Analytics engine uses big data to predict student performance

ExamCanadian education technology company, Desire2Learn, has created an analytics engine that uses big data to predict and improve student performance in higher education.

The tool predicts students’ success based on their past performance, helping instructors and students for the duration of a course by warning instructors when students are falling behind on key concepts and offering insights that could help them keep up.

“It provides deeper insights to teachers on how to achieve better outcomes, what’s working and what’s not working,” said Desire2Learn CEO John Baker.

Students interact with Desire2Learn by digitally reviewing course materials, submitting homework assignments, communicating with classmates and completing tests and quizzes.

The system’s algorithms then continuously analyse each student’s personal collection of education data.

Instead of showing the teacher a dashboard of students’ grades and completed assignments, it isolates the areas in which each student is faltering, suggests pathways for student improvement and predicts their grade at the end of the course.

Students who have completed one semester can use the tool to predict their final grade in that course, which Desire2Learn says is 90 percent accurate.