Flexible Assessment in Digital Teaching-Learning Processes: Case Studies via Computational Thinking

Amanda Cardozo, Catherine Gayer, Simone Cavalheiro, Luciana Foss, Andre Du Bois, Renata Reiser

Resumo


This proposal presents three applications: (i) the F-ATL methodology expressing the uncertainty inherent in assessment of teaching-learning (ATL) processes; (ii) two case studies validating the F-ATL methodology via activities of Computational Thinking (CT) applying fuzzy logic and the interval-valued fuzzy logic; (iii) the impact analysis related to the validation of both case studies. This proposal also focuses on modelling uncertainty in the assessment of digital educational resources and technologies in ATL processes, regarding the development of relevant thinking skills via CT. The case studies classify the studentsmarks in elementary school, evaluating their performance and considering CT skills as algorithm, generalization, abstraction, decomposition and evaluation.

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DOI: https://doi.org/10.5753/cbie.sbie.2019.429