The aim of this study was to investigate the extent to which pre-service teachers' belief in academic engagement, student burnout, and proactive strategies predicts academic self-efficacy through machine learning approach. The study group consisted of 446 pre-service teachers at Sivas Cumhuriyet University, Faculty of Education. The Academic…

Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source data. The…

In recent years, there has been an increase in the demand for higher education in Turkey, where the demand, as in most other countries, exceeds what is available. The main purpose of this research is to develop machine learning algorithms for predicting the percentage of student placement based on the data related to the university's academic…

The aim of this study is to investigate the causes of reading problems experienced by third-grade students because of the instructional malpractices in education and develop a modeling with artificial neural networks. It was carried out according to the exploratory sequential model and consisted of two stages. In the qualitative part, a data pool…

The purpose of this research is a comprehensive review of studies towards educational data mining (EDM) in Turkey. For the purpose of this study, graduate theses and articles conducted in Turkey were examined in detail. As a result of the literature review, 48 studies were analyzed in the context of the data mining purpose, the technique used in…

In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes. As part of comparison of normalization methods, input variables were set as: work discipline, environmental awareness, instrumental motivation, science self-efficacy, and weekly…

This study aims to predict the final exam scores and pass/fail rates of the students taking the Basic Information Technologies -- 1 (BIL101U) course in 2014-2015 and 2015-2016 academic years in the Open Education System of Anadolu University, through Artificial Neural Networks (ANN). In this research, data about the demographics, educational…

In this study, it was aimed to compare the predictions of the academic achievement of the artificial neural networks (ANN) run in MATLAB and SPSS software and to determine the factors related to their academic achievement. Sample consisted of 465 students who were studying at Grade 4 in primary schools in the Central Anatolian Region of Turkey in…

Writing in L2 is both crucial and difficult for teachers and students since most of the assessment in higher education is in written form. The production of texts as well as providing feedback to them requires time and effort on both sides. For this reason, prediction of future L2 writing performance in advance may prove quite useful both for…

This study aims to predict the academic achievements of Turkish and Malaysian vocational and technical high school (VTS) students in science courses (physics, chemistry and biology) through artificial neural networks (ANN) and to put forth the measures to be taken against their failure. The study population consisted of 10th and 11th grade 922 VTS…

Turkey is ranked at the 54th out of 72 countries in terms of science achievement in the Programme for International Student Assessment (PISA) survey conducted in 2015, which is a very big disappointment for that country. The aim of this research was to determine factors affecting Turkish students' science achievements in order to identify the…

The purpose of this study is to examine a neural network based approach to predict achievement in graduate education for Elementary Mathematics prospective teachers. With the help of this study, it can be possible to make an effective prediction regarding the students' achievement in graduate education with Artificial Neural Networks (ANN). Two…

This study predicts the number of correct answers given by pre-service classroom teachers in Civil Servant Recruitment Examination's (CSRE) educational sciences test based on their high school grade point averages, university entrance scores, and grades (mid-term and final exams) from their undergraduate educational courses. This study was…

The ability to predict the success of students when they enter a graduate program is critical for educational institutions because it allows them to develop strategic programs that will help improve students' performances during their stay at an institution. In this study, we present the results of an experimental comparison study of Logistic…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…