Music reading and music notation software
a multiple-case study
DOI:
https://doi.org/10.35699/2317-6377.2024.48079Keywords:
Music reading, Music notation software, Technological acceptance, Multiple-case study, College studentsAbstract
A multiple-case study was conducted within the context of the subject “Musical Practices and Fundamentals” of the Degree of Primary Education at the University of Seville. Five volunteers were subjected to an oral test in which they had to study four music sheets of two different difficulty levels, using two different means. The main objective of this study was to understand the differences between the perceptions of the participants toward the use of these two different means. The results show that the software had greater acceptance for those participants who had lower knowledge and skills regarding the musical content of the music sheets used in this study. Based on the results, it is understood that the introduction of this type of means could pose an improvement in the performance of the students, thereby reducing the differences in previous musical knowledge and skills, which, in turn, could enrich the methodology of the subject.
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Bangert, Marc; Udo Haeusler and Eckart Altenmüller. 2001. “On practice: How the brain connects piano keys and piano sounds”, Annals of the New York Academy of Sciences 930: 425–428, https://doi.org/10.1111/j.1749-6632.2001.tb05760.x
Baxter, Pamela and Susan Jack. 2008. “Qualitative case study methodology: Study design and implementation for novice researchers”, The Qualitative Report 13 (4): 544-559. https://doi.org/10.46743/2160-3715/2008.1573
Boersma, Paul and David Weenink. 2021, “PRAAT” [Software]. University of Amsterdam, https://www.fon.hum.uva.nl/praat/
Brodsky, Warren, Yoav Kessler, Bat.S. Rubinstein, Jane Ginsborg and Avishai Henik. 2008, “The mental representation of music notation: Notational audiation”. Journal of Experimental Psychology: Human Perception and Performance 34 (2): 427–445, https://doi.org/10.1037/0096-1523.34.2.427
Buenaño Logroño, Édagar R. 2016, “Análisis de herramientas de software libre orientadas al aprendizaje del lenguaje musical para mejorar el rendimiento académico en los estudiantes del primer año de bachillerato de la unidad educativa “Juan Velasco” “. Master´s thesis, Chimborazo: Escuela Superior Politécnica de Chimborazo. http://dspace.espoch.edu.ec/handle/123456789/4635
Chan, Liz, Ann C. Jones, Eileen Scanlon and Richard Joiner 2006, “The use of ITC to support the development of practical music skills through acquiring keyboard skills: a classroom-based study”, Computer and Education 46 (4): 391-406. https://doi.org/10.1016/j.compedu.2004.08.007
Davis, Fred D. 1989, “Perceived usefulness, perceived ease of use and user acceptance of information technology”, MIS Quarterly 13 (3): 319–340. https://doi.org/10.2307/249008
Davis, Jane. 2001. “CAI: Does It Have an Effect on Aural Skills Performances?”. Paper presented at the Eighth International Technological Directions in Music Education Conference, San Antonio, Texas.
Drost, Ulrich C, Martina Rieger, Marcel Brass, Thomas C. Gunter and Wolfgang Prinz. 2005, “When hearing turns into playing: Movement induction by auditory stimuli in pianists”. Quarterly Journal of Experimental Psychology: Human Experimental Psychology 58 (8): 1376–1389. https://doi.org/10.1080/02724980443000610
Galera-Núñez, Mar, Jesús Tejada and Eva Trigo. 2013. “Music notation software as a means to facilitate the study of singing musical scores”. Electronic Journal of Research in Psychology Education 29: 215-237. http://dx.doi.org/10.25115/ejrep.v11i29.1564
Goodhue, Dale. L. and Ronald L. Thompson. 1995. “Task-technology fit and individual performance”. MIS Quarterly 19 (2): 213–236. https://doi.org/10.2307/249689
Goodwin, Mary A. 1991. “The effectiveness of “Pitch Master” compared to traditional classroom methods in teaching sight singing to college music students”. Master´s Thesis, South Florida University.
Hasegawa, Takehiro, Ken-Ichi Matsuki, Takashi Ueno, Yasuhiro Maeda, Yoshihiko Matsue, Yukuo Konishi and Norihiro Sadato. 2004. “Learned audio-visual cross-modal associations in observed piano playing activate the left planum temporale: An fMRI study”. Cognitive Brain Research 20 (3): 510–518. https://doi.org/https://doi.org/10.1016/j.cogbrainres.2004.04.005
Hernández, Elena and María J. Navarro. 2017. “Percepciones de los estudiantes sobre el uso del ordenador personal y otros recursos en el aula universitaria”. Píxel-Bit 50: 123-135. https://recyt.fecyt.es/index.php/pixel/article/view/61767
Jeremic, Biljana, Rajko Pecanac, Emilija Stankovic and Tanja Durdevic. 2020. “Music Technology Software in Adopting Music Teaching Contents”. Croatian Journal of Education 22 (1): 263- 286. https://doi.org/10.15516/cje.v22i1.3282
Lemons, Robert M. 1985. “The development and trial of micro-computer-assited techniques to supplement traditional training in musical sightreading”. PhD diss., University of Colorado. https://www.proquest.com/dissertations-theses/development-trial-microcomputer-assisted/docview/303292212/se-2
Larasati, Maria T. L. and Yudi Sukmayadi. 2021. “Mobile Learning Design for Sight Reading”. Proceedings of the 3rd International Conference on Arts and Design Education, ICADE 2020: 70–73. https://doi.org/https://doi.org/10.2991/assehr.k.210203.015
Lituma, Julio A. 2015, “El Manejo de programas editores de partituras en el aprendizaje musical de los estudiantes del 6to semestre nivel técnico del conservatorio de música ¨Salvador Bustamante Celi”“. Master´s Thesis, Universidad Nacional de Loja. https://dspace.unl.edu.ec/jspui/handle/123456789/21209
Marton, Ference. 1995. “Phenomenography: A research approach to investigating different understandings of reality”, In Qualitative research in education: focus and methods, edited by Robert R. Sherman and Rodman B. Webb, 141-161. London and New York: Routledge Falmer Press.
McPherson, Gary and Alf Gabrielsson 2002. “From sound to sign”, In The science and psychology of music performance: Creatives strategies for teaching and learning, edited by Richard Parncutt and Gary McPherson, 99-115. New York: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195138108.001.0001
Merchán Sánchez-Jara, Javier F. 2016. “Lectura Musical en el ámbito digital: aplicaciones para tablets”, Education in the Knowledge Society 17 (1): 109-128. https://doi.org/10.14201/eks2016171109128
Miles, Matthew B. and A. Michael Huberman. 1994. Qualitative data analysis: an expanded sourcebook. Newbury Park, CA: Sage.
Mulet, Julie, Cécile van de Leemput and Frank Amadieu. 2019. “A critical literature review of perceptions of tablets for learning in primary and secondary schools”. Educational Psychology Review 31: 631–662. https://doi.org/10.1007/s10648-019-09478-0
Nicholson, Jennifer, Darren B. Nicholson and Joseph Valacich. 2008. “Examining the effects of technology attributes on learning: a contingency perspective”. Journal of Information Technology Education 7: 185-204. https://doi.org/10.28945/185
Ozeas, Natalie L. 1991. “The effect of the use of a computer assisted drill program on the aural skill development of students in beginning solfége”. PhD diss., University of Pittsburg. https://dl.acm.org/doi/book/10.5555/145605
Palazón-Herrera, José. 2014. “Software musical y sus posibilidades didácticas: una panorámica para los estudiantes del Máster de Secundaria en la especialidad de Música”. In La era de las TT.II.CC. en la nueva docencia, coordinated by José F. Durán Medina and Susana Durán Valero, 363-372. Madrid: McGraw-Hill Interamericana de España.
Parker, Robert C. 1979. “The relative effectiveness of the TAP system in instruction in sight singing: An experimental study”. PhD diss., University of Miami. https://www.proquest.com/dissertations-theses/relative-effectiveness-tap-system-instruction/docview/302924482/se-2
Prasso, Nina M. 1997. “An examination of the effect of writing melodies using a computer-based song-writing program on high school students: Individual learning of sight-singing skills”. Ph.D. thesis, Columbia University Teachers College. https://dl.acm.org/doi/abs/10.5555/925246
Savage, Jonathan. 2010. “A survey of ICT usage across English secondary schools”. Music Education Research 12 (1): 89-104. https://doi.org/10.1080/14613800903568288
Schön, Daniele and Besson, Mirelle. 2005. “Visually induced auditory expectancy in music reading: a behavioural and electrophysiological study”. Journal of Cognitive Neuroscience 17(4): 694-705. https://doi.org/10.1162/0898929053467532
Sloboda, John. 1974. “The eye-hand span: an approach to the study of sight reading”. Psychology of Music 2: 4-10. https://doi.org/10.1177/030573567422001
Sloboda, John. 1977. “Phrase units as determinants of visual processing in music reading. British Journal of Psychology 68 (1): 117-124. https://doi.org/10.1111/j.2044-8295.1977.tb01566.x
Sloboda, John. 2004. “Experimental studies of music reading: A review”. In Exploring the musical mind, edited by John A. Sloboda, 27-42. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780198530121.003.0002
Schulz, Matthias, Bernhard Ross and Christo Pantev. 2003. “Evidence for training-induced crossmodal reorganization of cortical functions in trumpet players”, Neuroreport 14 (1): 157–161. https://doi.org/10.1097/00001756-200301200-00029
Venkatesh, Viswanath and Fred D. Davis. 2000. “A theoretical extension of the technology acceptance model: four longitudinal field studies”. Management Science 46 (2): 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, Viswanath, Michael Morris, Gordon B. Davis and Fred D. Davis 2003, “User acceptance of information technology: Toward a unified view”. MIS Quarterly 27 (3): 425–478. https://doi.org/10.2307/30036540
Watson, Maike. 2018. “MuseScore”. Journal of the Musical Arts in Africa 15(1-2): 143-147. https://doi.org/10.2989/18121004.2018.1534342.
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