Pdf Predicting Students Performance In Distance Learning Using

Comparison Of Predicting Students Performance Using Machine Learning It compares some of the state of the art learning algorithms to find out which algorithm is more appropriate not only to predict student’s performance accurately, but also to be used as an educational supporting tool for tutors. By analyzing data on learner behavior, engagement patterns, and performance metrics, machine learning algorithms can identify trends and make predictions, enabling personalized learning experiences and targeted interventions that enhance educational outcomes.

Pdf Predicting Students Academic Performance Using E Learning Logs This study proposed a model that predicts the academic achievements of primary, secondary, and high school students who receive education with the learning management system in the distance education process using data mining methods. 7 different models were created with data mining methods. This study proposes the employment of several active learning algorithms to predict students performance in higher education and more speci cally in distance ’ education. Student performance m. sc. thesis, 35 pages june 2017 this thesis examines the application of machine learning algorithms t. predict whether a student will be successful or not. the specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in term. Students’ marks in the first assessment and quiz scores in conjunction with social factors are used to predict students’ final performance in online course.

Pdf Student Performulator Predicting Students Academic Performance Student performance m. sc. thesis, 35 pages june 2017 this thesis examines the application of machine learning algorithms t. predict whether a student will be successful or not. the specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in term. Students’ marks in the first assessment and quiz scores in conjunction with social factors are used to predict students’ final performance in online course. This study aims to predict unknown course grades based on students’ previous learning situations and use clustering algorithms to identify similar learning situations, thereby improving. The scope of this work is to compare some of the state of the art learning algorithms. two experiments have been conducted with six algorithms, which were trained using data sets provided by the hellenic open university. The edm research community utilizes session logs and student databases for processing and analyzing student performance prediction using a machine learning algorithm.

Pdf Prediction Of Academic Performance Of Students Using Machine Learning This study aims to predict unknown course grades based on students’ previous learning situations and use clustering algorithms to identify similar learning situations, thereby improving. The scope of this work is to compare some of the state of the art learning algorithms. two experiments have been conducted with six algorithms, which were trained using data sets provided by the hellenic open university. The edm research community utilizes session logs and student databases for processing and analyzing student performance prediction using a machine learning algorithm.