Використання інтересу студентів до музики задля мотивації вивчення іноземної мови
Bibliographic record
Abstract
Література 1. Cole, K. 2011. Brain-based-research music advocacy. 2. Music Educators Journal 98 (1): 26–29. Cummins, J. 1981.The role of primary languagedevelopment in promoting educational success for language minority students. In Schooling and language minority students:A theoretical framework, ed. Office of Bilingual Bicultural Education, California State Department of Education, 3–49. Los Angeles: Evaluation, Dissemination and Assessment Center, California State University. 3. Dalton, C., and O. Lewes. 2015. Utilizing karaoke in the ESL classroom:The Beatles. English inTexas 45 (1): 32–36. 4. Deutsch, D. 2010. Speaking in tones. Scientific American Mind 21 (3): 36–43. 5. Ho, P., J. C. I.Tsao, L. Bloch, and L. K. Zeltzer. 2011. The impact of group drumming on social-emotional behavior in low-income children. Evidence-Based Complementary and Alternative Medicine 2011: 1–14. 6. Lapo, N. 2016. SIOP Lesson PlanTemplate #2: Soundtrack to my life. Unpublished academic assignment for CIL505, ESL Methods. Chicago, IL: National Louis University. 7. Lems, K., L. D. Miller, andT. M. Soro. 2017. Building literacy with English language learners:Insights from linguistics. 2nd ed. NewYork: Guilford Press. \n8. Leutwyler, K. 2001. Exploring the musical brain. Scientific American, January 23, 2–4. http://www. scientificamerican.com/article/exploring-the- musical-bra/ 9. Maess, B., S. Koelsch,T. Gunter, and A. Friederici. 2001. Musical syntax is processed in Broca’s area: An MEG study. Nature Neuroscience 4 (5): 540–545. Martin. 2013. How to teach English infographic. KBlog. https://www.kaplaninternational.com/blog/how-to-teach-english-kaplaninfographic 10. Mayo, L. H., M. Florentine, and S. Buus. 1997.Age of secondlanguage acquisition and perception of speech in noise. Journal of Speech,Language,and Hearing Research 40 (3): 686–693. 11. McGowan, K. 2008. Music, memory, and learning. Meeting report from the Neurosciences and Music III—Disorders and Plasticity conference at McGill University, Montreal, Quebec, June 25–28. https:// www.nyas.org/ebriefings/songs-of-experience/ 12. Moreno, S. 2009. Can music influence language and cognition? Contemporary Music Review 28 (3): 329–345. 12. Murphey, T. 1990. Song and music in language learning: An analysis of pop song lyrics and the use of song and music in teaching English to speakers of other languages. New York: Peter Lang. 13. Posner, M., M. K. Rothbart, B. E. Sheese, and J. Kieras. 2008. How arts training influences cognition. Arts and Cognition Monograph, 1–10. NewYork: Dana Foundation. TierneyA., J. Krizman, E. Skoe, K. Johnston, and N. Kraus. 2013. 14. High school music classes enhance the neural processing of speech. Frontiers in Psychology 4: 1–7. Weissman, M. J. 2005. Sing about Martin.YouTube video. https://www.youtube.com/watch?v=dF3hPT3PDI 15. Kristin Lems, Leah D. Miller, Tenena M. Soro. 2017. Building Literacy with English Language Learners, Second Edition: Insights from Linguistics. Guilford Publications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".