A Resource Recommendation Algorithm for Online English Learning Systems Based on Learning Ability Evaluation

Zhou, Zhenfang

doi:10.3991/ijet.v16i09.22745

Cited by 8 publications

(4 citation statements)

References 24 publications

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“…Khosravi et al in [8] studied another aspect of a personalized learning engine for helping students to find resources based on their interests and knowledge gaps. These learning resource recommendations, however, are limited to a few specific subjects [9] and do not take into account question types.…”

Section: Related Workmentioning

confidence: 99%

Question-Type Identification for Academic Questions in Online Learning Platform

Rabiee¹,

Goel²,

Johnson³

et al. 2023

Signal Image Processing and Multimedia

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Online learning platforms provide learning materials and answers to students' academic questions by experts, peers, or systems. This paper explores question-type identification as a step in content understanding for an online learning platform. The aim of the question-type identifier is to categorize question types based on their structure and complexity, using the question text, subject, and structural features. We have defined twelve question-type classes, including Multiple-Choice Question (MCQ), essay, and others. We have compiled an internal dataset of students' questions and used a combination of weak-supervision techniques and manual annotation. We then trained a BERT-based ensemble model on this dataset and evaluated this model on a separate human-labeled test set. Our experiments yielded an F1-score of 0.94 for MCQ binary classification and promising results for 12-class multilabel classification. We deployed the model in our online learning platform as a crucial enabler for content understanding to enhance the student learning experience.

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Section: Related Workmentioning

confidence: 99%

Question-Type Identification for Academic Questions in Online Learning Platform

Rabiee¹,

Goel²,

Johnson³

et al. 2023

Signal Image Processing and Multimedia

View full text Add to dashboard Cite

show abstract

“…The traditional recommendation methods for English learning resources cannot meet the needs of students for in-depth learning. To solve the problem, Zhou [23] designed a resource recommendation algorithm for online English learning systems, based on learning ability evaluation, introduced the workflow of the algorithm, and developed a four-layer test system for evaluating English learning ability. Their results provide a reference for resource recommendation of other online learning systems.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Filtering Recommendation of Online Learning Resources Based on Knowledge Association Model

Jia

Yang²,

Cui

2022

Int. J. Emerg. Technol. Learn.

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Online learning platforms are prone to information overload, as they contain a huge number of diverse resources. To solve the problem, domestic and foreign scholars have focused their attention on personalized recommendation of learning resources. However, the existing studies perform poorly in the prediction of online learning paths, failing to clarify the overall knowledge system of students and the associations of resource knowledge. Therefore, this paper explores the collaborative filtering recommendation (CFR) of online learning resources (OLRs) based on knowledge association model. Firstly, the knowledge units were extracted from the semantic information of OLRs, and a knowledge association model was established for OLR recommendation. Next, a CFR algorithm was designed to couple semantic adjacency with learning interest, and used to quantify the semantic similarity of OLRs. The proposed algorithm was proved effective through experiments.

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“…Distance English education platforms like ABC360 and Rocky English provides a new learning model, which facilitates the autonomous English learning [11][12][13][14][15][16]. Given a computer or smartphone with Internet access, students can learn English autonomously anytime, anywhere, including applied oral English like English for overseas studies and workplaces [17][18][19][20][21][22][23][24]. With students as the subjects, the autonomous English learning is immune to the interference from any people or things.…”

Section: Introductionmentioning

confidence: 99%

Big Data-Based Behavior Analysis of Autonomous English Learning in Distance Education

Han¹

2022

Int. J. Emerg. Technol. Learn.

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Distance English education platforms like ABC360 and Rocky English provides a new learning model, which facilitates the autonomous English learning. This study aims to clarify the relationship between learning process and learning efficiency of distance English education, and provide personalized services for distance English teaching. To this end, we carried out a big data analysis on the behavior of autonomous English learning in distance education, in a bid to reveal the learning law and behavior pattern of the learners. Section 2 provides the research strategy for the motivation and behavior of autonomous English learning in distance education, and establishes a research model for such motivation and behavior. Section 3 constructs a behavior analysis model for autonomous English learning in distance education, computes the correlation between the target autonomous learning resources (ALRs) and the series of clicked ALRs, and calculates the probability for autonomous English learners in distance education to click on new resources. The proposed network model can handle a massive amount of learning behavior data, i.e., boast a certain ability to process the big data. The three parts of the model were introduced in details. The effectiveness of the model was demonstrated through experiments.

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A Resource Recommendation Algorithm for Online English Learning Systems Based on Learning Ability Evaluation

Cited by 8 publications

References 24 publications

Question-Type Identification for Academic Questions in Online Learning Platform

Question-Type Identification for Academic Questions in Online Learning Platform

Collaborative Filtering Recommendation of Online Learning Resources Based on Knowledge Association Model

Big Data-Based Behavior Analysis of Autonomous English Learning in Distance Education

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