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

• Amanda Argou Universidade Federal de Pelotas (UFPel)
• Catherine Gayer Universidade Federal de Pelotas (UFPel)
• Simone Cavalheiro Universidade Federal de Pelotas (UFPel)
• Luciana Foss Universidade Federal de Pelotas (UFPel)
• André Du Bois Universidade Federal de Pelotas (UFPel)
• Renata Reiser Universidade Federal de Pelotas (UFPel)

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

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 modeling 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 students' marks in elementary school, evaluating their performance and considering CT skills as algorithm, generalization, abstraction, decomposition, and evaluation.

Palavras-chave: Flexible Assessment, Computational Thinking, Fuzzy Logic, Digital Teaching-Learning

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