Reporting NAEP Results Using Standards

What is the difference between NAEP anchor levels and achievement levels? How are the processes different for creating these levels? What points of controversy surround use of these levels for reporting achievement? Will having standards for NAEP promote improvement of public education?     

What is literacy for students with severe learning difficulties? Exploring conventional and inclusive literacy

This paper arises from research into inclusive literacy for pupils with severe learning difficulties who do not learn to read and write conventionally. The ultimate aim of the study was to seek out examples of good practice in teaching and learning literacy that includes students with severe learning difficulties and disseminate them as widely as possible. Thirty-five schools were visited and observations made in 122 lessons. Sixty-one teachers were interviewed and their paperwork examined. Ten focus groups and five 'expert witnesses' were consulted, alongside desk-based research designed to locate 'good practice'. Teachers used a mixture of conventional (e.g., texts) and non-conventional (e.g., pictures, film and oral) media, although more observations were made of conventional literacy teaching (e.g., phonic work) than of non-conventional (e.g., filmmaking). Results from the research suggest that few students with severe learning difficulties are likely to learn to read and write conventionally (i.e., read for pleasure, work and study) and teachers may be relying too much on teaching traditional literacy to them. It may be useful to explore teaching and learning around alternative media such as still and moving images, live theatre and storytelling, digital technology and the arts. Although some teachers are making good use of these media, the potential of these media for providing inclusive literacy experiences could be further developed.     

The Wiley handbook of adult literacy

International Review of Education -     

Revisiting print exposure: exploring differential links to vocabulary,comprehension and reading rate

Undergraduates (N=171) completed a revised version of the Author Recognition Test ( Stanovich & West, 1989 ). The resulting print exposure scores were divided into two dimensions: personal reading experience (primary print knowledge – PPK) and secondary print knowledge (SPK). Both PPK and SPK were correlated with print exposure, but not with each other. PPK correlated more strongly with reading‐related variables (vocabulary, comprehension and reading rate) than did SPK. Of particular importance, PPK accounted for variance in all three criterion variables after the effects of SPK had been factored out. Thus, these data support the notion that it is the act of reading over and above memory for reading‐related information that furthers the development of linguistic skill.     

Middle Grade Teachers’ Learning through Students’ Engagement with Modeling Tasks*

We report on how two middle-grade teachers supported their students’ mathematical reasoning within the context of a novel modeling task in data analysis. We examine how the task features supported the development of teachers’ knowledge as their students engaged with the task. Analyses of the teachers’ practices suggest that the task features enabled teachers: (a) to develop new understandings of the mathematical content and the ways in which student ideas develop and are represented; (b) to adopt new roles in their interactions with the students, including a focus on listening and observing, and on asking questions for understanding and clarification; and (c) to engage in forms of interpretative listening that shifted the role of evaluation from the teacher to the student. This material is based upon work supported by the National Science Foundation (NSF) under Grant No. 9722235 and by the Australian Research Council (ARC).     

Beyond Average: Contemporary statistical techniques for analysing student evaluations of teaching

Student evaluations of teaching (SETs) have been used to evaluate higher education teaching performance for decades. Reporting SET results often involves the extraction of an average for some set of course metrics, which facilitates the comparison of teaching teams across different organisational units. Here, we draw attention to ongoing problems with the naive application of this approach. Firstly, a specific average value may arise from data that demonstrates very different patterns of student satisfaction. Furthermore, the use of distance measures (e.g. an average) for ordinal data can be contested, and finally, issues of multiplicity increasingly plague approaches using hypothesis testing. It is time to advance the methodology of the field. We demonstrate how multinomial distributions and hierarchical Bayesian methods can be used to contextualise the SET scores of a course to different organisational units and student cohorts, and then show how this approach can be used to extract sensible information about how a distribution is changing.