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.
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History education frequently aims at developing active citizenship by using the past to orientate to the present and the future. A pedagogy for pursuing this aim is making connections between the past and the present by means of comparing cases of an enduring human issue. To examine the feasibility and desirability of this case-comparison teaching approach, students (N = 444) and teachers (N = 15) who participated in an implementation study conducted in the Netherlands were questioned about their experiences and views. Results show that both students and teachers felt that case-comparison in the context of an enduring human issue is feasible and not more complex than the usual history teaching in which topics are studied separately without explicitly making comparisons between past and present, even if some students thought that taking account of episodes from different historical periods concurrently required an extra learning effort. Both students and teachers believed that connecting past and present in history teaching enhances engagement and meaning making. They suggested a curriculum combining the case-comparison approach with the type of history teaching they were accustomed to. Mixed methods were used for data collection. Implications for further research on case-comparison learning in history are being discussed.
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BACKGROUND: Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.METHODS: Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined.RESULTS: We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small.CONCLUSIONS: We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.
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Morssink-Santing, V. E., van der Zee, S., Klaver, L. T., de Brouwer, J., andamp; Sins, P. H. (2024). The long-term effect of alternative education on self-regulated learning: A comparison between Montessori, Dalton, and traditional education. Studies in Educational Evaluation, 83, 101380. https://doi.org/10.1016/j.stueduc.2024.101380
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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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Background: Over the years, a plethora of frailty assessment tools has been developed. These instruments can be basically grouped into two types of conceptualizations – unidimensional, based on the physical–biological dimension – and multidimensional, based on the connections among the physical, psychological, and social domains. At present, studies on the comparison between uni- and multidimensional frailty measures are limited. Objective: The aims of this paper were: 1) to compare the prevalence of frailty obtained using a uni- and a multidimensional measure; 2) to analyze differences in the functional status among individuals captured as frail or robust by the two measures; and 3) to investigate relations between the two frailty measures and disability.
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This report summarizes the result of the comparison between 4 weather stations: 2 Kestrels 5400 Heat Stress and 2 Davis Vantage Pro2. The measurements were performed from the 08/04/2019 to 11/04/2019 on the rooftop of the Benno Premselahuis from the Hogeschool van Amsterdam.
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OBJECTIVE: Our aim was to determine whether the impact of upward and downward social comparison information on individuals' motivation to manage their diabetes is dependent on their regulatory focus (promotion or prevention focus) and self-efficacy.DESIGN: The hypotheses were examined in a cross-sectional study. Patients with diabetes (N = 234) read a fictitious interview with a fellow patient, either an upward or a downward target, and they filled out questionnaires.MAIN OUTCOME MEASURES: Motivation to work on diabetes regulation.RESULTS: High promotion-focused patients reported more motivation than low promotion-focused patients when confronted with the upward target (positive role model). High prevention-focused patients reported more motivation than low prevention-focused patients when confronted with the downward target (negative role model). This latter finding was qualified by patients' self-efficacy, as it applied only to patients with relatively high levels of self-efficacy.CONCLUSION: The current study highlights the importance of considering individual differences when using role models to encourage self-care activities in persons with diabetes.
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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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This paper compares different low-cost sensors that can measure (5G) RF-EMF exposure. The sensors are either commercially available (off-the-shelf Software Defined Radio (SDR) Adalm Pluto) or constructed by a research institution (i.e., imec-WAVES, Ghent University and Smart Sensor Systems research group (S3R), The Hague University of Applied Sciences). Both in-lab (GTEM cell) and in-situ measurements have been performed for this comparison. The in-lab measurements tested the linearity and sensitivity, which can then be used to calibrate the sensors. The in-situ testing confirmed that the low-cost hardware sensors and SDR can be used to assess the RF-EMF radiation. The variability between the sensors was 1.78 dB on average, with a maximum deviation of 5.26 dB. Values between 0.09 V/m and 2.44 V/m were obtained at a distance of about 50 m from the base station. These devices can be used to provide the general public and governments with temporal and spatial 5G electromagnetic field values.
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