An ontology model for content recommendation in personalized learning environment

Learning analytics and collaborative groups of learners in distance education: a systematic mapping study

“…The main recommendation systems have similar characteristics, namely, they are based on the analysis of student profiles and mostly offer learning content recommendation (Sharma and Ahuja, 2016;Venugopalan et al, 2016;Chanaa and Faddouli, 2018;Joy et al, 2019;Kim and Kim, 2020), recommendation of learning objects (Kapembe and Quenum, 2019), exercise recommendation (Huang et al, 2019), course recommendation (El Moustamid et al, 2017;Dahdouh et al, 2019) and learning resources (Chen et al, 2020).…”

“…The benefits categorized as intelligent services are: learning management system (Lavoie and Proulx, 2019), semantic recommendation using ontology (Sharma and Ahuja, 2016); hybrid recommendation based on student profile (Kapembe and Quenum, 2019); deep reinforcement learning structure (Huang et al, 2019); decision-making system (El Fouki et al, 2017), content-based recommendation system (Venugopalan et al, 2016), domain-specific language (Balderas et al, 2013), WAVE architecture (Manhães et al, 2014), intelligent teaching assistant system (Wang et al, 2019), profile analysis system (El Moustamid et al, 2017), algorithm based on the technique of optimizing ant colonies (Kozierkiewicz-Hetmańska and Zyśk, 2013), prototype indicators (Florian et al, 2011), online learning systems based on big data technologies (Dahdouh et al, 2018), agentbased recommendation system, Java2D technology-based e-learning system (Hamada, 2012), ID based recommendation system (Zakrzewska, 2012;Anaya et al, 2013), capture system (Lagman and Mansul, 2017), custom model (Chanaa and Faddouli, 2018), ontology model (Joy et al, 2019), evaluation tool (Dimopoulos et al, 2013), adaptive recommendation method (Chen et al, 2020), Kernel Context Recommendender System algorithm (Iqbal et al, 2019), distributed course recommendation systems (Dahdouh et al, 2019), custom user interface (Kolekar et al, 2018), recommendation system techniques for educational data mining (Thai-Nghe et al, 2010), individualized artificial intelligence tutor and LBA model (Kim and Kim, 2020) based on a system called SBAN (Zaoudi and Belhadaoui, 2020). The application of methods and techniques of data analysis provide student grade prediction, behavior pattern detection, academic progress forecasting, modeling, course dropout risk prediction, also providing student performance feedback to teachers.…”

“…The identification and presentation of clusters point to the main terms explored in the final corpus comprising 51 articles. After analyzing the 48 grouping terms, 6 terms were identified that stand out as a search trend, being: recommendation system (Thai-Nghe et al, 2010;Anaya et al, 2013;Venugopalan et al, 2016;Kapembe and Quenum, 2019;Iqbal et al, 2019;Dahdouh et al, 2019), educational data mining (Thai-Nghe et al, 2010;Lara et al, 2014;Olivé et al, 2018), analysis (Zorrilla et al, 2010;Graf et al, 2011;Olanrewaju et al, 2016;Ros et al, 2017;Peñafiel et al, 2018;Uzir et al, 2020), learning management system (Okubo et al, 2017;Olivé et al, 2018;Chanaa and Faddouli, 2018;Lavoie and Proulx, 2019), e-learning and platform e-learning (Chang and Chu, 2010;Zorrilla et al, 2010;Hamada, 2012;Anaya et al, 2013;Olanrewaju et al, 2016;Omar and Abdesselam, 2017;El Fouki et al, 2017;Lagman and Mansul, 2017;Clarizia et al, 2018;Joy et al, 2019;Dahdouh et al, 2019). These terms are within the red, blue and green clusters, and they have connections with each other and connections to the other clusters.…”

A Literature Review on Intelligent Services Applied to Distance Learning

“…Joy et al [35] proposed an ontology to integrate the student's profile and the attributes of the learning objects. The ontology conceptualizes the characteristics of the student and the learning object and suggests an adaptive learning environment.…”

“…The results of the experience indicated that the proposed model can generate and recommend qualified and personalized learning paths to improve learning experiences. Joy et al [35] Ontology model that encompasses the student profile and learning object attributes, which can be used for recommending content on an e-learning platform.…”