Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Computers in Education
Diversity
18
10.18260/1-2--37624
https://peer.asee.org/37624
465
Associate Professor of Practice, Computer Science Department, Virginia Tech
My research interests include examining ways to improve engineering educational environments to facilitate student success, especially among underrepresented groups.
Interactive visualizations were developed to improve the learning of list-based iteration by students in an introductory Computer Science course for non-majors. An initial quantitative evaluation of the visualizations raised questions about their long-term effectiveness and ease of use. A complementary qualitative study was done to gain deeper insight into the experiences of students. The results of this study, reported here, showed that students had highly varied strategies for using the visualizations, that context was an important factor in determining the visualizations' helpfulness, and that students had an approach to understanding the visualizations that was both helpful and problematic. These findings help to inform visualization and curriculum designers about student attitudes and strategies in using course materials.
Domino, M. R., & Ellis, M. O., & Kafura, D. (2021, July), Qualitative Evaluation of Visualizations for List-based Iteration Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37624
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