The decisive learning skill for the scientific knowledge acquisition developed by artificial intelligence

Abstract

Several researchers in the field of education have taken an interest in the development of scientific skills. Their objective is to enable learners to have an attitude of reflection and behavior in the face of the different pedagogical situations that may arise. We are also interested in these scientific skills, namely C1: Appropriate, C2: Analyze and reason, C3: Achieve, C4: Validate and C5: Communicate, we have characterized them by capacities whose objective is to evaluate them with interesting precision. We are interested in all these scientific skills but with significant weightings in order to realize a balanced, complete and effective overall assessment of scientific learning. In this work, we will also discover the most important scientific skill for the construction of Knowledge in a given scientific session, using artificial intelligence based on the decision tree by implementing a program in Python. Therefore, taking into consideration the one that leads to the birth of ideas and that allows to converge towards the objective, the teacher gives more importance to this skill and develops it by proposing different specific pedagogical situations. This learning approach allows the teacher to make the right decisions at the right time and it allows equity between the learners to acquire the different scientific skills according to their learning ability. Therefore it allows the learner an intrinsic motivation for the acquisition of scientific knowledge.