Abstract
Numerical problem solving in classical mechanics in university physics education offers a learning situation where students have many possibilities of control and creativity. In this study, expertlike beliefs about physics and learning physics together with prior knowledge were the most important predictors of the quality of performance of a task with many degrees of freedom. Feelings corresponding to control and concentration, i.e., emotions that are expected to trigger students' intrinsic motivation, were also important in predicting performance. Unexpectedly, intrinsic motivation, as indicated by enjoyment and interest, together with students' personal interest and utility value beliefs did not predict performance. This indicates that although a certain degree of enjoyment is probably necessary, motivated behavior is rather regulated by integration and identification of expertlike beliefs about learning and are more strongly associated with concentration and control during learning and, ultimately, with high performance. The results suggest that the development of students' epistemological beliefs is important for students' ability to learn from realistic problem-solving situations with many degrees of freedom in physics education.
Highlights
In recent years there has been an increasing interest in using numerical methods including interactive simulations and visualizations in university physics education [1,2,3]
Our results show that the students’ prior knowledge and epistemological beliefs, together with control and concentration emotions, are important variables for predicting performance, while evaluations of the utility of physics knowledge in everyday life, i.e., value beliefs, or the extent to which students enjoyed working with the simulation, pleasure emotions, are not correlated with performance as much
Students who have well-developed schemata in the subject area have better opportunities to quickly overview the task and identify key issues and possible strategies to solve the task, but will experience a reduced load on working memory, due to information chunking, which allows for more creative thinking. This would certainly be the case in any learning situation, but we argue that the need for relevant and well-structured prior knowledge is accentuated in situations with a high degree of freedom like in the present study
Summary
In recent years there has been an increasing interest in using numerical methods including interactive simulations and visualizations in university physics education [1,2,3]. Increasing computer capacity together with a number of modeling and problem-solving environments offer new possibilities for physics students to model complex physics systems as well as to numerically solve physics problems. Depending on the modeling environment, students are given different opportunities to numerically solve physics problems, create visual simulations, practice mathematical modeling, and investigate the process of a physics phenomena, rather than just focusing on an answer [3,4,5,6,7]. But not all, simulation and modeling environments represent learning situations that offer many degrees of freedom and open up avenues for students to take control of their
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