From mateja.skraba at ijs.si Fri Jan 12 13:18:13 2024 From: mateja.skraba at ijs.si (Mateja Skraba) Date: Fri, 12 Jan 2024 12:18:13 +0000 Subject: [Solomonov Seminar] 292. Solomonov seminar Message-ID: <404D1607-950E-4332-9B44-F63225C965AF@ijs.si> V petek, 19. januarja 2024 bo ob 11ih v Veliki predavalnici (prvo nadstropje glavne stavbe) 292. Solomonov seminar. Velika predavalnica je v drugem nadstropju glavne stavbe IJS na Jamovi 39. Posnetki preteklih seminarjev so na http://videolectures.net/solomon/ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Ttile: Educational Recommender System to Diagnose and Promote Collaboration in Virtual Learning Environments Lecturer: Antônio Moraes Neto A software can recommend interactions among students in a Virtual Learning Environment (VLE) for the purpose of supporting collaborative learning. However, assessing collaboration in this environment to continuously encourage learning remains a challenge. The research Educational Recommender System (ERS) to Diagnose and Promote Collaboration in VLEs addresses the implementation of an ERS that adopts the Conversational Analysis (CA) to diagnose students’ collaboration and make recommendations in order to promote collaborative learning in discussion forums of a VLE. From literature review, indicators, obtained through a CA layer, were established to: (1) characterize the amount of students’ responses to each message, (2) point out each student message that contains a question, and (3) infer the topic with the highest word distribution in each discussion forum. Then, the Students Collaboration Level (SCL) of each message is formed by the average of these indicators. Based on experiments, a CA strategy to determine the level of collaboration among students and possibilities for intervention in favor of collaborative learning are pointed out. The results corroborate the relevance of the recommendations made based on the indicators and the SCL, which, in general, motivated participation and collaboration. A mechanism is being developed to make recommendations available to students and teachers, in addition a knowledge modeling will be done, utilizing machine learning with Python, to reveal the most appropriate recommendations in each monitored forum. The said research is advised by Professor Márcia Fernandes, co-advised by Professor Tel Amiel, and developed under the Federal University of Uberlândia Computer Science Program (PPGCO) by doctoral student Antônio J. Moraes Neto, which has been working with Information and Communication Technologies (ICT) since 1987 and has been teaching since 1994 in vocational schools. In two graduations, he majored in Management of Information Systems (1994) and in High School Teaching (1996). He specialized in Linux Network Management (2006) and Software Engineering (2008). Develops research in educational technologies. He has a master's degree in Education (2016), carried out in the area of Education, Technologies and Communication. Since 2019, he is a doctoral student in the PPGCO in the Artificial Intelligence Applied to Distance Learning area. He has been developing research in these areas: professional education, educational technology or informatics in education, computer-supported collaborative learning, distance learning; artificial intelligence in education, educational data mining, and educational software engineering. The following papers can be highlighted. § Moraes Neto, A. J., & Fernandes, M. A. (2019). Chatbot and Conversational Analysis to Promote Collaborative Learning in Distance Education. 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), 2161-377X, 324–326. https://doi.org/10.1109/ICALT.2019.00102. § Moraes Neto, A. J., Fernandes, M. A., & Amiel, T. (2020). Chatbot e Análise Conversacional para Recomendação da Aprendizagem Colaborativa na EaD. Anais do Simpósio Brasileiro de Informática na Educação, 1142–1151. https://doi.org/10.5753/cbie.sbie.2020.1142. § Moraes Neto, A. J., Costa, N. T., Fernandes, M. A., & Amiel, T. (2022). Análise Conversacional para Diagnosticar e Recomendar a Colaboração em Ambientes Virtuais de Aprendizagem. Anais do Simpósio Brasileiro de Informática na Educação, 1209–1221. https://doi.org/10.5753/sbie.2022.225776. § Moraes Neto, A. J., Fernandes, M. A., & Amiel, T. (2022). Conversational Analysis to Recommend Collaborative Learning in Distance Education. 196–203. https://www.scitepress.org/Link.aspx?doi=10.5220/0011092600003182. _______________________________________________ -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 4287 bytes Desc: not available URL: