Active Learning has been referred to as many things, including “project-based learning” and “flipped classes.” The fundamental premise of active learning is the replacement of passive class time with ...

Active learning strategies engage students in the learning process, fostering deeper understanding and retention. By encouraging participation, collaboration, and critical thinking during classroom ...

Have you ever given a lecture to a group of adult learners? If so, you may have noticed their eyes losing focus and phones appearing as you moved through your session. This is because the traditional ...

Active and Collaborative Learning Strategies The classic: think-pair-share Think-pair-share (TPS) is the black dress of active learning: a highly flexible tool that can take as little or as much time ...

Active learning teaching strategies in K-12 education encompass dynamic approaches that engage students in the classroom learning process, fostering deeper understanding and retention. When we examine ...

The University of Colorado Boulder has been chosen by the Association of Public and Land-grant Universities (APLU) to help lead the SEMINAL project—a study funded by the National Science Foundation ...

Fifty-five percent of students say a teaching style that didn’t work for them has impeded their success in a class since starting college. That makes it the No. 1 reported barrier to academic success ...

We are often so fixated on online learning’s shortcomings that we slight its unique advantages. Students can have anytime, anywhere access to class materials. We can make a wealth of primary sources ...

Associate Teaching Professor Cecil Joseph remembers the first time he taught physics in one of UMass Lowell’s Technology Enhanced Active Learning (TEAL) classrooms. Instead of facing rows of students ...

Activities are the experiences that allow students to achieve learning outcomes. These may consist of readings, lectures, group work, labs or projects to name a few. While situations and learning ...

Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...