Improving the learning process with artificial intelligence techniques in engineering education

Education is the key for the development of societies. Improvement of education is closely related to improvement of learning processes. Learning processes can improve if the learning status of the students can be determined accurately. This research firstly aims to determine accurately with artificial intelligence techniques whether learning takes place during and after a lecture. In this context course preparation, course time and post course learning questions were prepared for a selected "Introduction to GAMS optimization software" course. Learning data were collected with the designed web based "E-Learning Analysis Program" by asking the prepared questions to 82 participants. Four different models were created by learning data. Each model is evaluated with Decision Tree, Random Forest, XGBoost and MLP algorithms. As a result of the research, accuracy values for Model 1, Model 2, Model 3 and Model 4 were obtained as 0.82, 0.93, 0.89, 0.93,respectively. And F1-score (precision-recall) values for Model 1, Model 2, Model 3 and Model 4 were obtained as 0.81, 0.92, 0.90, 0.92, respectively. Learning detection has been achieved with high accuracy, precision and recall. Keywords: Artificial Intelligence in Education, Machine Learning, Learning Analytics