Design of an Intelligent Agent for Personalization of Moodle’s Contents

Morales-Rodríguez, María Lucila; Ramírez-Saldivar, José Apolinar; Sánchez-Solís, J. Patricia; Hernández-Ramírez, Arturo

doi:10.13053/rcs-56-1-1

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Literature Review1

Koncepcinis E Testo Duomenų Modelis1

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2014

2022

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Cited by 3 publications

(2 citation statements)

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“…There exist several proposed frameworks and systems that incorporate agent technology in order to support adaptivity in e-learning environments. It is impossible to mention all of them, but the work presented in Chang and Chen (2012), Morales-Rodríguez et al (2012) and Pitigala Liyanage et al (2013) are worth highlighting. To the best of our knowledge, no work has been done incorporating the concept of the ECA model and agents as a hybrid approach to support adaptivity in e-learning environments.…”

Section: Literature Reviewmentioning

confidence: 99%

A hybrid approach for supporting adaptivity in e-learning environments

Al-Omari

Carter

Chiclana

2016

IJILT

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Section: Literature Reviewmentioning

confidence: 99%

A hybrid approach for supporting adaptivity in e-learning environments

Al-Omari

Carter

Chiclana

2016

IJILT

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“…Modelis susietas su kitais žinomais stilių tyrybos modeliais. VARK klausimynas integruotas į VMA Moodle išmaniąsias mokymo valdymo sistemas (Morales-Rodriguez ir kt., [10]). Studentų studijų stilius Lietuvoje analizavo S. Preidys [12] ir I. Žilinskienė [17].…”

Section: Koncepcinis E Testo Duomenų Modelisunclassified

Exploration of learning styles by applying data mining technologies

Kaklauskienė¹,

Turskienė²

2014

LMR

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The article deals with the possibilities to estimate students’ learning styles by applying data mining technologies and the methods suggested by the VARK learning styles model. Using the method of communication, the VARK learning style model in a chosen respondents’ set was estimated. This enables to formulate recommendations for an author of a distance learning course concerning possibilities of personalisation of a particular distance learning course. The concept-baseddata model was chosen to model the research data. The data of the designed e-test data base was processed by applying five stages of data mining.

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