Multisensory Literacy Instruction: Efficacy for Struggling Multilingual Learners

By the year 2025, approximately 25% of U.S. public school students will be multilingual learners. However, many mainstream teachers have not received any development in supporting this particular group of students. This capstone explores best literacy practices for multilingual learners, multisensory learning, and teacher professional development to answer the focus question: how can multisensory instruction be utilized to add engagement and rigor in order to improve the literacy skills of multilingual learners between 5 - 8 years old who score between a 1.0 - 2.9 on the WIDA Access Assessment and are struggling with basic reading skills? Multisensory literacy instruction can be used to close the opportunity gap for multilingual learners who are struggling readers. The research concludes that dual coding theory explains how multisensory instruction can support struggling readers by activating working memory through both the phonological loop and the visual-spatial sketchpad, as well as increased repetition and review. This project is comprised of four hour-long professional development sessions in a series intended for all literacy teachers of multilingual learners. Through this development, teachers will increase their knowledge of multisensory instruction as well as their levels of self-efficacy in teaching multilingual learners

An evaluation on the Wilson Reading Program for students with learning disabilities: a longitudinal study

The purpose of this study was to examine the effects of the Wilson Reading Program as a supplemental reading program for students with disabilities. A school district\u27s student decoding and comprehension scores in three years were reviewed and synthesized for the program evaluation. The analysis of variance (ANOVA) with a repeated measure was used to compare possible differences of student performance in decoding and word recognition, and overall reading skills at each grade level respectively. It was found that the Wilson Reading Program had a significant effect on students\u27 Word Reading Scores in Year 2 of the intervention, but not significant on Year 3, although their scores were increased compared to Year 1. This indicates that novelty of the program may have a great impact on students\u27 reading performance. Although the findings are not consistent from one group to another, there seems to be some correlation between Word Reading and Measurement of Academic Progress (MAP) scores

Improving Phonics and Fluency Skills Using a Multisensory Language Intervention

The purpose of this single case design study was to examine the efficacy of multisensory language instruction, specifically the Wilson Reading System, on the phonetic analysis skills and reading fluency of a single student identified as dyslexic. Data was collected for a period of eight weeks and analyzed using visual representations to determine participant growth in all areas assessed. Data showed growth of 20 words read correctly per minute (WCPM) with a projected gain of 16 WCPM according to Hasbrouk and Tindal\u27s (2006) reading fluency normative chart. The education implications of the study are discussed and recommendations for further research are given. Overall, the intervention was deemed successful from data collected

Identification of Dendritic Processing in Spiking Neural Circuits

A large body of experimental evidence points to sophisticated signal processing taking place at the level of dendritic trees and dendritic branches of neurons. This evidence suggests that, in addition to inferring the connectivity between neurons, identifying analog dendritic processing in individual cells is fundamentally important to understanding the underlying principles of neural computation. In this thesis, we develop a novel theoretical framework for the identification of dendritic processing directly from spike times produced by spiking neurons. The problem setting of spiking neurons is necessary since such neurons make up the majority of electrically excitable cells in most nervous systems and it is often hard or even impossible to directly monitor the activity within dendrites. Thus, action potentials produced by neurons often constitute the only causal and observable correlate of dendritic processing. In order to remain true to the underlying biophysics of electrically excitable cells, we employ well-established mechanistic models of action potential generation to describe the nonlinear mapping of the aggregate current produced by the tree into an asynchronous sequence of spikes. Specific models of spike generation considered include conductance-based models such as Hodgkin-Huxley, Morris-Lecar, Fitzhugh-Nagumo, as well as simpler models of the integrate-and-fire and threshold-and-fire type. The aggregate time-varying current driving the spike generator is taken to be produced by a dendritic stimulus processor, which is a nonlinear dynamical system capable of describing arbitrary linear and nonlinear transformations performed on one or more input stimuli. In the case of multiple stimuli, it can also describe the cross-coupling, or interaction, between various stimulus features. The behavior of the dendritic stimulus processor is fully captured by one or more kernels, which provide a characterization of the signal processing that is consistent with the broader cable theory description of dendritic trees. We prove that the neural identification problem, stated in terms of identifying the kernels of the dendritic stimulus processor, is mathematically dual to the neural population encoding problem. Specifically, we show that the collection of spikes produced by a single neuron in multiple experimental trials can be treated as a single multidimensional spike train of a population of neurons encoding the parameters of the dendritic stimulus processor. Using the theory of sampling in reproducing kernel Hilbert spaces, we then derive precise results demonstrating that, during any experiment, the entire neural circuit is projected onto the space of input stimuli and parameters of this projection are faithfully encoded in the spike train. Spike times are shown to correspond to generalized samples, or measurements, of this projection in a system of coordinates that is not fixed but is both neuron- and stimulus-dependent. We examine the theoretical conditions under which it may be possible to reconstruct the dendritic stimulus processor from these samples and derive corresponding experimental conditions for the minimum number of spikes and stimuli that need to be used. We also provide explicit algorithms for reconstructing the kernel projection and demonstrate that, under natural conditions, this projection converges to the true kernel. The developed methodology is quite general and can be applied to a number of neural circuits. In particular, the methods discussed span all sensory modalities, including vision, audition and olfaction, in which external stimuli are typically continuous functions of time and space. The results can also be applied to circuits in higher brain centers that receive multi-dimensional spike trains as input stimuli instead of continuous signals. In addition, the modularity of the approach allows one to extend it to mixed-signal circuits processing both continuous and spiking stimuli, to circuits with extensive lateral connections and feedback, as well as to multisensory circuits concurrently processing multiple stimuli of different dimensions, such as audio and video. Another important extension of the approach can be used to estimate the phase response curves of a neuron. All of the theoretical results are accompanied by detailed examples demonstrating the performance of the proposed identification algorithms. We employ both synthetic and naturalistic stimuli such as natural video and audio to highlight the power of the approach. Finally, we consider the implication of our work on problems pertaining to neural encoding and decoding and discuss promising directions for future research

The Impact of a Multisensory Intervention on Literacy Attitudes of Students with Dyslexia

The purpose of this qualitative multiple case study was to explore the impact of a pull-out multisensory reading intervention on the attitudes towards reading and writing of fourth-grade students identified with dyslexia. Students identified with dyslexia must receive an evidence-based reading intervention as required by Texas educational state law. The multisensory reading intervention utilized in this study and known as Structured Literacy, included explicit instruction in phonological awareness, sound-symbol association, syllabication, orthography, morphology, and reading comprehension. The researcher focused on a variety of data sources including field notes, audio-recorded interviews, reading interest survey responses, and spelling assessments. The data collected was analyzed holistically for an in-depth exploration leading to a rich interpretation of emerging themes. Four themes emerged from this study and are as follows: (a) participant self-awareness of reading and writing improvement; (b) increased classroom participation; (c) positive literacy attitude; and (d) an awareness and confidence of ability to learn with dyslexia. Findings from this study have the potential to inform educational decisions for teachers, administrators, and policymakers concerned about improving literacy achievement in students identified with dyslexia and related language disabilities in the elementary grades

Decoding strategies for emerging readers

The effects of using explicit decoding and phonological awareness instruction for struggling readers were studied. Four kindergarten students who were showing no academic gains in reading took part in an intervention program over seven weeks, while a comparison group of four students at a similar reading level continued their business as usual reading program. The students were tested using sections from the Woodcock Reading Mastery and Fountas and Pinnel Reading Level test before and after the study. The results showed support for the hypotheses that an explicit decoding and phonological awareness intervention would improve student reading level

Particle-filtering approaches for nonlinear Bayesian decoding of neuronal spike trains

The number of neurons that can be simultaneously recorded doubles every seven years. This ever increasing number of recorded neurons opens up the possibility to address new questions and extract higher dimensional stimuli from the recordings. Modeling neural spike trains as point processes, this task of extracting dynamical signals from spike trains is commonly set in the context of nonlinear filtering theory. Particle filter methods relying on importance weights are generic algorithms that solve the filtering task numerically, but exhibit a serious drawback when the problem dimensionality is high: they are known to suffer from the 'curse of dimensionality' (COD), i.e. the number of particles required for a certain performance scales exponentially with the observable dimensions. Here, we first briefly review the theory on filtering with point process observations in continuous time. Based on this theory, we investigate both analytically and numerically the reason for the COD of weighted particle filtering approaches: Similarly to particle filtering with continuous-time observations, the COD with point-process observations is due to the decay of effective number of particles, an effect that is stronger when the number of observable dimensions increases. Given the success of unweighted particle filtering approaches in overcoming the COD for continuous- time observations, we introduce an unweighted particle filter for point-process observations, the spike-based Neural Particle Filter (sNPF), and show that it exhibits a similar favorable scaling as the number of dimensions grows. Further, we derive rules for the parameters of the sNPF from a maximum likelihood approach learning. We finally employ a simple decoding task to illustrate the capabilities of the sNPF and to highlight one possible future application of our inference and learning algorithm

Systematic biases in human heading estimation.

Heading estimation is vital to everyday navigation and locomotion. Despite extensive behavioral and physiological research on both visual and vestibular heading estimation over more than two decades, the accuracy of heading estimation has not yet been systematically evaluated. Therefore human visual and vestibular heading estimation was assessed in the horizontal plane using a motion platform and stereo visual display. Heading angle was overestimated during forward movements and underestimated during backward movements in response to both visual and vestibular stimuli, indicating an overall multimodal bias toward lateral directions. Lateral biases are consistent with the overrepresentation of lateral preferred directions observed in neural populations that carry visual and vestibular heading information, including MSTd and otolith afferent populations. Due to this overrepresentation, population vector decoding yields patterns of bias remarkably similar to those observed behaviorally. Lateral biases are inconsistent with standard bayesian accounts which predict that estimates should be biased toward the most common straight forward heading direction. Nevertheless, lateral biases may be functionally relevant. They effectively constitute a perceptual scale expansion around straight ahead which could allow for more precise estimation and provide a high gain feedback signal to facilitate maintenance of straight-forward heading during everyday navigation and locomotion

Contributions of local speech encoding and functional connectivity to audio-visual speech perception

Seeing a speaker’s face enhances speech intelligibility in adverse environments. We investigated the underlying network mechanisms by quantifying local speech representations and directed connectivity in MEG data obtained while human participants listened to speech of varying acoustic SNR and visual context. During high acoustic SNR speech encoding by temporally entrained brain activity was strong in temporal and inferior frontal cortex, while during low SNR strong entrainment emerged in premotor and superior frontal cortex. These changes in local encoding were accompanied by changes in directed connectivity along the ventral stream and the auditory-premotor axis. Importantly, the behavioral benefit arising from seeing the speaker’s face was not predicted by changes in local encoding but rather by enhanced functional connectivity between temporal and inferior frontal cortex. Our results demonstrate a role of auditory-frontal interactions in visual speech representations and suggest that functional connectivity along the ventral pathway facilitates speech comprehension in multisensory environments