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Digital Transformation of Education Toward Successful Internships: A Methodology Developed Over Seven Years and Tested During COVID-19
IEEE Transactions on Education ; 66(3):244-253, 2023.
Article Dans Anglais | ProQuest Central | ID: covidwho-20241825
ABSTRACT
Contribution This article provides a teaching methodology which combines project-based learning, self-regulated learning (SRL), and design projects (DPs) to improve the preparedness of students for computing science-related internships. The methodology is supported by the implementation of the educational technology that transforms the way teaching and learning is transformed to benefit on-campus and off-campus students equitably, during the COVID-19 pandemic.

Background:

Success in the workspace is governed by the ability of an individual to learn on-the-job and independently. Online learning has led to a shift from instructor-led learning to SRL. This requires individuals to discipline themselves, and be in control of their learning and education.

Outcome:

The success of internships is improved with skills learnt in class through hands-on real-world projects. Both on/off-campus students gain equitable relevant experience. The teaching methodology developed over several years combines project-based learning, SRL, and DPs. Application

Design:

The methodology was applied using a flipped classroom approach. The educational technology was used to enhance SRL before in-class learning. This way, in-class rote learning was replaced with hands-on projects. Exam assessments were replaced with DPs where soft skills and technical skills are applied.

Findings:

The effectiveness of the developed methodology is measured through quantitative and qualitative evaluation tools. The evaluation demonstrates that combining well-designed education technology for SRL, with in-class project-based learning and DPs, can improve students' chances in getting high-impact internships.
Mots clés

Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: ProQuest Central Type d'étude: Études expérimentales / Étude pronostique / Recherche qualitative langue: Anglais Revue: IEEE Transactions on Education Année: 2023 Type de document: Article

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Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: ProQuest Central Type d'étude: Études expérimentales / Étude pronostique / Recherche qualitative langue: Anglais Revue: IEEE Transactions on Education Année: 2023 Type de document: Article