This paper reports on a study of undergraduate students' experiences with criteria-referenced selfassessment. Fourteen students who had taken a course involving self-assessment were interviewed in focus groups segregated by gender. The findings suggest that students had positive attitudes toward self-assessment after extended practice; felt they can effectively self-assess when they know their teacher's expectations; claimed to use self-assessment to check their work and guide revision; and believed the benefits of self-assessment include improvements in grades, quality of work, motivation and learning. There were indications that some students sensed a tension between their own standards for good work and some of their teachers' standards. There was no evidence of differences in the responses of male and female students. The paper concludes with the suggestion that selfassessment involves a complex process of internalization and self-regulation, and with implications for research and practice. A master can tell you what he expects of you. A teacher, though, awakens your own expectations. (Patricia Neal

The RNA transcriptome varies in response to cellular differentiation as well as environmental factors, and can be characterized by the diversity and abundance of transcript isoforms. Differential transcription analysis, the detection of differences between the transcriptomes of different cells, may improve understanding of cell differentiation and development and enable the identification of biomarkers that classify disease types. The availability of high-throughput short-read RNA sequencing technologies provides in-depth sampling of the transcriptome, making it possible to accurately detect the differences between transcriptomes. In this article, we present a new method for the detection and visualization of differential transcription. Our approach does not depend on transcript or gene annotations. It also circumvents the need for full transcript inference and quantification, which is a challenging problem because of short read lengths, as well as various sampling biases. Instead, our method takes a divide-and-conquer approach to localize the difference between transcriptomes in the form of alternative splicing modules (ASMs), where transcript isoforms diverge. Our approach starts with the identification of ASMs from the splice graph, constructed directly from the exons and introns predicted from RNA-seq read alignments. The abundance of alternative splicing isoforms residing in each ASM is estimated for each sample and is compared across sample groups. A non-parametric statistical test is applied to each ASM to detect significant differential transcription with a controlled false discovery rate. The sensitivity and specificity of the method have been assessed using simulated data sets and compared with other state-of-the-art approaches. Experimental validation using qRT-PCR confirmed a selected set of genes that are differentially expressed in a lung differentiation study and a breast cancer data set, demonstrating the utility of the approach applied on experimental biological data sets. The software of DiffSplice is available at http://www.netlab.uky.edu/p/bioinfo/DiffSplice.

The purpose of this study was to investigate the effect of reading a model written assignment, generating a list of criteria for the assignment, and self‐assessing according to a rubric, as well as gender, time spent writing, prior rubric use, and previous achievement on elementary school students' scores for a written assignment (N = 116). Participants were in grades 3 and 4. The treatment involved using a model paper to scaffold the process of generating a list of criteria for an effective story or essay, receiving a written rubric, and using the rubric to self‐assess first drafts. The comparison condition involved generating a list of criteria for an effective story or essay, and reviewing first drafts. Findings include a main effect of treatment and of previous achievement on total writing scores, as well as main effects on scores for the individual criteria on the rubric. The results suggest that using a model to generate criteria for an assignment and using a rubric for self‐assessment can help elementary school students produce more effective writing.

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