Course Recommender System for Student Enrollment Using Augmented Reality

Anuvareepong, Sakuna; Phooim, Supawadee; Charoenprasoplarp, Nawachon; Vimonratana, Samitra

doi:10.1109/iiai-aai.2017.174

Cited by 9 publications

(4 citation statements)

References 10 publications

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“…Thus the RS in education has different purposes which is summarized in the table. To recommend online courses [32], [43], [17], [46], [6], [57], [53], [33], [42], [38], [21], [60], [54], [31], [7] 2…”

Section: Purposementioning

confidence: 99%

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A Systematic Review of Recommender Systems in Education

Vaidhehi¹,

Suchithra²

2018

IJET

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Recommender system (RS)s are widely used in different walks of life. This research work is to explore the usage of RS in the field of education. This review is performed in five dimensions which includes, Purpose of RS in Education, various techniques to build RS, input parameters used in design of RS, type of students involved in design of RS and Modelling strategies for RS to represent the data. The outcome of the research work is to facilitate the efficient design of the recommender system in education which will help the students by generating the appropriate recommendations.

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Section: Purposementioning

confidence: 99%

“…The various type of students involved in the design of RS is summarized in the table 4. Online students [32], [43], [51], [18], [42], [46], [58], [39], [26], [38], [61], [21], [37], [34] 2 Regular university/college students [23], [49], [15], [8], [17], [52]…”

Section: Types Of Studentsmentioning

confidence: 99%

A Systematic Review of Recommender Systems in Education

Vaidhehi¹,

Suchithra²

2018

IJET

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“…Nevertheless, upon reviewing existing research papers in the field of recommender systems within the education domain [16][17][18], it is evident that the majority of scholars have focused their efforts on the application of recommendation techniques, namely collaborative filtering and content-based filtering. Furthermore, researchers have also explored the integration of compelling technologies like augmented reality [19], machine leaning [20], and data mining technique [21]. with their recommender systems.…”

Section: Introductionmentioning

confidence: 99%

An Online Course Recommender System in e-Learning Using Learners’ Profile and Learning Behavior-Based Mechanism

Charoensuk

2024

IJIET

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The advent of online learning platforms, such as Coursera and Udemy, has facilitated global access to diverse educational opportunities. However, integrating recommender algorithms into these online learning systems presents a notable challenge. To address this challenge, this research paper proposes an architecture for online course recommender systems that leverages learners’ profiles and learning behavior. The proposed architecture comprises six core components: 1) User Management Engine, 2) Online Course Content Management Engine, 3) Learning Behavior Observer and Recorder, 4) Profile and Learning Behavior Builder Engine, 5) Course Recommendation and Filtering Engine, and 6) Feedback Engine. These components collectively form the foundation of the online course recommender system. In order to facilitate practical implementation, a prototype of the online course recommender system has been developed. To evaluate the system’s performance, a comparative analysis was conducted, to compare the personalized recommended list with the non-personalized recommended list. The analysis revealed an average precision of 77.60% for the personalized recommended list, while the non-personalized recommended list achieved an average precision of 65.60%. These findings highlight the superiority of the personalized approach in generating more accurate and relevant online course recommendations.

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“…To solve the problem, this research introduces a Recommender system (RS), which in this context is an artificial intelligence technological assistant tool to support and guide user decisions with relevant information. This can be a great solution for fresh college students, as it efficiently decides the best fit specialization, based on students' preference and information [5].…”

Section: Introductionmentioning

confidence: 99%

Using Recommender Systems for Matching Students with Suitable Specialization: An Exploratory Study at King Abdulaziz University

Alshaikh

Bahurmuz

Torabah

et al. 2021

Int. J. Emerg. Technol. Learn.

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In Saudi Arabia, all high school graduates who want join local universities have to go through a preparatory year before selecting their specific specialization/major. One of the most concerning issues for those fresh undergraduate college students is the selection of their specialization. College specialization selection is critical for them, as their academic and career future will be affected by this decision. An un-suitable specialization selection will have unfortunate consequences, not only on the students' future but also on the university’s resources and budget. This paper sug-gests a solution to this problem by introducing a preliminary study of a recommend-er system (RS), which will recommend the appropriate specialization for the students based on various tests and grades during the preparatory year at King Abdulaziz University (KAU). The proposed system guides students through their specialization selection process based on their abilities. The collaborative filtering technique was used to build the RS and K-fold cross-validation was adopted to evaluate its accura-cy and performance. The results showed the prediction of a specialization for each student with good accuracy ratio. These promising initial results provide a feasible solution to assess this issue further in future studies.

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Course Recommender System for Student Enrollment Using Augmented Reality

Cited by 9 publications

References 10 publications

A Systematic Review of Recommender Systems in Education

A Systematic Review of Recommender Systems in Education

An Online Course Recommender System in e-Learning Using Learners’ Profile and Learning Behavior-Based Mechanism

Using Recommender Systems for Matching Students with Suitable Specialization: An Exploratory Study at King Abdulaziz University

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