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Learning Models for Higher Education in Engineering: Motivation, Self-Determination, and the Role of Information and Communication Technologies

doi: 10.3390/su151712869
In the last decade, great strides have been made to increase access to education and enrollment rates at all levels (primary, secondary, and higher education). Actions such as promoting equal access to education, preventing school dropout, and establishing free education, among other actions proposed by organizations such as UNESCO, seek to guarantee the universality of education. This is undoubtedly a great challenge, and to address it, it is necessary to characterize how students face the learning process, considering factors such as autonomy, competencies, and their own basic psychological needs, looking for effective learning models based on students’ needs in a changing world, where ICTs play a relevant role. This research analyzes learning models, motivation, self-determination, and technologies used for learning achievement in higher engineering education. The study will highlight relevant initiatives and the most commonly used technological tools. It will also identify learning models that seek to link emotional intelligence, self-determination, cognitive skills, and ICT. The PRISMA protocol guided the study, finding 132 relevant articles to be analyzed and proposing best practices in using learning models, strategies, and ICT to foster students’ intrinsic motivation.
- University of La Frontera Chile
- Technological University of Mexico Mexico
- Universidad Autónoma de Chile Chile
- University of La Frontera Chile
- Universidad Americana Panama
Environmental effects of industries and plants, engineering, self-determination, TJ807-830, emotional intelligence, TD194-195, Renewable energy sources, motivation models, Environmental sciences, higher education, GE1-350, metacognition
Environmental effects of industries and plants, engineering, self-determination, TJ807-830, emotional intelligence, TD194-195, Renewable energy sources, motivation models, Environmental sciences, higher education, GE1-350, metacognition
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).6 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
