Deep learning techniques assess student performance in the classroom
Monday – 19 Jumada Al-Thani 1442 AH – 01 February 2021 AD Issue No. [
Establish academic programs that aim to increase student participation in activities
San Francisco: “Middle East”
Given the difficulty of effectively and reliably assessing participation in educational activities within the classroom by monitoring students’ performance without negatively affecting the educational process itself, a team of researchers in Germany and the United States has come up with the possibility of employing deep learning techniques in evaluating the degree of efficiency of different educational programs. And the extent of its impact on students in the classes.
The study team from the University of Tübingen and the Leitnitz Institute in Germany, in conjunction with experts at the University of Colorado Boulder, created an artificial intelligence system that can evaluate students’ academic performance by analyzing video clips recorded inside the classroom.
“We have used video clips recorded during the classroom to train a deep learning system on how to predict the level of students’ engagement in the educational process in the classroom,” said researcher Inclida Castensi, head of the study team, in statements to the TechExplor website, adding: “After completing Training the system, it can now determine, for example, whether the information provided by the student during a certain stage of the study period reflects a high or low academic participation level.
The researchers confirmed that the new system can analyze a huge database of video clips of the educational environment in the classroom and determine the times when students ‘participation in the educational process increases or decreases, and the study team believes that this technology can help in identifying sound strategies that help attract students’ interest. While taking lessons, establish effective teacher training programs themselves.