Teaching Programming through Multi-Context Physical Computing

Abstract

With the growing demand for computational skills in the job market, it’s imperative that lower secondary school students grasp basic programming concepts such as repetition, modularity, conditionals, and variables. Yet, many students perceive computer science as daunting and irrelevant. Physical computing offers a promising solution to this motivational gap. It enhances intrinsic motivation, self-efficacy, and positive attitudes towards technology. Moreover, they engage students who may not identify as typical programmers and foster essential computational thinking skills. This research investigates the efficacy of employing the same educational robot in different contexts, such as music, images, colors, and simple video games, while teaching basic programming concepts. We call this approach “multi-context physical computing” to emphasize the focus on the different application scenarios. We believe that this could benefit students for two reasons. Firstly, by presenting the same concept across different contexts, learners can better grasp the essence of the concept, disentangling it from extraneous contextual associations. Secondly, catering to individual interests by offering diverse contexts may enhance motivation, consequently fostering improved learning outcomes, as predicted by the expectancy-value theory. In order to assess the benefits of the multi-context approach on learning outcomes and motivation, we will compare it to a more traditional single-context approach centered on robot locomotion in a randomized controlled study.