Problem-Solving Efficiency and Cognitive Load for Adaptive Parsons Problems vs. Writing the Equivalent Code

被引:13
|
作者
Haynes, Carl C. [1 ]
Ericson, Barbara J. [1 ]
机构
[1] Univ Michigan, Ann Arbor, MI 48109 USA
关键词
Cognitive Load Theory; Computing Education; Parsons Problems; Programming; STUDENTS CONCEPTIONS; TASK; PERFORMANCE; STRATEGIES; DESIGN;
D O I
10.1145/3411764.3445292
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Novice programmers need differentiated assessments (such as adaptive Parsons problems) to maximize their ability to learn how to program. Parsons problems require learners to place mixed-up code blocks in the correct order to solve a problem. We conducted a within-subjects experiment to compare the efficiency and cognitive load of solving adaptive Parsons problems versus writing the equivalent (isomorphic) code. Undergraduates were usually more significantly efficient at solving a Parsons problem than writing the equivalent code, but not when the solution to the Parsons problem was unusual. This has implications for problem creators. This paper also reports on the mean cognitive load ratings of the two problem types and the relationship between efficiency and cognitive load ratings. Lastly, it reports on think-aloud observations of 11 students solving both adaptive Parsons problems and write-code problems and the results from an end-of-course student survey.
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页数:15
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