Prediction of maximum oxygen consumption from walking, jogging, or running

The purpose of this study was to develop a submaximal, 1.5-mile endurance test for college-aged students using walking, jogging, or running exercise. College students (N = 101: 52 men, 47 women), ages 18-26years, successfully completed the 1.5-mile test twice, and a maximal graded exercise test. Participants were instructed to achieve a "somewhat hard" exercise intensity (rating of perceived exertion = 13) and maintain a steady pace throughout each 1.5-mile test. Multiple linear regression generated the following prediction equation: VO2 max = 65.404 + 7.707 x gender (1 = male; 0 =female) - 0.159 x body mass (kg) - 0.843 x elapsed exercise time (min; walking, jogging orrunning). This equation shows acceptable validity (R = .86, SEE = 3.37 ml x kg(-1) min(-1)) similar to the accuracy of comparable field tests, and reliability (ICC = .93) is also comparable to similar models. The statistical shrinkage is minimal (R(press) = 0.85, SEE(press) = 3.51 ml x kg(-) x min(-1)); hence, it should provide comparable results when applied to other similar samples. A regression model (R =.90, and SEE = 2.87 ml x kg(-1) min(-1)) including exercise heart rate was also developed: VO2 max = 100.162 +/- 7.301 x gender(1 = male; 0 =female) - 0.164 x body mass (kg) - 1.273 x elapsed exercise time -0.156 x exercise heart rate, for those who have access to electronic heart rate monitors. This submaximal 1.5-mile test accurately predicts maximal oxygen uptake (VO2max) without measuring heart rate and is similar to the 1.5-mile run in that it allowsfor mass testing and requires only a flat, measured distance and a stopwatch. Further, it can accommodate a wide range of fitness levels (from walkers to runners).     

Statistical analyses in the physiology of exercise and kinanthropometry

Research into the physiology of exercise and kinanthropometry is intended to improve our understanding of how the body responds and adapts to exercise. If such studies are to be meaningful, they have to be well designed and analysed. Advances in personal computing have made available statistical analyses that were previously the preserve of elaborate mainframe systems and have increased opportunities for investigation. However, the ease with which analyses can be performed can mask underlying philosophical and epistemological shortcomings. The aim of this review is to examine the use of four techniques that are especially relevant to physiological studies: (1) bivariate correlation and linear and non-linear regression, (2) multiple regression, (3) repeated-measures analysis of variance and (4) multi-level modelling. The importance of adhering to underlying statistical assumptions is emphasized and ways to accommodate violations of these assumptions are identified.     

Talent,Schmalent: An Instructional Design/Action Research Framework for the Professionalization of Teaching in Academic Libraries

When myths become canonical beliefs within a professional culture, they can have a profound impact on professional practice. In this paper we identify as a pernicious educational myth the belief that the ability to teach well is a naturally occurring innate talent or skill. The first two sections of the paper aim to demonstrate (i) that the concept of the naturally gifted teacher is a myth based on factually incorrect assumptions about expertise development and (ii) that this myth has several major negative implications for professional practices around teaching in academic libraries. We then we draw on the education literature to offer an alternative model for the cultivation of teaching excellence, an instructional design/action research framework that prioritizes ‘deliberative’ practice over innate talent. We close with suggestions for how academic librarians and library administrators can implement this framework within their institutions.     

Cognitive load in algebra: element interactivity in solving equations

Central to equation solving is the maintenance of equivalence on both sides of the equation. However, when the process involves an interaction of multiple elements, solving an equation can impose a high cognitive load. The balance method requires operations on both sides of the equation, whereas the inverse method involves operations on one side only. In an experiment, middle school students (N?=?71) were randomly assigned to the balance and inverse methods to complete a pre-test, an acquisition phase and a post-test. Pre-test and post-test comparisons found that the inverse group outperformed the balance group for those equations that involved high element interactivity. Instructional efficiency measures further confirmed that the balance method imposed higher cognitive load. The inverse method was capable of reducing cognitive load due to the interacting elements.