Experienced tutors' deployment of thinking skills and what might be entailed in enhancing such skills

In the context of research that reports weaknesses in adults' critical thinking skills, the primary aim was to examine adults' use of critical thinking skills that are described in taxonomies and to identify areas for development. Position papers written by an opportunity sample of 32 experienced adult educators formed the data for a descriptive sample survey design intended to reveal participants' use of critical thinking skills. Each 6000-word paper was written during a development programme that supported such skills. A content analysis of the papers revealed that when participants drew on personal and published ideas about learning to derive their proposals for change, they accepted the ideas uncritically, thereby implying that they might find it difficult to help learners to examine ideas critically. The evidence supports research that implies that critical thinking skills are unlikely to develop unless overall course design privileges the development of epistemological understanding (King and Kitchener 1994, Kuhn 1999). A fundamental assumption underlying the study is that this understanding influences effective citizenship and personal development, as well as employability. A proposition that merits attention in future research is that the development of epistemological understanding is largely neglected in current curricula in formal post-16 education

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The Optimal Exponent Base for emPAI Is 6.5

Exponentially Modified Protein Abundance Index (emPAI) is an established method of estimating protein abundances from peptide counts in a single LC-MS/MS experiment. EmPAI is defined as 10PAI minus one, where PAI (Protein Abundance Index) denotes the ratio of observed to observable peptides. EmPAI was first proposed by Ishihama et al [1] who found that PAI is approximately proportional to the logarithm of absolute protein concentration. I define emPAI65 = 6.5PAI-1 and show that it performs significantly better than emPAI, while it is equally easy to compute. The higher accuracy of emPAI65 is demonstrated by analyzing three data sets, including the one used in the original study [1]. I conclude that emPAI65 ought to be used instead of the original emPAI for protein quantitation

Designing Engaging Learning Experiences in Programming

In this paper we describe work to investigate the creation of engaging programming learning experiences. Background research informed the design of four fieldwork studies to explore how programming tasks could be framed to motivate learners. Our empirical findings from these four field studies are summarized here, with a particular focus upon one – Whack a Mole – which compared the use of a physical interface with the use of a screen-based equivalent interface to obtain insights into what made for an engaging learning experience. Emotions reported by two sets of participant undergraduate students were analyzed, identifying the links between the emotions experienced during programming and their origin. Evidence was collected of the very positive emotions experienced by learners programming with a physical interface (Arduino) in comparison with a similar program developed using a screen-based equivalent interface. A follow-up study provided further evidence of the motivation of personalized design of programming tangible physical artefacts. Collating all the evidence led to the design of a set of ‘Learning Dimensions’ which may provide educators with insights to support key design decisions for the creation of engaging programming learning experiences

Is There a Role for Adversariality in Teaching Critical Thinking?

Although there has been considerable recent debate on the topic of adversariality in argumentation, this debate has rarely found its way into work on critical thinking theory and instruction. This paper focuses on the implications of the adversariality debate for teaching critical thinking. Is there a role for adversarial argumentation in critical thinking instruction? Is there a way to incorporate the benefits of adversarial argumentation while mitigating the problems

Blowing big bubbles

Although street artists have the know-how to blow bubbles over one meter in length, the bubble width is typically determined by the size of the hoop, or wand they use. In this article we explore a regime in which, by blowing gently downwards, we generate bubbles with radii up to ten times larger than the wand. We observe the big bubbles at lowest air speeds, analogous to the dripping mode observed in droplet formation. We also explore the impact of the surfactant chosen to stabilize the bubbles. We are able to create bubbles of comparable size using either Fairy liquid, a commercially available detergent often used by street artists, or sodium dodecyl sulfate (SDS) solutions. The bubbles obtained from Fairy liquid detach from the wand and are stable for several seconds, however those from SDS tend to burst just before detachment

Assessing L2 Argumentation in the UAE Context

In this rapidly changing world, argumentation and critical thinking skills are undeniably crucial for new generations of Emirati students. These skills lay the groundwork for a competitive economy, which is a priority for the UAE in its Vision 2021. Specifically, today’s modern workplaces require workers to evaluate different propositions and develop their own after weighing up these various ideas, and thus the ability to defend arguments in English has become increasingly important for UAE university students in English-medium universities as well as their future professional contexts. Despite this importance, research regarding argumentation and the related critical thinking skills is sorely lacking in the UAE. This chapter delineates how written argumentation was assessed in a timed essay in a mandatory argumentative writing course taken by university freshmen in a government university in the UAE, and how the feedback gleaned from this common assessment was mapped to the teaching curriculum to shed light on the teaching effectiveness and to provide directions for future teaching

A Dynamic Noise Level Algorithm for Spectral Screening of Peptide MS/MS Spectra

<p>Abstract</p> <p>Background</p> <p>High-throughput shotgun proteomics data contain a significant number of spectra from non-peptide ions or spectra of too poor quality to obtain highly confident peptide identifications. These spectra cannot be identified with any positive peptide matches in some database search programs or are identified with false positives in others. Removing these spectra can improve the database search results and lower computational expense.</p> <p>Results</p> <p>A new algorithm has been developed to filter tandem mass spectra of poor quality from shotgun proteomic experiments. The algorithm determines the noise level dynamically and independently for each spectrum in a tandem mass spectrometric data set. Spectra are filtered based on a minimum number of required signal peaks with a signal-to-noise ratio of 2. The algorithm was tested with 23 sample data sets containing 62,117 total spectra.</p> <p>Conclusions</p> <p>The spectral screening removed 89.0% of the tandem mass spectra that did not yield a peptide match when searched with the MassMatrix database search software. Only 6.0% of tandem mass spectra that yielded peptide matches considered to be true positive matches were lost after spectral screening. The algorithm was found to be very effective at removal of unidentified spectra in other database search programs including Mascot, OMSSA, and X!Tandem (75.93%-91.00%) with a small loss (3.59%-9.40%) of true positive matches.</p

Score regularization for peptide identification

<p>Abstract</p> <p>Background</p> <p>Peptide identification from tandem mass spectrometry (MS/MS) data is one of the most important problems in computational proteomics. This technique relies heavily on the accurate assessment of the quality of peptide-spectrum matches (PSMs). However, current MS technology and PSM scoring algorithm are far from perfect, leading to the generation of incorrect peptide-spectrum pairs. Thus, it is critical to develop new post-processing techniques that can distinguish true identifications from false identifications effectively.</p> <p>Results</p> <p>In this paper, we present a consistency-based PSM re-ranking method to improve the initial identification results. This method uses one additional assumption that two peptides belonging to the same protein should be correlated to each other. We formulate an optimization problem that embraces two objectives through regularization: the smoothing consistency among scores of correlated peptides and the fitting consistency between new scores and initial scores. This optimization problem can be solved analytically. The experimental study on several real MS/MS data sets shows that this re-ranking method improves the identification performance.</p> <p>Conclusions</p> <p>The score regularization method can be used as a general post-processing step for improving peptide identifications. Source codes and data sets are available at: <url>http://bioinformatics.ust.hk/SRPI.rar</url>.</p