ARTICLE

PREDICTION OF STUDENT ACHIEVEMENT THROUGH TEACHERS PROFESSIONAL CHARACTERISTICS BY USING ARTIFICIAL INTELLIGENCE

  1. HOME
  2. ARTICLE

31 Pages : 325-339

http://dx.doi.org/10.31703/gesr.2022(VII-II).31      10.31703/gesr.2022(VII-II).31      Published : Jun 2022

Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence

Abstract

    Teacher characteristics are important for teaching learning and are important predictors of students' achievement. The present study aims to predict students' academic achievement criteria on teachers' characteristics with the help of artificial intelligence (AI). The data were collected from 100 students from one of the universities in Lahore, Pakistan, through a questionnaire comprising of teachers' characteristics effective for teaching, against a 4-point scale varying from strongly agree to strongly disagree to the find extant of the existence of certain characteristics in the teachers. The analysis was done to predict the student grade based on teacher characteristics in the class with the help of artificial intelligence. Two machine learning models were built, and their accuracy was compared. Thek-Nearest Neighbor (KNN) and Multiple Linear Regression (MLR) models were built. The accuracies of the KNN and MLR were 83 Percent and 91 Percent, respectively. This work concluded that the MLR model could be effectively used to predict student performance.

    K-NN, MLR, AI, Student Grade, SVM

    (1) Muhammad Ismail Sheikh
    BS B.ed Hons(2018-2022) University of Education, Lahore, Punjab, Pakistan.
    (2) Haseeb Ahmad
    BS Electrical Engineering(2018-2022) Comsats University, Lahore, Punjab, Pakistan.
    (3) Huma Lodhi
    Assistant Professor, University of Education, Lahore, Punjab, Pakistan
Fulltext PDF

References

  • Aissaoui, O., Madani, Y., Oughdir, L., Dakkak, A., & el ALLIOUI, Y. (2020). A Multiple Linear Regression-Based Approach to Predict Student Performance. https://doi.org/10.1007/978-3-030-36653-7_2
  • Bakhshinategh, B., Zaïane, O., Elatia, S., & Ipperciel, D. (2018). Educational data mining applications and tasks: A survey of the last 10 years. Education and Information Technologies, 23. https://doi.org/10.1007/s10639-017-9616-z
  • Gadhavi, M., Smt., & Patel, C. M. (2017). Student final grade prediction based on linear regression.
  • Ihsan Zul, M. (2016). Prediction of Student Final Grade by using k-Nearest Neighbor Algorithm.
  • Kaya Uyanık, G., & Güler, N. (2013). A Study on Multiple Linear Regression Analysis. Procedia - Social and Behavioral Sciences, 106, 234–240. https://doi.org/10.1016/j.sbspro.2013.12.027
  • Walker, R. (2008). Twelve Characteristics of an Effective Teacher: A Longitudinal, Qualitative, Quasi-Research Study of In- Service and Pre-Service Teachers’ Opinions. Educational Horizons, 87
  • Wook, M., Yahaya, Y. H., Wahab, N., Isa, M. R. M., Awang, N. F., & Seong, H. Y. (2009). Predicting NDUM Student’s Academic Performance Using Data Mining Techniques. 2009 Second International Conference on Computer and Electrical Engineering, 2, 357–361. https://doi.org/10.1109/ICCEE.2009.168
  • Zamanian, J., & Saeidi, M. (2017). Iranian EFL Teachers’ Perceptions, Practices and Problems Regarding Raising Students’ Intercultural Awareness. International Journal of English Linguistics, 7, 257 https://doi.org/10.5539/ijel.v7n4p257
  • Zhang, Z. (2016). Introduction to machine learning: K-nearest neighbors. Annals of Translational Medicine, 4, 218. https://doi.org/10.21037/atm.2016.03.37

Cite this article

APA

    APA : Sheikh, M. I., Ahmad, H., & Lodhi, H. (2022). Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence. Global Educational Studies Review, VII(II), 325-339. https://doi.org/10.31703/gesr.2022(VII-II).31

CHICAGO

    CHICAGO : Sheikh, Muhammad Ismail, Haseeb Ahmad, and Huma Lodhi. 2022. "Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence." Global Educational Studies Review, VII (II): 325-339 doi: 10.31703/gesr.2022(VII-II).31

HARVARD

    HARVARD : SHEIKH, M. I., AHMAD, H. & LODHI, H. 2022. Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence. Global Educational Studies Review, VII, 325-339.

MHRA

    MHRA : Sheikh, Muhammad Ismail, Haseeb Ahmad, and Huma Lodhi. 2022. "Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence." Global Educational Studies Review, VII: 325-339

MLA

    MLA : Sheikh, Muhammad Ismail, Haseeb Ahmad, and Huma Lodhi. "Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence." Global Educational Studies Review, VII.II (2022): 325-339 Print.

OXFORD

    OXFORD : Sheikh, Muhammad Ismail, Ahmad, Haseeb, and Lodhi, Huma (2022), "Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence", Global Educational Studies Review, VII (II), 325-339

TURABIAN

    TURABIAN : Sheikh, Muhammad Ismail, Haseeb Ahmad, and Huma Lodhi. "Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence." Global Educational Studies Review VII, no. II (2022): 325-339. https://doi.org/10.31703/gesr.2022(VII-II).31