2017 5th National Conference on E-Learning &Amp; E-Learning Technologies (ELELTECH) 2017
DOI: 10.1109/eleltech.2017.8074997
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Implementation of learning analytics framework for MOOCs using state-of-the-art in-memory computing

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Cited by 13 publications
(9 citation statements)
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“…In Figure 3:Taxonomy of research literature on learning analytics, the number of publications is grouped based on the objectives of learning analytics, results as in Tabel 2: Objective identification in learning analytics. Aguilar & Valdiviezo-Díaz, 2017;Dirk, Rienties, Mitterlmeier, & Nguyen, 2018;Laveti, Kuppili, Ch, Pal, & Babu, 2017;Pappas, Giannakos, & Sampson, 2017;Serrano-Laguna et al, 2012) Table 2 shows that learning analytics studies are grouped into objectives. Most of the objective research of learning analytics that is often done is (1) monitoring and analysis, (2) assessment and feedback, and (3) prediction and intervention.…”
Section: Results Of the Researchmentioning
confidence: 99%
“…In Figure 3:Taxonomy of research literature on learning analytics, the number of publications is grouped based on the objectives of learning analytics, results as in Tabel 2: Objective identification in learning analytics. Aguilar & Valdiviezo-Díaz, 2017;Dirk, Rienties, Mitterlmeier, & Nguyen, 2018;Laveti, Kuppili, Ch, Pal, & Babu, 2017;Pappas, Giannakos, & Sampson, 2017;Serrano-Laguna et al, 2012) Table 2 shows that learning analytics studies are grouped into objectives. Most of the objective research of learning analytics that is often done is (1) monitoring and analysis, (2) assessment and feedback, and (3) prediction and intervention.…”
Section: Results Of the Researchmentioning
confidence: 99%
“…Devido a esses potenciais, diversas experiências relacionadas ao uso de LA em MOOCs têm sido desenvolvidas. Laveti et al (2017) empregaram LA em uma experiência com a plataforma de MOOCs edX, a fim de calcular a probabilidade de abandono de um curso. Os autores efetuaram cálculos de uma variedade de eventos com o intuito de prever se um estudante permanecerá ou não em um curso.…”
Section: Uso De Learning Analytics Em Moocsunclassified
“…Os autores efetuaram cálculos de uma variedade de eventos com o intuito de prever se um estudante permanecerá ou não em um curso. Para o recolhimento de dados foram considerados: número de acesso dos estudantes; número de navegação em páginas do curso; número de páginas fechadas; quantidade de atividades resolvidas; total de vídeos assistidos; total de visualizações em fóruns; entre outros elementos, totalizando 16 variáveis de análise (Laveti et al, 2017). Lu et al (2017) aplicaram LA em um experimento com um MOOC sobre programação em Python, contendo 102 estudantes inscritos.…”
Section: Uso De Learning Analytics Em Moocsunclassified
“…First, we built models to predict students completing the course, using the dataset grouped by course with all features. Our Random Forest classifier had F β=1 = 79.34% (Table 3.10(i)), in line with some papers that presented accurate classification models to predict student drop out rates through their interaction in the VLE (Shi et al, 2017;Laveti et al, 2017). Next, using only features related to assignment submissions and quiz attempts, we analyzed whether assignment submissions could be used as a predictor of course completion (Andres et al, 2018;Al-Shabandar et al, 2018).…”
Section: Coursementioning
confidence: 57%