A Flexible Latent Class Approach to Estimating Test‐Score Reliability

The latent class reliability coefficient (LCRC) is improved by using the divisive latent class model instead of the unrestricted latent class model. This results in the divisive latent class reliability coefficient (DLCRC), which unlike LCRC avoids making subjective decisions about the best solution and thus avoids judgment error. A computational study using large numbers of items shows that DLCRC also is faster than LCRC and fast enough for practical purposes. Speed and objectivity render DLCRC superior to LCRC. A decisive feature of DLCRC is that it aims at closely approximating the multivariate distribution of item scores, which might render the method suited when test data are multidimensional. A simulation study focusing on multidimensionality shows that DLCRC in general has little bias relative to the true reliability and is relatively accurate compared to LCRC and classical lower bound methods coefficients α and λ2 and the greatest lower bound.     

In good company: The influence of peers on industry engagement by academic scientists

Previous research on academic entrepreneurship and engagement with industry has found that the behaviour of academics is influenced by their local social context. However, we know little about the mechanisms that produce this effect. We argue that academic scientists’ industry engagement is influenced significantly by the behaviour of their peers, that is, the behaviour of colleagues of similar seniority. Using insights from social psychology, we hypothesize that these peer effects are produced by the mechanism of social comparison. In an analysis of data from multiple sources for 1370 UK academic scientists and engineers, we find that peer effects are stronger for early career individuals and weaker for star scientists, suggesting the incidence of social comparison. We argue that individuals look to their immediate peers for inspiration, because they view them as an important reference group and use them as a benchmark for their own ambitions and behaviours. Our findings have important implications for how universities may encourage scientists’ behaviours by paying attention to local work contexts.     

Self-regulated learning and the role of ePortfolios in business studies

Students’ work in ePortfolios was assessed through a case study supported by observation techniques and eQuestionnaires to gather data from a sample of eighty students over a period of 4 years (20 students per academic year). The main purpose of the study was to explore whether ePortfolios can be used efficiently to support the learning process of postgraduate business students taking a course where finance modules were a major component. The use, role and learning value of integrating ePortfolios into the learning process in a higher education institution was analysed over the period of study. The empirical findings suggest that ePortfolios could be used to facilitate and enhance students’ self-regulated learning. Additionally, the role of the instructor was found to be fundamental during early stages of the learning process to guide and coach students on how to use the tool. This role diminished as students became familiar with the course requirements. Overall, students judged the ePortfolio as being positive to their education, noting a significant improvement in their learning experience when compared to a traditional learning approach. The evidence suggests that ePortfolios could be used to support technical and complex modules in a controlled environment. At the same time, ePortfolios were found to be flexible enough to give students creative space by helping them to integrate their own ideas and views through their learning process. Students were also able to offer their instructors feedback on their learning achievements.     

Academic engagement: A review of the literature 2011-2019

We provide a systematic review of the literature on academic engagement from 2011 onwards, which was the cut-off year of a previous review article published in Research Policy. Academic engagement refers to knowledge-related interactions of academic scientists with external organisations. It includes activities such as collaborative research with industry, contract research, consulting and informal ties. We consolidate what is known about the individual, organisational and institutional antecedents of academic engagement, and its consequences for research, commercialisation, and society at large. Our results suggest that individual characteristics associated with academic engagement include being scientifically productive, senior, male, locally trained, and commercially experienced. Academic engagement is also socially conditioned by peer effects and disciplinary characteristics. In terms of consequences, academic engagement is positively associated with academics’ subsequent scientific productivity. We propose new areas of investigation where evidence remains inconclusive, including individual life cycle effects, the role of organisational contexts and incentives, cross-national comparisons, and the impact of academic engagement on the quality of subsequent research as well as the educational, commercial and society-wide impact.     

The impact of an online tool for monitoring and regulating learning at university: overconfidence,learning strategy,and personality

Being overconfident when estimating scores for an upcoming exam is a widespread phenomenon in higher education and presents threats to self-regulated learning and academic performance. The present study sought to investigate how overconfidence and poor monitoring accuracy vary over the length of a college course, and how an intervention consisting of (1) a monitoring exercise and (2) a monitoring and regulation strategy, improves students’ monitoring accuracy and academic performance. Moreover, we investigated how personality factors (i.e., grandiose and vulnerable narcissism, optimism) influence monitoring accuracy. We found that the Monitoring and Regulation Strategy positively influenced monitoring accuracy and exam scores, whereas the Monitoring Exercise that confronted students with their overconfidence protected students against overconfidence in the second exam score prediction but did not affect exam score. The results further revealed that exam score predictions lowered from the start to the end of the course for both poor and high performing students, but still leaving poor performers overconfident and high performers underconfident. Topic knowledge gained in the course did not wash out the Dunning Kruger effect, and results indicate that poor and high performers use different cues when predicting exam scores. Both grandiose and vulnerable narcissism contributed to overconfidence on exam score predictions but not on the Monitoring Exercise. These findings underline the potential of the Monitoring and Regulation Strategy intervention and ask for upscaling it to include measurements of self-regulated learning activities.     

Predictors of reading and comprehension abilities in bilingual and monolingual children: a longitudinal study on a transparent language

Many studies have shown that learning to read in a second language (L2) is similar, in many ways, to learning to read in a first language (L1). Nevertheless, reading development also relies upon oral language proficiency and is greatly influenced by orthographic consistency. This longitudinal study aimed to analyze the role of linguistic predictors (phonological awareness, letter knowledge, pseudoword repetition, morphosyntactic comprehension, lexical knowledge and rapid naming) in reading outcomes (fluency, accuracy and comprehension) in a group of bilingual children (n = 30) reading Italian as an L2, compared to a group of monolingual children (n = 56). We ran a multi-group structural equation model. Our findings showed that rapid automatized naming was a significant predictor of reading speed in both groups. However, the study revealed different patterns of predictors for reading accuracy, predictors for monolinguals being LK, phonological awareness and lexical knowledge, while pseudoword repetition was a predictor for bilinguals. Morphosyntactic comprehension was the most significant predictor of comprehension skills in bilingual children. Implications for clinical and educational settings are discussed.