2017
DOI: 10.1007/s10639-017-9637-7
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Learning path recommendation based on modified variable length genetic algorithm

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Cited by 117 publications
(76 citation statements)
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“…Considering the educational context and its inherent diversity of search and optimization problems, the use of bio-inspired evolutionary algorithms to seek for solutions and solve optimization problems is an interesting strategy to support personalized recommendation of LOs [Bhaskaran and Santhi 2017, Kurilovas et al 2014, Dwivedi et al 2018. According to [Krishnanand et al 2009], bio-inspired evolutionary algorithms are probabilistic search methods that simulate the evolution or the behavior 2 http://dbpedia.org/sparql IX Congresso Brasileiro de Informática na Educação (CBIE 2020) Anais do XXXI Simpósio Brasileiro de Informática na Educação (SBIE 2020) of biological entities.…”
Section: Background and Related Workmentioning
confidence: 99%
“…Considering the educational context and its inherent diversity of search and optimization problems, the use of bio-inspired evolutionary algorithms to seek for solutions and solve optimization problems is an interesting strategy to support personalized recommendation of LOs [Bhaskaran and Santhi 2017, Kurilovas et al 2014, Dwivedi et al 2018. According to [Krishnanand et al 2009], bio-inspired evolutionary algorithms are probabilistic search methods that simulate the evolution or the behavior 2 http://dbpedia.org/sparql IX Congresso Brasileiro de Informática na Educação (CBIE 2020) Anais do XXXI Simpósio Brasileiro de Informática na Educação (SBIE 2020) of biological entities.…”
Section: Background and Related Workmentioning
confidence: 99%
“…Recently, [21] relied on deep learning, precisely LSTM associated with clustering. [3] focused on students learning styles and knowledge levels with a variable length genetic algorithm to recommend personalised LPs. Few years ago, Bayes theorem, Association Link Network, Item Response Theory, graph theory were studied to form and recommend LPs.…”
Section: Learning Path Recommender Systemsmentioning
confidence: 99%
“…However, other approaches are based on previous knowledge www.ijacsa.thesai.org and log file of online activities [1]; therefore, the seminar taken adequately by learner interacts with individual preference [1]. The reference [2] proposed a genetic algorithm to sequence learning path based on learner preferences. Learning analytics provides tools for collecting analyzing data about learners to optimize learning.…”
Section: Learning Pathsmentioning
confidence: 99%