18062 research outputs found
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A Descriptive Analysis of Elementary Music Teachers\u27 Planning Time
No full textThe purpose of this descriptive study was to examine elementary music teachers’ planning times. The existing literature on planning time is scarce and the literature on elementary music teachers’ planning time is nearly non-existent. The following research questions guided the study: (a) How many minutes of planning time do elementary music teachers have? (b) What type(s) of planning do elementary music teachers participate in? (c) What do elementary music teachers do during their planning time? The researcher modified an existing survey (Hixson et al., 2013), which underwent two piloting phases to establish content validity and statistical reliability. The participants (N = 246) were randomly selected from across the United States via the National Association for Music Education (NAfME) survey research assistance program. The survey items relating to planning time were based on the participants’ teaching rotations. All but one participant reported having individual planning time and most (85.8%, n = 211) participants did not participate in common planning time or in a Professional Learning Community for music teachers (54.1%, n = 133). Elementary music teachers planned lessons (n = 240, 97.6%), called students’ parents (n = 132, 53.7%), graded student work (n = 131, 73.6%), attended meetings (n = 131, 53.3%), cleaned their rooms between classes (n =18, 20.1%), repaired instruments (n = 6, 6.8%), and composed and arranged music (n = 3.4%) during their planning times. The results of this study will lay the foundation for future studies regarding elementary music teachers’ planning time and impact future education policy regarding planning time
“It’s like Mental Marginalization”: Stories of Four Music Students at a Hispanic Serving Institution.
No full textResearchers have explored the ways in which P-12 teachers and students negotiate Latino/a/x/e cultural and musical identities in the classrooms (Abril, 2009; Lechuga & Schmidt, 2018; Palkki, 2015). While some have connected culturally responsive teaching to the needs of the growing number of Latino/a/x and Hispanic students in P-12 settings (Abril & Kelly-McHale, 2015), currently, no studies within music education address the experiences of music students at Hispanic Serving Institutions (HSIs), as well as the music making practices, curriculum, and faculty experiences at HSI. This case study examined how a music department at an HSI served the needs of its racially minoritized student population. Research questions guiding this study included: In what ways do racially minoritized students make meaning of the intersections between their racial, cultural, and student identities; and, what barriers or success have these students experienced in their musical studies in relation to their identities? Themes emerged from the data included: devaluing of “whoness” (Davis, 2021), community centered values, and access to preparation for higher education
How Attention Related Brainwaves Vary with Performance on Speech-In-Noise Tasks
No full textPrior studies have found alpha (8-12 Hz) and beta (15-30 Hz) oscillations measured with EEG both increase in power when people are performing speech-in-noise tasks. In theory, variation in speech-in-noise performance could reflect the ability to segregate and neurally encode background versus foreground sounds. Here, we aim to examine how alpha and beta oscillations play a role in ignoring background sounds versus attending to foreground speech sounds. We had thirty-four healthy young adults perform a speech-in-noise task while we recorded brain signals using 64-channel EEG. Subjects were instructed to ignore the randomly varied background “noise” sounds that onset at the beginning of each trial and attend to foreground digits. After listening to each digit sequence, subjects reported the digits heard. We analyzed the EEG data using custom MATLAB scripts developed by our lab, finding that speech-in-noise performance is easier when the background sound has high stationarity in acoustic features over time. Our results indicate a high involvement of alpha and beta oscillations in attending to foreground sounds amidst background noise, with the alpha oscillations increasing prior to foreground sound onset during background sound onset in order to suppress brain processing of the distracting background sound in preparation for focusing on the attended foreground digits. Interestingly, the increase of beta power prior to onset of the attended digit sequence supports the theory that beta oscillations engage to generate a working memory encoding of the ignored background sounds. Additionally, the more dynamically variable speech “Babble” background sound induced more beta oscillations, in theory reflecting more working memory processes and detection of temporal amplitude modulations over time for the speech “Babble” sounds as compared to the other sounds, such as “White Noise”. Given that the behavioral performance for correctly reporting the digit sequence was also lower for “Babble” background sounds, the higher beta power for “Babble” may index distractibility as well as a working memory representation of the “Babble” sound
Comparative Data Science Education Policy and Management: United States and Europe
No full textThis study examines what “good” curricula and administration for undergraduate data science are by surveying and interviewing U.S. and European data science educators and administrators. Many U.S. and European higher education institutions have embraced data science education with a kind of inertial sensibility, i.e., it is inevitable that data science education needs to be offered to students. Information and data affect so many areas of knowledge that higher education administrators feel they must assure students are “ready” for the world they are inheriting. Academic capitalism and isomorphism theories help elucidate social and market forces influencing higher education decision-making. Topics to which I contribute using a comparative perspective include knowledge management across higher education institutions; data science education practice; transdisciplinarity; and the designing and implementation of public policies at the federal and local levels
Embedding Internationalization at Home – What do Irish HEIs need?
No full textIn Irish higher education, only four percent of learners have benefited from mobility opportunities. Whilst mobility continues to be accessible to a limited few, Irish higher education institutions (HEIs) increasingly realize the need to engage in \u27Internationalization at home (IaH)\u27 to provide international experiences to all learners. However, as evident from the literature review, IaH has been underdeveloped and understudied to date in the Irish context. Grounded in organizational and curriculum design and change management theories, this study critiques the development of IaH and suggests strategies to embed a culture of IaH in Irish HEIs. It adopts a constructivist-interpretivist methodology that examines IaH from different stakeholder perspectives utilizing qualitative focus groups and semi-structured interviews. The preliminary findings reveal the conceptual confusion, fragmented implementation and the need for a top-down, bottom-up approach to IaH. This study provides a unique theoretical lens for embedding IaH holistically
Cultivating a Sense of Community: International Students Navigating Community Engaged Learning Opportunities in Line with Their Social Goals
No full textInternational students often envision their time studying abroad with particular academic, professional, social, linguistic, and identity-related goals in mind (Fong, 2011; Jones, 2013; Montgomery & McDowell, 2009; Page, 2019; Page & Chahboun, 2019). Post-secondary institutions can provide resources and opportunities to help this heterogeneous group of students bring their vision into fruition. One such opportunity is community engaged learning (CEL), which has been shown to help students expand their social and academic abilities as they make contributions to an organization (Arnold, 2019; Greenberg, London & McKay, 2020; Mayer et al., 2019). Through in-depth interviews with 25 new international students who participated in optional course-based CEL programming at a large Canadian research university, we document the ways participants interpreted and navigated this experience in line with their social goals. We show how students’ CEL meaning-making processes align with McMillan and Chavis’ (1986) four dimensions of a perceived sense of community: membership, influence, fulfillment of needs, and shared emotional connection. We conclude with recommendations for educators designing socially-oriented CEL opportunities with new international students
Internationalization as Transformation: Teaching, Research, and Innovation in Gulf STEM Education
No full textThis special issue examines the internationalization of higher education in the Gulf region, with a focus on culturally responsive approaches to teaching, learning, and research in STEM disciplines. Contributors investigate how institutions across the UAE, Saudi Arabia, and the wider Gulf are leveraging digital technologies, cross-border collaborations, and development centers to advance innovation, inclusivity, and sustainability. The articles highlight diverse strategies, from embedding intercultural fluency and equity in curricula to addressing grand challenges through global student perspectives and faculty role transformation. Together, these contributions present a forward-thinking vision of internationalization—one that resists conventional models and instead emphasizes cultural preservation, collaborative research, and interdisciplinary problem-solving
Multimodal Benchmarking for NCAA Basketball
No full textWe present the first multimodal, multitask benchmark for NCAA basketball, synthesizing structured statistical features with large language model (LLM)-generated game summaries across 19,739 games spanning four NCAA Division I seasons (2021--2025). We evaluate three model families---XGBoost, deep neural networks, and Transformers---under tabular-only and early-fusion settings to measure the impact of LLM-derived textual embeddings. To assess practical utility, we simulate fixed-stake and Kelly criterion-based betting strategies using historical bookmaker odds, analyzing both profitability and downside risk via Monte Carlo simulation. Our results show that XGBoost with early-fusion achieves the highest return on investment and the lowest risk of loss. This work is, to our knowledge, the first to integrate LLM-generated narrative data with structured inputs for calibrated forecasting in sports, offering a reproducible benchmark for multimodal decision-making under uncertainty
