A promising contribution of Learning Analytics is the presentation of a learner's own learning behaviour and achievements via dashboards, often in comparison to peers, with the goal of improving self-regulated learning. However, there is a lack of empirical evidence on the impact of these dashboards and few designs are informed by theory. Many dashboard designs struggle to translate awareness of learning processes into actual self-regulated learning. In this study we investigate a Learning Analytics dashboard based on existing evidence on social comparison to support motivation, metacognition and academic achievement. Motivation plays a key role in whether learners will engage in self-regulated learning in the first place. Social comparison can be a significant driver in increasing motivation. We performed two randomised controlled interventions in different higher-education courses, one of which took place online due to the COVID-19 pandemic. Students were shown their current and predicted performance in a course alongside that of peers with similar goal grades. The sample of peers was selected in a way to elicit slight upward comparison. We found that the dashboard successfully promotes extrinsic motivation and leads to higher academic achievement, indicating an effect of dashboard exposure on learning behaviour, despite an absence of effects on metacognition. These results provide evidence that carefully designed social comparison, rooted in theory and empirical evidence, can be used to boost motivation and performance. Our dashboard is a successful example of how social comparison can be implemented in Learning Analytics Dashboards.
MULTIFILE
In medical education, student distress is known to hamper learning and professional development. To address this problem, recent studies aimed at helping students cope with stressful situations. Undergraduate students in clinical practice frequently use experiences of surrounding peers to estimate their abilities to master such challenging situations. This use of the experiences of others, known as social comparison, may affect student distress both positively and negatively. To find characteristics of a beneficial use of social comparison, we examined differences in comparison behaviours between students expressing low and high levels of distress. The participants in our study, response rate 93% (N = 301/321), were all medical students in their first year in clinical practice. They completed the General Health Questionnaire (GHQ-12) to measure distress, and three separate questionnaires to measure: (1) orientation to comparison, (2) motive for comparison, and (3) interpretation of comparison. Differences were analysed using multivariate analysis of variance. Although all students were oriented towards social comparison, the analyses showed that this orientation was less apparent among low-distress students. Besides, the low-distress students were less inclined to use motives indicative for comparisons with peers perceived as performing worse and were less negative in the interpretations of their comparisons. As social comparison is frequently used among all students, we recommend to make them aware of their comparison behaviours and inform them about the pros and cons of the distinguished aspects of the comparison process.
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To improve people’s lives, human-computer interaction researchers are increasingly designing technological solutions based on behavior change theory, such as social comparison theory (SCT). However, how researchers operationalize such a theory as a design remains largely unclear. One way to clarify this methodological step is to clearly state which functional elements of a design are aimed at operationalizing a specific behavior change theory construct to evaluate if such aims were successful. In this article, we investigate how the operationalization of functional elements of theories and designs can be more easily conveyed. First, we present a scoping review of the literature to determine the state of operationalizations of SCT as behavior change designs. Second, we introduce a new tool to facilitate the operationalization process. We term the tool blueprints. A blueprint explicates essential functional elements of a behavior change theory by describing it in relation to necessary and sufficient building blocks incorporated in a design. We describe the process of developing a blueprint for SCT. Last, we illustrate how the blueprint can be used during the design refinement and reflection process.
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