“Action Research into Pre-sessional Students' Differentiation of Assessments: Using Findings to Improve Courses”

Conference proceedings papaer in Whong, M. (Ed.), Proceedings of the 2007 BALEAP conference: English in a globalising world: English as an academic lingua franca,. Bern: Peter Lang.

Enzymatically-triggered, isothermally responsive polymers: re-programming poly(oligoethylene glycols) to respond to phosphatase

Polymers which can respond to externally applied stimuli have found much application in the biomedical field due to their (reversible) coil–globule transitions. Polymers displaying a lower critical solution temperature are the most commonly used, but for blood-borne (i.e., soluble) biomedical applications the application of heat is not always possible, nor practical. Here we report the design and synthesis of poly(oligoethylene glycol methacrylate)-based polymers whose cloud points are easily varied by alkaline phosphatase-mediated dephosphorylation. By fine-tuning the density of phosphate groups on the backbone, it was possible to induce an isothermal transition: A change in solubility triggered by removal of a small number of phosphate esters from the side chains activating the LCST-type response. As there was no temperature change involved, this serves as a model of a cell-instructed polymer response. Finally, it was found that both polymers were non cytotoxic against MCF-7 cells (at 1 mg·mL–1), which confirms promise for biomedical applications.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

Elderly learners and Massive Open Online Courses: a review

Background: Massive open online courses (MOOCs) have become commonplace in the e-learning landscape. Thousands of elderly learners are participating in courses offered by various institutions on a multitude of platforms in many different languages. However, there is very little research into understanding elderly learners in MOOCs. Objective: We aim to show that a considerable proportion of elderly learners are participating in MOOCs and that there is a lack of research in this area. We hope this assertion of the wide gap in research on elderly learners in MOOCs will pave the way for more research in this area. Methods: Pre-course survey data for 10 University of Reading courses on the FutureLearn platform were analyzed to show the level of participation of elderly learners in MOOCs. Two MOOC aggregator sites (Class Central and MOOC List) were consulted to gather data on MOOC offerings that include topics relating to aging. In parallel, a selected set of MOOC platform catalogues, along with a recently published review on health and medicine-related MOOCs, were searched to find courses relating to aging. A systematic literature search was then employed to identify research articles on elderly learners in MOOCs. Results: The 10 courses reviewed had a considerable proportion of elderly learners participating in them. For the over-66 age group, this varied from 0.5% (on the course “Managing people”) to 16.3% (on the course “Our changing climate”), while for the over-56 age group it ranged from 3.0% (on “A beginners guide to writing in English”) to 39.5% (on “Heart health”). Only six MOOCs were found to include topics related to aging: three were on the Coursera platform, two on the FutureLearn platform, and one on the Open2Study platform. Just three scholarly articles relating to MOOCs and elderly learners were retrieved from the literature search. Conclusions: This review presents evidence to suggest that elderly learners are already participating in MOOCs. Despite this, there has been very little research into their engagement with MOOCs. Similarly, there has been little research into exploiting the scope of MOOCs for delivering topics that would be of interest to elderly learners. We believe there is potential to use MOOCs as a way of tackling the issue of loneliness among older adults by engaging them as either resource personnel or learners.