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Reflection and Transformational Learning in a Data Structures Course

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Computing and Information Technology Division Poster Session

Tagged Division

Computing and Information Technology

Page Count

13

Permanent URL

https://peer.asee.org/37651

Download Count

373

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Paper Authors

biography

Cheryl Lynn Resch University of Florida

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BS, MS Mechanical Engineering University of MD
MS Computer Science Johns Hopkins University

2017-present University of Florida
Teach core Computer Science courses and cybersecurity courses.

1988-2017 Johns Hopkins University Applied Physics Laboratory

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Christina Gardner McCune University of Florida

biography

Amanpreet Kapoor University of Florida

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Amanpreet Kapoor is a lecturer in the Department of Engineering Education, and he teaches computing undergraduate courses in the Department of Computer & Information Science & Engineering (CISE). He received his M.S. in Computer Science from the University of Florida in 2016 and a B. Tech. in Computer Science & Engineering from Jaypee University of Engineering and Technology, India in 2015.

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Abstract

Answering reflection prompts has been shown to aid students in learning problem solving skills. The use of reflection in the computer science curriculum is nascent but growing. However, there is limited empirical evidence on the effectiveness of reflective practice in computer science courses. To fill this gap, we evaluate the effectiveness of guided reflection prompts with programming assignments in an undergraduate Data Structures course. 219 students completed two programming assignments and were asked to respond to reflection prompts after each. The prompts were ‘What did you learn?’, ‘What was the hardest part?’ and ‘What did you change from your initial design?’. A total of 1074 responses were collected. Students’ responses were (1) analyzed for word and sentence count as a measure of thoughtful engagement in the reflection assignment and (2) deductively coded using four progressive levels of reflection derived from Dewey and Moon: Noticing, Making Sense, Making Meaning, and Transformative Learning. Noticing is naming the problem and imparting facts. Making Sense is describing the problem, but not in relation to previous understandings. Making Meaning is integrating ideas and making comparisons to previous understandings. Transformative Learning is a restructuring of ideas, including plans for the future. Students were advised to write two to three sentences in response to the prompts. We found that most students gave thoughtful responses for each prompt that averaged of 3.8 sentences and 83 words. Students going beyond the suggested length provides evidence that provides evidence that many students find the activity useful. As a result of our coding the responses, we found that 46% of 1074 responses exhibited high levels of reflection with the majority of these responses on level 3 - Making Meaning (40.7%) and a small minority of responses exhibiting level 4 - Transformative Learning (5.3%). We also found that 63.9% of 219 students’ highest coded level of reflection (n= 140) were on the level of Making Meaning and 22.4% were on the level of Transformative Learning (n=49). Thus, 86% of 219 students were capable of demonstrating level 3 or 4 reflection criteria. Level 3 and 4 reflections, Making Meaning and Transformative Learning, are the targeted levels of reflection that can result in meaningful improvements in students' problem-solving skills. Finally, we surveyed students about their attitudes toward reflection and found that 70% of students agreed or strongly agreed that reflection helps them with problem solving. The thoughtful responses and positive attitude toward reflection indicates that students find reflection beneficial to their learning and will expend effort on the process. The number of students reaching levels of Making Meaning and Transformative Learning indicates that students are successfully using the reflection prompts to make connections in their learning and develop new ways of thinking and problem solving.

Resch, C. L., & McCune, C. G., & Kapoor, A. (2021, July), Reflection and Transformational Learning in a Data Structures Course Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37651

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