Development of audiovisual comprehension skills in prelingually deaf children with cochlear implants

Objective: The present study investigated the development of audiovisual comprehension skills in prelingually deaf children who received cochlear implants. Design: We analyzed results obtained with the Common Phrases (Robbins et al., 1995) test of sentence comprehension from 80 prelingually deaf children with cochlear implants who were enrolled in a longitudinal study, from pre-implantation to 5 years after implantation. Results: The results revealed that prelingually deaf children with cochlear implants performed better under audiovisual (AV) presentation compared with auditory-alone (A-alone) or visual-alone (V-alone) conditions. AV sentence comprehension skills were found to be strongly correlated with several clinical outcome measures of speech perception, speech intelligibility, and language. Finally, pre-implantation V-alone performance on the Common Phrases test was strongly correlated with 3-year postimplantation performance on clinical outcome measures of speech perception, speech intelligibility, and language skills. Conclusions: The results suggest that lipreading skills and AV speech perception reflect a common source of variance associated with the development of phonological processing skills that is shared among a wide range of speech and language outcome measures

A longitudinal study of audiovisual speech perception by hearing-impaired children with cochlear implants

The present study investigated the development of audiovisual speech perception skills in children who are prelingually deaf and received cochlear implants. We analyzed results from the Pediatric Speech Intelligibility (Jerger, Lewis, Hawkins, & Jerger, 1980) test of audiovisual spoken word and sentence recognition skills obtained from a large group of young children with cochlear implants enrolled in a longitudinal study, from pre-implantation to 3 years post-implantation. The results revealed better performance under the audiovisual presentation condition compared with auditory-alone and visual-alone conditions. Performance in all three conditions improved over time following implantation. The results also revealed differential effects of early sensory and linguistic experience. Children from oral communication (OC) education backgrounds performed better overall than children from total communication (TC backgrounds. Finally, children in the early-implanted group performed better than children in the late-implanted group in the auditory-alone presentation condition after 2 years of cochlear implant use, whereas children in the late-implanted group performed better than children in the early-implanted group in the visual-alone condition. The results of the present study suggest that measures of audiovisual speech perception may provide new methods to assess hearing, speech, and language development in young children with cochlear implants

Addressing Leandro: Supporting Student Learning by Mitigating Student Hunger

Many students face barriers that prevent them from reaching their full potential in school and beyond. Although some of these barriers are outside the domain of education, solving hunger is one challenge that is both important for school performance and feasible as a policy option. This report reviews the economic importance of investing in strategies to reduce hunger among students, highlights innovative approaches available to schools and districts, and reviews state-level policies to mitigate this challenge for students in North Carolina

The Learning Healthcare System: How an Adult Education Lens Can Be Used to Inform a Paradigm Shift in US Healthcare Landscape

Adult education researchers and practitioners have an unprecedented opportunity to inform and learn with the health care system as it embraces learning as a process to provide the best care at lower cost

No Such Thing As A Free Lunch? A Three Part Analysis Of Free School Meal Programs Under The Community Eligibility Provision

Traditional federal school meals help mitigate food insecurity among students (Hinrichs, 2010) but do not fully eliminate it. The Community Eligibility Provision (CEP) is a federal attempt to expand access to school meals in areas of targeted need. Schools that opt into CEP offer meals at no cost to all students regardless of individual need, thus replacing free and reduced-price meal applications. However, by virtue of the funding design, schools with lower levels of documented poverty are financially disincentivized from participating in CEP and despite promising benefits, many of these schools do not take up the program. Importantly, even though these schools demonstrate “lower” need, their needs may still be persistent and severe as qualification standards may under-diagnose poverty, especially in specific communities. I conduct a three-part analysis of CEP. Part one is a systematic review of existing CEP literature. CEP has shown promise in initial research to benefit students with positive outcomes on student participation in meal programs, improved nutrition quality, improved test scores, and improved attendance and taken cumulatively, indicate a reduction in anti-poverty stigma. In part two, I conduct a novel analysis of schools that opt into CEP before subsequently opting out. I find that students miss more school when CEP is taken away, an effect driven largely by students who are economically disadvantaged. In part three, I analyze the economic implications of policy proposals that expand or contract CEP. Results indicate that CEP could be expanded to provide access to nearly 20 million more students with a net federal school meal expenditure change of between 11-15.3%. Taken together, CEP is a program that benefits economically disadvantaged students in spite of a sliding scale finance schedule that disadvantages schools. Policy changes that would improve this sliding scale feature are reasonably feasible and would impact millions of economically disadvantaged students. These analyses are timely, given recent interest in the expansion of CEP and have the potential to contribute to important conversations on the future of federal school meal policy

Female administrators perceptions of distance learning

Gender disparity is evident in tenure track and tenured faculty positions at universities. However, distance education may provide more supportive environments for female academicians to grow and develop. The term distance learning is used to encompass any type of instruction delivered off campus. Distance learning has increased dramatically and has gained strategic importance possibly presenting women with a new realm for advancement. Leaders in distance learning must have qualities such as good listening skills, be understanding, engage in collaboration, be cooperative, demonstrate openness, have interpersonal sensitivity and empathy; attributes traditionally associated with females. This qualitative study utilizing a survey design, asked 21 participants, female administrators in distance education: “What are your perceptions of the role of distance learning in education today?” They perceived the role of distance learning in education today to be of utmost import and discussed the needs of learners, the access of distance learning, value of distance learning, federal and state requirements, the future of distance learning, the significant impact on Higher Education and the improvement needed

Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI

As the importance of high-throughput screening (HTS) continues to grow due to its value in early stage drug discovery and data generation for training machine learning models, there is a growing need for robust methods for pre-screening compounds to identify and prevent false-positive hits. Small, colloidally aggregating molecules are one of the primary sources of false-positive hits in high-throughput screens, making them an ideal candidate to target for removal from libraries using predictive pre-screening tools. However, a lack of understanding of the causes of molecular aggregation introduces difficulty in the development of predictive tools for detecting aggregating molecules. Herein, we present an examination of the molecular features differentiating datasets of aggregating and non-aggregating molecules, as well as a machine learning approach to predicting molecular aggregation. Our method uses explainable graph neural networks and counterfactuals to reliably predict and explain aggregation, giving additional insights and design rules for future screening. The integration of this method in HTS approaches will help combat false positives, providing better lead molecules more rapidly and thus accelerating drug discovery cycles.Comment: 17 pages, plus S

Comparing Emotion Recognition Skills among Children with and without Jailed Parents

Approximately five million children in the United States have experienced a co-resident parent’s incarceration in jail or prison. Parental incarceration is associated with multiple risk factors for maladjustment, which may contribute to the increased likelihood of behavioral problems in this population. Few studies have examined early predictors of maladjustment among children with incarcerated parents, limiting scholars’ understanding about potential points for prevention and intervention. Emotion recognition skills may play a role in the development of maladjustment and may be amenable to intervention. The current study examined whether emotion recognition skills differed between three- to eight-year-old children with and without jailed parents. We hypothesized that children with jailed parents would have a negative bias in processing emotions and less accuracy compared to children without incarcerated parents. Data were drawn from 128 families, including 75 children (53.3% male, M = 5.37 years) with jailed parents and 53 children (39.6% male, M = 5.02 years) without jailed parents. Caregivers in both samples provided demographic information. Children performed an emotion recognition task in which they were asked to produce a label for photos expressing six different emotions (i.e., happy, surprised, neutral, sad, angry, fearful). For scoring, the number of positive and negative labels were totaled; the number of negative labels provided for neutral and positive stimuli were totaled (measuring negative bias/overextension of negative labels); and valence accuracy (i.e., positive, negative, neutral) and label accuracy were calculated. Results indicated a main effect of parental incarceration on the number of positive labels provided; children with jailed parents presented significantly fewer positive emotions than the comparison group. There was also a main effect of parental incarceration on negative bias (the overextension of negative labels); children with jailed parents had a negative bias compared to children without jailed parents. However, these findings did not hold when controlling for child age, race/ethnicity, receipt of special education services, and caregiver education. The results provide some evidence for the effect of the context of parental incarceration in the development of negative emotion recognition biases. Limitations and implications for future research and interventions are discussed

Predictive Neural Computations Support Spoken Word Recognition: Evidence from MEG and Competitor Priming.

Human listeners achieve quick and effortless speech comprehension through computations of conditional probability using Bayes rule. However, the neural implementation of Bayesian perceptual inference remains unclear. Competitive-selection accounts (e.g., TRACE) propose that word recognition is achieved through direct inhibitory connections between units representing candidate words that share segments (e.g., hygiene and hijack share /haidʒ/). Manipulations that increase lexical uncertainty should increase neural responses associated with word recognition when words cannot be uniquely identified. In contrast, predictive-selection accounts (e.g., Predictive-Coding) propose that spoken word recognition involves comparing heard and predicted speech sounds and using prediction error to update lexical representations. Increased lexical uncertainty in words, such as hygiene and hijack, will increase prediction error and hence neural activity only at later time points when different segments are predicted. We collected MEG data from male and female listeners to test these two Bayesian mechanisms and used a competitor priming manipulation to change the prior probability of specific words. Lexical decision responses showed delayed recognition of target words (hygiene) following presentation of a neighboring prime word (hijack) several minutes earlier. However, this effect was not observed with pseudoword primes (higent) or targets (hijure). Crucially, MEG responses in the STG showed greater neural responses for word-primed words after the point at which they were uniquely identified (after /haidʒ/ in hygiene) but not before while similar changes were again absent for pseudowords. These findings are consistent with accounts of spoken word recognition in which neural computations of prediction error play a central role.SIGNIFICANCE STATEMENT Effective speech perception is critical to daily life and involves computations that combine speech signals with prior knowledge of spoken words (i.e., Bayesian perceptual inference). This study specifies the neural mechanisms that support spoken word recognition by testing two distinct implementations of Bayes perceptual inference. Most established theories propose direct competition between lexical units such that inhibition of irrelevant candidates leads to selection of critical words. Our results instead support predictive-selection theories (e.g., Predictive-Coding): by comparing heard and predicted speech sounds, neural computations of prediction error can help listeners continuously update lexical probabilities, allowing for more rapid word identification