Utilizing online learning data to design face-to-face activities in a flipped classroom: a case study of heterogeneous group formation

This study investigates the possibility of utilizing online learning data to design face-to-face activities in a flipped classroom. We focus on heterogeneous group formation for effective collaborative learning. Fifty-three undergraduate students (18 males, 35 females) participated in this study, and 8 students (3 males, 5 females) among them joined post-study interviews. For this study, a total of 6 student characteristics were used: three demographic characteristics obtained from a simple survey and three academic characteristics captured from online learning data. We define three demographic group heterogeneity variables and three academic group heterogeneity variables, where each variable is calculated using the corresponding student characteristic. In this way, each heterogeneity variables represents a degree of diversity within the group. Then, a two-stage hierarchical regression analysis was conducted to identify the significant group heterogeneity variables that influence face-to-face group achievement. The results show that the academic group heterogeneity variables, which were derived from the online learning data, accounted for a significant proportion of the variance in the group achievement when the demographic group heterogeneity variables were controlled. The interviews also reveal that the academic group heterogeneity indeed affected group interaction and learning outcome. These findings highlight that online learning data can be utilized to obtain relevant information for effective face-to-face activity design in a flipped classroom. Based on the results, we discuss the advantages of this data utilization approach and other implications for face-to-face activity design.

     

The effects of a data use intervention on educators’ satisfaction and data literacy

Schools in many different countries are increasingly expected to use data for school improvement. However, schools struggle with the implementation of data use, because building human capacity around data use in education has not received enough attention. Educators urgently need to develop data literacy skills for being able to use data. For supporting schools with the endeavor of developing data literacy skills, we developed and implemented a data use intervention in secondary schools based in the Netherlands. This study therefore focuses on the effects of this intervention on educator satisfaction with the intervention and their data literacy skills and attitude toward data use. This study uses a quasi-experimental research design and employs a mixed-methods approach with a data use questionnaire filled in by data team schools (N = 9) and comparison schools (N = 42), a satisfaction questionnaire filled in by data team participants (N = 55), pre- and posttest knowledge tests filled in by data team participants (N = 36), and interview data (N = 11) from three case study schools. The results show that the participants were, for example, very satisfied with the support received during the intervention. Also, respondents developed new data literacy skills and showed a more positive attitude toward data use. The results show how teachers can be supported systematically in data use in their educational practice. In the conclusions, we discuss some important implications for practice regarding the intensity and duration of support and implications for further research.     

Chemosensory conditioning in molluscs: II. A critical review

We critically review chemosensory conditioning studies with molluscs and find that, in many studies, the influence of nonassociative processes complicates, obscures, and renders ambiguous the unique contribution of associative learning. These nonassociative processes include sensory adaptation, habituation, sensitization, and changes in feeding motivation. They arise from both the food extracts that have often been used as conditioned stimuli and the aversive stimuli that have been used as unconditioned stimuli.     

Academic-industry liaison in the United Kingdom: economic perspectives

In recent years, higher educational institutions (HEIs) have been under increasing pressure to liaise more closely with industry. This paper draws on some relevant areas of economic theory to analyse the relationship between HEIs and industrial organisations. The nature of the benefits from liaison is examined, and the implications for financing liaison activities are considered. It is argued that liaison can frequently strengthen the traditional functions of HEIs by contributing to teaching and research. However, there is justification for the fears of many academics that in practice the outcome of closer industrial involvement may be to weaken these functions. Such undesirable outcomes reflect the weaknesses of the internal organisation of HEIs; in particular, the scope for opportunistic behaviour provided by the incompleteness of the academic contract, and the informational disadvantages suffered by senior management. In the light of these arguments, the final section considers alternative systems for organising liaison, drawing on examples from the United Kingdom. The criteria for assessment are concerned with the likely effectiveness of the systems in reducing the costs of both facilitating and policing liaison activities.     

Measurement Invariance Testing Across Between-Level Latent Classes Using Multilevel Factor Mixture Modeling

This simulation study examines the efficacy of multilevel factor mixture modeling (ML FMM) for measurement invariance testing across unobserved groups when the groups are at the between level of multilevel data. To this end, latent classes are generated with class-specific item parameters (i.e., factor loading and intercept) across the between-level classes. The efficacy of ML FMM is evaluated in terms of class enumeration, class assignment, and the detection of noninvariance. Various classification criteria such as Akaike’s information criterion, Bayesian information criterion, and bootstrap likelihood ratio tests are examined for the correct enumeration of between-level latent classes. For the detection of measurement noninvariance, free and constrained baseline approaches are compared with respect to true positive and false positive rates. This study evidences the adequacy of ML FMM. However, its performance heavily depends on the simulation factors such as the classification criteria, sample size, and the magnitude of noninvariance. Practical guidelines for applied researchers are provided.     

Topology evolutions of silhouettes

We give the topology changing of the silhouette in 3D space while others study the projections in an image. Silhou- ettes play a crucial role in visualization, graphics and vision. This work focuses on the global behaviors of silhouettes, especially their topological evolutions, such as splitting, merging, appearing and disappearing. The dynamics of silhouettes are governed by the topology, the curvature of the surface, and the view point. In this paper, we work on a more theoretical level to give enu- merative properties of the silhouette including: the integration of signed geodesic curvature along a silhouette is equal to the view cone angle; in elliptic regions, no silhouette can be contained in another one; in hyperbolic regions, if a silhouette is homotopic to a point, then it has at least 4 cusps; finally, critical events can only happen when the view point is on the aspect surfaces (ruled surface of the asymptotic lines of parabolic points with surface itself). We also introduce a method to visualize the evolution of silhouettes, especially all the critical events where the topologies of the silhouettes change. The results have broad applications in computer vision for recognition, graphics for rendering and visualization.     

Using Multilevel Regression Mixture Models to Identify Level-1 Heterogeneity in Level-2 Effects

This article proposes a novel exploratory approach for assessing how the effects of Level-2 predictors differ across Level-1 units. Multilevel regression mixture models are used to identify latent classes at Level 1 that differ in the effect of 1 or more Level-2 predictors. Monte Carlo simulations are used to demonstrate the approach with different sample sizes and to demonstrate the consequences of constraining 1 of the random effects to 0. An application of the method to evaluate heterogeneity in the effects of classroom practices on students is used to show the types of research questions that can be answered with this method and the issues faced when estimating multilevel regression mixtures.     

Patterns of image comparison using compare and contrast feature in Urinalysis Tutor™

This study examined how students interacted with a computer-based feature, Compare and Contrast , which facilitated image comparisons. Unlike previous research, which explored the use of images ordered and presented by investigators, this study examined emerging patterns of image comparison as students selected the presentation mode. Three main image-viewing modes emerged including one successive mode and two simultaneous modes: (1) single image viewing in which only one image was viewed at a time; (2) paired viewing in which different pairs of images were displayed; and (3) anchored viewing in which a single image in one image panel served as an anchor against which multiple image comparisons were made using the second panel. Overall, anchored viewing was the most predominant image-viewing mode used by the students (41%) compared to single viewing (22%) and paired viewing (11%). Students who viewed images in the anchored-viewing mode attained the highest scores on the post-test exam. Our study suggests that a computer instructional program with a user-controlled interactivity feature can provide insights on how learners form different types of visual comparison strategies. Future experimental studies involving interface design that explicitly supports single, paired, and anchored viewing modes could confirm or challenge the results of our study and therefore, contribute to on-going research on the effective mode of image presentation for visual concept acquisition.