Potential utility of actuarial methods for identifying specific learning disabilities

This article describes how actuarial methods can supplant discrepancy models and augment problem solving and Response to Intervention (RTI) efforts by guiding the process of identifying specific learning disabilities (SLD). Actuarial methods use routinized selection and execution of formulas derived from empirically established relationships to make predictions that fall within a plausible range of possible future outcomes. In the case of SLD identification, the extent to which predictions are reasonable can be evaluated by their ability to categorize large segments of the population into subgroups that vary considerably along a spectrum of risk for academic failure. Although empirical comparisons of actuarial methods to clinical judgment reveal that actuarial methods consistently outperform clinical judgment, multidisciplinary teams charged with identifying SLD currently rely on clinical judgment. Actuarial methods provide educators with an empirically verifiable indicator of student need for special education and related services that could be used to estimate the relative effects of exclusionary criteria. This indicator would provide a defensible endpoint in the process of identifying SLD as well as a means of informing and improving the SLD identification process. © 2010 Wiley Periodicals, Inc.     

Addressing the context of e‐learning: using transactional distance theory to inform design

The rapidly expanding range of options available for innovative e‐learning approaches based on emerging technologies has given renewed importance to teaching and learning issues that have long been familiar to distance educators. These issues arise from the separation between learners, and between teacher and learners, which occurs when learning is undertaken wholly or partly online. There may be important implications that emerge from aspects of separation, depending on whether students are studying primarily on‐campus, off‐campus, trans‐nationally, or in specific contexts such as the home, the workplace, fieldwork locations, or other places made possible by mobile learning technologies. We suggest that the context of learning has significant implications for e‐learning design, and that one way of analysing these implications is to draw on understandings from distance education, particularly the theory of transactional distance. We use cases from two Australian universities to illustrate the practical application of these implications to e‐learning design, including designs that involve Web 2.0 technologies.     

Psychometric quality of a student evaluation of teaching survey in higher education

Student evaluations of teaching (SET) are used globally by higher education institutions for performance assessment of academic staff and evaluation of course quality. Higher education institutions commonly develop their own SETs to measure variables deemed relevant to them. However, ‘home-grown’ SETs are rarely assessed psychometrically. One potential consequence of this limitation is that an invalidated instrument may not provide accurate information for the intended purposes. Moreover, in the absence of psychometric assessment, the students’ voices collected by the SETs often fail to provide insight relative to their intended purpose. The present study evaluates a ‘home-grown’ SET using a Rasch model and confirmatory factor analysis. Our results identified weaknesses in two areas: the rating categories and the number of items used to measure the intended constructs. Suggestions are provided to address these weaknesses. This work provides an additional tool set for critical analysis of SET that is generally applicable for a variety of institutions, including those in Asia.