Suchergebnisse

Digital technologies hold the potential to transform educational assessment. Recent advances reveal that digital environments will support the development of learning and assessment activities in ways that will both increase the inferential fidelity of assessments and change the form of assessments altogether. Digital technologies can also automate data collection and the production of assessment inferences on a massive scale. Here, we discuss the wide variation in digital learning experiences and explain how they are transforming traditional language for discussing assessment. We argue that the predigital constraints on assessment have skewed our thinking about assessment and give examples of new and novel approaches. Second, we discuss how digital environments can allow us to capture and make inferences from simple or complex learning activities in new ways. Third, we point to advances in machine learning and AI that have the potential to change current and future assessment practices. Finally, we argue for balancing enthusiasm for digital environments against the challenges of making appropriate assessment inferences.

Abstract Background The Millennium Cohort Study is a longitudinal cohort study designed in the late 1990s to evaluate how military service may affect long-term health. The purpose of this investigation was to examine characteristics of Millennium Cohort Study participants who responded to the open-ended question, and to identify and investigate the most commonly reported areas of concern. Methods Participants who responded during the 2001-2003 and 2004-2006 questionnaire cycles were included in this study ( n = 108,129). To perform these analyses, Latent Semantic Analysis (LSA) was applied to a broad open-ended question asking the participant if there were any additional health concerns. Multivariable logistic regression was performed to examine the adjusted odds of responding to the open-text field, and cluster analysis was executed to understand the major areas of concern for participants providing open-ended responses. Results Participants who provided information in the open-ended text field ( n = 27,916), had significantly lower self-reported general health compared with those who did not provide information in the open-ended text field. The bulk of responses concerned a finite number of topics, most notably illness/injury, exposure, and exercise. Conclusion These findings suggest generalized topic areas, as well as identify subgroups who are more likely to provide additional information in their response that may add insight into future epidemiologic and military research.