404 resultados para Experimental Pedagogy


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In silico experimental modeling of cancer involves combining findings from biological literature with computer-based models of biological systems in order to conduct investigations of hypotheses entirely in the computer laboratory. In this paper, we discuss the use of in silico modeling as a precursor to traditional clinical and laboratory research, allowing researchers to refine their experimental programs with an aim to reducing costs and increasing research efficiency. We explain the methodology of in silico experimental trials before providing an example of in silico modeling from the biomathematical literature with a view to promoting more widespread use and understanding of this research strategy.

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Experiments were undertaken to study effect of initial conditions on the expansion ratio of two grains in a laboratory scale, single speed, single screw extruder at Naresuan University, Thailand. Jasmine rice and Mung bean were used as the material. Three different initial moisture contents were adjusted for the grains and classified them into three groups according to particle sizes. Mesh sizes used are 12 and 14. Expansion ratio was measured at a constant barrel temperature of 190oC. Response surface methodology was used to obtain optimum conditions between moisture content and particle size of the materials concerned.

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Recently, a constraints- led approach has been promoted as a framework for understanding how children and adults acquire movement skills for sport and exercise (see Davids, Button & Bennett, 2008; Araújo et al., 2004). The aim of a constraints- led approach is to identify the nature of interacting constraints that influence skill acquisition in learners. In this chapter the main theoretical ideas behind a constraints- led approach are outlined to assist practical applications by sports practitioners and physical educators in a non- linear pedagogy (see Chow et al., 2006, 2007). To achieve this goal, this chapter examines implications for some of the typical challenges facing sport pedagogists and physical educators in the design of learning programmes.

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Data analysis sessions are a common feature of discourse analytic communities, often involving participants with varying levels of expertise to those with significant expertise. Learning how to do data analysis and working with transcripts, however, are often new experiences for doctoral candidates within the social sciences. While many guides to doctoral education focus on procedures associated with data analysis (Heath, Hindmarsh, & Luff, 2010; McHoul & Rapley, 2001; Silverman, 2011; Wetherall, Taylor, & Yates, 2001), the in situ practices of doing data analysis are relatively undocumented. This chapter has been collaboratively written by members of a special interest research group, the Transcript Analysis Group (TAG), who meet regularly to examine transcripts representing audio- and video-recorded interactional data. Here, we investigate our own actual interactional practices and participation in this group where each member is both analyst and participant. We particularly focus on the pedagogic practices enacted in the group through investigating how members engage in the scholarly practice of data analysis. A key feature of talk within the data sessions is that members work collaboratively to identify and discuss ‘noticings’ from the audio-recorded and transcribed talk being examined, produce candidate analytic observations based on these discussions, and evaluate these observations. Our investigation of how talk constructs social practices in these sessions shows that participants move fluidly between actions that demonstrate pedagogic practices and expertise. Within any one session, members can display their expertise as analysts and, at the same time, display that they have gained an understanding that they did not have before. We take an ethnomethodological position that asks, ‘what’s going on here?’ in the data analysis session. By observing the in situ practices in fine-grained detail, we show how members participate in the data analysis sessions and make sense of a transcript.

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The explanation of social inequalities in education is still a debated issue in economics. Recent empirical studies tend to downplay the potential role of credit constraint. This article tests a different potential explanation of social inequalities in education, specifically that social differences in aspiration level result in different educational choices. Having existed for a long time in the sociology of education, this explanation can be justified if aspiration levels are seen as reference points in a prospect theory framework. In order to test this explanation, this article applies the method of experimental economics to the issue of education choice and behaviour. One hundred and twenty-nine individuals participated in an experiment in which they had to perform a task over 15 stages grouped in three blocks or levels. In order to continue through the experiment, a minimum level of success was required at the end of each level. Rewards were dependent on the final level successfully reached. At the end of each level, participants could either choose to stop and take their reward or to pay a cost to continue further in order to possibly receive higher rewards. To test the impact of aspiration levels, outcomes were either presented as gains or losses relative to an initial sum. In accordance with the theoretical predictions, participants in the loss framing group choose to go further in the experiment. There was also a significant and interesting gender effect in the loss framing treatment, such that males performed better and reached higher levels.