Academic Journal

Assessment of Students’ Achievements and Competencies in Mathematics Using CART and CART Ensembles and Bagging with Combined Model Improvement by MARS

التفاصيل البيبلوغرافية
العنوان: Assessment of Students’ Achievements and Competencies in Mathematics Using CART and CART Ensembles and Bagging with Combined Model Improvement by MARS
المؤلفون: Snezhana Gocheva-Ilieva, Hristina Kulina, Atanas Ivanov
المصدر: Mathematics, Vol 9, Iss 1, p 62 (2020)
بيانات النشر: MDPI AG, 2020.
سنة النشر: 2020
المجموعة: LCC:Mathematics
مصطلحات موضوعية: mathematical competency, assessment, machine learning, classification and regression tree, CART ensembles and bagging, ensemble model, Mathematics, QA1-939
الوصف: The aim of this study is to evaluate students’ achievements in mathematics using three machine learning regression methods: classification and regression trees (CART), CART ensembles and bagging (CART-EB) and multivariate adaptive regression splines (MARS). A novel ensemble methodology is proposed based on the combination of CART and CART-EB models in a new ensemble to regress the actual data using MARS. Results of a final exam test, control and home assignments, and other learning activities to assess students’ knowledge and competencies in applied mathematics are examined. The exam test combines problems on elements of mathematical analysis, statistics and a small practical project. The project is the new competence-oriented element, which requires students to formulate problems themselves, to choose different solutions and to use or not use specialized software. Initially, empirical data are statistically modeled using six CART and six CART-EB competing models. The models achieve a goodness-of-fit up to 96% to actual data. The impact of the examined factors on the students’ success at the final exam is determined. Using the best of these models and proposed novel ensemble procedure, final MARS models are built that outperform the other models for predicting the achievements of students in applied mathematics.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2227-7390
Relation: https://www.mdpi.com/2227-7390/9/1/62; https://doaj.org/toc/2227-7390
DOI: 10.3390/math9010062
URL الوصول: https://doaj.org/article/21f0e9e606054918b349e530c6c5c84c
رقم الانضمام: edsdoj.21f0e9e606054918b349e530c6c5c84c
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22277390
DOI:10.3390/math9010062