Interactive technologies in the instrumental music classroom:

a case study with the Music Paint Machine.

Luc Nijs IPEM, Ghent University, Belgium Luc.Nijs@Ugent.be

Marc Leman IPEM, Ghent University, Belgium Marc.Leman@Ugent.be

Abstract

In this paper we describe a nine-month longitudinal study in which twelve children (1st and 2nd grade) learned to play the clarinet. Six of the children received instruction with an interactive music system, called the Music Paint Machine. This educational technology allows a musician to make a digital painting by playing music and by making various movements on a coloured pressure mat. The aim of the system is to support instrumental music teaching and learning by stimulating musical creativity, by promoting an embodied understanding of music and by supporting the development of an optimal musician-instrument relationship. The overall goal of the longitudinal study was (1) to integrate the Music Paint Machine in instrumental music instruction in order to develop good practices with the system and (2) to investigate the possible effect of instruction with the system on the learning process. The study adopted a non-equivalent control groups design with several pre-tests and a post-test. To measure the effectiveness of instruction with the system, children were administered the Primary and Intermediate Measures of Music Audiation (Gordon, 1986) as pre- and post-test. Furthermore, pre-tests were organised to map possible confounding variables, such as personality, home musical environment, motor skills and self-regulation skills. No statistically significant differences were found between the control and intervention group. Dealing with the complexity of a real-life educational setting and with the requirements of the quasi-experimental design, this study has provided insights on methodology (design, measures, analysis) in music educational technology research. As such, it can contribute to the further development of this branch of educational research.

1. Introduction

The emergence of new technologies has always led to new possibilities

for teaching and learning. In particular, the increasing computational

power and the embedded computing continuously change the way

we interact with computers and learn (Dourish, 2004). The traditional

desktop computing is increasingly complemented and possibly even

gradually replaced by a new breed of computational systems (iPads,

smartphones) in which mouse and keyboard are exchanged for other

types of sensors and controllers. Evidently, this offers possibilities for the

design of new educational technologies and applications.

In the domain of music education, an emerging trend is the

development of interactive systems that offer active ways of engaging

with music, using the multimodal nature of the musical experience as a

basis for visual, sonic and bodily interactions. Some of these systems

focus at instrumental teaching and learning. They monitor a musician’s

playing and provide auditory and visual feedback on music and

movement (e.g. Larkin, Koerselman, Ong, & Ng, 2008; Ng, Larkin,

Koerselman & Ong, 2007; Brandmeyer, Hoppe, Sadakata, Timmers &

Desain, 2006; Howard, Welch, Brereton, Himonides, De Costa, Williams

& Howard, 2004; Welch, Himonides, Howard, & Brereton, 2004).

Interactive music systems are assumed to stimulate the musical

learning process (e.g. Pritchard and Woollard, 2010) for several reasons,

such as: the engagement of multimodal processing capabilities (e.g.

de Jong, 2010; Sweller, Van Meriënboer & Paas, 1998), the use of

objective performance measurement (e.g. Hoppe, Brandmeyer,

Sadakata, Timmers, & Desain, 2006; Howard, et al., 2007), the

stimulation of student autonomy and self-regulation (Carneiro, Lefrere

& Steffens, 2011), the creation of a powerful learning environment (e.g.

Jonassen, Campbell & Davidson, 1994), and their appeal to the daily

life world of young people (e.g. Burnard, 2007; Folkestad, 2006). As

such, interactive music systems have the potential contribute to a

constructivist approach to instrumental teaching and learning. This

approach is embodied and extended in the sense that new interactive

technologies intervene with the multimodal aspects of perception and

action that underlay how to play a music instrument.

Clearly, the belief in a didactic potential of interactive music systems

needs to be substantiated on the basis of empirical studies. At this point

we believe a critical stance is needed in relation to feedback, use of

technologies, pedagogical model, and intervention studies. Due to the

stimulation of multiple senses, feedback systems may cause a

degrading of learning due to cognitive load (e.g. Sadakata, Hoppe,

Brandmeyer, Timmers, & Desain, 2008; Thorpe, 2002), dependency (e.g.

Ronsse, Puttemans, Coxon, Goble, Wagemans & Wenderoth, 2011;

Schmidt, 2008) and the stimulation of an internal focus (e.g. Wulf &

Lewthwaite, 2009). Innovative educational technologies may be used

for the sake of the technologies and at the cost of the pedagogical

goals. The pedagogical model may stick with the schoolish master-

apprentice model of traditional instrumental music teaching (Bowman,

2002; Hennessy, 2001; Lehmann, Sloboda, & Woody, 2007). Last but not

least, there is a lack of longitudinal interventions studies that show the

effectiveness in using interactive music systems for learning. Studies are

often based one-shot experiences, a limited number of participants

and a lack of statistical analysis that supports the findings. Therefore,

studies are needed that take these issues into account and that pave

the path towards full-blown intervention studies.

In this paper we address these issues on the basis of our work with the

Music Paint Machine, an interactive music system that translates the

combination of music and movement into a creative visualization, i.e.

a digital painting. To avoid as much as possible the above-mentioned

pitfalls, the design and implementation of the Music Paint Machine has

been embedded in a framework that addresses pedagogy,

technology and intervention (see Fig 1.1; see also Nijs, Moens, Lesaffre

& Leman, 2012a).

<<<<<<< INSERT NIJS_Fig1_1 >>>>>>>>>>>>>

Figure 1.1. Overview of the research framework. The research unfolded through the iteration between a pedagogical, a technological and empirical component.

Goals at these three levels guided the iterative process according to

which the Music Paint Machine was designed and arrived at its current

state. Although our study does not realize a full-blown intervention

study, we believe that it contributes to that goal. In the following

sections we first shortly explain the system, then we report on our

intervention study with the Music Paint Machine.

2. The Music Paint Machine, a short introduction.

The Music Paint Machine (henceforth: MPM) is an interactive music

system that allows a musician to make a digital painting by playing

music and by making various movements on a pressure sensing

coloured mat. A detailed description is given elsewhere (Nijs et al,

2012a). Here we shortly describe the aims and features of the system.

2.1 Educational goals of the Music Paint Machine

Our overall objective is to enhance instrumental learning using the

MPM as a facilitator for creativity, understanding, and control.

Consequently, the MPM should invite learners to be playful with musical

parameters (e.g. Deliège & Wiggins, 2006; Kratus, 1991) and enhance

the occurrence of an optimal experience (e.g. Addessi & Pachet,

2005; Csikszentmihalyi, 1990; Woszczynski, Roth, & Segars, 2002). An

experimental study with the MPM has shown its potential to induce this

kind of experience (Nijs et al, 2012a, 2012b). In addition, we aim at

supporting an embodied understanding of music (e.g. Leman, 2007;

Bowman, 2004) by integrating body movement as an essential

component of musical expression and by providing a multimodal

experience in which body movement and music converge into a

common visual stimulus, i.e. the digital painting. The MPM invokes a

variety of non-instrumental movements and as such stimulates bodily

involvement. Based on the embodied music cognition paradigm

(Leman, 2007; Bowman, 2004), it is believed that this appeals to the

bodily basis of music learning. Finally, we aim at supporting the

development of an optimal relationship between musician and

musical instrument by using the combination of movement and music

to control the multimodal interaction. The design concept of the

system is based on a philosophical investigation of the musician-

instrument relationship (Nijs, Lesaffre & Leman, in press). A key

inspiration of the system is the notion of original motility and its

importance for (musical) perception (Merleau-Ponty, 1945). These

goals are reflected in the four basic features of the system.

2.2 Basic features of the Music Paint Machine

A first feature concerns the creative use of visual feedback. The system

visualizes in real-time parameters of the music that is being played as

well as how the musician moves while playing. For example, the system

can provide information on the degree to which intonation is steady

when dynamics changes (see figure 2.1).

<<<<<<< INSERT NIJS_Fig2_1 >>>>>>>>>>>>>

Figure 2.1. The system shows changes in intonation when, as exemplified in this figure, the musician plays crescendo and diminuendo.

However, the visualization of music and movement is more than mere

visual feedback on aspects of playing music. It invites users to

creatively use movement and music in order to obtain a personalized

outcome, namely the digital “painting”. Consequently, the visualization

can be considered a creative output that results from the expressive

intentions of the musician (see Fig. 2.2.).

<<<<<<< INSERT Nijs_Fig2_2 >>>>>>>>>>>>>

Figure 2.2. An example of a creative output of playing with the system

Therefore our visual feedback differs from most existing interactive

systems where visual feedback is most often in the form of symbolic

representations (see Fig. 2.3 for some examples).

<<<<<<< INSERT Nijs_Fig2_3 >>>>>>>>>>>>>

Figure 2.3. Some example of the kind of visual feedback that is used in interactive music systems. Upper left: Seeing Sound (Ferguson, 2006) - Upper right: Practice Space (Brandmeyer, Hoppe, Sadakata, et al., 2006) – Bottom left: WinsingAd (Howard, et al., 2007) – Bottom right: AMIR (Larkin, Koerselman, Ong, & Ng, 2008)

Instead the MPM provides an enactive-iconic representation of the

learner’s music and movement (Bruner, Oliver, & Greenfield, 1966).

A second feature concerns body movement as controller of the

system. This feature invites the learner to actively use the body

movements in order to generate a desired effect such as, for example,

drawing from right to left instead of drawing from left to right by

pointing left with the body. In this way, the system introduces a

variability of movement, the deployment of which is believed to

stimulate the development of body awareness and to increase

enactive -– knowledge, i.e. knowing in and through the body

(Juntunen & Westerlund, 2001). This approach to the body is related to

the idea of differential learning (Schöllhorn, 2000) and to the variability

of practice hypothesis (Schmidt, 1975). Using this approach, the system

goes beyond the corporeal dimension of merely instrumental gestures

(sound-producing and sound-facilitating; Jensenius, 2010).

A third feature concerns the adaptability to a variety of didactic

practices. The software of the MPM allows the design of all kinds of

practices to support different educational goals. For example, the

mapping from musical and movement parameters to visual

parameters can be changed. One educational goal might favour the

mapping of pitch to vertical position (e.g. matching melodic patterns),

while another educational goal might favour the mapping of pitch to

colour transparency (e.g. when the goal concerns intonation). In

addition, the range of the measured values (e.g. pitch, loudness) is

adaptable to the learners’ range of notes (see Figure 2.4) or loudness

(see Figure 2.5). At the same time, it allows challenging learners by

setting ranges that delicately exceed their ranges.

<<<<<<< INSERT Nijs_Fig2_4 >>>>>>>>>>>>>

Figure 2.4. The screen height of the Music Paint Machine’s visual output can be adapted to the player’s tessitura (range of notes).

<<<<<<< INSERT Nijs_Fig2_5 >>>>>>>>>>>>>

Figure 2.5. Ranges of in- and output can be controlled to fine-tune the system to a player's skills

As such the system allows the teacher to create a learning context that

appeals to but also challenges the current skill level of the learner.

A fourth feature concerns the control of conditions for optimal

experience, using the features defined above. These conditions are: a

balance between skills and challenge, clear goals every step of the

way and unambiguous feedback (Cszicksentmihalyi, 1990).

3. Learning to play the clarinet: An intervention study with the

MPM.

In this section we describe a study with the MPM, in which 12 children

learned to play the clarinet during nine months. The goal of the study

was to develop good practices with the MPM in the classroom. In

addition, we wanted to test the effectiveness of instruction with the

system in supporting the musical learning process.

3.1 Methods

3.1.1. Participants

Twelve children (first and second grade, six boys and six girls) and one

teacher (the researcher in this study and first author of this paper)

participated. Seven children were grade one and five children were

grade two. Most of the children’s parents were highly educated. The

researcher-teacher received formal training in music performance and

music teaching. He was a clarinet, saxophone and ensemble teacher

for fourteen years.

3.1.2. Design

This study was conducted during nine months. In order to investigate

the possible effect of instruction with the MPM, a non-equivalent

control groups design was used. Six children were non-randomly

assigned to the intervention group and received instruction with the

support of the system. A timetable was constructed to schedule the

lessons of the children in such a way that the parents’ organizational

demands were met but at the same time age and grade of the

children were as equally as possible distributed (see Table 3.1).

Table 3.1. Assignment of the children to the control or treatment group aimed at an equal distribution with regard to age and gender.

<<<<<<< INSERT Nijs_Tab3_1 >>>>>>>>>>>>>

All children were pre-tested (O) and post-tested (O). In Table 3.2, a

diagram of the experimental design is shown.

Table 3.2. Diagram of the experimental design of the study. Groups were non-randomized (NR). The study used four measurements (O) of music aptitude as dependent variable. In between the measurements, children received instrumental music instruction. The treatment group received instruction with the Music Paint Machine (X).

<<<<<<< INSERT Nijs_Tab3_2 >>>>>>>>>>>>>

It was hypothesized that instruction with the MPM (independent

variable) would enhance the development of tonal and rhythmic

discrimination skills and, as such, to the developmental tonal and

rhythmic aptitude (dependent variable) (Gordon, 1986).

3.1.3. Procedure

In this study, the researcher acted as teacher. The practical reason for

this decision concerned the difficulty to find a teacher who wanted to

work a whole year with the MPM. The substantive reason concerned

the unique position the teacher-researcher holds in order to gather,

interpret and use research-generated data about the different aspects

of teaching and learning (Regelski, 1994; Campbell, 2011).

Participants were recruited through a large-scale information

campaign in local schools. An information letter and a website were

provided with detailed information on the program, the experiment,

the enrolment procedures, practical matters (e.g. location, important

dates), the requirements (minimum attendance and participation in

data collection) to enrol for the program and the compensations

(refund of enrolment fee and reduction on the cost of the instrument)

participants would receive. There was no selection procedure. A

meeting was organized during which the necessary information was

provided so parents could make an informed decision on enrolling

their child for the program. All parents who enrolled their child signed

an informed consent.

Prior to the instruction, the parents and the children participated in a

number of pre-tests. Parents were administered three questionnaires in

which they reported on their child’s self-regulation skills (Schwarzer,

Diehl, & Schmitz, 1999), home musical environment (in-house designed)

and personality (Mervielde & De Fruyt, 1999). The children participated

in two standardized tests. One test probed the children’s music

aptitude (Primary Measure of Music Audiation; Gordon, 1986); the

other tested the children’s motor skills (M-ABC-2; Henderson, Sugden, &

Barnett, 2007).

Lessons were given once a week for a period of 9 months, with the

exception of school holiday weeks. Children attended class in groups

of three and received instruction during one hour. The first two groups

received regular instruction; the second two groups received

instruction with the Music Paint Machine. The learning content for all

groups was kept the same as much as possible. Lessons were based on

an aural approach in which the children were guided from sound to

sign on the basis of a carefully designed learning path. The children

learned to play by ear, starting from well-known children’s song. Both

improvisation and composition were an integral part of the lessons.

Throughout the nine months of instruction, several variables were

repeatedly measured. First, parents were asked to keep a log of their

child’s practice time per day and of the help they provided. Second,

at the end of each lesson, the children completed a questionnaire on

classroom experience. Third, every three months the children were

administered the music aptitude test (Gordon, 1986).

3.2 Results

3.2.1. Development of good practices

The weekly use of the Music Paint Machine has led to several good

practices with regard to the use of visual feedback and movement.

These practices can be categorized into free exploration, guided

exploration and direct instruction. Free exploration consisted of sessions

in which learners were completely free to make a digital painting.

Figure 3.1 shows some examples of digital paintings that resulted from

the free play sessions.

<<<<<<< INSERT Nijs_Fig3_1 >>>>>>>>>>>>>

Figure 3.1. Four examples of flashcards that were used in musical games to develop musical skills and to stimulate musical creativity. Some flashcards used Morse code to learn about note duration and rhythm (top left), to develop children’s emotional expression (top right), to use

movement (bottom left) or to be creative with melodic contour (bottom right).

Guided exploration was based on activities with game cards that

contained specific tasks with regard to different musical, movement

and visual parameters. In Figure 3.2, some examples of these game

cards are presented.

<<<<<<< INSERT Nijs_Fig3_2 >>>>>>>>>>>>>

Figure 3.2. Four examples of flashcards that were used in musical games to develop musical skills and to stimulate musical creativity. Some flashcards used Morse code to learn about note duration and rhythm (top left), to develop children’s emotional expression (top right), to use movement (bottom left) or to be creative with melodic contour. This exercise could be done with or without the Music Paint Machine.

Direct instruction activities consisted of consecutive sessions in which

learning content was gradually built up based on carefully designed

practices with the system. Figures 3.3, 3.4, 3.5 and 3.6 give some

examples.

<<<<<<< INSERT Nijs_Fig3_3 >>>>>>>>>>>>>

Figure 3.3. The “painting” of the MPM gives visual feedback on pitch differences (a). In this example pitch is mapped to position on the vertical axis, while duration is mapped to length on the horizontal axis. Children can try to overwrite (b) or copy (c) tonal or rhythmic patterns.

<<<<<<< INSERT Nijs_Fig3_4 >>>>>>>>>>>>>

Figure 3.4. Painting duration & rhythm: an enactive basis for symbolic representation. First students learn about long and short, then the learn how to “measure” duration, then learn rhythmic patterns and, finally, they learn about notation.

<<<<<<< INSERT Nijs_Fig3_5 >>>>>>>>>>>>>

Figure 3.5. Playing scales with the Music Paint Machine. The split screen allows comparing two paintings (e.g. visualization of scales) and finding possible mismatches as an opportunity for learning. Here the mismatch concerns the position of a semitone in a major scale. The visual pattern of the second scale (Fmaj) differs from the original (Gmaj) while it should be the same because of the specific sequence of tones and semitones in a major scale. This mismatch was a motivation to learn a new note (B♭).

<<<<<<< INSERT Nijs_Fig3_6 >>>>>>>>>>>>>

Figure 3.5. Playing scales with the Music Paint Machine. Here, each note of the scale is played as a whole note (4 beats). Using different colours per two beats, this exercise adds movement to feel the subdivision of the whole note in half notes.

3.2.2. Effectiveness of instruction with the system

The results of the PMMA pre-test show moderate scores in most groups.

In table 3.3 the mean percentile scores are presented.

Table 3.3. The mean scores and standard deviations of the PMMA pre-test.

<<<<<<< INSERT Nijs_Tab3_3 >>>>>>>>>>>>>

An initial difference exists between the control group and the

treatment group, showing a moderately higher music aptitude for the

control group. This difference is larger with regard to the rhythmical

aptitude. Standard deviations of both the control and treatment

groups are rather large, indicating the heterogeneity of the group.

Clearly, Group A stands out with a high score (80th percentile or

above) for both tonal and rhythmical tests. The standard deviation of

this group was rather small in comparison to the other groups,

indicating the homogenous nature of this group. However, a Mann-

Whitney U statistic did not reveal a significant difference between the

control and treatment group.

With regard to the development of the children’s music aptitude,

differences can be found between the control (ID = 1 to 6) and

intervention (ID = 7 to 12) groups. Table 3.4 shows the scores of both

PMMA and IMMA when categorized as low (1), average (2) or high (3).

Table 3.4. Scores of both the PMMA (regular) and IMMA (italic) transformed into three categories: low score (1; 20th percentile or lower), average score (2; between 20th and 80th percentile), high score (3; 80th percentile or higher) (3).

<<<<<<< INSERT Nijs_Tab3_4 >>>>>>>>>>>>>

In the control group, two children were administered the IMMA already

from the second test and additionally the other children from the third

test on. The sixth child of the control group also took the IMMA in the

post-test. In the experimental group, three children were administered

the PMMA throughout the whole study, which indicates that they did

not reach the 80th percentile of the PMMA (Gordon, 1986). Two

children of the treatment group took the IMMA from the third test and

one in the post-test. These results also show that children with a high

score from the beginning, except for one child (ID=3), keep scoring

high in the next tests, regardless which test (PMMA or IMMA) has been

administered. Children with a low score in the pre-test show a different

result. Some children (ID = 4,6,12) have an increased score; some

children (ID = 8,10) show a more stabilized score. At the end of the nine

months, most children (75%) were administered the IMMA test.

Although scores of the PMMA and IMMA cannot be compared, the

shift from PMMA to IMMA indicates that development music aptitude

progressed. Three children (25%) were still administered the PMMA. The

mediocre scores of the three children (all part of the treatment group)

who were administered the PMMA throughout the whole study suggest

a rather low aptitude of these three children. Yet, the high standard

deviation has to be taken into account. One of the three children had

a high score (93) for tonal aptitude. Table 3.6 shows the mean and

standard deviations of the post-test.

Table 3.5. Mean and standard deviations of the post-test. Because results of the PMMA and IMMA cannot be compared, scores are differentiated.

<<<<<<< INSERT Nijs_Tab3_5 >>>>>>>>>>>>>

To investigate the influence of possible confounding variables, a

correlation analysis was performed between the different measures

and the P/IMMA scores. Findings indicated a positive correlation

between singing behaviour and results of the tonal pre-test test,

between the personality aspect ‘perseverance and results of the tonal

pre-test, and between the personality aspect ‘concentration’ and

scores on the rhythmic pre-test. A negative correlation was found

between the personality aspects ‘anxiety’ and ‘irritability’ and the

scores for the tonal pre-test. Due to the small sample size and the

mixture of PMMA and IMMA scores in the post-test, it was not possible

to perform a correlation analysis to investigate the relationship

between the potential confounding variables (e.g. HME, personality)

and the post-test.

4 Discussion and conclusion

In this study, a specific educational technology, the Music Paint

Machine (MPM), was integrated in instrumental music instruction. The

first aim of the study was to design good practices with the system.

The weekly lesson preparations and the experience of using the system

during instruction led to different practices (free exploration, guided

exploration, direct instruction) that were carefully designed in function

of specific learning goals. They were tested and refined throughout the

study.

The second aim of this study was to investigate whether instruction with

the system could positively influence the developmental music

aptitude of the children. It was hypothesized that providing instruction

with the MPM would contribute to the establishment of a rich musical

environment in which the development of music aptitude can be

stimulated. We used the PMMA and IMMA (Gordon, 1986) to measure

music aptitude. Although for most children a progress in the scores was

found, some children’s scores showed a fluctuating effect and one

child’s score even degraded continuously. No significant differences

between the control and intervention group were found. However, in

line with a study by Tai (2010) results suggested that singing behaviour

has an effect on the scores of the PMMA. Results also suggested a

relationship between facets of personality (e.g. concentration,

perseverance) and the PMMA score. Personality has been linked

before to music aptitude, in particular to Cattell’s personality factor

intelligence (Schleuter, 1972). We believe that these results shed light

on the occurrence of variables that might influence the scores on the

aptitude test and as such urge caution with regard to the

interpretation of its results. Another point of attention with regard to the

use of these tests is the fact that results of the PMMA and IMMA cannot

be compared (Gordon, 1986). Because most students progressed

towards a PMMA score above the 80th percentile, they needed to do

the IMMA as post-test instead of the PMMA. As such and because of

the limited number of participants, it was not possible to perform a

correlation analysis to investigate the relationship between the

potential confounding variables (e.g. HME, personality) and the scores

for musical aptitude. Therefore, it remains inconclusive whether the

changes that occurred in the children’s scores are due to instruction

with the MPM. Further investigations are needed and the choice of the

dependent variable and the instrument to measure it needs to be

reconsidered.

Next to the limitations with regard to measuring the dependent

variable, this study had other limitations. One limitation concerned the

use of the system. Students were not able to use it at home. Arguably

this affected the results. Being able to use the system at home might

reinforce its influence on the development of music aptitude. A second

limitation was the limited number of participants (n = 12). This affected

statistical power. Nevertheless, we believe that working towards a full-

blown intervention study was worth the effort. A third limitation

concerned the system itself, which is a proto-type and sometimes

didn’t work as expected. However, besides these limitations, the

presented study has provided several insights and outcomes that are

important for further research.

First, conducting the study led to insights with regard to the focus of the

study (effectiveness of the technology) and to the adopted method

(design, measures). It became clear that it is necessary to focus on the

transformative impact of technology (see also: Beckstead, 2001;

Kiesler, 1992). It also became clear that the control group design has

many benefits in educational technology research but needs to be

conducted in function of investigating processes (transformative

impact) and not only products (amplicative impact).

Second, didactic practices have been designed that can be used to

conduct future experiments. These practices are further developed in

collaboration with other teachers through currently ongoing follow up

studies. The further development of the MPM’s software will entail the

design of ready-to-use modules based on these practices.

Third, in this study video footage of all lessons (132 hrs) was made. A

follow up observational study will be conducted in order to

complement current data. This will allow studying how the integration

of an educational technology such as the MPM affects the different

components of instruction, i.e. student behaviour, teacher behaviour,

student-teacher interaction and materials (Kennel, 2002). It is expected

that different behavioural measures will also provide insights on the

results of the repeated measurers used in this study.

To conclude, this study investigated the integration of an educational

technology in a naturalistic instrumental music classroom setting.

Although we knew in advance that the limited amount of children

participating in this study (due to all kinds of practical concerns) could

not be considered to be representative for our statistical tests, we

believe that our study went a step further than the lab experiments that

are more commonly in this research domain. Dealing with the

complexity of a real-life educational setting and with the requirements

of the quasi-experimental design, this study has provided insights on

methodology (design, measures, analysis) in music educational

technology research. We believe that our approach holds a promising

potential to conduct ecologically valid music education intervention

studies.

ACKNOWLEDGMENTS

This work is part of the EmcoMetecca Project (Leman, 2007) supported by the Flemish

Government (http://www.ipem.ugent.be/EmcoMetecca). The authors wish to thank

their IPEM colleagues Ivan Schepers and drs. Bart Moens. Also many thanks to the

children and their parents for participating in this study.

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