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Reflections and Decomposition in Problem Based Learning


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1 KLE Technological University, Hubli, India

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Problem Based Learning and Computational Thinking together have been applied in several studies, proven to be effective to bring out the best of problem solving. While both of them share several common features, computational thinking is a way of solving problems in problem based learning. One of the major components that direct a student towards critical thinking and self-directed learning are reflections. The components of computational thinking can be used to intervene reflections. This paper proposes to use decomposition for reflections. A multi method study was conducted on 37 students who were asked to write reflections for software architectural problems. The data was qualitatively analyzed using structural, in vivo and focused coding. Further, we used ttest to quantitatively analyze the data after receiving evaluation parameters from the qualitative analysis. The results are presented in this paper along with the themes generated and how reflections are effective when decomposition is explicitly stated. The work positively contributes towards design of effective PBL reflections.

Keywords

Computational Thinking; Decomposition; Problem Based learning; Reflections
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  • Reflections and Decomposition in Problem Based Learning

Abstract Views: 35  | 

Authors

Anusha Chikkamath
KLE Technological University, Hubli, India
Prakash Hegade
KLE Technological University, Hubli, India
Ashok Shettar
KLE Technological University, Hubli, India

Abstract


Problem Based Learning and Computational Thinking together have been applied in several studies, proven to be effective to bring out the best of problem solving. While both of them share several common features, computational thinking is a way of solving problems in problem based learning. One of the major components that direct a student towards critical thinking and self-directed learning are reflections. The components of computational thinking can be used to intervene reflections. This paper proposes to use decomposition for reflections. A multi method study was conducted on 37 students who were asked to write reflections for software architectural problems. The data was qualitatively analyzed using structural, in vivo and focused coding. Further, we used ttest to quantitatively analyze the data after receiving evaluation parameters from the qualitative analysis. The results are presented in this paper along with the themes generated and how reflections are effective when decomposition is explicitly stated. The work positively contributes towards design of effective PBL reflections.

Keywords


Computational Thinking; Decomposition; Problem Based learning; Reflections