Priming and Fake News: The Effects of Elite Discourse on Evaluations of News Media

Fake news has become a prominent topic of public discussion, particularly among elites. Recent research has explored the prevalence of fake news during the 2016 election cycle and possible effects on electoral outcomes. This scholarship has not yet considered how elite discourse surrounding fake news may influence individual perceptions of real news. Through an experiment, this study explores the effects of elite discourse about fake news on the public’s evaluation of news media. Results show that exposure to elite discourse about fake news leads to lower levels of trust in media and less accurate identification of real news. Therefore, frequent discussion of fake news may affect whether individuals trust news media and the standards with which they evaluate it. This discourse may also prompt the dissemination of false information, particularly when fake news is discussed by elites without context and caution.     

Extended Mixed‐Effects Item Response Models With the MH‐RM Algorithm

A mixed‐effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed‐effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis‐Hastings Robbins‐Monro (MH‐RM) stochastic imputation algorithm to accommodate for increased dimensionality due to modeling multiple design‐ and trait‐based random effects. As a consequence of using this algorithm, more flexible explanatory IRT models, such as the multidimensional four‐parameter logistic model, are easily organized and efficiently estimated for unidimensional and multidimensional tests. Rasch versions of the linear latent trait and latent regression model, along with their extensions, are presented and discussed, Monte Carlo simulations are conducted to determine the efficiency of parameter recovery of the MH‐RM algorithm, and an empirical example using the extended mixed‐effects IRT model is presented.     

You can lead a horse to water but you cannot make him learn: Smartphone use in higher education

Smartphone technology is penetrating world markets and becoming ubiquitous in most college settings. This study takes a naturalistic approach to explore the use of these devices to support student learning. Students that had never used a smartphone were recruited to participate and reported on their expectations of the value of smartphones to achieve their educational goals. Instrumented iPhones that logged device usage were then distributed to these students to use freely over the course of 1 year. After the study, students again reported on the actual value of their smartphones to support their educational goals. We found that students' reports changed substantially before and after the study; specifically, the utility of the smartphone to help with education was perceived as favorable prior to use, and then, by the end of the study, they viewed their phones as detrimental to their educational goals. Although students used their mobile device for informal learning and access to school resources according to the logged data, they perceived their iPhones as a distraction and a competitor to requisite learning for classroom performance.     

Child and Adolescent Predictors of Personality in Early Adulthood

This study investigated development of the Big Five personality traits from early childhood into adulthood. An initial group of 137 Swedish children were assessed eight times between ages 2 and 29 years. Initial decreases in extraversion leveled off in early adulthood; agreeableness and conscientiousness increased from ages 2 to 29; neuroticism initially increased, leveled off in later childhood and adolescence, and decreased throughout early adulthood; while openness to experience showed an initial increase, then decreased and leveled off in early adulthood. Individual developmental trajectories varied significantly, particularly in relation to gender. Personality traits became increasingly stable, and the fact that childhood scores predicted scores in adulthood indicated that personalities are fairly stable across this portion of the life span.     

Modeling Growth in Electronic Learning Environments Using a Longitudinal Random Item Response Model

In educational environments, monitoring persons' progress over time may help teachers to evaluate the effectiveness of their teaching procedures. Electronic learning environments are increasingly being used as part of formal education and resulting datasets can be used to understand and to improve the environment. This study presents longitudinal models based on the item response theory (IRT) for measuring persons' ability within and between study sessions in data from web-based learning environments. Two empirical examples are used to illustrate the presented models. Results show that by incorporating time spent within- and between-study sessions into an IRT model; one is able to track changes in ability of a population of persons or for groups of persons at any time of the learning process.     

Estimation of a Nonlinear Intervention Phase Trajectory for Multiple-Baseline Design Data

A multilevel logistic model for estimating a nonlinear trajectory in a multiple-baseline design is introduced. The model is applied to data from a real multiple-baseline design study to demonstrate interpretation of relevant parameters. A simple change-in-levels (ΔLevels) model and a model involving a quadratic function (Quadratic) for the nonlinear intervention phase data were also estimated. In addition, a simulation study was conducted to assess Markov chain Monte Carlo estimation of the logistic model and compare its trajectory recovery with use of the ΔLevels and Quadratic models. While most of the logistic model's parameter values were recovered well, trajectory recovery was very reasonable using the simpler Quadratic model. Results are discussed along with recommendations for practitioners and directions for future research.     

Endorsing achievement goals exacerbates the big-fish-little-pond effect on academic self-concept

The big-fish-little-pond effect (BFLPE) model predicts students’ academic self-concept to be negatively predicted by the achievement level of their reference group, controlling for individual achievement. Despite an abundance of empirical evidence supporting the BFLPE, there have been relatively few studies searching for possible moderators. Integrating the BFLPE model with Achievement Goal Theory, the present study aims to determine whether the negative effect of class-average achievement on academic self-concept is moderated by individual and class-average achievement goals. Our sample comprised of 2987 students (50% boys) from Grade 6 in 112 elementary schools in the Flemish region of Belgium (174 classes). Applying multilevel modelling, we found a stronger BFLPE when students’ individual achievement goals were higher, regardless of the specific nature of these goals. The BFLPE was not moderated by class-average levels of achievement goals. Overall, our findings demonstrate that the BFLPE is moderated by individual goal-related factors.     

Social capital in the classroom: a study of in-class social capital and school adjustment

Social capital is generally considered beneficial for students’ school adjustment. This paper argues that social relationships among pupils generate social capital at both the individual and the class levels, and that each has its unique effect on pupils’ performance and well-being. The sample in this study consists of 1036 children in 60 first-grade classes in 46 Dutch elementary schools. Multilevel regression results show that a substantial proportion of the variance in school adjustment can be attributed to the class level and that both individual-level and classroom-level social capital have substantial effects on school adjustment. At the individual level, the size of one’s network is more important than its structure. At the collective level, social capital also has a ‘dark side’ because it can have negative effects on adjustment, lowering the academic performance in a class.     

Design and implementation of multi-campus,modular master classes in biochemical engineering

The Master of Science in engineering technology: biochemical engineering is organised in KU Leuven at four geographically dispersed campuses. To sustain the Master's programmes at all campuses, it is clear that a unique education profile at each campus is crucial. In addition, a rationalisation is required by increased cooperation, increased exchange of lecturers, and increased student mobility. To achieve this, a multicampus education system for the M.Sc. in engineering technology: biochemical engineering was developed by offering modules that are also available for students of other campuses. Such a module is primarily based on the research expertise present at the campus. In the development, special attention has been given to the optimal organisation of the modules, evaluation, required modifications of the current curricula, and the practical consequences for students following the module at another campus. Even in the first year of implementation, around 30% of the students followed a multicampus module, which indicates the potential success of the multicampus concept described here.     

Using statement banks to return online feedback: limitations of the transmission approach in a credit-bearing assessment

Electronic marking tools that incorporate statement banks have become increasingly prevalent within higher education. In an experiment, printed and emailed feedback was returned to 243 first-year students on a credit-bearing laboratory report assessment. A transmission approach was used, students being provided with comments on their work, but no guidance as to how they should use these remarks. A multiple-choice question test, undertaken before and after the return of feedback, was used to measure learning. Although returned comments included model answers, test scores showed no overall enhancement, even when students’ marks for their laboratory reports were initially hidden. A negative and significant (p = .010) linear trend between relative test scores and test date suggests that even modest improvements in subject knowledge were lost over time. Despite this, students could accurately guess their mark based on emailed feedback alone, estimated and awarded marks being linearly correlated (p < .001). It is concluded that statement banks organised according to published assessment criteria can ultimately help students to appreciate how their work was graded. However, students should be encouraged to produce a structured response to received feedback if self-assessment is to occur.