Development of a Method for Evaluating Quality of Education in Secondary Schools Using ML Algorithms

Rakhmanov, Ochilbek

doi:10.1145/3369255.3369272

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2021

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Cited by 4 publications

(1 citation statement)

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“…A measure of the linear relationship between and X and Y. In this paper, the correlation coefficients was used to check how well data of sentiment analysis is correlated to scale-rated survey scores [7,15]. P-value.…”

Section: Statistical Measurementsmentioning

confidence: 99%

On Validity of Sentiment Analysis Scores and Development of Classification Model for Student-Lecturer Comments Using Weight-based Approach and Deep Learning

Rakhmanov

2020

Proceedings of the 21st Annual Conference on Information Technology Education

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In this paper, a novel state-of-art classification method was presented for student-lecturer comment classification. Tf-Idf was used to assign weights for each word and several different ANN structures were tested. A large dataset, 52571 comments, was used during training. The results show that developed models clearly overperformed existing classification models in this field. 97% of prediction accuracy was achieved on 3-class dataset, while the prediction accuracy for 5-class dataset was 92%. CCS CONCEPTS • CCS → Applied computing → Education → Computermanaged instruction.

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Section: Statistical Measurementsmentioning

confidence: 99%

On Validity of Sentiment Analysis Scores and Development of Classification Model for Student-Lecturer Comments Using Weight-based Approach and Deep Learning

Rakhmanov

2020

Proceedings of the 21st Annual Conference on Information Technology Education

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An Automated Framework for Swift Lecture Evaluation Using Speech Recognition and NLP

Rakhmanov¹

2021

Communications in Computer and Information Science

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Improving the Prediction Accuracy of Academic Performance of the Freshman Using Wonderlic Personnel Test and Rey-Osterrieth Complex Figure

Rakhmanov

Dane

2021

Communications in Computer and Information Science

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Development of a Method for Evaluating Quality of Education in Secondary Schools Using ML Algorithms

Cited by 4 publications

References 7 publications

On Validity of Sentiment Analysis Scores and Development of Classification Model for Student-Lecturer Comments Using Weight-based Approach and Deep Learning

On Validity of Sentiment Analysis Scores and Development of Classification Model for Student-Lecturer Comments Using Weight-based Approach and Deep Learning

An Automated Framework for Swift Lecture Evaluation Using Speech Recognition and NLP

Improving the Prediction Accuracy of Academic Performance of the Freshman Using Wonderlic Personnel Test and Rey-Osterrieth Complex Figure

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