Models for Paired Comparison Data: A Review with Emphasis on Dependent Data

Thurstonian and Bradley-Terry models are the most commonly applied models in the analysis of paired comparison data. Since their introduction, numerous developments have been proposed in different areas. This paper provides an updated overview of these extensions, including how to account for object- and subject-specific covariates and how to deal with ordinal paired comparison data. Special emphasis is given to models for dependent comparisons. Although these models are more realistic, their use is complicated by numerical difficulties. We therefore concentrate on implementation issues. In particular, a pairwise likelihood approach is explored for models for dependent paired comparison data, and a simulation study is carried out to compare the performance of maximum pairwise likelihood with other limited information estimation methods. The methodology is illustrated throughout using a real data set about university paired comparisons performed by students.Comment: Published in at http://dx.doi.org/10.1214/12-STS396 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Tac-tiles: multimodal pie charts for visually impaired users

Tac-tiles is an accessible interface that allows visually impaired users to browse graphical information using tactile and audio feedback. The system uses a graphics tablet which is augmented with a tangible overlay tile to guide user exploration. Dynamic feedback is provided by a tactile pin-array at the fingertips, and through speech/non-speech audio cues. In designing the system, we seek to preserve the affordances and metaphors of traditional, low-tech teaching media for the blind, and combine this with the benefits of a digital representation. Traditional tangible media allow rapid, non-sequential access to data, promote easy and unambiguous access to resources such as axes and gridlines, allow the use of external memory, and preserve visual conventions, thus promoting collaboration with sighted colleagues. A prototype system was evaluated with visually impaired users, and recommendations for multimodal design were derived

A case study of the barriers and enablers affecting teaching staff e-learning provision

Presented at the International Conference on Information Communication Technologies in Education, 7-9 July, 2016, Rhodes Greece.The present paper reports the outputs of a focus group examining the perceived uses, enablers and barriers of utilising virtual learning environments (VLEs), amongst a small group of postgraduate teachers. Sixteen pedagogical/teaching functions were identified and were mapped to MacLean and Scott’s (2011) model of VLE elements. Whilst a number of enablers of VLE use were apparent, participants’ insights and inputs indicated a larger number of VLE barriers. It appears that the biggest barrier to overcome in using VLEs is finding the time to develop the materials and navigate the technology

Logistic Knowledge Tracing: A Constrained Framework for Learner Modeling

Adaptive learning technology solutions often use a learner model to trace learning and make pedagogical decisions. The present research introduces a formalized methodology for specifying learner models, Logistic Knowledge Tracing (LKT), that consolidates many extant learner modeling methods. The strength of LKT is the specification of a symbolic notation system for alternative logistic regression models that is powerful enough to specify many extant models in the literature and many new models. To demonstrate the generality of LKT, we fit 12 models, some variants of well-known models and some newly devised, to 6 learning technology datasets. The results indicated that no single learner model was best in all cases, further justifying a broad approach that considers multiple learner model features and the learning context. The models presented here avoid student-level fixed parameters to increase generalizability. We also introduce features to stand in for these intercepts. We argue that to be maximally applicable, a learner model needs to adapt to student differences, rather than needing to be pre-parameterized with the level of each student's ability

Model-based clustering with data correction for removing artifacts in gene expression data

The NIH Library of Integrated Network-based Cellular Signatures (LINCS) contains gene expression data from over a million experiments, using Luminex Bead technology. Only 500 colors are used to measure the expression levels of the 1,000 landmark genes measured, and the data for the resulting pairs of genes are deconvolved. The raw data are sometimes inadequate for reliable deconvolution leading to artifacts in the final processed data. These include the expression levels of paired genes being flipped or given the same value, and clusters of values that are not at the true expression level. We propose a new method called model-based clustering with data correction (MCDC) that is able to identify and correct these three kinds of artifacts simultaneously. We show that MCDC improves the resulting gene expression data in terms of agreement with external baselines, as well as improving results from subsequent analysis.Comment: 28 page

Joint perception: gaze and social context

We found that the way people looked at images was influenced by their belief that others were looking too. If participants believed that an unseen other person was also looking at what they could see, it shifted the balance of their gaze between negative and positive images. The direction of this shift depended upon whether participants thought that later they would be compared against the other person or would be collaborating with them. Changes in the social context influenced both gaze and memory processes, and were not due just to participants' belief that they are looking at the same images, but also to the belief that they are doing the same task. We believe that the phenomenon of joint perception reveals the pervasive and subtle effect of social context upon cognitive and perceptual processes