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Student teachers often struggle to keep track of everything that is happening in the classroom, and particularly to notice and respond when students cause disruptions. The complexity of the classroom environment is a potential contributing factor that has not been empirically tested. In this experimental study, we utilized a virtual reality (VR) classroom to examine whether classroom complexity affects the likelihood of student teachers noticing disruptions and how they react after noticing. Classroom complexity was operationalized as the number of disruptions and the existence of overlapping disruptions (multidimensionality) as well as the existence of parallel teaching tasks (simultaneity). Results showed that student teachers (n = 50) were less likely to notice the scripted disruptions, and also less likely to respond to the disruptions in a comprehensive and effortful manner when facing greater complexity. These results may have implications for both teacher training and the design of VR for training or research purpose. This study contributes to the field from two aspects: 1) it revealed how features of the classroom environment can affect student teachers' noticing of and reaction to disruptions; and 2) it extends the functionality of the VR environment-from a teacher training tool to a testbed of fundamental classroom processes that are difficult to manipulate in real-life.
Teachers frequently express stress associated with teaching in large classrooms. Despite the timehonored tradition in teacher stress research of treating class size as a job-related stressor, the underlying premise that class size directly impacts teachers' stress reactions remains untested. In this randomized controlled experiment targeted at preservice teachers, we utilized a standardized virtual reality (VR) classroom to examine whether class size (number of student avatars) directly affected physiological (heart rate) or psychological (subjective rating) stress reactions among 65 preservice teachers. Results from linear mixed-effects modeling (LMM) showed that class size significantly predicted both their physiological and psychological stress reactions in the simulated environment: Average heart rate and subjective stress ratings were both significantly higher in the large class size condition. Further investigations into the causes of this association has been proposed. These findings may contribute to a better understanding of the effects of classroom features on preservice teachers' emotional experiences and well-being.
Chapter 17 : Summary
(2004)
Change in test-taking motivation and its relationship to test performance in low-stakes assessments
(2017)
Since the turn of the century, an increasing number of low-stakes assessments (i.e., assessments without direct consequences for the test-takers) are being used to evaluate the quality of educational systems. Internationally, research has shown that low-stakes test results can be biased due to students’ low test-taking motivation and that students’ effort levels can vary throughout a testing session involving both cognitive and noncognitive tests. Thus, it is possible that students’ motivation varies throughout a single cognitive test and in turn affects test performance. This study examines the change in test-taking motivation within a 2-h cognitive low-stakes test and its association with test performance. Based on expectancy-value theory, we assessed three components of test-taking motivation (expectancy for success, value, and effort) and investigated its change. Using data from a large-scale student achievement study of German ninth-graders, we employed second-order latent growth modeling and structural equation modeling to predict test performance in mathematics. On average, students’ effort and perceived value of the test decreased, whereas expectancy for success remained stable. Overall, initial test-taking motivation was a better predictor of test performance than change in motivation. Only the variability of change in the expectancy component was positively related to test performance. The theoretical and practical implications for test practitioners are discussed.
Recently, interest in collecting and mining large sets of educational data on student background and performance to conduct research on learning and instruction has developed as an area generally referred to as learning analytics. Higher education leaders are recognising the value of learning analytics for improving not only learning and teaching but also the entire educational arena. However, theoretical concepts and empirical evidence need to be generated within the fast evolving field of learning analytics. In this paper, we introduce a holistic learning analytics framework. Based on this framework, student, learning, and curriculum profiles have been developed which include relevant static and dynamic parameters for facilitating the learning analytics framework. Based on the theoretical model, an empirical study was conducted to empirically validate the parameters included in the student profile. The paper concludes with practical implications and issues for future research.
Causes, Time, and Truth
(2016)
We need causation, time, and truth in order to know how things in the broadest sense of the term hang together in the broadest sense of the term. The essays try to say something clarifying about those three classical questions of traditional metaphysics. Not dogmatic answers are offered, but guiding perspectives and possible justifiable ways of dealing with such fundamental