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Frontiers in Educational Research, 2023, 6(4); doi: 10.25236/FER.2023.060408.

Studies on the EFL Assessment Framework Driven by Data Mining Technology

Author(s)

Wen Gong

Corresponding Author:
Wen Gong
Affiliation(s)

School of Foreign Studies, Lingnan Normal University, Zhanjiang, Guangdong, 524000, China

Abstract

This essay looks at how data mining technology is used in the assessment of EFL instruction. The accuracy of traditional assessment methods are constrained because they rely on subjective indicators rather than objective criteria. Data mining technology can be utilized as a useful method to assess college English instruction and offer in-depth analysis of the procedure. By seeing patterns and trends in the data, it can assist in enhancing the assessment's accuracy and validity. Data mining techniques are used to find patterns in datasets and reveal correlations between variables. The literature on data mining and its applications to the evaluation of college English education is reviewed in this study. It also discusses the advantages of data mining and looks into the difficulties associated with its application. Additionally, this study suggests and effectively executes a way for data mining implementation in college English teaching assessment. It implies that data mining is a valuable technique that can enhance the timeliness and accuracy of the evaluation process. With regard to the potential of data mining for the evaluation of college English education, the research offers helpful insights for administrators and educators.

Keywords

EFL; assessment framework; data mining technology; U Campus; big data

Cite This Paper

Wen Gong. Studies on the EFL Assessment Framework Driven by Data Mining Technology. Frontiers in Educational Research (2023) Vol. 6, Issue 4: 40-47. https://doi.org/10.25236/FER.2023.060408.

References

[1] Boontam P. & Phoocharoensil, S. (2018) “Effectiveness of English Preposition Learning Through Data-Driven Learning (DDL)”. 3L The Southeast Asian Journal of English Language Studies, vol. 24, number 3.

[2] Cui Y. (2021) “Research on The Design of Lexical-chunks Centered Mode of Writing under Artificial Intelligence in College English Course”. 2021 2nd International Conference on Big Data and Informatization Education, April.

[3] Gong W. (2023). “Reshaping the EFL Formative Assessment with Blockchain Technology”. International Journal of English Linguistics, vol. 13, number 1.

[4] Gong W. (2022 a). “An Empirical Study of College English Smart Teaching Driven by Intelligent Technology. Asia-Pacific Journal of Humanities and Social Sciences, vol. 2, number 3, 165-172. 

[5] Gong W. (2022 b). “Research on Foreign Language Cloud-based Examination Driven by Intelligent Technology.” Advances in Social Science, Education and Humanities Research, volume 637, 205-210. 

[6] Gong W. (2021). “Design and Implementation of EFL Blended Smart Teaching Based on Rain Classroom.” Frontiers in Educational Research, volume 4, issue 9, 43-49.

[7] Öztürk G. & Gürbüz, N. (2017) “Re-defining Language Teacher Cognition Through A Data-driven Model: The Case of Three EFL Teachers", Cogent Education, vol. 4, issue 1.

[8] Lin M. H. & Lee J.Y. (2015) “Data-driven Learning: Changing the Teaching of Grammar in EFL Classes”. ELT Journal, vol. 69, number 3.

[9] Zeide E. (2017) “The Structural Consequences of Big Data-Driven Education”. Big Data, vol. 5, number 2.

[10] Zhen Li. (2019) “The Formation of Core Qualities of Teachers in Higher Vocational Colleges under Big Data”. Science Innovation, vol. 7, issue 1.