Research Print
Thursday, 02 April 2009 22:49

The research of the Cognitive Science Research Group covers a range of topics from reading research, computational modelling of perception and language, through to studies of complex learning tasks.

READING

  • Thai
Most current models of eye movements in reading of alphabetic scripts rely on word targetting as the main strategy for guiding the eye. In alphabetic scripts that employ spaces, target selection is relatively straightforward. In the case of the Thai writing system, however, spaces are used to indicate clause boundaries (though not reliably) and ends of sentences. The lack of visible word boundaries presents the reader of Thai with a significant challenge. Central among these is how to learn reliable visual cues for locating a word's optimal viewing position.  This project aims to discover how this and other similar challenges are met. Once we have a good understanding of the low-level dynamics of eye movements in reading Thai script, it opens the way to more subtle explorations of the psycholinguistic processes involved in Thai reading.  Eye movement data was collected from a sample of readers at the Centre for Research in Speech and Language (CRSLP), Chulalongkorn University Bangkok, Thailand. This project was initially funded by an Enterprise Ireland International Collaboration Grant, and is a collaboration with Dr Sudaporn Luksaneeyanawin of the CRSLP.
Sample of Thai readers eye movements Ziying with the tracker












  • Braille

This research project has two phases: (1) to carry out a baseline study of Braille reading using an innovative combination of hand-tracking and computer-controlled Braille display; and (2) to use information from both the Braille and sighted reading studies to determine ways of improving the learning of Braille.  This project is supported in part by funding from a NUIM John and Pat Hume Scholarship.

Braille hand tracking setupRecord of one braille reader

  • Irish
The main aim of this study is to gain a deeper understanding of what typographical aspects of a text influence the ease with which children read in Irish. We use a computer-based eye-tracking system that provides a detailed picture of the moment-to-moment processes involved in reading. The type of factors we will consider relate to the size and nature of the font, the length of line, the spacing between lines, and so on. In addition, we are interested in understanding how these factors interact with such issues as the age of the reader, and the syntactic and semantic complexity of the text. This project is funded by Foras na Gaeilge.
Foras na Gaeilge
  • EEG
This project applies a novel EEG signal processing technique, VESPA, developed inter alia by researchers in NUI Maynooth, to the development of a new experimental paradigm combining EEG and eye tracking (Lalor, Kelly, Pearlmutter, Reilly & Foxe, 2007; Lalor, Pearlmutter, Foxe, Reilly & McDarby, 2006). The VESPA technique represents a significant breakthrough in the clinical use of the visually evoked potential (VEP) paradigm but more importantly offers the exciting possibility of combining the VEP and event related potential (ERP) paradigms, allowing us the to trace brain activity from stimulus through to percept with unprecedented temporal precision. This project is supported in part by funding from a NUIM John and Pat Hume Scholarship.
plot of two VESPAs
  • Glenmore
The Glenmore model of reading (Reilly & Radach, 2002) is an interactive activation model that can account within one mechanism for basic patterns of eye movement behaviour and accommodate a wide range of well-established empirical phenomena including parafoveal preview effects (Rayner & Pollatsek, 1989). A saliency map acts as an arena for the interplay of bottom-up visual features of the text, and top-down lexical features. These factors combine to create a pattern of activation which, using results from ongoing parallel word processing, selects one word as the saccade target (Findlay & Walker, 1999). The model is the focus of ongoing refinement, specifically in its application to non-western writing systems.  This project is a collaboration with Ralph Radach at Florida State University, Tallahasse, Florida.
Overview of Glenmore model



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PREDICTION OF ACADEMIC PERFORMANCE

It is well known in the Computer Science Education community that students have difficulty with learning to program and this can result in high drop-out and failure rates. Identifying struggling students is difficult as introductory programming modules tend to have a very high student to lecturer ratio (100:1 or greater) and often lecturers do not know how well students are doing until after the first assessment. At this stage, it may be too late for students to withdraw from the course or to intervene to prevent struggling students from failing. This is a cause of great concern for educators and has led to a body of research in the area. Although many studies have interesting results it can be hard to know how to apply the results to other educational settings. Furthermore, the factors examined are often dependent upon the students' experience on the module and with the material and therefore it is difficult to know how predictive the factors would be if measured at the commencement of the module.

A classification model that could predict likely programming performance in the first few weeks of a module would considerably help to alleviate this problem. To build such a model would require (1) the identification of early-assessable predictors of introductory programming performance and (2) the appropriate implementation and evaluation of a scientifically sound, predictive computational model. This research project is concerned with the successful development of such a model.

 

 

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Natural Computing

Recent discoveries in genetics suggest that some organisms (eg Arabidopsis thaliana and the mouse) use a surprising and controversial mechanism to repair some genetic defects. They appear to use a non-Mendelian form of inheritance, whereby the corrective genetic information appears to by-pass some generations. We are using this ancestral genetic repair strategy to solve some evolutionary optimisation problems with two distinct objectives in mind. First, we wish to evaluate the applicability of this proposed non-Mendelian genetic repair strategy to evolutionary optimisation tasks. Secondly, we wish to assess the conditions under which the proposed genetic repair process might be an effective strategy in nature.

 

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Last Updated on Thursday, 03 March 2011 14:57