This study aims to conduct a comparative study of Bagging and Boosting algorithms among ensemble methods and to compare the classification performance of TreeNet and Random Forest methods using these algorithms on the data extracted from ABIDE application in education. The main factor in choosing them for analyses is that they are Ensemble methods…

Exploring the relationship between student ability and test-taking effort is an important area of study, offering insights into their approach to educational assessments. Previous research shows this relationship, yet there is a scarcity of research comparing the test-taking effort of students. In addition, researchers have frequently employed…

We report on an innovative design of algorithmic analysis that supports automatic online assessment of students' exploration of geometry propositions in a dynamic geometry environment. We hypothesized that difficulties with and misuse of terms or logic in conjectures are rooted in the early exploration stages of inquiry. We developed a generic…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…