Mobile composing: Professional practices and impact on students’ motivation in popular music

Abstract

This pilot study focuses on the use of mobile tablets to allow secondary students to compose in class with the application GarageBand. The empirical research has two aims: to demonstrate the possibility of using mobile tablets as a composing device, and to examine professional practices for using mobile technologies in music learning. A 12-week e-learning curriculum was specially designed for students to learn to use mobile tablets to compose popular music. A total of 159 secondary school students participated in the study and responded to a set of pre- and post-activity questionnaires, modelled on items developed for a motivational study by McPherson and O’Neill (2010). The paired sample t-test compared the mean score changes in the dimensions of intrinsic value, attainment value, utility value, perceived cost and expectancy in motivation. Furthermore, one-way analysis of variance compared the mean scores for scale questions on learning motivation between groups based on number of years spent learning to play an instrument as revealed by the student survey. The findings of SPSS analysis reveal that both non-instrument learners and instrument learners showed significant increases in motivation when using mobile tablets as an instrument to compose popular music in class. Different modes of learning, limitations and suggestions are also discussed in mobile composing.

Keywords

mobile composing motivation GarageBand e-learning popular music

Introduction

This mobile learning project was supported by a grant from the Knowledge Transfer (KT) Fund of the University Grant Council (UGC) to study motivation and mobile learning within an e-learning environment. The research was conducted in collaboration with a local secondary school that owns 100 iPads. The participants were students enrolled in a one-year e-learning in music curriculum designed by the principal investigator. A total of 159 (82 male and 77 female) secondary school (aged 12 to 13) students were involved. For 12 weeks, they used mobile tablets to compose popular music in class with virtual instruments, such as a voice sampler, drum set, electric bass, electric guitar, keyboards and strings.

Background

Motivation is regarded as a crucial factor affecting the effectiveness of learning and academic achievement. Intrinsic and extrinsic motivations have been identified and discussed extensively in the literature. Expectancy-value theory (Eccles et al., 1983; Wigfield & Eccles, 2000) identifies two areas that contribute to student motivation: a) the expectancies of task-specific beliefs and ability beliefs, and b) the achievement values of individuals with regard to specific domains. According to Eccles and others (1983), ‘expectancy’ refers to individuals’ beliefs about how well they will perform a task in the near future. When individuals possess high expectancy in a specific domain, they tend to achieve better performance outcomes in that domain. Achievement is further defined according to four types of value in relation to a specific domain: a) attainment value, b) intrinsic value, c) utility value, and d) cost (Eccles et al., 1983). ‘Attainment value’ describes the importance of doing well in a specific domain according to the individual’s subjective judgment. ‘Intrinsic value’ refers to the individual’s enjoyment in undertaking the specific task. ‘Utility value’ refers to how individuals benefit from participating and learning in a specific domain. Finally, ‘cost’ refers to the perceived loss to individuals engaged in learning within the domain.

Self-efficacy (Bandura, 1977, 1995, 1997; Pajares, 1996) is another important theory concerning the effectiveness of learning and academic achievement. Self-efficacy is defined as ‘personal judgments of one’s capabilities to organize and execute courses of action to attain designated goals’ (Zimmerman, 2000, p. 83). An individual’s personal judgment of his or her ability in a certain domain is believed to be determinative of achieving outstanding performance in that domain. When individuals believe in their own abilities, they tend to work harder, persist longer and have fewer negative motivational reactions when they encounter difficulties (Bandura, 1997). Individuals who possess higher self-efficacy are more likely to undertake challenging tasks (Bandura & Schunk, 1981; Zimmerman, Bandura, & Martinez-Pons, 1992). Students who possess higher self-efficacy have been shown to be more persistent and better at monitoring their working time and solving conceptual problems (Bouffard-Bouchard, Parent, & Larivee, 1991).

In these theories, motivation can be attributed to six types of human desire for success in a specific discipline or work. These comprise: belief in achievement in a discipline in the near future (expectancy), desire to achieve a certain level within a discipline (attainment value), desire to participate in an activity (intrinsic value), consideration of the benefits that can accrue from pursuing the identified work (utility value), consideration of the cost one must pay to engage in the work (cost), and the perception of one’s ability to pursue a discipline (self-efficacy). Taken together, these theories provide a relatively comprehensive understanding of human motivation in learning.

Leung and McPherson (2011) conducted a motivation study of music with 4495 students in 23 secondary and 20 primary schools in Hong Kong:

Compared with other academic subjects, including Chinese and mathematics, and cultural subjects, including visual arts and physical education, music was ranked quite low in terms of different variables. Students perceived music to be a rather difficult subject, believed themselves to have low competency in music and considered music to be of low value. (p. 1)

Author (2017) conducted a detailed study of 120 teachers in Hong Kong, comprising 60 in-service and 60 pre-service music teachers in 2014 and 2015, respectively, to examine their concerns and expectations regarding mobile learning in the music curriculum. ‘The top three concerns among teachers were equipment setup, technical support and financial burden. The top three expectations were e-learning resources, interactive functions and self-directed learning’ (Chen, 2017, p. 4). In the current study, the relationship between motivation and mobile learning is investigated to explore the possibility of using mobile learning to increase students’ motivation to learn popular music in a classroom setting in Hong Kong.

In some countries, such as the United Kingdom and the United States, the use of technology has been a ‘major trend’ in music education (Savage, 2007; Bauer & Mito, 2017). Savage (2007) argued that information technology in music classrooms could positively disrupt traditional approaches to music teaching and learning. In this study, a survey was used to examine how students learn in the new classroom setting and how teachers change their pedagogical approaches when new technologies are introduced. The researcher found that new teaching approaches greatly benefited composition skills, as technology could help learners who lacked traditional instrumental skills. Bauer and Mito (2017) claimed that technology could enhance creative thinking in music, and found that students in classes facilitated by technology demonstrated increased creative musical thinking:

In New York, a public school music teacher, Ada Goldberg, experimented with using iPads in class to give students with mental and physical disabilities the opportunity to explore their musical creativity. The experiment used iPads because iPad applications do not require users to have well-developed musical technique: students can thus experience the pleasures of composing and arranging music in their own way. (p. 95)

Mobile tablets, including the iPad, are tools that can be used in general music classrooms to explore music through non-traditional instrumental means (Kratus, 2007). From pre-school to secondary school, students have been able to learn, perform and compose music on tablets. Randles (2013) shared his experience of using an iPad to perform as an ensemble for university students, and provided instructive insights into how to use the tablet in the general music classroom setting. Despite these innovations, however, there has been little research on how mobile learning affects students’ motivation within a specially designed popular music curriculum in the general music classroom setting.

In recent years, music technology and popular music education have been linked in terms of research and practice, at both tertiary and secondary school levels. Green (2002) believed that including popular music in a school’s curriculum is highly beneficial, and evaluated in her research that musicianship, discipline and self-esteem could be gained through popular music education. Ruthmann (2007) suggested that students nowadays are immersed in a ‘sound world’, due to the diversity of music in their daily lives. However, there is a gap between ‘inside’ and ‘outside’ experiences of music. Tobias (2012, 2013) investigated how secondary students engaged with music and acted as musicians in a song-writing and technology class, which involved the creation, performance, recording and production of original music with instruments and music technology. Based on these experiences, Tobias developed a theoretical framework for popular music pedagogy that addresses the role of production in contemporary music making and expands the notions of aural skills and music literacy in producing popular music. Crucially, Tobias’ work incorporated the details of production processes in music classrooms. By contrast, Moir and Medbøe (2015) suggested that teaching, learning and assessment in popular music education should be based on an understanding of popular music composition as ‘performance-centred practice’. The current study builds on both of these insights. It explores connections between mobile learning and popular music education by centring the mobile tablet as a tool for ‘performance-centred practice’, capable of expanding our notion of aural skills and music literacy in popular music pedagogy. This study can thus serve as an exemplar for teachers implementing e-learning techniques in popular music education. Videos and teaching materials are made available on the website created by the investigator and research team.

Methodology

This study addresses the following research questions.

What are the affordances and constraints upon student motivation associated with the utilisation of mobile composing in popular music classes?

How does the utilisation of mobile composing in popular music classes influence the professional practice of music teachers?

Project implementation

One hundred and fifty-nine students were divided into five classes. The project was implemented in two stages, which started in January and ended in May, 2018 and lasted 12 weeks. The first stage focused on specific popular music styles, including introductions to popular music, hip-hop, jazz and rock; these lessons took place within the ordinary class timetable once a week for the first six weeks. The lessons were 40 minutes long and divided into two parts: 20 minutes of teaching followed by 20 minutes of practising. The second stage took place over the following six weeks, during which students spent their time composing in popular music styles using the tablet application. Readers can refer to the curriculum by clicking the link to the KT website provided at the end of this paper.¹

Research design and data collection

The principal investigator designed the implemented curriculum and has assisted music teachers in developing a music curriculum in which mobile tablets are used to perform and compose popular music with the free application GarageBand. The music teacher is a classically trained musician. The students were able to use mobile tablets provided by the school or their own devices during the e-learning music lessons. Different kinds of popular music were involved in this pilot study, including hip-hop, jazz and rock. The learning process was captured through three data sources: pre- and post-activity surveys on motivation; focus group interviews with students; an individual interview with the teacher.

Data sources

Pre- and post-activity questionnaire: Online surveys were implemented before and after the curricular intervention to measure changes in students’ motivation. The main part of the questionnaire comprised 15 questions, which were modelled on items developed by McPherson and O’Neill (2010) for a motivational study comparing the motivation of students from eight countries to study music relative to other subjects. Demographic data including age, gender, level and number of years of instrument learning were acquired at the beginning of the questionnaire. The questions were categorised into six motivational measures following self-efficacy theory and expectancy-value theory. These measures were: a) self-efficacy, b) intrinsic value, c) attainment value, d) utility value, e) cost, and f) expectancy. The students were asked to state their level of motivation on a seven-point semantic differential scale, except for the question on self-efficacy, which asked students to exhibit their confidence in performing music using a mobile device on an 11-point scale (i.e. from 0%, 10%, 20%, etc., to 100% confidence). A paired sample t-test was used to compare the mean score changes under the dimensions of intrinsic value, attainment value, utility value, perceived cost and expectancy in motivation. Analysis of variance (ANOVA) was used to compare the learning motivation changes between groups of students with different years of instrument learning, based on information from the student survey (see Appendix A for the survey questions).

Student focus group interview: Students’ feedback and comments were collected after the first semester. Through random sampling, male and female students were invited to respond to five open-ended questions. The interview data were recorded and transcribed for further analysis to triangulate with other data sources, such as survey results and video observations (see Appendix B for the focus group interview questions).

Individual interview with the teacher: An in-depth interview was conducted with the music teacher involved in the study to share his experiences of, reflections on and professional practice in teaching mobile composing in popular music.

The interrelationship between these three data sources was to be complimentary in not only measuring the pre- and post-test of motivation, but also collecting the responses from the students’ interviews to explain the general trend of the survey. Also, the teacher’s view was collected to share experience and how to improve the practice in order to complete the whole picture of the study.

Limitations

The findings of this pilot study cannot be generalised to all secondary school students, because timetabling, the amount of time spent each week on e-learning and the availability of equipment differ between schools. However, it can serve as a reference for the practice of mobile composing in popular music in secondary schools.

Results

Online survey

In terms of self-efficacy, students responded positively to the first key question in the survey: 1. How confident are/were you that you can/could use an iPad to compose music? The results show an increase in mean score from 4.32 to 5.20 on an 11-point scale (i.e. from 0%, 10%, 20%, etc., to 100% confidence). The reason to choose an 11-point scale is to show the confidence level in 100% as a reference point to demonstrate how confident are the students before and after the project.

As shown in Table 1, Cronbach’s alpha analysis was used to determine the internal consistency of the survey instrument’s close-ended questions (2–15) both pre- and post-test. Cronbach’s alphas for the components of intrinsic value (four items), attainment value (two items), utility value (two items), perceived cost (four items) and expectancy (two items) were .901, .844, .773, .534 and .760, respectively. The results were highly consistent across the variables, suggesting excellent consistency for the data collected in this study (α = .925) for all 14 items.

Table 1.

Items of the motivation measure and its internal consistency.

14 items developed from a motivational study by McPherson et al. (2010) to compare students’ motivation to study music
Intrinsic value 2. To what extent do you think using an iPad to compose music might be/was interesting? 3. To what extent do you think using an iPad to compose music might be/was enjoyable? 4. Compared with other musical activities that you normally do at school, such as singing and listening, how interesting do you think using an iPad to compose music will be/was? 5. Compared with other musical activities you normally do at school, such as singing and listening, how enjoyable do you think using an iPad to compose music will be/was? Cronbach’s alpha (4 items)	.901
Attainment value 6. To what extent do you think using an iPad to compose music might be/was important? 7. Compared with other musical activities you normally do at school, such as singing and listening, how important do you think using an iPad to compose music will be/was? Cronbach’s alpha (2 items)	.844
Utility value 8. To what extent do you think using an iPad to compose music might be/was useful? 9. Compared with other musical activities you normally do at school, such as singing and listening, how useful do you think using an iPad to compose music will be/was? Cronbach’s alpha (2 items)	.773
Perceived cost 10. To what extent do you think using an iPad to compose music might be/was challenging? 11. To what extent do you think using an iPad to compose music might be/was easy? 12. Compared with other musical activities you normally do at school, such as singing and listening, how challenging do you think using an iPad to compose music will be/was? 13. Compared with other musical activities you normally do at school, such as singing and listening, how easy do you think using an iPad to compose music will be/was? Cronbach’s alpha (4 items)	.534
Expectancy 14. How good do you think you will be/were using an iPad to compose music? 15. How hard do you think you will try/tried to use an iPad to compose music? Cronbach’s alpha (2 items)	.760

A paired sample t-test was used to compare the means of all items from the five dimensions measuring motivation in music. The difference between the pre-test mean score of 4.33 and the post-test score of 4.79 in intrinsic value was statistically significant, t(172) = 6.486, p < .001. For questions related to attainment value, the mean scores were 3.91 and 4.43, and the difference was statistically significant, t(172) = 6.856, p < .001. Statistically significant gain was also clearly found for utility value, with both pre-test 4.01 and post-test 4.47, t(172) = 5.841, p < .001. A statistically significant difference was evident for perceived cost, t(172) = 4.746, p < .001, with pre-test and post-test means of 4.01 and 4.28, respectively. A statistically significant gain was also clearly shown for expectancy, both pre-test 3.65 and post-test 4.10, t(172) = 5.611, p < .001.

In Table 2, from the pre-test and post-test samples, the mean changes in attainment value ranked highest after the project.

Table 2.

Paired sample t-test for all samples of the different dimensions of motivation.

Dimensions	Pre-test	Post-test	df	t	Sig
Intrinsic value	4.33	4.79	172	6.486	.000
Attainment value	3.91	4.43	172	6.856	.000
Utility value	4.01	4.47	172	5.841	.000
Perceived cost	4.01	4.28	172	4.746	.000
Expectancy	3.65	4.10	172	5.611	.000

In Table 3, the number of years students had spent learning an instrument was collected to check for a correlation between instrument learning and motivation to use mobile devices to compose popular music. A survey was conducted to divide the students into a control group (instrument learners) and experimental group (non-instrument learners) at the beginning of the pilot study.

Table 3.

Distribution of students in years of learning in musical instruments.

Years of learning	Number of students	Percentage (%)
Did not learn musical instruments	35	20.2
Less than 1 year	11	6.4
1–2 years	34	19.7
3–4 years	42	24.3
5–6 years	27	15.6
More than 6 years	24	13.9
Total	173	100.0

Furthermore, one-way ANOVA was used to compare the learning motivation changes between different groups of years of instrument learning. Both the control group (instrument learners) and the experimental group (non-instrument learners) had significant increases from pre-test to post-test in the dimensions of intrinsic value, attainment value, utility value, perceived cost and expectancy. Among these five dimensions, no significant differences (p < .05) were found between the control group (instrument learners) and experimental group (non-instrument learners).

E-learning from students’ perspectives

A focus group interview was conducted after the implementation of the mobile learning project. Content analysis was used to analyse the responses from the students’ interview scripts and summarise them into a table comparing traditional ways of teaching and e-learning in popular music.

In Table 4, students mentioned that the experience, process, mode and learning styles in e-learning were different from the traditional ways of learning popular music. They found that the learning experiences were more enjoyable and engaging in mobile composing. However, there were also limitations in e-learning.

Table 4.

E-learning from students’ perspectives.

Perspective	E-learning	Traditional ways of learning
Experience of learning	Fun and enjoyable Learn more about the instruments Can try different instruments in composing	Learn knowledge through presentation from teachers Do not get to experience a lot of instruments in composing
Process of learning	Use different instruments and styles such as drum and bass. We experience more by composing directly on the iPad	Think of the music by ourselves and maybe sometimes hear the notes on the piano
Mode of learning	More convenient Saves a lot of time during the learning process We can continue our learning experience after school	Spend a lot of time learning to compose Finish the composing task in class due to the limitations of the instruments
Style of learning	Listen to the creative outcome in e-learning Easily play and record different instruments even if we have not learned that instrument before	Listen to the music in normal teaching Difficult and time-consuming to learn popular music because there are many instruments we do not know how to play

Limitations of e-learning

Issues were also identified during the focus group interview. Students mentioned several difficulties and how they overcame them during the composing stage. Students commented on their difficulties recording instruments on the iPad such as guitar, violin and keyboard. Students A, B, C and D stated as follows:

The most challenging part was that when I was playing notes on the guitar, the screen only showed a certain number of frets, but not the whole fretboard. Therefore, I could not play or record the notes that were higher than the fretboard on the screen. I tried to tackle the challenge by recording the notes an octave lower during the recording stage and then transposing the notes an octave higher afterwards. (Student A)

The major challenge during the composing stage was that I wanted to try the violin in GarageBand, but the violin was difficult to play accurately even though I have played violin for many years. I tackled the challenge by trying other instruments because I had not tried many of the instruments before. So, the difficult part pushed me to experience more at the same time. (Student B)

I think the major difficulty during the composing stage was that playing the guitar on the screen was not the same feeling as playing a real guitar. Sometimes I recorded some notes, but the notes were not the pitch I expected. To tackle this difficulty, I practised several times and got more familiar with the layout. (Student C)

While composing, the limited range of the keyboard was the greatest challenge to me. As the number of keys on the screen was limited, it was quite difficult to record piano. To tackle this challenge, I simply split the input process into smaller parts. (Student D)

Professional practice and reflections from the teacher’s perspective

An individual interview was conducted with the music teacher after the implementation of the project. He mentioned that in the past he had adopted the traditional way of teaching music theory, including music notation, metre and tonality. He spent a great deal of time teaching students music theory before they began composing, and most of the students became bored with learning theory. In this mobile composing project, he focused more on different chord progressions, and students could listen directly to the outcomes on the iPad. This approach was quite effective in class, and students were fully engaged during the music lesson. He found that the most successful lesson in this project was teaching jazz using the 12-bar blues. Students could easily improvise a melody based on the given chord progression and develop their own drum pattern. In the past, students had few opportunities to improvise in class. With the mobile tablet, students could improvise their ideas immediately during the practice session. The teacher also found that teaching rock music was not as easy as he thought, because there were frequent variations in terms of chord progressions, so it was quite difficult to make students understand the usual practice. He stated that he would consider limiting the number of chord progressions next time, or change to an easier topic in his next trial, such as Canto-pop music.

Discussion

Responses to research questions

What are the affordances and constraints upon student motivation associated with the utilisation of mobile composing in popular music classes?

The online survey revealed that the students’ motivation increased in six dimensions, based on 15 items, including self-efficacy (one item), intrinsic value (four items), attainment value (two items), utility value (two items), perceived cost (four items) and expectancy (two items). From the statistical data, the internal consistency value (α = .534) for perceived cost was lower than that for the other domains. Although this discrepancy did not affect the internal consistency value (α = .925) for the other 14 items in the survey, we still must address it. It may imply that the mobile learning activities were somewhat challenging to the students, as indicated by survey question 10, ‘To what extent do you think using an iPad to perform music might be/was challenging?’, with a mean score difference from 3.94 to 4.14. This concurred with the findings in the context of the existing literature on motivation that individuals who possess higher self-efficacy are more likely to undertake challenging tasks (Bandura & Schunk, 1981; Zimmerman, Bandura, & Martinez-Pons, 1992).

Apart from the online survey, students also expressed in the interview that the mode and style of learning have been changed. They can take up more challenging tasks in e-learning than in traditional ways of learning, such as ‘easily play and record different instruments even if we have not learned that instrument before’ and ‘continue our learning experience after school’.

In the paired sample t-test, the mean changes in attainment value ranked highest, suggesting that students attained high levels of goal achievement after the project. Students may have found mobile learning to be somewhat challenging, but if they achieved the goal by the end of the project, then they may still be seen as highly motivated to complete the task. This echoes the theory of motivation in self-efficacy that ‘personal judgments of one’s capabilities to organize and execute courses of action to attain designated goals’ (Zimmerman, 2000, p. 83).

During the interview, students also commented that they attained high levels of goal achievement because e-learning has transformed their experience and process of learning as compared with the traditional learning, such as ‘we can try different instruments in composing’ and ‘experience more by composing directly on the iPad’.

One-way ANOVA was used to compare the learning motivation changes between groups based on years of instrument learning. Both the control group (instrument learners) and the experimental group (non-instrument learners) showed increases between the pre- and post-tests in the dimensions of intrinsic value, attainment value, utility value, perceived cost and expectancy. Thus, mobile learning can be considered a useful approach when teaching music at schools to narrow the learning gap between students who study instruments (instrument learners) and those who do not (non-instrument learners). In the past, music teachers have always faced the problem of learning diversity among instrument learners and non-instrument learners in the classroom, as it may create issues in curriculum design around sight-reading, aural dictation, performance skills, etc. One of the major benefits of music technology is that it helps lower the skill barrier in performing and composing music, such that non-instrument learners can learn, perform and compose music. From the interviews, students described their experience of learning as ‘fun and enjoyable’, especially for the non-instrumental learners, while the mode of learning was ‘convenient’ and ‘save[s] lots of time during composing’. It is always a challenging task for non-instrumental learners to compose in class, since they may not be as confident as instrumental learners. In this way, all students can find music lessons more enjoyable and become more self-motivated. This study extends the existing literature from Moir and Medbøe (2015) on the mobile tablet as a virtual instrument tool for ‘performance-centred practice’, capable of expanding our notion of aural skills and music literacy in popular music pedagogy.

In addition to pointing out the benefits of e-learning in this project, it is worth noting some of the perceived limitations of virtual instruments. During the focus group interview, one student reported that ‘the screen only showed a certain number of frets, not the whole fretboard’ on the guitar, and the student tried to tackle the challenge by recording the notes an octave lower and then transposing the notes an octave higher afterwards. Another student said that she ‘wanted to try the violin in GarageBand, but the violin was difficult to play accurately’ even though she had played violin for many years. The implication is that virtual instruments can only serve as a tool for recording; they cannot replace acoustic instruments. A student also mentioned that ‘the number of keys on the screen was limited, so it was quite difficult to record piano’. Thus, mobile composing has some limitations on the touchscreen panel when it is used as a virtual instrument for recording. Students may have to tackle the limitations by switching one octave up or down when recording their musical ideas or practise in advance before making the real recording for each track.

RQ2. How does the utilisation of mobile composing in popular music classes influence the professional practice of music teachers?

In this project, the music teacher commented that mobile learning has changed his pedagogy from the traditional method of teaching music theory to teaching chord progressions in specific styles, such as a 12-bar blues for improvisation or chord progressions for rock and hip-hop. Therefore, students can fully engage in applying the tools of mobile composing in a specific style.

The practice of e-learning can help bridge the gap between the decline in learning motivation (Leung & McPherson, 2011), in which students believe themselves to have low competency in music and consider music to be of low value, and the rising importance of popular music (Ruthmann, 2007) that immerses students in a ‘sound world’, through the diversity of music in daily life. Therefore, a well-designed e-learning music curriculum with the support of mobile tablets can enhance students’ motivation to learn music in weekly music lessons, and thus reduce the gap between ‘inside’ and ‘outside’ music experiences in the classroom setting. The music teacher who makes use of mobile composing performs multiple roles as a curriculum designer, instructor, facilitator, adviser and assessor in the e-learning curriculum.

Footnotes

Appendix A

Appendix B

Focus group interview questions.

Acknowledgements

I wish to thank the music teacher Zeralano Lie and Vice-Principal Lau at the HKBU-Affiliated School Wong Kam Fai Secondary School for their support. Thanks also to my research assistant, Elvis Tsang, and student assistant, Tina Fan.

Funding

This project is funded by the KT Fund (ref. no. 05919), supported by the UGC in Hong Kong.

Ethical issues

This study was approved by the Human Ethical Review Committee of the university. A consent form was provided and signed by the participants and their parents or legal guardians before the research was conducted.

Notes

ORCID iD

Jason Chi Wai Chen

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