test and non-parametric test (Kruskal–Wallis test) were used. In addition, the Bonferroni correction for multiple comparisons was used. With the stress, study workload, and seven proactive coping styles scales, bivariate analyses with scatterplots, Pearson correlation, and multiple linear regression were used.
In Article III, the data of the 155 respondents to the WSC questionnaire was used for a different analysis to answer different sub-questions. Descriptive statistics were computed for demographic characteristics (country, gender, level of degree, genre group, working while studying, funding, and loans), and bivariate analysis with Kendall’s rank correlation was computed to examine the relationships between study workload and stress scales. The Bayesian approach was utilised to build models to predict music students’ responses to experienced study workload and stress, and 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.
The participants’ responses to working while studying, funding, and loans were added to analyse music students’ livelihoods as predictors in the model.
Bayesian mixed effects ordinal probit regressions were performed for model evaluations and to identify variation across each study workload item and the stress item, as well as variation across individual responses.
4.6.2 Factor structure of the questionnaire
Exploratory Factor Analysis (Appendix 9) was carried out to explore the factor structure of the WSC questionnaire and to determine whether its nine-factor structure holds for the sample of music students. Three respondents were excluded because they had missing values in most of the proactive coping styles scales. Thus, the factor analysis was conducted with a sample of 152 respondents. Principal Axis Factor (PAF) with a Varimax (orthogonal) rotation was conducted to minimise the number of variables that have high loadings on each factor. The factorability of the 61 items was examined. The Kaiser-Meyer- Olkin measure of sampling adequacy and Bartlett’s test of sphericity were computed. The communalities were examined, and variables with insufficient factor loadings were excluded. Finally, the Alpha values for the scales in the
WSC questionnaire and the scales in the new factor structure were examined.
In addition, the respondents’ feedback about the WSC questionnaire (see item 87 in Appendix 7) was utilised to evaluate the general structure of the questionnaire.
4.6.3 Qualitative data analysis
In the qualitative data analysis (see Appendix 10), a thematic coding framework was built on 13 codes, four categories, and three overarching themes deduced from the systematic review (Article I). Fourteen codes drawn inductively from the interview data were added to the thematic coding framework in order to clarify and incorporate music students’ lived experiences of workload while studying. The adaptation of the analytical process of transcendental phenomenology (Moustakas, 1994) was followed in seven phases16:
1) Through horizonalisation (Moustakas, 1994), all the music students’
responses that were relevant to their workload were listed, grouped, and coded using 13 literature-based and 14 interview-based codes, and then separated within each interview and WSC questionnaire participant’s data.
2) Through reduction and elimination, only relevant references were selected as significant statements. Two questions were used to select these significant statements: 1) Does this quote illuminate the music student’s experiences of workload? and 2) Does this quote highlight any connections between the music student’s experiences of workload and the linked code(s)? These questions served to refine the data set by eliminating all irrelevant, repetitive, and overlapping statements.
3) Through clustering and thematising, the selected 1,584 significant statements were arranged according to linked codes into four categories (drawn from 13 literature-based and 14 interview-based codes). Each significant statement was then assigned a theme describing the context of the student’s experienced workload: student, teacher, or environment.
Through this process, three overarching theme groups were formulated:
music students’ ability to cope with their workload, tools for teachers
An example of a full procedure, with the transcendental phenomenology approach applied to the methodology across six phases of the research plan and data collection and seven phases of data analysis procedure, is presented in Jääskeläinen (2022b) and Jääskeläinen (2022c).
16
to support music students to manage and cope with workload, and developing learner-centred environments in higher music education.
4) Through validation, the three overarching theme groups were compared with the original transcripts to ensure that these themes had adequately captured the participants’ experiences of their workload in relation to the linked code(s) and categories. Some adjustments were made in this phase, such as linking some of the significant statements from one code to another code and moving some codes from one category to another category.
5) Individual textural and structural descriptions were constructed by going through each participant’s significant statements and creating narratives of their experienced workload (textural description) in connection with the relevant contexts of workload (structural description): student, teacher, or environment.
6) Composite textural and structural descriptions were constructed for each overarching theme group, including the students’ experiences of their workload as textural descriptions of what occurred, and the context of workload as structural descriptions of how it occurred. This process involved combining the textural and structural descriptions from all participants together and distilling them into expressions of music students’ workload in each of the three contexts. During this phase, some significant statements were selected to be utilised in articles as examples of music students’ experiences of workload.
7) Through intuitive integration, the composite textural descriptions and the composite structural descriptions were synthesised together to create a universal description of the phenomenon. Finally, recommendations for good practice related to music students’ workload in higher education were constructed and findings were then reported in three separate articles, in this dissertation, and as policy and intervention recommendations (see Jääskeläinen, 2022a)
The thematic coding framework, including the number of significant statements, is presented in Table 5.
Table 5. Thematic coding framework including the number of significant statements in questionnaire (Q) and interview (I) participants’ data
13 literature- based codes *
(Q:526+I:327=853)
14 interview- derived codes
(Q:354+I:377=731)
Four categories of different workload meanings drawn from columns 1 and 2
(Q:880+I:704=1,584)
Three overarching themes of proposed recommendations for good practice related to music students’
workload in higher education
Structure of student workload
(Q:82+I:20=102)
Work
(Q:41+I:25=66) +
Competition
(Q:4+I:12=16)
Funding
(Q:14+I:22=36)
Musician career
(Q:16+I:73=89)
Social media
(Q:0+I:4=4)
Structure of workload
(Q:157+I:157=314)
Music students’ ability to cope with their workload (including excerpts related to ‘the student’ in four of the categories to the left)
*** (Q:197+I:276=473)
Tools for teachers to support music students to manage and cope with workload (including excerpts related to ‘the teacher’
in four of the categories to the left) ****
(Q:455+I:157=612)
Developing learner- centred environments in higher music education (including excerpts related to ‘the
environment’ in four of the categories to the left) *****
(Q:228+I:271=499)
Approaches to learning
(Q:56+I:29=85)
Experiences in the first year of study
(Q:4+I:15=19)
Flow
(Q:2+I:6=8)
Time management
(Q:27+I:51=78)
+
Coping
(Q:86+I:53=139)
Enjoyment
(Q:16+I:15=31)
Meaning of musicianship **
(Q:2+I:30=32)
Practising
(Q:24+I:33=57)
Religion
(Q:2+I:2=4)
A student’s workload
(Q:219+I:234=453)
One-to-one tuition
(Q:106+I:36=152)
Teaching and learning environments
(Q:71+I:40=111)
+
Assessment
(Q:12+I:25=37)
Curriculum
(Q:45+I:35=80)
Group tuition
(Q:131+I:23=154)
Student feedback
(Q:1+I:39=40)
Workload relating to teaching and learning environments
(Q:366+I:209=575)
Burnout
(Q:8+I:14=22)
Health
(Q:25+I:25=50)
Musculoskeletal problems
(Q:5+I:19=24)
Performance anxiety
(Q:9+I:22=31)
Stress
(Q:90+I:25=115)
+
Physical exercise
(Q:1+I:11=12) Psychological and
physiological issues
(Q:138+I:116=254)
Results and findings reported in *Article I (2022), **Jääskeläinen (2022b, 2022c), ***Article II (2022), ****Article IV (2022), and *****Article III (2020).
5 RESULTS AND FINDINGS
This chapter presents the results and findings of the explanatory stage of the MSW project’s research, as reported in the four peer-reviewed journal articles that are included as appendices to this dissertation (Appendices 1–4). In this chapter, each article is presented independently with its sub-questions. The order is not chronological, as it follows the order of the research design outlined in the fourth chapter. In the sixth chapter the results and findings of all of the articles will be combined to discuss the overarching research question: What are music students’ experiences of workload, stress, and coping in higher education? The discussion is guided through the four research sub-questions shown here:
1) How does the previous international research define music students’
experienced workload in higher education? (Article I) 2) How do music students in Finland and the United Kingdom
experience workload and stress and use coping styles in their studies, their teaching and learning environments, and their interactions with teachers? (Articles II–IV)
3) To what extent are experienced study workload, stress, and proactive coping associated with gender, level of degree, genre group, and study programme among music students in Finland and the United Kingdom? (Articles II and III)
4) How could this dissertation’s results and findings about music students’ experiences of workload, stress, and coping be used to develop pedagogical practices and educational policies in higher music education? (Articles I–IV)
In addition, this chapter presents the results of the evaluation of the factor structure used in the WSC questionnaire and the respondents’ feedback.