Category Archives: Reading

Reading: Lessons for Teachers: What Lower Secondary School Students Tell Us about Learning a Musical Instrument

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Lowe, G. (2012). Lessons for Teachers: What Lower Secondary School Students Tell Us about Learning a Musical Instrument. International Journal Of Music Education, 30(3), 227-243.

Problem: “Retaining students in elective music programs through to the senior years is an international problem. Walker (2003) states that only 5% of the total student cohort in North America enroll in elective music programs in senior school, while Bray (2000) reports only around 2% of students undertake A level music studies in the United Kingdom (UK). In Western Australia three out of four students in the government system cease learning an instrument before their final year of secondary school and, at a federal level, retention has been highlighted as a priority area requiring urgent attention.”

Instrument lessons in West Australia:

“Orchestral instruments are taught by specialist peripatetic staff on a weekly basis. Lessons range from 20–30 minutes each, and students in the first year of secondary school generally learn in groups ranging from one to five. Students are withdrawn from regular classes on a rotating timetable basis to minimize the impact on other school subjects. /…/ Wind and brass students commence in-school instruction in year 6 in primary school, and string players start earlier. As year 8 (ages 12–13) is the first year of secondary school in WA, on-going students are into at least their third year of learning when they enter year 8.”
Positive aspects that students brought out:
  • an intimate, comfortable and non-threatening learning environment that is different from other subjects
  • teacher attitude associated with rapport and respect
  • professional teacher attributes including organization, enthusiasm, encouragement and patience
  • professional musician attributes including the ability to model the instrument to a high standard
  • activity selection, relating to repertoire choice and ensemble playing
Negative aspects that students brought out:
  • dislike of technical work, particularly the need to practice scales
  • differing levels of ability which lead to embarrassment and feelings of incompetence
  • repetition, including a lack of repertoire turnover
  • lack of rapport with the teacher, manifested in a lack of attention and lack of encouragement

 

Reading: Teachers’ Practices and Beliefs Regarding Teaching Tuning in Elementary and Middle School Group String Classes

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Hopkins, M. T. (2013). Teachers’ Practices and Beliefs Regarding Teaching Tuning in Elementary and Middle School Group String Classes. Journal Of Research In Music Education, 61(1), 97-114. doi:10.1177/0022429412473607

Not very relevant to my topic. Still, some knowledge about strings in group: children have problems with tuning in a group setting and teachers often feel they are not instructed to teach that. At the same time only 33% uses electronic tuners. It seems to take 4.5 years to obtain the necessary tuning skills.

Reading: University-level group piano instruction and professional musicians

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Young, M. M. (2013). University-level group piano instruction and professional musicians. Music Education Research, 15(1), 59-73. doi:10.1080/14613808.2012.737773

I mostly care about the literature overview here:

Group piano courses originated in Europe during the early nineteenth century (Richards 1962). /…/ By the twentieth century, group piano courses were included in private schools and public elementary schools and in the 1930s were introduced to universities. /…/ Currently, group piano classes can be found in private studios, public schools and institutions of higher education (Tsai 2007). Teachers continue to employ the group piano format because it is efficient and musical skills develop more quickly in a group setting (Kokotsaki and Hallam 2007; Shockley 1982).
Of the settings in which group piano classes can take place, university-level group piano courses are most common (Tsai 2007). University-level group piano courses fall into two major categories: courses for music majors and for non-music majors. Courses for non-music majors introduce non-musicians to reading notation and beginning piano pieces, whereas piano classes for music majors are responsible for developing the functional piano skills that undergraduate music students will use in the future (Chin 2002; National Association of Schools of Music [NASM] 2009; Tsai 2007). Now ubiquitous in universities and colleges in the USA, group piano courses for music majors are charged with developing the functional piano skills that undergraduate music students will use in their intended careers (Chin 2002; NASM 2009).

Reading: The attitudes of prospective music teachers to school musical instrument (Recorder) courses

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Ataman, O. G. (2014). THE ATTITUDES OF PROSPECTIVE MUSIC TEACHERS TO SCHOOL MUSICAL INSTRUMENT (RECORDER) COURSES. International Journal Of Academic Research, 6(2), 231-238. doi:10.7813/2075-4124.2014/6-2/B.34
Sample:
2015-03-13-105101_526x213_scrot
 Results:
2015-03-13-105039_809x458_scrotNobody seems to like studying the recorder in Turkey :) Or as the author puts it: “…prospective music teachers do not love School Musical Instruments (Recorder) courses enough; they do not take interest in these courses; they do not enjoy participating in these courses; and they fear these courses.”
He cites Kivrak: “There is a very serious tuning problem despite what is said. /…/ it is clear that a serious sound clarity problem will be experienced in collective playing activities when it is considered that the students in the learning stage cannot maintain breath control even though tuning is performed for each musical instrument.”
Conclusion:
– Curriculums of School Musical Instruments (Recorder) courses must be revised by the relevant academicians.
– It is recommended giving auditory examples related to the recorder in School Musical Instruments (Recorder) courses

Reading: Reading and working memory in adults with or without formal musical training: Musical and lexical tone

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Authors: Ching-I Lu and Margareth Greenwald. Psychology of Music 2015

Similarities between sight reading of musical notation and oral reading. Both are translating print to sound. Mentions Berz (1995) model for musical working memory. Says it’s close to Baddeley’s but just without empirical evidence. That’s bad I guess :)

For further reading> Berz, W. L. (1995). Working Memory in Music: A Theoretical Model. Music Perception: An Interdisciplinary Journal, (3). 353.

Salame, P., & Baddeley, A. (1989). Effects of background music on phonological short-term memory. The Quarterly Journal Of Experimental Psychology: Section A, 41(1), 107.

Studied the effects of music on the serial recall of sequences of 9 digits presented visually. Exp 1 with 44 undergraduates compared the effects of unattended vocal or instrumental music with quiet and showed that both types of music disrupted short-term memory performance, with vocal music being more disruptive than instrumental music. Exp 2 attempted to replicate this result in more highly trained Ss (24 male 25–40 yr old Ss). Vocal music caused significantly more disruption than instrumental music, which was not significantly worse than the silent control condition. Exp 3 (24 female undergraduates) compared instrumental music with unattended speech and with noise modulated in amplitude, the degree of modulation being the same as in speech. Both the noise condition and silence proved less disruptive than instrumental music, which was in turn less disruptive than the unattended speech condition. (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Main takeaway: The diff between musicians and non-musicians was often significant but still small. Music exp may have a small effect on language in case of normally developed people but it has much bigger effect for dyslexics and people with aphasia.

Reading: Measuring self-regulated practice behaviors in highly skilled musicians

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Author: Marcos Vinicius Araujo. Psychology of Music 2015. Seems to be a PhD student’s work.

From literature overview:

(Ericsson etc) Practicing is deliberate when musicians

1) have a well-defined task representing a personal challenge to overcome
2) are concentrating as much as possible during the task
3) have the persistence to repeat sections and correct errors
4) find alternative strategies to try to accomplish difficult elements within the task

Method has problems with sampling validity as many cases were excluded without satisfactory explanations. What characterized the cases that were excluded besides the fact that the questionnaires were incomplete? And a 58 y old with a practicing experience of 56 years? What a talented man…

Results. Time of practicing per day:

< 1 h 22.6%
1-2 hrs 30.7%
2-3 hrs 20.3%
3-4 hrs 16.5%
>4 hrs 9.4%

So let’s see – 53.3% practices less than 2 hrs a day. But that means that it takes more than 20 years to comply with the Ericsson’s 10 000 hrs rule. These people are clearly not on the way to become experts. At least not in music performance. I have tracked the practicing time for years and am pretty much convinced that an 8 hr working day hardly ever contains more than 4 hrs of pure practicing time. Let alone deliberate practicing..

Btw what is the point of giving median values for a 5 point Likert scale – almost straight 4s?

Reading: Manifestations of Personality in Online Social Networks: Self-Reported Facebook-Related Behaviors and Observable Profile Information

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Samuel D. Gosling, Adam A Augustine, Simine Vazire, Nicholas Holtzman, and Sam Gaddis, B.S.

Despite the enormous popularity of Online Social Networking sites (OSNs; e.g., Facebook and Myspace), little research in psychology has been done on them. Two studies examining how personality is reflected in OSNs revealed
several connections between the Big Five personality traits and self-reported Facebook-related behaviors and observable profile information. For example, extraversion predicted not only frequency of Facebook usage (Study 1), but also engagement in the site, with extraverts (vs. introverts) showing traces of higher levels of Facebook activity (Study 2). As in offline contexts, extraverts seek out virtual social engagement, which leaves behind a behavioral residue in the form of friends lists and picture postings. Results suggest that, rather than escaping from or compensating for their offline personality, OSN users appear to extend their offline personalities into the domains of OSNs.

Reading: Computer-based personality judgments are more accurate than those made by humans

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Wu Youyoua, Michal Kosinski, and David Stillwell

Judging others’ personalities is an essential skill in successful social living, as personality is a key driver behind people’s interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants’ Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy.

List of literature 2012/13

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2012/13 õppeaastal loetud kirjandus

Amador-Campos, J.A., Kirchner-Nebot, T. 1999. Correlations among scores on measures of field dependence-independence cognitive style, cognitive ability, and sustained attention. Perceptual and Motor Skills 88, 236-239.

Armstrong, V. 2011. Technology and the gendering of music education. Aldershot: Ashgate.

Angeli, C., Valanides, N., Kirschner, P. Field dependence–independence and instructional-design effects on learners’ performance with a computer-modeling tool. Computers in Human Behavior 25, 6: 1355–1366.

Baddeley, A. (2010). Working memory. Current biology, 20 (4), R136–R140.

Brändström, S., Wiklund, C., Lundström, E. 2012. Developing distance music education in Arctic Scandinavia: electric guitar teaching and master classes. Music Education Research 14, no. 4: 448-456. doi:10.1080/14613808.2012.703173.

Brünken, J., Seufert, T., Paas, F. 2010. Measuring cognitive load. In Cognitive load theory, ed. Plass, R. Moreno, J. Brünken. Cambridge: Cambridge University Press.

Chandler, P., & Sweller, J. 1991. Cognitive load theory and the format of instruction. Cognition and Instruction 8: 293-332. doi:10.1207/s1532690xci0804_2.

Chi, T.H. 2009. Active-Constructive-Interactive: A Conceptual Framework for Differentiating Learning Activities. Topics in Cognitive Science 1, 1: 73-105 doi: 10.1111/j.1756-8765.2008.01005.x.

Cowan, N., Morey, C. C., Chen, Z. and Bunting, M. F. (2007). What Do Estimates of Working Memory Capacity Tell Us? In N. Osaka, R. Logie, M. D’Esposito (Eds.), The Cognitive Neuroscience of Working Memory. Oxford: Oxford University Press.

Daniel, R. 2006. Exploring music instrument teaching and learning environments: video analysis as a means of elucidating process and learning outcomes. Music Education Research 8, 2:191-215.

Dervan, S., McCosker, C., MacDaniel, B., O’Nuallain, C. 2006. Educational multimedia. Current Developments in Technology-Assisted Education (Edited by A. Méndez-Vilas, A. Solano Martín, J.A. Mesa González and J. Mesa González). Badajoz, Spain: Formatex.

Dobbs, S., Furnham, A., McClelland, A. 2011. The effect of background music and noise on the cognitive test performance of introverts and extraverts. Applied Cognitive Psychology 25: 307-313. doi:10.1002/acp.1692.

Ericsson, K. A. (2009). Development of Professional Expertise: Toward Measurement of Expert Performance and Design of Optimal Learning Environments. Cambridge: Cambridge University Press.

Ericsson, K. A., Prietula, M. J., Cokelyo, E. T. (2007). Making of an Expert. Harvard Business Review July-Aug, 115-121.

Eyuboglu, F., Orhan, F. 2011. Paging and scrolling: Cognitive styles in learning from hypermedia. British Journal of Educational Technology 42, no. 1: 50-65.

Fassbender, E., Richards, D., Bilgin, A., Thompson, W.F., Heiden, W. 2012. VirSchool: the effect of background music and immersive display systems on memory for facts learned in an educational virtual environment. Computers & Education 58: 490-500. doi:10.1016/j.compedu.2011.09.002.

Fogg, B.J.  2009. A Behavior Model for Persuasive Design. Persuasive Technology Lab. Stanford University. http://www.behaviormodel.org/

Furnham, A., Strbac, L. 2002. Music is as distracting as noise: the differential distraction of background music and noise on the cognitive test performance of introverts and extraverts. Ergonomics 45, no. 3: 203-217. doi:10.1080/00140130210121932.

Hamilton, L. 2011. Case studies in educational research. http://www.bera.ac.uk/resources/case-studies-educational-research.

Hayes, J., Allinson, C.W. 1998. Cognitive style and the theory and practice of individual and collective learning in organizations. Human Relations 51, no. 7: 847-871. doi:10.1023/A:1016978926688.

Iznaola, R. (2001). On Practicing: A Manual for Students of Guitar Performance. Pacific: Mel Bay.

Garcia Rodicio, H., Sanchez, E. 2012. Aids to Computer-based Multimedia Learning: A Comparision of Human Tutoring and Computer Support Interactive. Learning Environments 20, 5: 423-439.

Gardner, J.S. 2008. Simultaneous media usage: effects on attention. (Doctoral dissertation, Virginia Polytechnic Institute and State University.)

Gray, R. 2004. Attending to the execution of a complex sensorimotor skill: expertise differences, choking, and slumps. Journal of Experimental Psychology: Applied 10, no. 1: 42–54. doi:10.1037/1076-898X.10.1.42.

Guisande, M.A., Páramo, M.F., Tinajero, M. Fernanda, C., Almeida, L.S. 2007. Field dependence-independence (FDI) cognitive style: An analysis of attentional functioning. Psicothema 19, 4: 572-577.

Kämpfe, J., Sedlmeier, P., Renkewitz, F. 2010. The impact of background music on adult listeners: A meta-analysis. Psychology of Music 39, 424.

Lee, J.J., Hammer, J. 2011. Gamification in education: what, how, why bother? Academic Exchange Quarterly 15, no. 2.

Lin, L., Lee J., Robertson, T. 2011. Reading while watching video: the effect of video content on reading comprehension and media multitasking ability.  Educational Computing Research 45, no. 2: 183-201. doi:10.2190/EC.45.2.d.

Liu, T., Lin, Y., Tsai, M., and Paas, F. 2012. “Split-attention and redundancy effects on mobile learning in physical environments.” Computers and Education 58 (1): 172–180. doi:10.1016/j.compedu.2011.08.007.

Marcus, Gary F. 2012. Musicality: Instinct or acquired skill? Topics in Cognitive Science 4: 498-512

Moreno, R., Mayer, R.E. 2000. A coherence effect in multimedia learning: the case for minimizing irrelevant sounds in the design of multimedia instructional messages. Journal of Educational Psychology 92, no. 1: 117-125. doi:10.1037//0022-0663.92.1.117.

Mayer, R.E., Moreno, R. 1998. A split-attention effect in Multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology 90: 312-320. Accession no. edselc.2-52.0-0032396526.

Mayer, R.E., Moreno, R. 2010. Techniques that reduce extraneous cognitive load and manage intrinsic cognitive load during multimedia learning. In Cognitive load theory, ed. Plass, R. Moreno, J. Brünken. Cambridge: Cambridge University Press.

Mikk, J., Luik, P. 2005. Do girls and boys need different electronic books? Innovations in Education & Teaching International 42, no. 2: 167-180. doi:10.1080/14703290500062565.

Miller, W. 2012. iTeaching and Learning: Collegiate Instruction Incorporating Mobile Tablets. Library Technology Reports 48, no. 8: 54-59. Accession no. 84297445.

Muntean, C. I. 2011. Raising engagement in e-learning through gamification. The 6th International Conference on Virtual Learning ICVL 2011. Accessed May 16, 2013, URL: http://www.icvl.eu/2011/disc/icvl/documente/pdf/met/ICVL_ModelsAndMethodologies_paper42.pdf

Pachman, M., Sweller, J., & Kalyuga, S. (2013). Levels of Knowledge and Deliberate Practice. Journal of Experimental Psychology: Applied. Advance online publication. doi: 10.1037/a0032149.

Papageorgi, I., Haddon, E., Creecha, A., Mortonc, F., de Bezenac, C., Himonides, E., Potter, J., Duffy, C., Whytond, T., Welcha, G. 2010. Institutional culture and learning I: perceptions of the learning environment and musicians’ attitudes to learning. Music Education Research 12, no. 2: 151-178. doi:10.1080/14613801003746550.

Partti, H., Karlsen, S. 2010. Reconceptualising musical learning: new media, identity and community in music education. Music Education Research 12, no. 4: 369-382. doi:10.1080/14613808.2010.519381.

Peng, H., Chou, C., Chang, C.-Y. 2008. From virtual environments to physical environments: Exploring interactivity in ubiquitous systems. Educational Technology & Society 11, no. 2: 54-66. Accession no. WOS:000256100600006.

Perry, G.T., Schnaid, F. 2012. A Case Study on the Design of Learning Interfaces. Computers & Education 59: 722-731.

Rees, F., Downs, D. 1995. Interactive television and distance learning. Music Educators Journal 82, no. 2: 21-25. doi:10.2307/3398864.

Repp, B.H. 2005. Sensorimotor synchronization: A review of the tapping literature. Psychonomic Bulletin & Review 12, 6: 969-992.

Sweller, J. 1994. Cognitive load theory, learning difficulty, and instructional design. Learning and instruction  4: 295-312. Accession no. edselc.2-52.0-43949152992.

Wright, D.J., Holmes, P.S., Di Russo, F., Loporto, M., Smith, D. 2012. Differences in cortical activity related to motor planning between experienced guitarists and non-musicians during guitar playing. Human Movement Science 31, 3: 567–577. doi:10.1016/j.humov.2011.07.001

Yin, R. 2009. Case study research : design and methods. Thousand Oaks: SAGE.

Yu, P.-T., Lai, Y.-S., Tsai, H.-S., Chang, Y.-H. 2010. Using a multimodal learning system to support music instruction. Educational Technology & Society 13, 3: 151-162. Accession no. WOS:000282274000014

Reading: Institutional culture and learning I: perceptions of the learning environment and musicians’ attitudes to learning

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Music Education Research, 12:2, 151-178
Authors: Papageorgi, I., Haddon, E., Creech, A., Morton, F., de Bezenac, C., Himonides, E., Potter, J., Duffy, C., Whyton, T., Welch, G. (2010)

Main point:

Online survey (n=170, students from three British higher music education institutions)+case study with focus groups.

Authors conclude that “positive learning environments are perceived as being inspirational, facilitating academic, professional and personal development, fostering a supportive community of learning and allowing the development and pursuit of personal interests.