Learning from video modeling examples: Does gender matter?

Abstract

Online learning from video modeling examples, in which a human model demonstrates and explains how to perform a learning task, is an effective instructional method that is increasingly used nowadays. However, model characteristics such as gender tend to differ across videos, and the model-observer similarity hypothesis suggests that such characteristics may affect learning. Therefore, this study investigated whether the effectiveness of learning how to solve a probability calculation problem from video modeling examples would vary as a function of the model’s and observer’s gender. In a 2 (Model: Female/Male) x 2 (Observer: Female/Male) between-subject design, 167 secondary education students learned how to solve probability calculation problems by observing video modeling examples. Results showed no effects of Model or Observer gender on learning and near transfer. Male students reported higher self-efficacy than female students. Compared to a female model, observing a male model enhanced perceived competence more from pretest to posttest, irrespective of observers’ gender. Furthermore, learning from a male model was less effortful and more enjoyable for male students than for female students. These results suggest that gender of both model and observer can matter in terms of affective variables experienced during learning, and that instructional designers may want to consider this when creating (online) learning environments with video modeling examples.