Higher Education and Public Good

Policy debate about whether to maintain public subsidies for higher education has stimulated reconsideration of the public mission of higher education institutions, especially those that provide student places conferring private benefits. If the work of higher education institutions is defined simply as the aggregation of private interests, this evaporates the rationale for higher education institutions as distinctive social foundations with multiple public and private roles. The private benefits could be produced elsewhere. If that is all there is to higher education institutions, they could follow the Tudor monasteries into oblivion. But what is ‘public’ in higher education institutions? What could be ‘public’? What should be ‘public’? The paper reviews the main notions of ‘public’ (public goods in economics, public understood as collective good and Habermas' public sphere) noting the contested and politicised environment in which notions of ‘public’ must find purchase. A turn to global public goods offers the most promising strategy for re‐grounding the ‘public’ character of higher education.     

Tool Support for Teaching the Personal Software Process

Software engineering education can be viewed as a challenging task. Computer science students tend to focus on the programming aspects of a project, and take a “hacking approach” to completing a project, rather than viewing the process. Our course material includes teaching the Personal Software Process (PSP). Students are required to produce defect and effort metrics, as well as project summary reports. Tools to assist information recording and production of reports are difficult for students to access. The cost in terms of financial and learning time is usually too high at the educational level to justify using commercial tools that are available for the professional software engineer. We have developed a tool—Personal Assistant for Software Engineers—to aid students in the learning of the PSP. The tool has been successfully used in four subjects for a semester. Following feedback and evaluation, it has been redesigned, and is currently in stage two. The tool has been useful for students, and has automated the previous manual process of producing time and defect reports, along with project summaries, thus allowing them to focus on the meaning of the information.     

Teachers' and At‐Risk Students' Stimulated Recall of Instruction

Abstract

Using the stimulated recall of instruction methodology, we interviewed teachers and students at risk for referral to special education about their perceptions, judgments, and decision making during the course of instruction. The results of the teacher interviews suggest that teachers respond to complex collections of student cues in their decision making about students. Teachers described themselves as more frequently monitoring the at‐risk students, although their attempts to modify instruction consisted primarily of attempts to motivate these students. The at‐risk students indicated awareness that they are experiencing difficulty in class, had somewhat less understanding of how teachers attempt to help them, and responded with anger and frustration to their learning problems.     

Inter-participant variability in daily physical activity and sedentary time among male youth sport footballers: independent associations with indicators of adiposity and cardiorespiratory fitness

Participation in youth sport is assumed to promote and contribute towards more physically active lifestyles among children and adolescents. The aim of this study was to examine inter-participant variability in objectively measured habitual physical activity (PA) behaviours and sedentary time among youth sport participants and their implications for health. One-hundred-and-eighteen male youth sport footballers (Mean ± s = 11.72 ± 1.60) wore a GT3X accelerometer for 7 days. Average daily PA [min · day^?1, in light (LPA), moderate (MPA), vigorous (VPA) and combined moderate-to-vigorous (MVPA)] and sedentary time were calculated. Participants’ body mass index adjusted for age and sex (BMI–standard deviation score), per cent body fat (BF%), waist circumference and cardiorespiratory fitness were assessed. Results revealed that variability in daily PA behaviours and sedentary time (min · day^?1) was associated with BMI–standard deviation score [VPA (?), MVPA (?)], BF% [sedentary time (+), VPA (?), MVPA (?)], waist circumference [sedentary time (+), LPA (?)] and cardiorespiratory fitness [sedentary time (?), MPA (+), VPA (+), MVPA (+)]. Whilst sedentary time and MVPA were not related to health outcomes independent of one another, associations with markers of adiposity and cardiorespiratory fitness were stronger for sedentary time. Sedentary time was also significantly positively related to waist circumference independent of VPA. Results demonstrate inter-participant variability in habitual PA and sedentary time among youth sport participants which holds implications for their health. Thus, promoting PA and, in particular, reducing sedentary time may contribute towards the prevention of adverse health consequences associated with a physically inactive lifestyle for children and adolescents active in the youth sport context.     

A review of tennis racket performance parameters

The application of advanced engineering to tennis racket design has influenced the nature of the sport. As a result, the International Tennis Federation has established rules to limit performance, with the aim of protecting the nature of the game. This paper illustrates how changes to the racket affect the player-racket system. The review integrates engineering and biomechanical issues related to tennis racket performance, covering the biomechanical characteristics of tennis strokes, tennis racket performance, the effect of racket parameters on ball rebound and biomechanical interactions. Racket properties influence the rebound of the ball. Ball rebound speed increases with frame stiffness and as string tension decreases. Reducing inter-string contacting forces increases rebound topspin. Historical trends and predictive modelling indicate swingweights of around 0.030–0.035 kg/m² are best for high ball speed and accuracy. To fully understand the effect of their design changes, engineers should use impact conditions in their experiments, or models, which reflect those of actual tennis strokes. Sports engineers, therefore, benefit from working closely with biomechanists to ensure realistic impact conditions.     

Active recovery of the finger flexors enhances intermittent handgrip performance in rock climbers

This study aimed to (1) evaluate the effect of hand shaking during recovery phases of intermittent testing on the time–force characteristics of performance and muscle oxygenation, and (2) assess inter-individual variability in the time to achieve the target force during intermittent testing in rock climbers. Twenty-two participants undertook three finger flexor endurance tests at 60% of their maximal voluntary contraction until failure. Performances of a sustained contraction and two intermittent contractions, each with different recovery strategies, were analysed by time–force parameters and near-infrared spectroscopy. Recovery with shaking of the forearm beside the body led to a significantly greater intermittent test time (↑ 22%, P?P?P?相似文献   

Determining optimal cadence for an individual road cyclist from field data

The cadence that maximises power output developed at the crank by an individual cyclist is conventionally determined using a laboratory test. The purpose of this study was two-fold: (i) to show that such a cadence, which we call the optimal cadence, can be determined using power output, heart-rate, and cadence measured in the field and (ii) to describe methodology to do so. For an individual cyclist's sessions, power output is related to cadence and the elicited heart-rate using a non-linear regression model. Optimal cadences are found for two riders (83 and 70 revolutions per minute, respectively); these cadences are similar to the riders’ preferred cadences (82–92?rpm and 65–75?rpm). Power output reduces by approximately 6% for cadences 20?rpm above or below optimum. Our methodology can be used by a rider to determine an optimal cadence without laboratory testing intervention: the rider will need to collect power output, heart-rate, and cadence measurements from training and racing sessions over an extended period (>6 months); ride at a range of cadences within those sessions; and calculate his/her optimal cadence using the methodology described or a software tool that implements it.