Visual complexity has been known to be a significant predictor of preference for artistic works for some time. The first study reported here examines the extent to which perceived visual complexity in art can be successfully predicted using automated measures of complexity. Contrary to previous findings the most successful predictor of visual complexity was Gif compression. The second study examined the extent to which fractal dimension could account for judgments of perceived beauty. The fractal dimension measure accounts for more of the variance in judgments of perceived beauty in visual art than measures of visual complexity alone, particularly for abstract and natural images. Results also suggest that when colour is removed from an artistic image observers are unable to make meaningful judgments as to its beauty.

Complexity is conventionally defined as the level of detail or intricacy contained within a picture. The study of complexity has received relatively little attention-in part, because of the absence of an acceptable metric. Traditionally, normative ratings of complexity have been based on human judgments. However, this study demonstrates that published norms for visual complexity are biased. Familiarity and learning influence the subjective complexity scores for nonsense shapes, with a significant training X familiarity interaction [F(1,52) = 17.53,

Feedback is an emotional business in which personal disposition influences what is attended to, encoded, consolidated and, eventually retrieved. Here we examine the extent to which student's perceptions of feedback and their personal dispositions can be used to predict whether students appreciate, engage with and act on the feedback that they receive. Framed in psychological theories of mindset (Dweck, 2002), defensive behaviours (Bandura, 1977) and new psychometric measures of the psychological integration of assessment feedback (Boudrias, Bernaud & Plunier, 2012). Results suggest that, in this University population, growth mindset students were in the minority. Generally students are fostering self-defensive behaviours that fail to nurture remediation following feedback. Recommendations explore the implications for students who engage in self-deception and the ways in which psychologists and academics may intercede to help student's progress academically by increasing their self-awareness.

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Internationally, the political appetite for educational measurement capable of capturing a metric of value for money and effectiveness has momentum. While most would agree with the need to assess costs relevant to quality to help support better governmental policy decisions about public spending, poorly understood measurement comes with unintended consequences. This article provides a comprehensive overview of the development of measures of learning gain in higher education, exploring political contexts, methodological challenges, and the multiple purposes and potential of learning gain metrics for quality assurance, accountability and enhancement, and most importantly, we argue, the enhancement of learning and teaching. Learning gain approaches should be integral to curriculum design and delivery and not extraneous to it. Enhancing shared understandings of concepts, measures, and instruments, transparency in reporting and investment in developing pedagogical research literacy, including effective use of data are essential in the pursuit of meaningful approaches to measuring learning gain within higher education.