{"id":656470,"date":"2013-05-07T11:01:03","date_gmt":"2013-05-07T15:01:03","guid":{"rendered":"http:\/\/gigaom.com\/?p=642870"},"modified":"2013-05-07T11:01:03","modified_gmt":"2013-05-07T15:01:03","slug":"new-tool-uses-big-data-to-predict-student-performance","status":"publish","type":"post","link":"https:\/\/mereja.media\/index\/656470","title":{"rendered":"New tool uses big data to predict student performance"},"content":{"rendered":"

To help figure out how well they might do in a particular class, college students can turn to faculty-ranking websites, school surveys and their peers. But a new tool from Canadian ed tech company Desire2Learn<\/a>\u00a0aims to predict students’ success based not on the experiences of others but on their own past performance.<\/p>\n

The company\u2019s analytics engine also helps instructors and students for the duration of a course, warning instructors when students are falling behind on key concepts and offering insights that could help them keep up.\u00a0\u201cIt provides deeper insights to teachers on how to achieve better outcomes, what\u2019s working and what\u2019s not working,\u201d said Desire2Learn CEO John Baker.<\/p>\n

Based in Waterloo, Canada, Desire2Learn offers a learning management system for colleges that\u2019s competitive with Blackboard and says more than 10 million students in higher education use its technology.\u00a0Its new analytics product, which the company calls its Student Success System, builds on technology the company acquired earlier this year in the purchase of DegreeCompass<\/a>, a course recommendation engine developed at Austin Peay State University.<\/p>\n

As students progress through a course and interact with Desire2Learn \u2013 by digitally reviewing course materials, submitting homework assignments, communicating with classmates and completing tests and quizzes \u2013 the system’s algorithms continuously analyze each student\u2019s personal collection of education data.<\/p>\n

Instead of just giving the teacher a dashboard showing students\u2019 grades and completed assignments, it looks across all of the material to isolate the areas in which each student is faltering, suggests pathways for student improvement and predicts their grade at the end of the course.<\/p>\n

Before beginning a course, students who have completed one semester can use the tool to predict how they might fare in that course \u2013 and Desire2Learn says it\u2019s 90 percent accurate at predicting the letter grade.<\/p>\n

The new tool is part of a larger push in education to use data to improve student outcomes. CourseSmart, technology supported by McGraw-Hill, Pearson and other publishers that\u00a0allows professors to track students’ progress with digital textbooks<\/a>, similarly gives instructors a steady stream of data showing student engagement and performance (although it doesn’t make predictions).\u00a0But while some educators are ready to embrace a data-driven approach to education, others feel like it smacks too much of Big Brother<\/a>, and that could be a potential challenge the adoption of products like this.<\/p>\n

Image by\u00a0Vixit<\/a>\u00a0via Shutterstock.<\/em><\/p>\n

\"\"<\/p>\n

<\/a><\/p>\n

Related research and analysis from GigaOM Pro:<\/strong>
Subscriber content. Sign up for a free trial<\/a>.<\/p>\n