Variable uses of alternative conceptions: A case study in current electricity

Recent research related to the design of science instruction is often based on conceptual change theory and requires assessments of what knowledge students bring to instruction. The premise of this study was that it is also important to understand when and how students apply their knowledge. Fourteen elementary and middle school teachers in an in-service physics course were asked to solve qualitatively a variety of series and parallel circuit problems and explicate their reasoning. These teachers were found to share a common core of strongly held propositions that formed a coherent, but incorrect and contradictory model of sequential current flow. Yet their predictions about the circuits were highly variable. The variability in predictions resulted from differences and contradictions in additional “protective belts” of propositions, and differences in the ways in which the teachers changed and selectively applied those propositions to different problems. Understanding the variations in not only what teachers knew, but also the differences in when and how they applied their knowledge complicated the task of designing instruction. However, it also made possible the design of more precise instruction in which the teachers were required to recognize, confront, and reconcile specific inconsistencies in their beliefs.     

Analyzing and Selecting Instructional Strategies and Tactics

“Formulation of instructional strategy to match subject matter and learner requirements” is an integral part of most instructional design models (Andrews & Goodson, 1980, p.5). Yet the meaning and purpose of instructional strategies in these design models vary considerably. An instructional strategy in traditional design models usually refers to the selection of instructional delivery vehicles (e.g., lecture, demonstration, computer-assisted instruction) and support activities (e.g., practice exercises, tutoring) (cf. Tracey, Flynn, <& Legere, 1970). Contrast those conceptions with the many instructional strategies described in elaboration theory (Reigeluth & Stein, 1983), such as sub-sumptive sequencing, internally consistent orienting structures, synthesizers, summarizers, and cognitive strategy activators. What is obvious from these disparate conceptions is that instructional designers do not share a consistent definition of instructional strategies. Many of the activities that are referred to as instructional strategies are not in fact strategies, but rather are presentation vehicles. In this article, we first define instructional strategies and tactics in the context of an iterative design model. Instructional strategies are then distinguished from instructional tactics, which are the implementation of strategies. We then list the range of instructional strategies and tactics that implement them. Finally, we provide a decision tree for assisting designers to select appropriate instructional tactics.     

The KAIT with developmental students,honor students,and freshmen

The KAIT (Kaufman Adolescent and Adult Intelligence Test) is a relatively new test of intelligence. This paper explores its use in a southwestern university with three different student groups. The results are reported and implications noted.     

Responses to oral glucose challenge differ by physical activity volume and intensity: A pilot study

BackgroundOne-hour postprandial hyperglycemia is associated with increased risk of type 2 diabetes and cardiovascular disease. Physical activity (PA) has short-term beneficial effects on post-meal glucose response. This study compared the oral glucose tolerance test results of 3 groups of people with habitually different levels of PA.MethodsThirty-one adults without diabetes (age 25.9 ± 6.6 years; body mass index 23.8 ± 3.8 kg/m²; mean ± SD) were recruited and divided into 3 groups based on self-reported PA volume and intensity: low activity < 30 min/day of moderate-intensity activity (n = 11), moderately active ≥ 30 min/day of moderate-intensity PA (n = 10), and very active ≥ 60 min/day of PA at high intensity (n = 10). Participants completed an oral glucose tolerance test (50 g glucose) with capillary blood samples obtained at baseline, 15 min, 30 min, 45 min, 60 min, 90 min, and 120 min post-ingestion.ResultsThere were no significant differences between groups for age or body fat percentage or glycated hemoglobin (p > 0.05). The groups were significantly different in terms of baseline glucose level (p = 0.003) and, marginally, for gender (p = 0.053) and BMI (p = 0.050). There was a statistically significant effect of PA on the 1-h postprandial glucose results (p = 0.029), with differences between very active and low activity groups (p = 0.008) but not between the moderately active and low activity groups (p = 0.360), even when baseline glucose level and gender differences were accounted for. For incremental area under the curve there was no significant effect of activity group once gender and body fat percentage had been accounted for (p = 0.401). Those in the low activity group took 15 min longer to reach peak glucose level than those in the very active group (p = 0.012).ConclusionThe results suggest that high levels of PA have a beneficial effect on postprandial blood glucose profiles when compared to low and moderate levels of activity.     

几种蒸散模型在玉米农田蒸散量计算中的应用比较

模拟蒸散的物理过程,计算农田蒸散量是进行生态系统水资源评价和管理的重要手段,同时也是气象部门进行土壤湿度预报的首要条件.本研究以玉米农田为研究对象,基于涡度相关法观测的蒸散实测资料,比较分析了基于常规气象数据的蒸散模型(Hargreaves法、Priestlev-Taylor法、FAO-Penman-Monteith法)和基于气象梯度数据的蒸散模型(波文比法、梯度法、生态系统过程模型模拟)的模拟精度.结果表明:①Hargreaves法、Priestley-Taylor法和FAO-Penman-Monteith法日蒸散的模拟结果较为一致,总体上高估20%～26%,其中Priestley-Taylor法模拟结果最优;②生态系统过程模型模拟的农田日蒸散精度较高,但模型中涉及的物理过程和参数较多,在实际应用中难于获取;③波文比法在波文比小于0.4且仪器精度较高时可以得到较准确的估算值.研究同时还指出,仪器的安装高度及高差设计对梯度法估算蒸散十分重要.     

Mental health care for foster children in California

This paper reports on a study conducted to assess the health care needs of foster children in California. To evaluate foster children's mental health problems and the services provided to meet them, 154 program administrators, social workers, foster parents, and health care providers were interviewed in 14 counties. Foster parents and social workers were interviewed in groups, and foster parents and administrators also completed questionnaires. We found that although all counties care immediately for children who are injured, abused, or ill, only one county performs routine mental health evaluations of all children, and in most counties less than a third of children ever receive such evaluations. Informants identified mental health problems as more severe than medical problems in this population, and they identified four major barriers to access to appropriate therapy. Recommendations are that all children should receive comprehensive mental health evaluations, and procedures for immediate and ongoing care with consistent providers who are sensitive to foster children's needs should be included in case management plans, and covered by improved payment mechanisms. Additionally, communication, coordination and joint planning should be instituted among relevant agencies to address foster children's needs, and increased resources and training should be directed towards social service agencies and foster parents.     

Cardiorespiratory and perceptual responses of two interval training and a continuous training protocol in healthy young men

High Intensity Interval Training (HIIT) can be performed with different effort to rest time-configurations, and this can largely influence training responses. The purpose of the study was to compare the acute physiological responses of two HIIT and one moderate intensity continuous training (MICT) protocol in young men. A randomised cross-over study with 10 men [age, 28.3?±?5.5years; weight, 77.3?±?9.3?kg; height, 1.8?±?0.1?m; peak oxygen consumption (VO₂peak), 44?±?11?mL.kg^?1.min^?1]. Participants performed a cardiorespiratory test on a treadmill to assess VO₂peak, velocity associated with VO₂peak (vVO₂peak), peak heart rate (HRpeak) and perceived exertion (RPE). Then participants performed three protocols equated by distance: Short HIIT (29 bouts of 30s at vVO₂peak, interspersed by 30s of passive recovery, 29?min in total), Long HIIT (3 bouts of 4?min at 90% of vVO₂peak, interspersed by 3?min of recovery at 60% of vVO₂peak, 21?min in total) and MICT (21?min at 70% of vVO₂peak). The protocols were performed in a randomised order with ≥48 h between them. VO₂, HRpeak and RPE were compared. VO₂peak in Long HIIT was significantly higher than Short HIIT and MICT (43?±?11 vs 32?±?8 and 37?±?8?mL.kg^?1.min^?1, respectively, P?P?P?2, HR and RPE than Short HIIT and MICT, suggesting a higher demand on the cardiorespiratory system. Short HIIT and MICT presented similar physiologic and perceptual responses, despite Short HIIT being performed at higher velocities.     

3-min all-out effort on cycle ergometer is valid to estimate the anaerobic capacity by measurement of blood lactate and excess post-exercise oxygen consumption

The purpose of this study was to investigate the use of a single 3-min all-out maximal effort to estimate anaerobic capacity (AC) through the lactate and excess post-exercise oxygen consumption (EPOC) response methods (AC_{[La^?]+EPOCfast}) on a cycle ergometer. Eleven physically active men (age?=?28.1?±?4.0?yrs, height?=?175.1?±?4.2?cm, body mass?=?74.8?±?11.9?kg and ?O_2max?=?40.7?±?7.3?mL?kg^?1?min^?1), participated in the study and performed: i) five submaximal efforts, ii) a supramaximal effort at 115% of intensity of ?O_2max, and iii) a 3-min all-out maximal effort. Anaerobic capacity was estimated using the supramaximal effort through conventional maximal accumulated oxygen deficit (MAOD) and also through the sum of oxygen equivalents from the glycolytic (fast component of excess post-exercise oxygen consumption) and phosphagen pathways (blood lactate accumulation) (AC_{[La^?]+EPOCfast}), while during the 3-min all-out maximal effort the anaerobic capacity was estimated using the AC_{[La^?]+EPOCfast} procedure. There were no significant differences between the three methods (p?>?0.05). Additionally, the anaerobic capacity estimated during the 3-min all-out effort was significantly correlated with the MAOD (r?=?0.74; p?=?0.009) and AC_{[La^?]+EPOCfast} methods (r?=?0.65; p?=?0.029). Therefore, it is possible to conclude that the 3-min all-out effort is valid to estimate anaerobic capacity in physically active men during a single cycle ergometer effort.