Definition of Learner Choices from Learner-Driven Learning for Ubiquitous e-Learning Systems and its Application in the AdaptWeb Platform
Resumo
Nós percebemos que os usuários de perfil estudante geralmente realizam um conjunto de escolhas ou tomadas de decisão durante a aprendizagem, dependendo da plataforma de e-learning utilizada. Esse conjunto de escolhas pertence ao paradigma de Aprendizagem Autodirigida da Educação. Neste artigo, definimos essas escolhas em sistemas de e-learning, com base em padrões de interação e de navegação de usuários que observamos em diferentes sistemas e-learning durante uma revisão sistemática que realizamos. Além disso, apresentamos como essas escolhas são implementadas no AdaptWeb, um sistema de e-learning formal e ubíquo.
Palavras-chave:
aprendizagem autodirigida, e-learning ubíquo, padrões de interação, navegação de usuários, AdaptWeb
Referências
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CEC - Commission of the European Communities (2001) Communication from the commission - Making a European Area of Lifelong Learning a Reality. Report.
Dias, A. S. Wives, L. K. (2018) Assessment of the Most Relevant Learning Object Metadata: Relieving the Learner-User from Information Overload. In: Proceedings of the 10th International Conference on Computer Supported Education (CSEDU).
Drachsler, H. Verbert, K. Santos, O. and Manouselis, N. (2015) Panorama of Recommender Systems to Support Learning. In: Ricci F., Rokach L., Shapira B. (eds) Recommender Systems Handbook. Springer, Boston, MA, p.421-451.
Gates-Dell-EDUCAUSE - Bill & Melinda Gates Foundation, the Michael and Susan Dell Foundation, and EDUCAUSE (2017) A working definition of personalized learning. Available in: [link]. Access in: 20 jul. 2017.
Ginsberg, M. B. (2015) Excited to Learn: Motivation and Culturally Responsive Teaching. Corwin Press.
iNACOL - International Association for K-12 Online Learning; Patrick, S. Kennedy, K. Powell, A (2013) Mean What You Say: Defining and Integrating Personalized, Blended and Competency Education.
LEADLAB - The LEADLAB Project (2010) Available in: [link]. Access in: 25 feb. 2017.
Manouselis, N. Vuorikari, R., and Assche, F. V. (2010) Collaborative recommendation of e-learning resources: an experimental investigation. In: Journal of Computer Assisted Learning 26(4):227-242. DOI: 10.1111/j.1365-2729.2010.00362.x.
Miliband, D. (2006) Choice and voice in personalized learning. In: OECD, Personalizing education. DOI: 10.1787/9789264036604-2-en.
Overwien, B. (2017) The history of the term Informal Learning. Available in: [link]. Access in: 01 jun. 2018.
Watkins C, Carnell E, Lodge C (2007) Effective Learning in Classrooms. London, Paul Chapman Publishing. DOI= DOI: 10.4135/9781446211472.
Zheng, Y. Mobasher, B. and Burke, R. (2014) Context Recommendation Using Multilabel Classification. In: Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).
Zhuhadar, L. and Butterfield, J. (2014) Analyzing Students Logs in Open Online Courses Using SNA Techniques, In: Proceedings of the 20th Americas Conference on Information Systems, AMCIS 2014, Savannah, Georgia, USA.
CEC - Commission of the European Communities (2001) Communication from the commission - Making a European Area of Lifelong Learning a Reality. Report.
Dias, A. S. Wives, L. K. (2018) Assessment of the Most Relevant Learning Object Metadata: Relieving the Learner-User from Information Overload. In: Proceedings of the 10th International Conference on Computer Supported Education (CSEDU).
Drachsler, H. Verbert, K. Santos, O. and Manouselis, N. (2015) Panorama of Recommender Systems to Support Learning. In: Ricci F., Rokach L., Shapira B. (eds) Recommender Systems Handbook. Springer, Boston, MA, p.421-451.
Gates-Dell-EDUCAUSE - Bill & Melinda Gates Foundation, the Michael and Susan Dell Foundation, and EDUCAUSE (2017) A working definition of personalized learning. Available in: [link]. Access in: 20 jul. 2017.
Ginsberg, M. B. (2015) Excited to Learn: Motivation and Culturally Responsive Teaching. Corwin Press.
iNACOL - International Association for K-12 Online Learning; Patrick, S. Kennedy, K. Powell, A (2013) Mean What You Say: Defining and Integrating Personalized, Blended and Competency Education.
LEADLAB - The LEADLAB Project (2010) Available in: [link]. Access in: 25 feb. 2017.
Manouselis, N. Vuorikari, R., and Assche, F. V. (2010) Collaborative recommendation of e-learning resources: an experimental investigation. In: Journal of Computer Assisted Learning 26(4):227-242. DOI: 10.1111/j.1365-2729.2010.00362.x.
Miliband, D. (2006) Choice and voice in personalized learning. In: OECD, Personalizing education. DOI: 10.1787/9789264036604-2-en.
Overwien, B. (2017) The history of the term Informal Learning. Available in: [link]. Access in: 01 jun. 2018.
Watkins C, Carnell E, Lodge C (2007) Effective Learning in Classrooms. London, Paul Chapman Publishing. DOI= DOI: 10.4135/9781446211472.
Zheng, Y. Mobasher, B. and Burke, R. (2014) Context Recommendation Using Multilabel Classification. In: Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).
Zhuhadar, L. and Butterfield, J. (2014) Analyzing Students Logs in Open Online Courses Using SNA Techniques, In: Proceedings of the 20th Americas Conference on Information Systems, AMCIS 2014, Savannah, Georgia, USA.
Publicado
29/10/2018
Como Citar
DIAS, Alessandro da Silveira; WIVES, Leandro Krug
.
Definition of Learner Choices from Learner-Driven Learning for Ubiquitous e-Learning Systems and its Application in the AdaptWeb Platform. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 29. , 2018, Fortaleza/CE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 118-127.
DOI: https://doi.org/10.5753/cbie.sbie.2018.118.
