An Artificial Intelligence Case Based Approach to Motivational Students Assessment in (e)-learning Environments

• Autor(a) principal: Ribeiro, Jorge
• Data de Publicação: 2019
• Outros Autores: Dias, Almeida, Marques, José, Ávidos, Lliliana, Araújo, Isabel, Araújo, Nuno, Figueiredo, Margarida
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10174/25561; https://doi.org/10.1145/3306500.3306515
• topic: (e)-Learning Environments; Students Motivational Assessment; Artificial Intelligence; Logic Programming; Representation and Reasoning; Case Based Reasoning; Decision Support Systems

In the last decades effective teaching and learning and e-learning environments have been performed in order to construct courses jointly with the collaboration with Industry and High-Level Educational Institutions. On another way there are several terminologies that attempt to specify the best teaching and learning methods applied to engineering, from problem-based learning, project-based learning, work-based learning, teamlearning, self-direct learning for example. However motivational studies and motivational scales typically discard uncertainty characteristic in for quantitatively evaluating the different dimensions on student’s motivational assessment in (e)-learning environments. This paper presents a computerized framework grounded on Artificial Intelligence techniques, namely the Case Based Reasoning approach for problem solving, complemented with a Knowledge Representation and Reasoning method that considers unknown, incomplete or even self-contradictory data or knowledge in the motivational student’s assessment.