Utilize este identificador para referenciar este registo: http://hdl.handle.net/10198/4475
Título: Advances in artificial intelligence to model student-centred VLEs
Autor: Alves, Paulo
Palavras-chave: Learning styles
Case-based reasoning
Adaptive Web-based Educational systems
Data: 2010
Editora: INTECH
Citação: Alves, Paulo (2010) - Advances in artificial intelligence to model student-centred VLEs. In Advances in Learning Processes. p. 113-124. ISBN 978-953-7619-56-5
Resumo: The challenges to the educational paradigm, introduced with the change from a teacher to a student centred paradigm, has several implications in the organization of all the educational system. The adoption of e-learning in all of the educational levels, was a huge step forward in terms of access to resources without constrains of space and time. But e-learning didn’t reach the plato in lifelong learning scenarios, because we have a great diversity of learning contexts in universities, with more students come back to update their knowledge when they are already in the work market. The paradigm “one size fits all” is still being applied and all the pedagogical approaches adopt the traditional lecturer centred paradigm. Student centred learning is an educational paradigm that gives students greater autonomy and control over choice of subject matter, learning methods and pace of study (Gibbs, 1992). This approach is very similar to the Bologna Process goals in terms of student centred model based on learning outcomes and competences. Some of the characteristics of effective learners in the student centred learning paradigm are (de la Harpe et al., 1999): • Have clear learning goals; • Have a wide repertoire of learning strategies and know when to use them; • Use available resources effectively; • Know about their strengths and weaknesses; • Understand the learning process; • Deal appropriately with their feelings; • Take responsibility for their own learning; • Plan, monitor, evaluate and adapt their learning process. The majority of virtual learning environments (VLE) are used as mere repositories of content, based on the classroom paradigm and don’t support the individualization of the learning process. According to Dias (Dias, 2004), building spaces for online learning is a challenge that goes beyond the simple transfer of content to the Web. This approach tends to transform the environments in online repositories of information rather than in the desired spaces of interaction and experimentation. To allow a greater adaptation of the learning environment based on the student's profile, is proposed the adoption of theories of artificial intelligence in education, based on the learning experience, adapting contents and contexts to the student needs.
Peer review: yes
URI: http://hdl.handle.net/10198/4475
ISBN: 978-953-7619-56-5
Versão do Editor: http://www.intechopen.com/articles/show/title/advances-in-artificial-intelligence-to-model-student-centred-vles
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