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The L2L system for second language learning using visualised zoom calls among students
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In: Dey-Plissonneau, Aparajita, Lee, Hyowon orcid:0000-0003-4395-7702 , Pradier, Vincent orcid:0000-0002-7050-6408 , Scriney, Michael orcid:0000-0001-6813-2630 and Smeaton, Alan F. orcid:0000-0003-1028-8389 (2021) The L2L system for second language learning using visualised zoom calls among students. In: 16th European Conference on Technology-Enhanced Learning EC-TEL 2021, 20-24 Sept 2021, Bozen-Bolzano, Italy (Online). ISBN 978-3-030-86435-4 (2021)
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Conversational agent for supporting learners on a MOOC on programming with Java
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Analyzing learners' engagement and behavior in MOOCs on programming with the Codeboard IDE
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Redesigning a Freshman Engineering Course to Promote Active Learning by Flipping the Classroom through the Reuse of MOOCs
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Uncovering flipped-classroom problems at an engineering course on Systems Architecture through data-driven learning design
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Sentiment analysis in MOOCs: a case study
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Abstract:
Proceeding of: 2018 IEEE Global Engineering Education Conference (EDUCON2018), 17-20 April, 2018, Santa Cruz de Tenerife, Canary Islands, Spain. ; Forum messages in MOOCs (Massive Open Online Courses) are the most important source of information about the social interactions happening in these courses. Forum messages can be analyzed to detect patterns and learners' behaviors. Particularly, sentiment analysis (e.g., classification in positive and negative messages) can be used as a first step for identifying complex emotions, such as excitement, frustration or boredom. The aim of this work is to compare different machine learning algorithms for sentiment analysis, using a real case study to check how the results can provide information about learners' emotions or patterns in the MOOC. Both supervised and unsupervised (lexicon-based) algorithms were used for the sentiment analysis. The best approaches found were Random Forest and one lexicon based method, which used dictionaries of words. The analysis of the case study also showed an evolution of the positivity over time with the best moment at the beginning of the course and the worst near the deadlines of peer-review assessments. ; This work has been co-funded by the Madrid Regional Government, through the eMadrid Excellence Network (S2013/ICE-2715), by the European Commission through Erasmus+ projects MOOC-Maker (561533-EPP-1-2015-1-ESEPPKA2-CBHE-JP), SHEILA (562080-EPP-1-2015-1-BEEPPKA3-PI-FORWARD), and LALA (586120-EPP-1-2017-1-ES-EPPKA2-CBHE-JP), and by the Spanish Ministry of Economy and Competitiveness, projects SNOLA (TIN2015-71669-REDT), RESET (TIN2014-53199-C3-1-R) and Smartlet (TIN2017-85179-C3-1-R). The latter is financed by the State Research Agency in Spain (AEI) and the European Regional Development Fund (FEDER). It has also been supported by the Spanish Ministry of Education, Culture and Sport, under a FPU fellowship (FPU016/00526). ; Publicado
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Keyword:
Educación; Learners' behavior; Learning analytics; Machine learning; MOOC (Massive Online Open Course); MOOCs; Sentiment analysis; Telecomunicaciones
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URL: https://doi.org/10.1109/EDUCON.2018.8363409
http://hdl.handle.net/10016/32702
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MyLearningMentor: A Mobile App to Support Learners Participating in MOOCs
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In: ISSN: 0948-695X ; EISSN: 0948-6968 ; Journal of Universal Computer Science ; https://hal.archives-ouvertes.fr/hal-03276858 ; Journal of Universal Computer Science, Graz University of Technology, Institut für Informationssysteme und Computer Medien, 2015, 21 (5), pp.735-753. ⟨10.3217/jucs-021-05-0735⟩ ; http://www.jucs.org/jucs_21_5/my_learning_mentor_a (2015)
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Precise Effectiveness Strategy for Analyzing the Effectiveness of Students with Educational Resources and Activities in MOOCs
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In: ISSN: 0747-5632 ; EISSN: 0747-5632 ; Computers in Human Behavior ; https://hal.archives-ouvertes.fr/hal-03213972 ; Computers in Human Behavior, Elsevier, 2015, 47 (juin 2015), pp.108--118. ⟨10.1016/j.chb.2014.10.003⟩ ; https://www.sciencedirect.com/science/article/pii/S0747563214005263?via%3Dihub (2015)
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MyLearningMentor: A Mobile App to Support Learners Participating in MOOCs
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In: ISSN: 0948-695X ; EISSN: 0948-6968 ; Journal of Universal Computer Science ; https://hal.archives-ouvertes.fr/hal-03213971 ; Journal of Universal Computer Science, Graz University of Technology, Institut für Informationssysteme und Computer Medien, 2015, 21 (5), pp.735--753. ⟨10.3217/jucs-021-05-0735⟩ ; http://www.jucs.org/doi?doi=10.3217/jucs-021-05-0735 (2015)
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