The integration of results and findings showed that it is essential to identify common music-specific ways for coping with studies in higher education.
Nevertheless, there are differences in experienced study workload, experienced stress, and use of proactive coping styles between different genders, between different genre groups, and between different study programmes. These differences should be discussed in higher music education institutions to find ways to better support music students as individuals in their studies, to further their well-being, and to prepare them for their future careers.
5.3 Article III: Music students’ experienced workload, livelihoods and
music students’ experienced workload was examined in connection with their experienced stress and life and livelihoods. This explanatory mixed methods study involved the participation of 155 students at higher music education institutions in Finland and the United Kingdom. The article posed the following sub-questions:
1) Are there any relationships between music students’ experienced study workload and livelihoods (including socio-demographic characteristics, working whilst studying, funding and loans) and experienced stress in higher education in Finland and the United Kingdom?
2) What environmental factors determine music students’ experienced workload in higher education in these two countries?
3) How could the predictors and determinants of environmental factors affecting music students’ workload inform the development of university cultures and educational policies?
In the quantitative analysis phase, descriptive statistics were computed for demographic characteristics, and bivariate analysis with Kendall’s rank correlation were computed to examine the relationships between study
workload and stress scales. In order to build models to predict music students’
responses to experienced study workload and stress, multiple covariates were included for evaluating their potential effect on these experiences. In addition to a participant’s country, their gender, level of degree, and genre group were also included. To analyse music students’ livelihoods as predictors in the model, their responses to working while studying, funding, and loans were added.
Bayesian mixed effects ordinal probit regressions for the model evaluations were performed to identify variation across each study workload item and the stress item, and across individual responses. The results indicated that countries have a negligible effect on music students’ study workload and music students’
stress when additional predictors were not included in the model. However, modelling all predictors (experienced study workload, gender, level of degree, genre group, and livelihoods) at the same time increased the effect of countries on stress from negligible to positive, indicating that music students in the United Kingdom were more likely to experience stress than music students in
Finland. This contradictory result shows that environmental factors may have an effect on music students’ stress experiences. Thus, it would be useful in the future to evaluate music students’ experienced stress by modelling other predictors related to their experiences of studying in higher education. The detailed results are presented in Table 9.
Table 9. Results of the quantitative analysis phase in Article III
Methods Analyses Results
Kendall’s rank correlation
Relationship between five experienced study workload items and one experienced stress item
Correlations between items ranged from weak negative (‘workload is hard’ and ‘workload does not align with credits’) to strong positive (‘overload’ and ‘too intense pace’).
Bayesian ordinal probit regression
Simplified mixed effects models: Influence of countries on experienced study workload and influence of countries on experienced stress
There was a negligible effect of countries on music students’
total study workload and on music students’ stress. However, there was a non-negligible effect of countries across each study workload item and stress item. The effect on four study workload items (‘overload’, ‘workload is not easy’, ‘workload does not align with credits’, and ‘too intense pace’) and one stress item was greater in Finland than in the United Kingdom, and the effect on one workload item (‘workload is hard’) was greater in the United Kingdom than in Finland.
Bayesian ordinal probit regression
Larger mixed effects model: Influence of countries on experienced study workload
evaluated in relation to experienced stress, gender, level of degree, genre group, and livelihoods (i.e., work related to music, other work, amount of work, funding, and loans)
Modelling all predictors at the same time slightly increased the effect on the study workload observed in the simplified model in relation to countries. However, the effect still remained negative. Stress was the strongest predictor of study workload.
Music students with partial funding or no funding at all were less likely to experience study workload than music students with full funding. Work related to music had a greater effect than work not related to music, but the total amount of work undertaken alongside studies had a negligible effect on the study workload. Female music students were likely to experience more study workload than male or non-binary gender music students. The level of degree, in general, had a relatively small impact on the results. However, undergraduate music students were likely to experience more study workload than postgraduate music students or junior and doctoral music students. The genre group had little influence on the level of study workload, although studying music education had a greater effect compared to other genres group (i.e., other than music education genre group and classical music genre group), whereas the classical music genre group had negligible effect.
Having or not having a student loan did not lead to any noteworthy effects.
Bayesian ordinal probit regression
Larger mixed effects model: Influence of countries on experienced stress evaluated in relation to experienced study workload, gender, level of degree, genre group, and livelihoods (i.e., work related to music, other work, amount of work, funding, and loans)
Modelling all predictors at the same time increased the effect of countries on stress from negligible (observed in the simplified model) to positive, indicating that music students in the United Kingdom were more likely to experience stress than music students in Finland. The study workload was the strongest predictor of stress. There was also a noticeable effect of gender, such that female music students were more likely to experience stress than male music students. With non-binary gender there was a positive effect on stress, which was contradictory to the negligible effect on study workload in the larger study workload model. Both work not related to music and the total amount of work undertaken alongside studying had a small effect, but work related to music did not have an influence on stress. Junior or doctoral music students were much more likely to report stress than postgraduate music students or
undergraduate music students, which contradicts the larger study workload model in which being an undergraduate music student had more influence on study workload. The genre group had no effect on stress, nor did funding and loans.
• Further predictors of the impact of the structure of music students’
workload:
o work related to music is felt to be enjoyable, and even invaluable, for music students’ future careers;
o an equality issue indicating a large gap between well-off students (e.g., full scholarship or support from family) compared to low-income students who have to work long hours to earn their living;
o pressure within the field of music negatively affecting music students’ beliefs regarding their abilities as professional musicians;
o idealisation of talented musicians;
o competition and comparison in performing music;
o social media strengthening the myth of innately talented artists in society; and
o characteristics that may be unique to those students who have been devoted to a career in music since early childhood.
• Further predictors of the impact of music students’ workload while studying:
o approaches to learning when the curriculum and timetable in relation to a study programme are overloaded;
o the competitive atmosphere of the neoliberal university, its ideal world composed of individuals skilled in multitasking, and its lack of collegiality, in comparison to advocating realistic possibilities for coping with studies;
In the qualitative analysis phase, thematic analysis (see the adaptation of the analytical process of transcendental phenomenology used in the MSW project in the fourth chapter) was used to find further predictors of music students’
experienced workload and stress, to be utilised in the developmental work in higher music education institutions and educational policies.
o time management in studying music, which includes many additional commitments, such as rehearsals and gigs, compared to other disciplines in higher education;
o experiences during the first year of study, which can be a traumatic transition phase in a music student’s life;
o challenges connected with practising, such as practice room reservations and scheduling rehearsals for ensembles;
o flow experiences, indicating positively-experienced workload o the meaning of professional musicianship, and this form of study
as a unique and holistic experience for music students; and o enjoyment arising from playing both alone and with other
performers
o religion, especially nowadays when universities are multicultural learning environments including students with diverse religious backgrounds, as a way to find the tools and community to help students to cope with stressful periods.
• Further predictors of the impact of music students’ workload relating to teaching and learning environments:
o how the course, which helps music students to develop their time management skills, could impact music students’ experienced workload;
o the unique and sometimes challenging relationship between a music student and their one-to-one instrumental or singing teacher;
o compulsory courses (academic studies and some group tuition) with strict regulations for permissible amounts of non- attendance;
o the unpredictable and sometimes very intense workload in the curriculum;
o meaningless versus meaningful ways to utilise assessment; and
o university culture and the nature of behaviour in the music profession hindering music students from giving honest
feedback, as students may be afraid of jeopardising their future careers.
• Further predictors of the impact of psychological and physiological issues in studying music:
o serious consequences of stress on music students’ ability to study and the impact of stress on their self-image as students and musicians;
o music students’ experiences of burnout;
o performance anxiety as a particular factor in studying music;
o university support for music students’ musculoskeletal problems;
o the positive impact of active and regular exercise on decreasing music students’ experienced stress; and
o the fact that most music students need help from a student counsellor or a longer period of intensive therapy at some stage in their university studies.
The integration of results and findings showed that where neoliberal university culture impacts music students’ livelihoods alongside their studies, this is likely to increase experienced stress but not necessarily influence the experienced study workload. However, stress has a notable effect on music students’
experiences of workload. Therefore, attention should be paid to certain aspects related to workload in higher music education institutions, such as the gap between well-off students and low-income students who need to work, and stress, particularly with female and non-binary gender students. Furthermore, to counter and eliminate the negative impact of neoliberalism on music
students’ well-being while studying, institutions should find ways to change the competitive atmosphere towards a more cooperative one, and music students’
experiences should be utilised to further both the development of institutional cultures and educational policies.
5.4 Article IV: Tools for teachers to support music students in