@inproceedings{dc2a06b28eae422ea9ce0bf8f795dc8f,
title = "Distractors in parsons problems decrease learning efficiency for young novice programmers",
abstract = "Parsons problems are an increasingly popular method for helping inexperienced programmers improve their programming skills. In Parsons problems, learners are given a set of programming statements that they must assemble into the correct order. Parsons problems commonly use distractors, extra statements that are not part of the solution. Yet, little is known about the effect distractors have on a learner's ability to acquire new programming skills. We present a study comparing the effectiveness of learning programming from Parsons problems with and without distractors. The results suggest that distractors decrease learning efficiency. We found that distractor participants showed no difference in transfer task performance compared to those without distractors. However, the distractors increased learners cognitive load, decreased their success at completing Parsons problems by 26\%, and increased learners' time on task by 14\%.",
keywords = "Cognitive Load, Completion Problems, Distractors, Independent Learning, Parsons Problems",
author = "Harms, \{Kyle J.\} and Jason Chen and Caitlin Kelleher",
year = "2016",
month = aug,
day = "25",
doi = "10.1145/2960310.2960314",
language = "English",
series = "ICER 2016 - Proceedings of the 2016 ACM Conference on International Computing Education Research",
publisher = "Association for Computing Machinery, Inc",
pages = "241--250",
booktitle = "ICER 2016 - Proceedings of the 2016 ACM Conference on International Computing Education Research",
note = "12th Annual International Computing Education Research Conference, ICER 2016 ; Conference date: 08-09-2016 Through 12-09-2016",
}