Neuromyths in Music Education: Prevalence and Predictors of Misconceptions among Teachers and Students

Abstract

In the last decade, educational neuroscience has become increasingly important in the context of instruction, and its applications have been transformed into new teaching methods. Although teachers are interested in educational neuroscience, communication between scientists and teachers is not always straightforward. Thus, misunderstandings of neuroscientific research results can evolve into so-called neuromyths. The aim of the present study was to investigate the prevalence of such music-related neuromyths among music teachers and music students. Based on an extensive literature research, 26 theses were compiled and subsequently evaluated by four experts. Fourteen theses were selected, of which seven were designated as scientifically substantiated and seven as scientifically unsubstantiated (hereafter labeled as "neuromyths"). One group of adult music teachers (n = 91) and one group of music education students (n = 125) evaluated the theses (forced-choice discrimination task) in two separate online surveys. Additionally, in both surveys person-characteristic variables were gathered to determine possible predictors for the discrimination performance. As a result, identification rates of the seven scientifically substantiated theses were similar for teachers (76%) and students (78%). Teachers and students correctly rejected 60 and 59%, respectively, of the seven neuromyths as scientifically unsubstantiated statements. Sensitivity analysis by signal detection theory revealed a discrimination performance of d' = 1.25 (SD = 1.12) for the group of teachers and d' = 1.48 (SD = 1.22) for the students. Both groups showed a general tendency to evaluate the theses as scientifically substantiated (teachers: c = -0.35, students: c = -0.41). Specifically, buzz words such as "brain hemisphere" or "cognitive enhancement" were often classified as correct. For the group of teachers, the best predictor of discrimination performance was having read a large number of media about educational neuroscience and related topics (R² = 0.06). For the group of students, the best predictors for discrimination performance were a high number of read media and the hitherto completed number of semesters (R² = 0.14). Our findings make clear that both teachers and students are far from being experts on topics related to educational neuroscience in music and would therefore benefit from current education-related research in psychology and neuroscience.

Keywords: education; educational neuroscience; music students; music teachers; neuromyths; neuroscience of music.

Figure 1

Flowchart of the selection process of theses.

Figure 2

(A,B) Histogram of sensitivity d' (left) and response bias c (right) for the sample of music teachers (y-axis indicates frequencies).

Figure 3

(A,B) Histogram of sensitivity d' (left) and response bias c (right) for the sample of music students (y-axis indicates frequencies).

Figure 4

Regression tree for sensitivity d' as outcome variable. The only relevant predictor for high vs. low discrimination performance is the number of read media (≤3, >3).