Abstract
Social robots are receiving an ever-increasing interest in popular media and scientific literature. Yet, empirical evaluation of the educational use of social robots remains limited. In the current paper, we focus on how different scaffolds (co-speech hand gestures vs. visual cues presented on the screen) influence the effectiveness of a robot second language (L2) tutor. In two studies, Turkish-speaking 5-year-olds (n = 72) learned English measurement terms (e.g., big, wide) either from a robot or a human tutor. We asked whether (1) the robot tutor can be as effective as the human tutor when they follow the same protocol, (2) the scaffolds differ in how they support L2 vocabulary learning, and (3) the types of hand gestures affect the effectiveness of teaching. In all conditions, children learned new L2 words equally successfully from the robot tutor and the human tutor. However, the tutors were more effective when teaching was supported by the on-screen cues that directed children's attention to the referents of target words, compared to when the tutor performed co-speech hand gestures representing the target words (i.e., iconic gestures) or pointing at the referents (i.e., deictic gestures). The types of gestures did not significantly influence learning. These findings support the potential of social robots as a supplementary tool to help young children learn language but suggest that the specifics of implementation need to be carefully considered to maximize learning gains. Broader theoretical and practical issues regarding the use of educational robots are also discussed.
Highlights
Educational technologies are becoming commonplace in schools and homes across the world
We aim to gain a better picture of how social robots should be used in language education, and examine the role of different scaffolds: hand gestures performed by the robot tutor and visual cues presented on the screen accompanying the robot
Our goal was to examine the role of social robots in L2 vocabulary learning
Summary
Educational technologies are becoming commonplace in schools and homes across the world. According to a 2020 report, the educational robot market is expected to grow 16% over the 5 years across the world (Mordor Intelligence, 2020). By May 2017, 101 empirical papers (with 309 study results) concerning educational robots were published from different parts of the world such as North America, East Asia, Europe, and the Middle East, and 58% of these studies tested children (Belpaeme et al, 2018a). Robot L2 Teaching most studies far focused on the affective components of the learning experience (e.g., whether the learner enjoyed the lesson or not) and did not evaluate learning gain and have a small sample size and lack a control group. This study aims to address this limitation and to gain insights into specific ways to maximize educational robots’ benefits for young learners
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