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This paper describes a number of simulations whichshow that SRN representations exhibit interactionsbetween m e m o r y and sentence and clauseboundaries reminiscent of effects described in theearly psycholinguistic literature (Jarvella, 1971;Caplan, 1972). Moreover, these effects can beaccounted for by the intrinsic properties of srnrepresentations without the need to invoke externalmemory mechanisms, as has conventionally beendone.

A connectionist attentional-shift model of eye-m o v e m e n t control (CASMEC) in reading is described.T h e model provides an integrated account of a rangeof saccadic control effects found in reading, such asword-skipping, refixation, and of course normalsaccadic progression.

This paper provides a short overview of current issues in research on continuous reading in non-Roman orthographies. At the same time it also serves as an introduction to the present Reading and Writing Special Issue on this topic. The main questions examined in the contributions to this volume are closely related to issues that have been central to research debates on reading in English, German and French. However, we argue that these innovative approaches to the dynamics of reading in Chinese, Japanese and Korean go far beyond a simple comparative research strategy. Instead, by illuminating phenomena like word segmentation, parafoveal processing and semantic analysis from their unique perspectives, they provide valuable insights into the more general question of to what extent information processing in reading is universal as opposed to language specific. Moreover, we expect that these initial studies will trigger more basic research on non-alphabetic reading, providing a foundation for useful application.

A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined. (Contains 5 tables.)

In her Behavioral and Brain Sciences target article, Greenfield (1991) proposed that early in a child's development Broca's area may serve the dual function of coordinating object assembly and organizing the production of structured utterances. As development progresses, the upper and lower regions of Broca's area become increasingly specialized for motor coordination and speech, respectively. This commentary presents a connectionist simulation of aspects of this proposal. The results of the simulation confirm the main thrust of Greenfield's argument and suggest that an important impetus for the developmental differentiation in Broca's area may be the increasing complexity of the computational demands made upon it.

This paper describes the use of on-line processing of anaphoric reference to explore the structure of sentence representations. Of central concern is whether or not the representation of verbs is componential The differential amounts of processing required by subjects to resolve references to objects and simple or complex actions was used to provide insights into the nature of the internal representation of sentences. Two conditions were created; one in which componential effects occured, and another in which they did not. It was concluded that processing demands dictated the nature of the representation, and that either a wholistic or compnential mode of representation could be used on-line with equal facility

This paper describes the use of semantic similarity measures based on distributed representations of words, sentences, and paragraphs (so-called "embeddings") to assess the impact of supra-lexical factors on eye-movement data from early readers of Chinese. In addition, we used a corpus-based measure of surprisal to assess the impact of local word predictability. Eye movement data from 56 Chinese students were collected (a) in the students' 4th grade and (b) one year later while they were in 5th grade. Results indicated that surprisal and some text similarity measures have a significant impact on the moment-to-moment processing of words in reading. The paper presents an easy-to-use set of tools for linking the low-level aspects of fixation durations to a hierarchy of sentence-level and paragraph-level features that can be computed automatically. The study is the first attempt, as far as we are aware, to track the developmental trajectory of these influences in developing readers across a range of reading abilities. The similarity-based measures described here can be used (a) to provide a measure of reader sensitivity to sentence and paragraph cohesion and (b) to assess specific texts for their suitability for readers of different reading ability levels. [ABSTRACT FROM AUTHOR]

Highlights ways in which standard information processing models of language, and specifically of reading, are deficient. Deficiencies are considered under four headings: (1) theoretical rigour, (2) the interaction of different levels of information during reading; (3) the parallel nature of much of human information processing, and (4) reading comprehension. (DF)

As the number of computational models of eye-movement control in reading increases, so too will their coverage and complexity. This will make their comparison and testing increasingly challenging. We argue here that there is a need to develop a methodology for constructing and evaluating such models, and outline aspects of a possible methodology.

Fractal patterns offer one way to represent the rough complexity of the natural world. Whilst they dominate many of our visual experiences in nature, little large-scale perceptual research has been done to explore how we respond aesthetically to these patterns. Previous research (Taylor et al., 2011) suggests that the fractal patterns with mid-range fractal dimensions (FDs) have universal aesthetic appeal. Perceptual and aesthetic responses to visual complexity have been more varied with findings suggesting both linear (Forsythe et al., 2011) and curvilinear (Berlyne, 1970) relationships. Individual differences have been found to account for many of the differences we see in aesthetic responses but some, such as culture, have received little attention within the fractal and complexity research fields. This two-study article aims to test preference responses to FD and visual complexity, using a large cohort (N = 443) of participants from around the world to allow universality claims to be tested. It explores the extent to which age, culture and gender can predict our preferences for fractally complex patterns. Following exploratory analysis that found strong correlations between FD and visual complexity, a series of linear mixed-effect models were implemented to explore if each of the individual variables could predict preference. The first tested a linear complexity model (likelihood of selecting the more complex image from the pair of images) and the second a mid-range FD model (likelihood of selecting an image within mid-range). Results show that individual differences can reliably predict preferences for complexity across culture, gender and age. However, in fitting with current findings the mid-range models show greater consistency in preference not mediated by gender, age or culture. This article supports the established theory that the mid-range fractal patterns appear to be a universal construct underlying preference but also highlights the fragility of universal claims by demonstrating individual differences in preference for the interrelated concept of visual complexity. This highlights a current stalemate in the field of empirical aesthetics. [ABSTRACT FROM AUTHOR]

A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined. [ABSTRACT FROM AUTHOR]

Borehole-wall imaging is currently the most reliable means of mapping discontinuities within boreholes. As these imaging techniques are expensive and thus not always included in a logging run, a method of predicting fracture frequency directly from traditional logging tool responses would be very useful and cost effective. Artificial neural networks (ANNs) show great potential in this area. ANNs are computational systems that attempt to mimic natural biological neural networks. They have the ability to recognize patterns and develop their own generalizations about a given data set. Neural networks are trained on data sets for which the solution is known and tested on data not previously seen in order to validate the network result. We show that artificial neural networks, due to their pattern recognition capabilities, are able to assess the signal strength of fracture-related heterogeneity in a borehole log and thus fracture frequency within a borehole. A combination of wireline logs (neutron porosity, bulk density, P-sonic, S-sonic, deep resistivity and shallow resistivity) were used as input parameters to the ANN. Fracture frequency calculated from borehole televiewer data was used as the single output parameter. The ANN was trained using a back-propagation algorithm with a momentum learning function. In addition to fracture frequency within a single borehole, an ANN trained on a subset of boreholes in an area could be used for prediction over the entire set of boreholes, thus allowing the lateral correlation of fracture zones. [ABSTRACT FROM AUTHOR]

Once an eye tracking experiment is complete, the task to review, clean and analyse the collected data begins. A researcher, depending on the hardware used to perform the experiment, may use a variety of tools to take their collected data and transform it into a working data set from which results relating to their experimental hypotheses can be obtained. This process can be time-consuming and complicated. EMDAS aims to improve how this process is carried out by leveraging the power of cloud computing. The platform allows data to be ingested, cleaned, analysed, transformed and allows results from the data to be obtained to either support or refute whatever experimental objective had been undertaken. Data from experiments is uploaded to the cloud-based platform, taking advantage of robust and highly available cloud storage services. Transformation of data facilitated using on-demand functions, storing the transformed artefact for analysis. Collected data is visualised within the browser, and can be cleaned in a manual or automated fashion. Areas of interest around words read by subjects are automatically determined using image recognition API's and presented alongside collected eye movement data. For data analysis, the platform provides a stable, browser-based, environment for analysis via platform containerisation technologies. Common statistical software is provided for data analysis. Results obtained from the statistical analysis can be stored securely using version control and downloaded for further use. By leveraging cloud computing, the platform provides a location for all elements of data analysis of an experiment. [ABSTRACT FROM AUTHOR]

Examples from Chinese, Thai, and Finnish illustrate why researchers cannot always be confident about the precise nature of the word unit. Understanding ambiguities regarding where a word begins and ends, and how to model word recognition when many derivations of a word are possible, is essential for universal theories of reading applied to both developing and expert readers [ABSTRACT FROM AUTHOR]

This paper describes the use of semantic similarity measures based on distributed representations of words, sentences, and paragraphs (so-called "embeddings") to assess the impact of supra-lexical factors on eye-movement data from early readers of Chinese. In addition, we used a corpus-based measure of surprisal to assess the impact of local word predictability. Eye movement data from 56 Chinese students were collected (a) in the students' 4th grade and (b) one year later while they were in 5th grade. Results indicated that surprisal and some text similarity measures have a significant impact on the momentto- moment processing of words in reading. The paper presents an easy-to-use set of tools for linking the low-level aspects of fixation durations to a hierarchy of sentence-level and paragraph-level features that can be computed automatically. The study is the first attempt, as far as we are aware, to track the developmental trajectory of these influences in developing readers across a range of reading abilities. The similarity-based measures described here can be used (a) to provide a measure of reader sensitivity to sentence and paragraph cohesion and (b) to assess specific texts for their suitability for readers of different reading ability levels., Competing Interests: The authors declare that the contents of the article are in agreement with the ethics described in http://biblio.unibe.ch/portale/elibrary/BOP/jemr/ethics.html and that there is no conflict of interest regarding the publication of this paper.

Eye-movement recording has made it possible to achieve a detailed understanding of oculomotor and cognitive behavior during reading and of changes in this behavior across the stages of reading development. Given that many students struggle to attain even basic reading skills, a logical extension of eye-movement research involves its applications in both the diagnostic and instructional areas of reading education. The focus of this symposium is on eye-movement research with potential implications for reading education. Christian Vorstius will review results from a large-scale longitudinal study that examined the development of spatial parameters in fixation patterns within three cohorts, ranging from elementary to early middle school, discussing an early development window and its potential influences on reading ability and orthography. Ronan Reilly and Xi Fan will present longitudinal data related to developmental changes in reading-related eye movements in Chinese. Their findings are indicative of increasing sensitivity to lexical predictability and sentence coherence. The authors suggest that delays in the emergence of these reading behaviors may signal early an increased risk of reading difficulty. Jochen Laubrock's presentation will focus on perceptual span development and explore dimensions of this phenomenon with potential educational implications, such as the modulation of perceptual span in relation to cognitive load, as well as preview effects during oral and silent reading --and while reading comic books. Video stream: https://vimeo.com/362645755.