A personalized English learning recommender system for ESL students

Hsu, Mei‐Hua

doi:10.1016/j.eswa.2006.10.004

Cited by 133 publications

(64 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Somehow, the encouraged researchers combine some adopted machine learning techniques or approaches [7] with contentbased filtering or collaborative filtering to emerge the artificial intelligent (AI) aspects in it [38,[41][42][43][44][45]. For example, [11] proposed user-oriented content-based recommender system (UCB-RS) [11] with two stages.…”

Section: Literature Backgroundmentioning

confidence: 99%

Retracted: E-Learning Recommender Systems Based on Goal-Based Hybrid Filtering

Chughtai

Selamat

Ghani

et al. 2014

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

This research work is based on the thesis contribution by proposing the goal-based hybrid filtering approach in e-learning recommender systems (eLearningRecSys). The proposed work has been used to analyze the personalized similarities between learner's profile preferences collaboratively. The proposed work consists of two hybridizations: the first hybridization has been made with content-based filtering and collaborative features to overcome the new-learners zero-rated profile recommendations issue; the second hybridization has been done with collaborative filtering and k-neighborhood scheme features to improve the averagelearner's low-rated profile recommendations issue. Therefore, the proposed goal-based hybrid filtering approach that hybridized content-based filtering, collaborative filtering and k-neighborhood features simultaneously works on both types of learner's profiles recommendation issues in e-learning environments. The experiments in the proposed work are done using the famous "MovieLens" dataset, while the evaluation of experimental results has been performed with mean of precision 83.44% and mean of recall 85.22%, respectively. t-test result shows the probability difference value of 0.29 between the proposed hybrid approach and the evaluated literature work. The results demonstrate the effectiveness of the proposed hybrid recommender systems in e-learning scenarios.

show abstract

Section: Literature Backgroundmentioning

confidence: 99%

Retracted: E-Learning Recommender Systems Based on Goal-Based Hybrid Filtering

Chughtai

Selamat

Ghani

et al. 2014

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…In the process of integration, the elements of curriculum form organic connection and organic structure. Instead of adding different subjects together, it regards the curriculum as a whole and integrates the knowledge of different disciplines, so that students can master different knowledge unconsciously and organically in the process of learning so as to improve their comprehensive quality [2]. Curriculum integration emphasizes the connection and consistency between different disciplines, and avoids premature or overemphasis on the boundaries between different disciplines so as to prevent isolation, repetition or disconnection between different fields.…”

Section: B Maintaining the Integrity Of The Specificationsmentioning

confidence: 99%

The Application of Information Technology in English Education and Reform

Xiao¹,

Wang²

2017

Proceedings of the International Conference on Education Innovation and Social Science (ICEISS 2017)

View full text Add to dashboard Cite

Abstract-Under the guidance of constructivism theory, information technology provides a good learning environment for College English teaching, so that students can establish truly dominant position, make the independent learning and collaborative learning. The purpose for the application of information is to realize the lifelong education and learning society possible, which has greatly effects to students' learning motivation, cultivate innovation and practice ability. The integration of information technology and College English curriculum cannot stay at the tool level. Teachers should explore the teaching design and teaching strategies in order to form a teaching model, combine teaching theory and practice to promote the thorough reform of English teaching.

show abstract

“…The item response theory introduced in the previous chapter plays an important role in the process of selecting exercises and exam questions. By choosing adaptive questions, we can promote the enthusiasm of learning and understand our failure in knowledge [12][13].…”

Section: Analysis Of Demands For English Learning Systemmentioning

confidence: 99%

Design Flow of English Learning System Based on Item Response Theory

Liu

Zhao

2017

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

Abstract-The popularity of computer technology in English teaching has led to the establishment of many English learning platforms, but the enhancement of students' English proficiency is limited due to the lack of relevance, self-adaptive test questions and analytical ability. The project management theory is introduced into English learning, which can provide students with teaching content and test questions that are more suitable for their own actual situation through a more intelligent, personalized way. At the same time, the static and dynamic database model based on students' own learning behavior is constructed to facilitate storage of students' learning record. Combined with the advantages of hierarchical selection, SH method and improved polynomial model, this paper puts forward a new type of item section model. This paper introduces the basic theory and related technology, and then makes an in-depth study on the demand analysis of English learning system. Finally, this paper realizes the design of English learning system based on item response theory and validates the good effect of English item selection from the perspective of application. The system provides teachers and students with convenient learning strategies, item selection strategies, test strategies and academic performance strategies. The introduction of item response theory enables the system to become truly student-centered and provides a more comprehensive and selfadaptive learning model, which is of great significance for improving the learning efficiency of English learning and the learning efficiency of college students in China.Keywords-item response theory, English learning, data model, item selection model, system requirements IntroductionThe rapid development of Internet technology and computer technology has pushed the process of network information modernization. Computer network technology has permeated into various fields and is widely applied in English teaching field. The English learning platform and system designed and created with the help of computer network technology have improved the English proficiency of students in China. However, the shortcomings like the lack of relevance, self-adaptive test questions and analytical ability can be found in most systems [1]. In view of the shortcomings iJET

show abstract

A personalized English learning recommender system for ESL students

Cited by 133 publications

References 19 publications

Retracted: E-Learning Recommender Systems Based on Goal-Based Hybrid Filtering

Retracted: E-Learning Recommender Systems Based on Goal-Based Hybrid Filtering

The Application of Information Technology in English Education and Reform

Design Flow of English Learning System Based on Item Response Theory

Contact Info

Product

Resources

About