The 2020–2021 academic year brought numerous challenges to teachers across the country as they worked to educate students amidst the COVID-19 pandemic. The current study is a secondary data analysis of qualitative responses collected as part of a teacher survey to evaluate a social emotional learning curriculum implemented during the 2020–2021 academic year. The lived experiences of teachers ( N = 52) across 11 elementary schools in the Great Plains region were captured through open-ended questions as the teachers transitioned from in-person to remote learning. A phenomenological approach was utilized to analyze the challenges expressed by teachers as they faced instability and additional professional demands. Given that stress and other factors that strain mental health exist within multiple layers of an individual's social ecology, a modified social-ecological framework was used to organize the results and themes. Findings suggest that during the academic year, teachers experienced stressors related to their personal and professional roles, concerns for students’ well-being which extended beyond academics, and frustrations with administration and other institutional entities around COVID safety measures. Without adequate support and inclusion of teacher perspectives, job-related stress may lead to teacher shortages, deterioration of teacher mental health, and ultimately worse outcomes for students. Implications for policy, research, and practice are discussed. Supplementary Information The online version contains supplementary material available at 10.1007/s12310-022-09533-2.
Familiar dialects can facilitate speech processing. However, recent investigations of speech processing of the Northern and Midland dialects of American English reveal a different pattern: in noise-masked speech, listeners from both dialect regions identify Midland words and phrases with higher accuracy than Northern words and phrases. This preference may be explained by inconsistencies between Northern talkers’ production and perception of their own dialect. The goal of the current study was to determine whether cross-dialect processing differences between the Northern and Midland dialects reflect listeners’ explicit dialect identification ability. Participants completed a speech intelligibility in noise task followed by a forced-choice dialect categorization task. Speech stimuli in both tasks were short phrases taken from passages read by eight Northern and eight Midland talkers. Responses in both tasks were scored for accuracy. Results revealed higher accuracy in intelligibility for Midland phrases than Northern phrases, as in previous work, but poor dialect categorization performance across all listeners. The inability of listeners to explicitly categorize talkers by dialect while showing an intelligibility benefit for Midland forms indicates that the observed cross-dialect processing differences emerge even in the absence of explicit dialect categorization, revealing a perceptual mismatch between speech processing and dialect perception.
Schools and students have faced a variety of challenges during the 2020–2021 academic year as the COVID-19 pandemic continues. These issues have drawn attention to the increased need for robust social-emotional learning skills at the elementary level to address the deficits exacerbated by the pandemic. Sources of Strength is an evidence-based suicide prevention program for middle and high school students. In 2020, Sources of Strength launched an elementary school curriculum focused on promoting protective factors and resilience. Data were collected across 11 elementary schools ( N = 1022; 3–5th graders) in the Great Plains region of the USA at two time points during the COVID-19 pandemic (T1: Fall of 2020, T2: Spring of 2021). We examine the effectiveness of the program using a pre- and post-test design measuring various student social-emotional outcomes including positive classroom climate, emotional problems, school belonging, help-seeking attitudes, bullying perpetration, peer victimization, student and teacher intervention, student well-being, and student resilience. The program was evaluated using multilevel regression models to examine the associations between self-reported student program exposure and student outcomes. Although comparisons between T1 and T2 indicated a worsening of several student outcomes, positive associations were found when accounting for the degree of student exposure to the program. Greater student exposure was associated with improved positive classroom climate, school belonging, help-seeking attitudes, student well-being, resiliency, and lower reports of emotional problems. Implications for research and practice are discussed. Supplementary Information The online version contains supplementary material available at 10.1007/s12310-023-09567-0.
Phonetic reduction due to lexical frequency, phonological neighborhood density, and discourse mention, as well as speaking style and social-indexical variation can constrain listeners’ ability to identify spoken single word tokens. In phrasal contexts, however, semantic predictability facilitates word recognition. The aim of the current study was to investigate how semantic predictability influences the intelligibility of words that vary in their lexical, stylistic, and socio-indexical properties. Listeners were presented with auditory English phrases extracted from read passages and were asked to identify each phrase. Phrases were mixed with speech-shaped noise and each contained a target word of interest. Linguistic and social properties of the target words were used to predict listeners’ target word recognition accuracy. These factors included semantic predictability, lexical frequency, neighborhood density, speaking style, discourse mention within the passage, talker gender, and talker dialect. The results revealed that greater semantic predictability increased word recognition accuracy, but only for the most phonetically reduced words (e.g., high-frequency words, second mentions, and words in a plain style). These results suggest that the semantic predictability benefit is enhanced primarily for words that might otherwise be difficult to recognize when removed from their semantic context.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.