Use of Decision Tree and Fuzzy Logic Methods to Predict Academic Achievement of University Freshmen

Author:

Salahli M. A.ORCID,Gasimzade T.,Salahli V.ORCID,Alasgarova F.,Guliyev A.

Publisher

Springer International Publishing

Reference16 articles.

1. Altaher, A., Barukab, O.: Prediction of student’s academic performance based on adaptive neuro-fuzzy inference. Int. J. Comput. Sci. Netw. 17, 165–169 (2018)

2. Mushtaq, I., Khan, S.N.: Factors affecting students’ academic performance. Glob. J. Manag. Bus. Res. 12(9), 17–22 (2012)

3. Alkhasawneh, R., Hargraves, R.H.: Developing a hybrid model to predict student first year retention in STEM disciplines using machine learning techniques. Int. J. STEM Educ. Innov. Res. 15(3), 35–42 (2014). https://doi.org/10.1080/07924360120043621

4. McKenzie, K., Schweitzer, R.: Who succeeds at university? Factors predicting academic performance in first year Australian university students. High. Educ. Res. Dev. 20(1), 21–33 (2010). https://doi.org/10.1080/07924360120043621

5. DeBerard, M.S., Spielmans, G.I., Julka, D.L.: Predictors of academic achievement and retention among college freshmen: a longitudinal study. Coll. Stud. J. 38(1), 66–80 (2004)

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