Fuzzy knowledge based assessment system for K-12 Scientific Reasoning Competencies

Developing Scientific Reasoning (SR) competencies at an early age, are challenging to meet expectation of the 4th sustainable development goal. Hence, educators and educational decision-makers try to embed these competencies into such subjects as the arts, language, technology, economics, mathematics and science, using an inter-disciplinary approach. In this context, this paper proposes a fuzzy knowledge-based solution to build practical pupils, educators, and decision-makers recommender system to support the development of SR competencies in a data driver manner. Our system consists of:(1) inferring and computational module that calculates in a fuzzy manner the global appreciation to each SR-competencies. (2) recommendation module that aims to help learners, educators and decision makers to assess the degree of development of SR competencies and to get alternative suggestion of remediation. The proposed solution has been tested on the last two levels of science education in four Tunisian elementary schools in different regions. A preliminary analysis showed that the learning process should be more focused on Tunisian pupil's profile, and that investigation and collaborative based learning should be applied further in Tunisian classroom.