Failure rates in introductory programming revisited.

Whilst working on an upcoming meta-analysis that synthesized fifty years of research on predictors of programming performance, we made an interesting discovery. Despite several studies citing a motivation for research as the high failure rates of introductory programming courses, to date, the majority of available evidence on this phenomenon is at best anecdotal in nature, and only a single study by Bennedsen and Caspersen has attempted to determine a worldwide pass rate of introductory programming courses. In this paper, we answer the call for further substantial evidence on the CS1 failure rate phenomenon, by performing a systematic review of introductory programming literature, and a statistical analysis on pass rate data extracted from relevant articles. Pass rates describing the outcomes of 161 CS1 courses that ran in 15 different countries, across 51 institutions were extracted and analysed. An almost identical mean worldwide pass rate of 67.7% was found. Moderator analysis revealed significant, but perhaps not substantial differences in pass rates based upon: grade level, country, and class size. However, pass rates were found not to have significantly differed over time, or based upon the programming language taught in the course. This paper serves as a motivation for researchers of introductory programming education, and provides much needed quantitative evidence on the potential difficulties and failure rates of this course

No tests required : comparing traditional and dynamic predictors of programming success.

Research over the past fifty years into predictors of programming performance has yielded little improvement in the identification of at-risk students. This is possibly because research to date is based upon using static tests, which fail to reflect changes in a student's learning progress over time. In this paper, the effectiveness of 38 traditional predictors of programming performance are compared to 12 new data-driven predictors, that are based upon analyzing directly logged data, describing the programming behavior of students. Whilst few strong correlations were found between the traditional predictors and performance, an abundance of strong significant correlations based upon programming behavior were found. A model based upon two of these metrics (Watwin score and percentage of lab time spent resolving errors) could explain 56.3% of the variance in coursework results. The implication of this study is that a student's programming behavior is one of the strongest indicators of their performance, and future work should continue to explore such predictors in different teaching contexts

Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure

The Disappearing Act of KH 15D: Photometric Results from 1995 to 2004

We present results from the most recent (2002-2004) observing campaigns of the eclipsing system KH 15D, in addition to re-reduced data obtained at Van Vleck Observatory (VVO) between 1995 and 2000. Phasing nine years of photometric data shows substantial evolution in the width and depth of the eclipses. The most recent data indicate that the eclipses are now approximately 24 days in length, or half the orbital period. These results are interpreted and discussed in the context of the recent models for this system put forward by Winn et al. and Chiang & Murray-Clay. A periodogram of the entire data set yields a highly significant peak at 48.37 +/- 0.01 days, which is in accord with the spectroscopic period of 48.38 +/- 0.01 days determined by Johnson et al. Another significant peak, at 9.6 days, was found in the periodogram of the out-of-eclipse data at two different epochs. We interpret this as the rotation period of the visible star and argue that it may be tidally locked in pseudosynchronism with its orbital motion. If so, application of Hut's theory implies that the eccentricity of the orbit is e = 0.65 +/- 0.01. Analysis of the UVES/VLT spectra obtained by Hamilton et al. shows that the v sin(i) of the visible star in this system is 6.9 +/- 0.3 km/sec. Using this value of v sin(i) and the measured rotation period of the star, we calculate the lower limit on the radius to be R = (1.3 +/- 0.1), R_Sun, which concurs with the value obtained by Hamilton et al. from its luminosity and effective temperature. Here we assume that i = 90 degrees since it is likely that the spin and orbital angular momenta vectors are nearly aligned.Comment: 55 pages, 18 figures, 1 color figure, to appear the September issue of the Astronomical Journa

Relationship between psychological and biological factors and physical activity and exercise behaviour in Filipino students

The aim of the present study was threefold. Firstly, it investigated whether a general measure or specific measure of motivational orientation was better in describing the relationship between motivation and exercise behaviour. Secondly, it examined the relationship between the four most popular indirect methods of body composition assessment and physical activity and exercise patterns. Thirdly, the interaction between motivation and body composition on physical activity and exercise behaviour was explored in a sample of 275 Filipino male and female students. Males were found to have higher levels of exercise whereas females had higher levels of physical activity. Furthermore, general self-motivation together with body weight and percentage body fat were found to be the best predictor of exercise behaviour whereas the tension/pressure subscale of the ‘Intrinsic Motivation Inventory’ (IMI) was the best predictor of levels of physical activity. However, significant gender differences were observed. That is, for the males only self-motivation and for the females only body weight and BMI predicted exercise behaviour. Also, tension/pressure predicted physical activity levels for the females but not the males. No inverse relationship was found between the four body composition measures and exercise and physical activity behaviour. The results support the notion that the psychobiological approach might be particularly relevant for high intensity exercise situations but also highlights some important gender differences. Finally, the results of this study emphasise the need for more cross-cultural research

ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification

Painting classification plays a vital role in organizing, finding, and suggesting artwork for digital and classic art galleries. Existing methods struggle with adapting knowledge from the real world to artistic images during training, leading to poor performance when dealing with different datasets. Our innovation lies in addressing these challenges through a two-step process. First, we generate more data using Style Transfer with Adaptive Instance Normalization (AdaIN), bridging the gap between diverse styles. Then, our classifier gains a boost with feature-map adaptive spatial attention modules, improving its understanding of artistic details. Moreover, we tackle the problem of imbalanced class representation by dynamically adjusting augmented samples. Through a dual-stage process involving careful hyperparameter search and model fine-tuning, we achieve an impressive 87.24\% accuracy using the ResNet-50 backbone over 40 training epochs. Our study explores quantitative analyses that compare different pretrained backbones, investigates model optimization through ablation studies, and examines how varying augmentation levels affect model performance. Complementing this, our qualitative experiments offer valuable insights into the model's decision-making process using spatial attention and its ability to differentiate between easy and challenging samples based on confidence ranking

The Seventh Data Release of the Sloan Digital Sky Survey

This paper describes the Seventh Data Release of the Sloan Digital Sky Survey (SDSS), marking the completion of the original goals of the SDSS and the end of the phase known as SDSS-II. It includes 11663 deg^2 of imaging data, with most of the roughly 2000 deg^2 increment over the previous data release lying in regions of low Galactic latitude. The catalog contains five-band photometry for 357 million distinct objects. The survey also includes repeat photometry over 250 deg^2 along the Celestial Equator in the Southern Galactic Cap. A coaddition of these data goes roughly two magnitudes fainter than the main survey. The spectroscopy is now complete over a contiguous area of 7500 deg^2 in the Northern Galactic Cap, closing the gap that was present in previous data releases. There are over 1.6 million spectra in total, including 930,000 galaxies, 120,000 quasars, and 460,000 stars. The data release includes improved stellar photometry at low Galactic latitude. The astrometry has all been recalibrated with the second version of the USNO CCD Astrograph Catalog (UCAC-2), reducing the rms statistical errors at the bright end to 45 milli-arcseconds per coordinate. A systematic error in bright galaxy photometr is less severe than previously reported for the majority of galaxies. Finally, we describe a series of improvements to the spectroscopic reductions, including better flat-fielding and improved wavelength calibration at the blue end, better processing of objects with extremely strong narrow emission lines, and an improved determination of stellar metallicities. (Abridged)Comment: 20 pages, 10 embedded figures. Accepted to ApJS after minor correction