Teachers’ perceptions and A‐level performance: is there any evidence of systematic bias?

Applications for places in UK Higher Education are usually made before the results of A‐level examinations are known, so references from schools and colleges normally refer to expected (or predicted) grades. Inaccuracies in these predictions may be systematically related to key characteristics of the applicant and could lead to under‐representation from various groups of students. This paper examines data on predicted A‐level grades for 415 recently‐enrolled university students. In contrast to the findings of previous studies however, we find that prediction bias is not particularly related to the gender, class or schooling of the student, but is closely linked to the predicted grades themselves—students predicted low grades performed above expectations, and vice‐versa. The implications of this for current UK government initiatives intended to widen participation in Higher Education are considered briefly in the conclusion.     

Students’ academic self-perception

Participation rates in higher education differ persistently between some groups in society. Using two British datasets we investigate whether this gap is rooted in students’ misperception of their own and other's ability, thereby increasing the expected costs to studying. Amongst high school pupils, we find that pupils with a more positive view of their academic abilities are more likely to expect to continue to higher education even after controlling for observable measures of ability and students’ characteristics. University students are also poor at estimating their own test performance and over-estimate their predicted test score. However, females, White and working class students have less inflated view of themselves. Self-perception has limited impact on the expected probability of success and expected returns amongst these university students.     

Vocational education and the revitalisation of manufacturing in the United States

Manufacturing in advanced open economies has experienced significant disruption. Rapid technological change, outsourcing and off shoring have beset manufacturing resulting in a general and steady decline in manufacturing employment. Despite this turbulence, there remains a strong nostalgia for manufacturing resulting in frequent public policy discussion about how best to revitalise the industry. A popular view is that a strong manufacturing industry relies upon an equally strong vocational, education and training (VET) system to provide requisite skill needs. Given the dramatic pace of change in the manufacturing industry do such arguments still hold true? This paper considers this question through an examination of what the revitalisation of US manufacturing means for employment and skills needs and the extent to which US’s decentralised and largely eroded VET system serves as a barrier to the industry’s revitalisation. Drawing upon a mixed method approach that includes primary and secondary data collected in three US cities, the paper argues that the focus on needing to have a strong VET system overlooks the emergence of flexible micro-skill ecosystems that evolve to address local skill needs. These micro skill eco-systems open the prospects for skills and training innovations to meet changing workforce needs in a changing industry.     

Sleep and the body mass index and overweight status of children and adolescents

Associations between sleep and the body mass index (BMI) and overweight status of children and adolescents were estimated using longitudinal data from a nationally representative sample of 2,281 children aged 3–12 years at baseline. Controlling for baseline BMI, children who slept less, went to bed later, or got up earlier at the time of the first assessment had higher BMIs 5 years later and were more likely to be overweight. Child age moderated the relationship between bedtime and BMI. In addition, the study reports nationally representative data on the sleep habits of American children aged 3–18 years. This study underscores the likely importance of sleep on children's physical health and suggests that sleep is important for understanding childhood weight problems.