Translating Normalcy: Tutors Navigating Spaces Between Expectations and Experiences for Non-Traditional Students

Non-traditional students make up a large portion of the current college student population. Mike Rose indicates that the “non-traditional student is becoming the new norm” for higher education, and according to the National Center for Education Statistics, nontraditional students make up “almost 40%” of all students enrolled in higher education (8). This number is slippery, however, as there are different definitions of non-traditional students. The National Center for Education Statistics defines non-traditional students as students who have had at least a five-year break in their education (National). Sometimes financial independence or high school-related experiences are the guides for this label, which includes those who have a GED, were homeschooled, or have an international schooling background (Hess, National). At my institution, non-traditional students are classified as students over the age of 25, and they make up 37% of our student population.University Writing Cente

Caring, sharing widgets: a toolkit of sensitive widgets

Although most of us communicate using multiple sensory modalities in our lives, and many of our computers are similarly capable of multi-modal interaction, most human-computer interaction is predominantly in the visual mode. This paper describes a toolkit of widgets that are capable of presenting themselves in multiple modalities, but further are capapble of adapting their presentation to suit the contexts and environments in which they are used. This is of increasing importance as the use of mobile devices becomes ubiquitous

Variable dimension weighted universal vector quantization and noiseless coding

A new algorithm for variable dimension weighted universal coding is introduced. Combining the multi-codebook system of weighted universal vector quantization (WUVQ), the partitioning technique of variable dimension vector quantization, and the optimal design strategy common to both, variable dimension WUVQ allows mixture sources to be effectively carved into their component subsources, each of which can then be encoded with the codebook best matched to that source. Application of variable dimension WUVQ to a sequence of medical images provides up to 4.8 dB improvement in signal to quantization noise ratio over WUVQ and up to 11 dB improvement over a standard full-search vector quantizer followed by an entropy code. The optimal partitioning technique can likewise be applied with a collection of noiseless codes, as found in weighted universal noiseless coding (WUNC). The resulting algorithm for variable dimension WUNC is also described

Finding an identity and meeting a standard : connecting the conflicting in teacher induction

This article has the apparently contradictory aims of describing a discourse of new teachers that is at odds with the policy-derived competence-based discourse of the professional standard for teachers, but of also seeking to find some points of connection that may help start a dialogue between policy and research. The experience of new teachers is conceptualized as personal stories of identity formation with a clear emotional-relational dimension and a sense of self and intrinsic purpose in which others, especially colleagues and children, are central - themes not visible in the standard. The empirical context is that of new teachers in Scotland but the argument is supported through a wider literature that extends beyond the traditional limits of teacher education, drawing on, for example, notions of self-identity, pure relationship and ontological security in the work of Giddens. Whether a more constructive dialogue can begin depends partly on the extent to which the formal standard can be expected to capture the complex, personal nature of the beginner's experience, and partly on the possibility of research identifying particular areas of competence, such as understanding difference, that connect in some way to the standard

One-pass adaptive universal vector quantization

The authors introduce a one-pass adaptive universal quantization technique for real, bounded alphabet, stationary sources. The algorithm is set on line without any prior knowledge of the statistics of the sources which it might encounter and asymptotically achieves ideal performance on all sources that it sees. The system consists of an encoder and a decoder. At increasing intervals, the encoder refines its codebook using knowledge about incoming data symbols. This codebook is then described to the decoder in the form of updates on the previous codebook. The accuracy to which the codebook is described increases as the number of symbols seen, and thus the accuracy to which the codebook is known, grows

Variable-rate source coding theorems for stationary nonergodic sources

For a stationary ergodic source, the source coding theorem and its converse imply that the optimal performance theoretically achievable by a fixed-rate or variable-rate block quantizer is equal to the distortion-rate function, which is defined as the infimum of an expected distortion subject to a mutual information constraint. For a stationary nonergodic source, however, the. Distortion-rate function cannot in general be achieved arbitrarily closely by a fixed-rate block code. We show, though, that for any stationary nonergodic source with a Polish alphabet, the distortion-rate function can be achieved arbitrarily closely by a variable-rate block code. We also show that the distortion-rate function of a stationary nonergodic source has a decomposition as the average of the distortion-rate functions of the source's stationary ergodic components, where the average is taken over points on the component distortion-rate functions having the same slope. These results extend previously known results for finite alphabets

Rates of convergence in adaptive universal vector quantization

We consider the problem of adaptive universal quantization. By adaptive quantization we mean quantization for which the delay associated with encoding the jth sample in a sequence of length n is bounded for all n>j. We demonstrate the existence of an adaptive universal quantization algorithm for which any weighted sum of the rate and the expected mean square error converges almost surely and in expectation as O(√(log log n/log n)) to the corresponding weighted sum of the rate and the distortion-rate function at that rate