Dublin Descriptors for Problem Scenarios in Problem Based Learning

Abstract

Problem-based learning has been one of the major pedagogies that support various learning styles, utilizing problems as a key element in studies. While there are many ways to solve a problem, Computational Thinking can be one of them. Typically, we formulate learning outcomes and design assessments to attain these goals. However, there are cases where a single outcome may not suffice, especially with multi-layered problems. In such scenarios, we propose using Dublin Descriptors and evaluate the study using system design problems. Two case studies were designed, requiring students to reflect on the components of computational thinking. Reflections in the second case study were designed according to the written Dublin Descriptors. We conducted qualitative and quantitative analyses on data from 37 students in two case studies to identify themes related to Bloom's and Dublin Descriptors, using In Vivo, Descriptive, and Focus coding in two rounds of analysis. Statistical inferences suggest that the method holds promise for cases requiring advancement beyond Level 4. Dublin Descriptors show promise in cases where information needs to be communicated from ideas to inferences.