Yearbook of Music Psychology

Correction of Nina Düvel & Franziska Altemeier (2025). Open Science Practices and New Statistics in the Yearbook of Music Psychology: A Bibliometric Analysis

2026-03-10T01:47:44+00:00

Correction to: Düvel, N., & Altemeier, F. (2025). Open Science practices and new statistics in the Yearbook of Music Psychology: A bibliometric analysis. Jahrbuch Musikpsychologie, 33, Article e229. https://doi.org/10.5964/jbdgm.229

Detection of Clash of Keys in a Non-Dichotomous Task: Effects of Musical Genres, Instruments and Participants’ Expertise

2026-02-25T00:42:04+00:00

When listening to music, people are able to separate the various parts or streams that the respective piece is made of, depending on their musical experience and aural training. Specific musical expertise affects these analytical listening skills, but different studies have shown that differences between experts and amateurs are smaller than often anticipated and depend heavily on the adequacy of the task for amateurs. The present replication study of Kopiez and Platz (2009) has investigated in a convenience sample (N = 97) whether a presumably obvious clash of keys between solo and accompaniment can be detected. In an incomplete study design, participants listened to two pieces of music (jazz and classical) with solos each played by one of two instruments (trumpet and saxophone) in either a clashing or fitting condition. Participants' musical training and perceptual abilities showed a medium correlation with the harmoniousness ratings difference between the clashing and fitting stimuli. Overall, the clashing version of the classical piece was rated as less harmonious than the jazz piece. These results are in line with similar research and raise questions concerning the appropriate research method to investigate the perception of participants with various degrees of expertise.

Adaptation and Validation of the Deliberate Practice in Music Inventory for Child Musicians

2025-12-17T00:18:53+00:00

Deliberate Practice (DP) is a fundamental aspect of musical expertise. Measuring DP in child musicians could provide useful information about its role in determining progress towards higher levels of expertise. This study aims to develop and validate a standardized instrument for measuring the level of DP that child musicians exhibit in their practice routine. The questionnaire is intended to be used by music teachers, parents and child musicians. The Deliberate Practice in Music Inventory (DPMI, Passarotto et al., 2022) for adult musicians was revised and simplified for the use with children by experienced musicians and music educators. The resulting child DPMI (cDPMI) consisted of 11 items, grouped into a main scale and four subscales. Analyses of data collected from a sample of primary school children, their parents, and teachers confirmed the appropriateness of the factor structure of the new questionnaire with good fit indices. The cDPMI main scale and subscales showed acceptable internal consistency in the parents and teachers groups, but internal consistency indices fell below the acceptable level in the children group. The cDPMI was invariant across groups of users (i.e., children, parents, and teachers) and times of measurement. Finally, the cDPMI main scale and subscales were significantly correlated with related personality traits and self-regulatory behaviors, suggesting its convergent validity. In conclusion, the new cDPMI is a standardized and valid instrument for measuring DP in child musicians, although it appears to be particularly suitable as an external evaluation tool for parents and teachers and less suitable as a self-assessment tool for primary school children.

Open Science Practices and New Statistics in the Yearbook of Music Psychology: A Bibliometric Analysis

2025-11-14T00:10:57+00:00

Open science practices and the use of the so-called new statistics can be understood as countermeasures to the crisis of confidence in psychology criticising questionable research practices. To trace developments toward improved research standards in German and German speaking music psychology research, a bibliometric analysis of research reports published in the Yearbook of Music Psychology (Vol. 22–32, 2012–June 2024) was conducted. Metadata from all articles were extracted and cleaned, and additional variables related to open science and new statistic practices were coded manually. The final dataset included 79 research reports, 59 of which reported quantitative studies. Since Volume 28, most quantitative papers included statements regarding the availability of data and materials, as well as disclosures of funding sources and potential conflicts of interest. However, none of the studies reported a preregistration. Effect sizes and p-values were frequently reported but only around half of the papers included confidence intervals. An international and interdisciplinary comparison revealed similar trends while also identifying areas where practices in the Yearbook were either comparatively high or contained some of the known problems and need improvement. The analysis offers a detailed overview of the evolution of publication practices in the Yearbook over the past decade. By providing empirical insights into the uptake of open science and statistical reporting standards, the study contributes to the ongoing development of both the Yearbook of Music Psychology and the broader field of music psychology. These findings may also inform editorial policies and future research practice more generally.

The Acquisition of Tonal Hierarchies in Western Music During School Years: A Re-Analysis of 40 Years of Research

2025-11-12T00:29:26+00:00

Understanding the relationships between different pitches as a form of tonality is a key element of listening skills in Western tonal music. Tonal hierarchies (i.e., genre-dependent differing prominence of tones) are reflected in the internal representations of tonal hierarchies (IRTH) in long-term memory. Over the past 40 years, research on how individuals—primarily students aged 6 to 15, as well as adults—acquire IRTH has yielded varied and sometimes contradictory conclusions about the timeline and underlying mechanisms of this process. This review aims to synthesize the evidence and critically examine potential reasons for the heterogeneity in prior findings. To this end, two approaches were applied. First, a Bayesian three-level meta-analysis of 60 effect sizes from 16 studies, reported in 13 articles, revealed a medium difference in IRTH sensitivity between younger and older participants. Second, a model comparison analysis based on cross-sectional data from a single study revealed a non-linear growth dynamic, with a larger increase during adolescence as the best model solution to describe the relationship between sensitivity and age. We also examined the considerable heterogeneity observed within and between studies, particularly how task-specific features of the operationalizations might account for these differences. These findings contribute to the development of theoretical models of music-related skill acquisition and suggest directions for future research.

Dimensions of Groove Affordances (DGA) When Listening to Popular Music

2025-10-09T02:58:21+00:00

Movement sensations and impulses triggered by listening to music can have very different qualities and, in everyday life, can lead to physical actions such as dance movements if the music is sufficiently enjoyable, at a sufficient volume and in a suitable situation. In order to address the qualitative diversity of movement sensations, we present the DGA, a new measurement instrument. It is based on a factor analysis of an already existing dataset and is able to differentiate between three fundamental dimensions of perceived rhythmic structures when listening to music: roll, drive and pulse. Digital methods of data collection (web scraping, APIs, digital audio sampling and online survey) in combination with structural equation modelling (SEM) and robust statistical analysis methods (LMMs) are used to investigate whether the new measurement instrument also proves itself in a large stimulus pool of k = 448 pop music pieces in terms of model fit, reliability and discriminant validity. For this purpose, after calculating factor scores from n = 1775 collected listener ratings, genre differences that occurred with regard to the sensation of movement when listening to short pop song excerpts are evaluated. Analysis results show that the DGA exhibit good model fit and reliability even with a large number of musically diverse stimuli and thus can fulfil its claim to map different phenomenological aspects of movement impulses in its measurements with comparatively less influence from personal liking.

The Creative Musical Achievement of AI Systems Compared to Music Students: A Replication of the Study by Schreiber et al. (2024)

2025-07-16T00:30:11+00:00

Although the last two years have seen AI systems progress significantly when it comes to
generating cultural products like literature, poems, or music, the jury is still out when it comes to
determining whether the aesthetic quality of these products increases in tandem with the
performance enhancements of underlying large language models (LLMs). We replicated the study
by Schreiber et al. (2024) to test whether the creative performance of selected LLMs had improved
over the past two years in the musical domain. In an online rating experiment based on a melody
continuation paradigm, 75 melodic continuations generated by the AI systems Qwen 2 (Version 72B
Instruct), Llama 3 (Version 70B Instruct), and ChatGPT (Version 4) were compared to 23 solutions
composed by humans. The aesthetic quality of the sound examples was then evaluated by N = 54
listeners (music students) using four criteria (convincing, logical and meaningful, interesting, and
liking). As the first main finding, human-based creative solutions outperformed all three AI
systems on all four dependent variables (large effect sizes 1.11 ≤ d_z ≤ 2.51), thus confirming the
finding by Schreiber et al. (2024). The second main finding revealed a mean (and meaningful)
discrimination sensitivity of d’ = 1.09 for AI- and human-based solutions. We conclude that merely
boosting the volume of training of the AI systems does not guarantee correlating improvement in
the creative musical output produced under controlled conditions.

Prevalence and Predictors of Neuromyths in (Music) Students: A Partial Replication of the Study by Düvel et al. (2017)

2025-04-02T00:29:08+00:00

The term neuromyth characterizes false or simplified representations of neuroscientific research findings in scientific discourses, public perception, and educational practices. Findings to date confirm the prevalence of neuromyths in educational contexts. Düvel et al. (2017) were the first to compare the prevalence and predictors of neuromyths among music teachers and music teacher students based on the paradigm of signal detection theory (SDT). Following this, our replication investigates possible changes in the abilities of music teacher students to distinguish between music-related and general theses regarding neuroscientific findings (neuromyths and neurofacts) both in comparison to students from other subject areas and the student sample of the reference study. The results of the replication show that music teacher students, teacher students with other subjects, and students from different degree programs do not show any significant differences in how well they can judge whether music-related or general neuromyths and neurofacts are scientifically proven or not. Compared to the reference study, the replication sample of music teacher students shows a significantly lower performance in discriminating neuromyths and neurofacts; moreover, the predictors determined in the reference study (amount of media read, previous duration of study) could not be replicated. To further investigate the formation and acceptance of neuromyths in higher education contexts, it will be necessary to analyze not only individual backgrounds and interests but also various teaching methods and course contents together with the role played by the brain and different cognitive processes in the study of music (listening, making, learning).The results of the replication show that music teacher students, teacher students with other subjects and students from other degree programmes do not show any significant differences in how well they can judge whether music-related or general neuromyths and neurofacts are scientifically proven or not scientifically proven. Compared to the reference study, the replication’s sample of music teacher students show a significantly lower performance in discriminating neuromyths and neurofacts; moreover, the predictors determined in the reference study (amount of media read, previous duration of study) could not be replicated. In order to further investigate the formation and acceptance of neuromyths in higher education contexts, it will be necessary to analyse not only individual backgrounds and interests, but also various teaching methods and course contents together with the role played by the brain and different cognitive processes in the study of music (listening, making, learning).

Student Engagement During Singing in Music Lessons: An Empirical Investigation of Possible Predictors

2024-10-01T02:20:44+00:00

Singing is a vital element of music learning in school. The present study investigates how selected factors influence students’ engagement during singing in music lessons. These factors are: (a) the basic psychological needs for competence, autonomy and relatedness based on self-determination theory; (b) the relationship between students and their teacher; (c) the students’ musical sophistication; (d) well-being through singing; (e) the frequency of singing in music classes; (f) whether the students like to sing in their leisure time; (g) whether students are member of a choir; (h) whether the students like the songs that are sung in music classes; and (i) the students’ age and gender. In order to identify potential relations between these factors and engagement, a questionnaire was administered to a sample of students (N = 225) aged 10 to 13 (M = 11.38, SD = 0.70). Various statistical methods show similar results: whether students like the songs they sing and how much well-being they experience during singing are the two most important predictors of their engagement. Apart from that, the need for competence and autonomy, along with the students’ relationship with their teacher and their degree of musical sophistication, can also be considered solid predictors of engagement. Out of all these factors that determine students’ engagement during singing in music lessons, the only predictor that cannot be influenced by teachers is the students’ well-being.

The Creative Performance of the AI Agents ChatGPT and Google Magenta Compared to Human-Based Solutions in a Standardized Melody Continuation Task

2024-09-05T02:51:48+00:00

Many generative artificial intelligence (AI) systems have been developed over the last decade. Some systems are more of a generic character, and some are specialized in music composition. However, whether these AI systems are serious competitors for human composers remains unclear. Despite increased public interest, there is currently little empirical foundation for a conceivably equivalent performance for creative AI when compared to human experts in a controlled task. Thus, we conducted an online experiment to evaluate the subjectively perceived quality of AI compositions with human-made products (by music students) in a standardized task. Based on a melody continuation paradigm, creative products using AI were generated by the AI agents ChatGPT (Version 3.5) and Google Magenta Studio (Version 2.0). The human creative performances were realized by 57 melodic continuations, composed by music students. In the online evaluation study, listeners (N = 71, mainly musicians) rated the aesthetic quality of the outcomes of the various systems. Additionally, the raters’ musical experience level was controlled as well as the length of the given melody completion task (two probe positions). As a main result, the overall quality of the AI compositions was rated significantly lower on all four target items compared to the human-made products (large effect sizes). Musical experience and the length of the melody did not influence the ratings. We conclude that the current capabilities of AI in the domain of musical creativity determined by a standardized composition task are far below human capabilities. However, we assume rapid progress will be made in the domain of generative music-specific AI systems.