Supporting adult-learners’ online interaction in computer-mediated learningOSF - Nanda van der Stap; Theo van den Bogaart; Ebrahim Rahimi; Stan van Ginkel; Tobey Nelson; Johan Versendaal (Computers in Human Behavior Reports)
Previous studies have revealed numerous benefits of computer-mediated learning, yet the design of such learning programmes are not always supportive for adult-learners. Studies show that higher education adult-learners are wary of the digital environment in computer-mediated courses, and hence refrain from online interaction resulting in lower learning outcomes and lower perceived learning satisfaction. Without an instructional model that supports adult-learners’ online interaction, teachers may fall back on traditional in-class teaching in an effort to make up for missed learning opportunities. To remedy this, design principles, specifically supportive for adult-learners, were co-designed into an instructional model reflecting the concentric dynamics that strengthen said programmes. In order to validate and improve the quality of the model a Delphi study was carried out among experts (n = 8) to evaluate the various components of the model, including its overall supportiveness for adult-learners in computer-mediated learning. The experts were selected based on their expertise and research in blended learning. Two evaluative rounds through surveys in the programme Crowdtech took place until full alignment of the experts’ opinions was had. The resulting model is a concentric one, illustrating how activities are best distributed across the online environment and the in-class environment, and how social presence can be evoked. This study provides insights into the design of computer-mediated learning programmes tailored for higher education adult-learners as it closes the gap in literature on instructional models and blended learning design. This validated instructional model may help course designers in designing or improving computer-mediated learning programmes.