NDLI: An Empirical Study of In-Class Laboratories on Student Learning of Linear Data Structures

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An Empirical Study of In-Class Laboratories on Student Learning of Linear Data Structures

Content Provider	ACM Digital Library
Author	Heckman, Sarah S.
Abstract	Active learning increases student learning through collaborative engagement with materials during class time. A CS1.5 course at NC State, CSC216, uses active learning lectures involving short simplified think-pair-share in-class exercises to engage students with course materials. However, students still struggle with the course materials and several students do not successfully complete the course on their first attempt. To increase student learning and engagement, we conducted a quasi-experimental study incorporating in-class labs into two sections of CSC216 during the linear data structures unit in the Fall 2014 semester. Both sections completed in-class labs on the Java Collections Framework and iterators. One section completed in-class labs on array-based lists; the other section completed in-class labs on linked lists, in a counter-balanced study design. The active learning lecture delivery was used for the control section and an Exam was administered between the array-based list and linked list topics. Overall, we found no significant difference in student learning on array-based and linked lists as measured by the final exam. Students displayed half as much disengaged behavior during in-class labs and were five times more likely to ask for help from the teaching staff during in-class labs.
Starting Page	217
Ending Page	225
Page Count	9
File Format	PDF
ISBN	9781450336307
DOI	10.1145/2787622.2787713
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-07-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Empirical computer science education In-class labs Cs1.5 Linear data structures
Content Type	Text
Resource Type	Article

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