol 2 (1) ◽  
pp. 53
Author(s):  
Johanna Lönngren ◽  
Tom Adawi ◽  
Marie Berge
Keyword(s):  
Problem Solving ◽  
Engineering Problem ◽  
Positioning Theory ◽  
Future Research ◽  
Methodological Issues ◽  
Engineering Problem Solving

Influence of Cognitive, Affective, and Conative Elements in Promoting Engineering Problem Solving Skills

2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Norasyikin Omar ◽  
◽  
Mimi Mohaffyza Mohamad ◽  
Marina Ibrahim Mukhtar ◽  
Aini Nazura Paimin ◽  
...  
Keyword(s):  
Problem Solving ◽  
Engineering Problem ◽  
Problem Solving Skills ◽  
Engineering Problem Solving

scholarly journals The Role of Mental Effort in Fostering Self-Regulated Learning with Problem-Solving Tasks

2020 ◽  
Vol 32 (4) ◽  
pp. 1055-1072 ◽  
Author(s):  
Tamara van Gog ◽  
Vincent Hoogerheide ◽  
Milou van Harsel
Keyword(s):  
Problem Solving ◽  
Self Regulation ◽  
Mental Effort ◽  
Future Research ◽  
Task Sequence ◽  
Self Monitoring ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
And Mathematics

Abstract Problem-solving tasks form the backbone of STEM (science, technology, engineering, and mathematics) curricula. Yet, how to improve self-monitoring and self-regulation when learning to solve problems has received relatively little attention in the self-regulated learning literature (as compared with, for instance, learning lists of items or learning from expository texts). Here, we review research on fostering self-regulated learning of problem-solving tasks, in which mental effort plays an important role. First, we review research showing that having students engage in effortful, generative learning activities while learning to solve problems can provide them with cues that help them improve self-monitoring and self-regulation at an item level (i.e., determining whether or not a certain type of problem needs further study/practice). Second, we turn to self-monitoring and self-regulation at the task sequence level (i.e., determining what an appropriate next problem-solving task would be given the current level of understanding/performance). We review research showing that teaching students to regulate their learning process by taking into account not only their performance but also their invested mental effort on a prior task when selecting a new task improves self-regulated learning outcomes (i.e., performance on a knowledge test in the domain of the study). Important directions for future research on the role of mental effort in (improving) self-monitoring and self-regulation at the item and task selection levels are discussed after the respective sections.

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