ERROR-DRIVEN LEARNING: A NEW TEACHING METHODOLOGY FOR IMPROVING THE LEARNING EXPERIENCE IN STEM EDUCATION

Autor: Carlos Reaño
Rok vydání: 2021
Předmět:
Zdroj: Reaño, C 2021, Error-Driven Learning: A New Teaching Methodology for Improving the Learning Experience in Stem Education . in 13th International Conference on Education and New Learning Technologies (EDULEARN 2021) Proceedings . International Conference on Education and New Learning Technologies: Proceedings, pp. 4254-4259, 13th International Conference on Education and New Learning Technologies (EDULEARN 2021, 05/07/2021 . https://doi.org/10.21125/edulearn.2021.0901
ISSN: 2340-1117
Popis: The most extended and popular teaching methodology is probably that of direct instruction. In this methodology, the teacher is in the centre of the model and directly instructs the students. The knowledge is transferred from the teacher to the students through lectures, following a one-way communication only. Students are therefore passive agents who merely receive the information. This allows for little interaction between the teacher and the students, and does not encourage student engagement in learning.This paper presents “Error-Driven Learning”, a new teaching methodology envisaged for improving the student learning experience, particularly in science, technology, engineering, and mathematics (STEM) academic disciplines. In this new methodology, not only the teacher but also the students participate in the learning process. There is a two-way communication between the teacher and the students. For achieving that, the teacher deliberately introduces errors in lectures and practical exercises with the purpose of encouraging the students to detect and correct those errors. This significantly increases the interactivity and participation in the lectures. The students are more attentive and engaged, which ultimately translates into a better learning experience. An undergraduate course in Computer Science is employed as a use case for evaluating the proposed approach.
Databáze: OpenAIRE