A Study on the Innovative Application of Multimedia Technology in Piano Teaching and Students’ Acceptance

In the traditional piano teaching mode, teachers mostly take teaching measures such as centralized explanation of theoretical knowledge and a large number of repetitive exercises, and students are often in the state of passive learning and passive training. This boring learning mode will make students gradually lose interest in learning piano [1]. And this mode of teaching is difficult to make students understand the art form of the piano in depth, students are more often appreciate the connotation of the piano works of art is not deep enough, the use of piano knowledge, skills to create a lack of innovation and many other problems, the effective development of piano teaching will have a greater negative impact [2].

However, in the context of the information age, the multimedia teaching technology represented by microclasses makes the teaching situation more vivid, and breaks the limitation of teaching in time and space. First of all, multimedia technology can stimulate students’ interest in learning, which not only injects new vitality into the traditional piano teaching, but also vividly presents the multiple dimensions of music, thus triggering students’ strong interest [3]. Secondly, multimedia technology can increase the interest of classroom teaching, which presents audio materials that can broaden students’ musical horizons, stimulate students’ interest in different styles and playing techniques, so that learning is no longer a single technical training, but a musical journey of exploration [4-5]. In addition, multimedia technology can help students master the piano playing skills, which provides students with a large number of piano playing videos and music demonstrations, which is not only conducive to the development of students’ perception of music, but also allows students to better master the organic combination of skills and performance, and improve the artistry of performance [6-7]. Finally, multimedia technology can cultivate students’ creative ability, and the rich music materials inspire students to explore the innovative combinations of different musical elements and expressions, thus cultivating students’ pluralistic understanding of music and independent aesthetic point of view. It can be said that the use of multimedia technology for piano teaching has become an important means [8-9].

The use of multimedia technology in piano teaching has the important role of enhancing the effectiveness of piano teaching and improving students’ piano artistic literacy, as well as further promoting the innovative development of piano teaching. Literature [10] that modern technology can help students to acquire useful music knowledge in a short time, the use of the developed applications can help to realize the ability to process sound, rhythm, hearing, transformed the music learning system, and improve the quality of piano and vocal training teaching. Literature [11] points out that the combination of modern technology and music teaching practice is very important in piano teaching and explores ways to introduce modern technology in piano teaching to improve the effectiveness of piano teaching, one of which is to increase the interactivity of group lessons and the other is to broaden the scope of individual learning. Literature [12] introduces complex network and multimedia technology in piano teaching cases, so as to design a typical network teaching case in line with modern learning theory, teaching requirements and characteristics of the piano discipline, to provide reference for piano teachers, and the study proves that multimedia and network technology provide a better auxiliary role for piano teaching and playing. Literature [13] based on K-means algorithm design load capacity, build multimedia network shared classroom, through the creation of piano music situation mobilize students music emotion, stimulate students’ learning interest, guide students’ knowledge extension, comprehensively improve students’ aesthetic ability and independent learning ability. Literature [14] evaluated the impact of mobile applications on students’ perception of music education, designed an application to help students improve their piano music score reading skills, verified the effectiveness of the designed program through experiments, and provided insights for the development of music education in the interactive teaching mode and self-learning mode. Literature [15] shows that piano teaching needs to have artistic characteristics and performance atmosphere, so the video image teaching method is integrated into piano teaching, and convolutional neural network is used to analyze the relevant features of piano teaching videos and images, and innovate the piano teaching mode. Literature [16] explored the possibility and effectiveness of distance piano teaching based on online learning applications, and developed three modules in online piano course teaching to improve students’ theoretical learning efficiency and technical performance skills. Literature [17] explored the innovation of multimedia and neural network technology on piano teaching mode, based on which piano online teaching will break the traditional forms of school, social and family music education, and utilize a variety of piano online applications to realize the transformation of modern music education. Literature [18] describes the integration of intelligent piano and piano teaching implementation path, taking piano timbre teaching as an example, proposes a kind of audio synthesis model with editable timbre, and designs a piano timbre library generation system based on the music analysis model and synthesis model, and experiments show that the proposed intelligent piano teaching mode effectively makes up for the limitations of traditional piano teaching.

Relying on multimedia technology to design piano learning evaluation software, it provides a strong guarantee for the continuous innovative development of teaching by providing important learning feedback. Literature [19] emphasized the use of computer multimedia software for piano teaching as a feasible method to alleviate the strain on piano education resources, and the establishment of a neural network model for evaluating piano playing can identify problems in computer piano teaching and improve the quality of teaching. Literature [20] studied the automatic evaluation method of piano playing to standardize music performance, using support vector machine, plain Bayes, convolutional neural network and long and short-term memory network methods respectively, to analyze the piano sound of different articulation types, and the experimental results show that the classification accuracy of convolutional neural network is higher. Literature [21] constructed a machine learning model for assessing the potential relevance of piano teaching, combined the association rule mining technique with the improved t-test method, proposed a new association rule metric and the degree of influence, and found that the evaluation data of multimedia-assisted piano teaching is potentially relevant.

Based on the advantages of multimedia technology and its application dilemmas, this paper designed a strategy for the innovative application of multimedia technology in piano teaching, and based on the two-sample t-test method and the Kano model, it evaluated the implementation effect of the strategy and the acceptance of students. Firstly, independent samples t-test was used to test the difference between the experimental group and the control group in the pre-test and post-test of the experiment, while paired samples t-test was used to analyze the difference between the two groups before and after the experiment. The Kano questionnaire was designed to analyze students’ acceptance of the multimedia innovation strategies designed in this paper from two perspectives: different majors and different grades.

2

Innovative application strategy design of multimedia technology in piano teaching

2.1

The advantages of multimedia technology applied to piano teaching

In the traditional piano teaching mode, teachers focus on theoretical knowledge, a large number of repetitive exercises and other teaching measures, students are often in the state of passive learning, passive training, which is not conducive to the cultivation of students’ interest and in-depth understanding of the connotation of piano works. In the context of the information age, multimedia technology has gradually been widely used in piano teaching, which has the following advantages compared to traditional teaching modes: 1)

Enhance the effectiveness of piano teaching

Through the effective use of multimedia technology, teachers can select and integrate high-quality teaching resources in the network, combined with music creation and other specific teaching needs and animation, audio and other forms of construction of vivid images and very interesting teaching situations, piano playing skills and other teaching content more intuitive and accurate to show to the students, so as to effectively stimulate the students’ interest in learning, mobilize the students’ motivation to learn, and enhance the effectiveness of piano teaching. Effectiveness.

2)

Enhance students’ aesthetic ability

Through the effective use of multimedia technology, teachers can create a more intuitive and highly infectious appreciation of the situation for students, while also a more vivid image of the artistic expression of piano knowledge. Students can thus deeply understand the piano art form, and accurately understand and capture the emotion and ideological connotation of the work, expression and other basic content, appreciation, creativity and then effectively enhance their own overall development is also realized.

3)

Meet students’ individualized learning and after-school practice needs

On the one hand, the foundation of each student is different, and the ability level is also different. On the other hand, practice is an important goal of piano teaching, and practical ability is also an essential quality of students, which is a neglected teaching module under the traditional teaching mode. Through the effective integration of multimedia technology, after class, students can carry out multiple learning activities such as pre-study, consolidation and practice expansion according to their own foundation through piano learning APP or micro-lesson videos designed by teachers, and they can control the learning progress independently, so that the personalized learning needs of students can be effectively met and the further development of piano teaching can be realized.

2.2

Major Dilemmas Facing Multimedia Piano Teaching in Colleges and Universities

The traditional piano teaching mode has some limitations that restrict the use of multimedia technology in piano teaching at colleges and universities. In the existing multimedia piano teaching in colleges and universities, the following dilemmas are mainly faced: 1)

Unclear teaching objectives

Undefined teaching objectives can lead to confusion in the classroom teaching process. If the teacher fails to clearly plan the teaching content, tasks and activities, and determine the teaching evaluation criteria, students will feel lost in their learning, and will not be able to effectively integrate and apply what they have learned. In this case, teaching activities become fragmented and it is difficult to form a systematic learning experience, which affects students’ deep understanding of knowledge and the cultivation of application ability.

2)

Teaching design needs to be optimized

The urgent need for optimizing teaching design is mainly reflected in the following two aspects:

On the one hand, the teaching design is too rigid. The lack of flexibility in teaching design leads to insufficient support for students’ individualization, which affects their interest and participation in learning. Optimizing instructional design requires taking into account diversity and differences to better address students’ learning characteristics.

On the other hand, the instructional design lacks practicality and interactivity. If the teaching design favors theory and lacks practical application and practice, it is difficult for students to translate what they have learned into practical abilities. The lack of interactivity reduces students’ participation, thus affecting their learning experience. The optimization of teaching design should emphasize the combination of theory and practice, with a focus on interaction and cooperation, in order to promote the overall development of students.

3)

Students’ low interest in piano learning

First of all, students have a negative attitude in the classroom and lack positive engagement and initiative. This negative attitude comes from lack of knowledge of the piano learning content or frustration with the learning process.

In addition, there is a decrease in motivation to learn and a disinclination to actively participate in practice and classroom activities. This is reflected in the decrease in after-class practice and the lack of interest in improving their skills. Students felt that learning piano had become dull and boring, leading to a loss of enthusiasm for music and resulting in a loss of motivation.

Finally, students’ progress slows down and stagnation in technique and repertoire occurs. The decline in learning interest is also manifested in students’ learning of new repertoire. Students steer clear of challenging repertoire and opt for repertoire that involves new techniques and complex syllabic structures.

4)

Piano classroom needs to be expanded urgently

The existing multimedia piano teaching needs to be expanded in terms of classroom content and form. First of all, the classroom content focuses too much on technique and music theory, and ignores the history, cultural background, and artistic understanding of music. Secondly, the classroom format is too traditional and lacks innovation and interactivity. Finally, the piano class focuses too much on solo performance and ignores the importance of ensemble performance and collaboration.

5)

Students’ poor understanding of the work

Firstly, students demonstrate mechanization in the process of playing and lack of understanding of the inner emotions and expression of musical works.

Secondly, students did not know enough about the historical and cultural background of the works and lacked a comprehensive understanding of the meaning of the works, thus they could not really understand the deeper connotation of the works, and their performance lacked depth and emotional commitment.

Thirdly, students lack a good understanding of the technical requirements of the piece, resulting in a lack of depth in their performance.

2.3

Innovative Application Strategies of Multimedia Technology in Piano Teaching

In order to overcome the realistic dilemma of implementing multimedia technology in piano teaching, this paper proposes an innovative application strategy that capitalizes on the advantages of multimedia technology, as demonstrated below: 1)

Virtual Piano Classroom

Multimedia technology has made piano teaching no longer subject to geographical constraints. Students can participate in a virtual piano classroom through the network, interact with students and teachers around the world. The use of this teaching method not only broadens students’ horizons, but also allows them to access more diverse teaching resources.

2)

Digital sheet music and automatic accompaniment

The appearance of digitized sheet music makes it possible for students to view sheet music through the computer anytime and anywhere, which greatly improves the convenience of learning. The automatic accompaniment function can also provide students with real-time accompaniment to aid in their understanding of rhythm and melody.

3)

Interactive Teaching Software

Interactive teaching software presents complex music theory knowledge and playing skills to students in a more intuitive way through animation, video, and audio. The software typically has practice modules and assessment systems that give personalized feedback and suggestions based on the student’s performance.

4)

Virtual Reality and Augmented Reality

Virtual Reality (VR) and Augmented Reality (AR) technologies provide students with an immersive piano learning experience. By wearing a VR helmet or AR glasses, students can immerse themselves in a virtual concert hall, interact with virtual musicians, and even participate in virtual music creation and performance.

3

Multimedia Piano Teaching Evaluation Model

This paper utilizes independent and paired samples t-tests to test the effectiveness of the designed innovative application strategy and to assess students’ acceptance of the strategy based on Kano’s model.

3.1

Assessment of teaching effectiveness based on two-sample t-tests

3.1.1

Two-sample t-test

Hypothesis testing (also known as significance testing) is an important statistical test. The method first makes some reasonable assumptions about the analyzed specimen, and then analyzes the sample to determine its validity. Hypothesis testing is divided into parametric and non-parametric tests depending on whether the overall distribution is known. When the overall distribution is known (e.g., normal distribution), the parameters included in the overall situation is called parametric testing. When the overall distribution is unknown, it is a non-parametric test.

The two-sample t-test, a common hypothesis test, is parametric and can be divided into two forms: the independent sample t-test and the paired sample t-test.

3.1.2

Independent samples t-test

The aim of the two independent samples t-test is to determine if there is a significant difference between the mean values of two totals by analyzing independent samples from both totals [22]. The original hypothesis of the two-sample t-test is that there is no significant difference between the means of the two totals. This test is usually performed in two steps: 1)

The homogeneity of the overall variance of the 2 sets of data is determined using the F-test.

2)

Based on the judgment of the homogeneity of variance, the t-statistic and the formula for calculating the degrees of freedom are decided, and then the results of the t-test are given an appropriate judgment.

The two independent samples t-test assumes that the overall means represented by the two samples follow normal distributions N(μ_l,σ_l) and N(μ₂,σ₂). If the two overall variances are equal $(σ_{1}^{2} = σ_{2}^{2})$ , i.e., the variances are chi-square, the t test is used. If the two overall variances are not equal, the t' test may be used.

F-test for chi-squaredness of two aggregates: 1 $F = \frac{S_{2}^{1} (b i g)}{S_{2}^{2} (s m a l l)}, ν_{1} = n_{1} - 1, ν_{2} = n_{2} - 1$

F values obey a F distribution with v₁ = n₁–1,v₂ = n₂–1 degrees of freedom, determine the probability P corresponding to the F values, and if P>0.05, indicate that the variances are chi-square use the t test. If P<0.05, the variance is not chi-square, use the t' test of approximation test.

1)

When the two overall variances are equal, use the t test, and because of $σ_{1}^{2} = σ_{2}^{2}$ , the two sample variances can be combined to find the common variance $S_{c}^{2}$ of the two. That is: 2 $S_{C}^{2} = \frac{(n_{1} - 1) S_{1}^{2} + (n_{2} - 1) S_{2}^{2}}{n_{1} + n_{2} - 2}$ 3 $t = \frac{{\bar{X}}_{1} - {\bar{X}}_{2}}{\sqrt{S_{C}^{2} (\frac{1}{n_{1}} + \frac{1}{n_{2}})}}, v = n_{1} + n_{2} - 2$

2)

When the overall variances are not equal, a corrected t test is used, i.e., a t' test: 4 $t^{'} = \frac{{\bar{X}}_{1} - {\bar{X}}_{2}}{\sqrt{\frac{S_{1}}{n_{1}} + \frac{S_{2}}{n_{2}}}}, (v_{1} = n_{1} - 1, v_{2} = n_{2} - 1)$

Satterthwaite’s method for degrees of freedom correction at t = t': 5 $ν = \frac{{(S_{{\bar{X}}_{1}}^{2} + S_{{\bar{X}}_{2}}^{2})}^{2}}{\frac{S_{{\bar{X}}_{1}}^{4}}{n_{1} - 1} + \frac{S_{{\bar{X}}_{2}}^{4}}{n_{2} - 1}} = \frac{{(\frac{S_{1}^{2}}{n_{1}} + \frac{S_{2}^{2}}{n_{2}})}^{2}}{\frac{{(\frac{S_{1}}{n_{1}})}^{2}}{n_{1} - 1} + \frac{{(\frac{S_{2}}{n_{2}})}^{2}}{n_{2} - 1}}$

3.1.3

Paired samples t-test

In order to compare whether there is a significant difference between the two methods, a comparison test is usually done under the same conditions to obtain 2 sets of paired test values, which are often correlated, and then the 2 sets of test values are analyzed to make statistical inferences. The t-statistic is utilized in hypothesis testing, hence the name paired-sample t-test [23].

Let x₁,x₁₂,⋯,x_n and x₂,x₂₂,⋯x_2n be random samples from 2 independent distributions x₁,x₂ respectively. Let d = X₁–X₂, the corresponding sample difference be d_i = X_1i–X_2i(i = 1,2,…,n) such that if the difference between the x₁,x₂ samples is small, then it can be assumed that d₁,d₂,⋯⋯,d_n it obeys a normal distribution N(μ_d,σ²) with mean zero.

Original hypothesis: H₀ : μ_d = 0 (i.e., the data between the two samples are considered not significantly different).

Alternative hypothesis: H₀ : μ_d ≠ O (i.e. the data between the two samples are considered to be significantly different).

The formula for the test statistic is as follows: 6 $t = \frac{\bar{d}}{\frac{S_{n}}{\sqrt{n}}}$

In Equation (6), $\bar{d}$ is the mean of d,d₂,⋯,d_i, n is the number of samples, S_n is the standard deviation of d₁,d₂,⋯,d_i. $\bar{d}$ ,S_n is calculated according to equations (7) to (8): 7 $\bar{d} = \frac{\sum_{i = 1}^{n} d_{i}}{n}$ 8 $S_{n} = \sqrt{\frac{1}{n - 1} \sum_{i = 1}^{n} {(d_{i} - \bar{d})}^{2}}$

When hypothesis H₀ holds, the t statistic conforms to a t distribution with (n–1) degrees of freedom.

For a given level of significance α(0<α<1), the critical value of the test t_α/2(n–1) can be obtained by looking up the t distribution table, such that P{|t|≥t_α/2(n–1)} = α, if |t|≥t_α/2(n–1), it is rejected H₀ and a significant difference is considered to exist between the two samples. Otherwise, it is considered that there is no significant difference between the two samples.

In the statistical analysis software currently in use, the difference between the two groups of samples is usually calculated, and the corresponding data are substituted into the formula (6) to calculate the test statistic and the corresponding probability P-value, and if the P-value is less than a given level of significance, the original hypothesis is rejected, otherwise the original hypothesis is accepted.

3.2

Student Acceptance Assessment Based on Kano Modeling

3.2.1

Kano Model Principles and Applications

Kano model is used to quantify the level of service quality and user satisfaction and to explore the relationship between different types of service quality characteristics and user satisfaction [24]. In this paper, the Kano model is used to explore students’ acceptance (satisfaction) of the designed innovative multimedia teaching strategy for piano.

The Kano model is schematically shown in Figure 1, which categorizes quality characteristics into five types: 1)

Basic quality, also known as must-have quality, is the user’s basic requirement for the product or service provided. When this requirement is fulfilled, user satisfaction will not increase, but if this type of service is missing, user satisfaction will decrease.

2)

Desired quality, also known as willingness-type quality. If the desired quality characteristics are met, user satisfaction increases dramatically, and this improvement is obtained through mutual efforts. When users’ desired quality characteristics are not met, their satisfaction will plummet.

3)

Charming quality, also known as excitement quality, is the quality of service that is not expected by users. When charismatic quality characteristics are met, user satisfaction will continue to increase. When charismatic qualities are not met, user satisfaction is not greatly affected.

4)

Non-differentiated quality, also known as irrelevant quality, whether or not this quality can be satisfied, for the user is “no pain, no gain”, which has no impact on user satisfaction.

5)

Reverse quality. Reverse quality refers to the majority of users do not have this need, when the provision of this quality, will cause strong dissatisfaction of the user, while the user’s satisfaction will also fall sharply, that is, the degree of provision and user satisfaction is inversely proportional to the degree.

3.2.2

Better-Worse coefficient method

The traditional Kano model is easy to form the thinking stereotype of frequency maximization, forming the judgment standard of basic demand (M) > expectation demand (O) > charm demand (A), ignoring the role of other frequencies, which makes the use of the model will produce errors in the results. By improving the limitations of the traditional Kano model, related scholars have proposed the Better-Worse coefficient as shown in Figure 2, which applies user satisfaction in the form of a formula. Its calculation formula is: 9 $B e t t e r = (A + O) / (A + O + M + I)$ 10 $W o r s e = - 1 \times (O + M) / (A + O + M + I)$

In this coordinate diagram, the horizontal coordinate is the Better coefficient and the vertical coordinate is the Worse coefficient, in which the first, second, third and fourth quadrants are the Expected needs (O), Must-have needs (M), Undifferentiated needs (I), and Attractive needs (A), and the degree of prioritization of the needs is ranked as M>O>A>I.

4

Effectiveness evaluation of innovative application strategies of multimedia technology

4.1

Controlled experiments for teaching

In this paper, a teaching control experiment was designed using the experimental control method in order to investigate the differences between the piano teaching mode based on the innovative application strategy of multimedia technology in this paper and the traditional piano multimedia teaching mode in terms of teaching effect. Students majoring in music at the University of H were selected as research subjects, totaling 60 students, including 24 female students and 36 male students. Students were randomly assigned to the experimental and control groups to ensure a balanced gender distribution and number of participants in both groups. The experimental group adopted the teaching method of this paper, while the control group adopted the traditional teaching method. The teaching experiment lasted 16 weeks.

In order to ensure the objectivity and accuracy of the experimental results, the experimental class and the control class were highly consistent in terms of the key elements such as the teacher, teaching content, teaching duration and teaching sequence. At the same time, all the assessment contents of the two classes will be synchronized in random order.

4.1.1

Comparative analysis of pre-laboratory piano expertise

Before the experiment, this study conducted a comprehensive piano professional ability test for the students in the two groups participating in the experiment to ensure the fairness and accuracy of the experiment. The test included items such as music theory knowledge, score reading ability, basic piano skills, and performance techniques, and the full score for each item was 30 points.Table 1 displays the descriptive statistical results of the scores of each current test.

Table 1.

Descriptive statistics of pre-test scores

Project	Group	Number	Mean value	Standard deviation	Standard error mean
Musical knowledge	Experimental group	30	18.41	4.037	0.630
Musical knowledge	Control group	30	18.23	3.615	0.565
Spectrum recognition ability	Experimental group	30	19.03	5.258	0.821
Spectrum recognition ability	Control group	30	18.92	5.049	0.789
Basic piano skills	Experimental group	30	15.69	2.654	0.414
Basic piano skills	Control group	30	16.12	2.733	0.427
Performance techniques	Experimental group	30	17.38	3.125	0.488
Performance techniques	Control group	30	16.85	3.346	0.523

As can be seen from Table 1, each of the experimental and control groups had 30 students who participated in the pre-test piano professional ability test, and both groups had the highest average scores in the music theory literacy program, which were 19.03 and 18.92 respectively, with the corresponding standard deviations of 5.258 and 5.049 respectively, while in the basic piano skills program, the experimental group and the control group had the lowest average scores, which were 15.69 and 16.12 respectively. Overall, in the Piano Professional Competence Test, which is comprised of 30 points, the average scores of students in both groups are below 20 points, which is low enough to facilitate the teaching experiment.

In order to compare the difference between the two groups of preexperimental scores, independent samples t-test was used to analyze the pre-test data of the two groups, and the results of the independent samples t-test of the experimental pre-test are shown in Table 2.

Table 2.

Independent sample T test results before the experiment

Project	Levin variance equivalence test				Average equivalent T test
	Assumption	F	Sig.	t	df	Sig.(2-tailed)	Mean difference	Std. error difference	95% CI
	Assumption	F	Sig.	t	df	Sig.(2-tailed)	Mean difference	Std. error difference	Lower limit	Upper limit
Musical knowledge	Equal variances	0.157	0.726	0.564	58	0.712	0.674	1.526	-3.327	2.145
Musical knowledge	Unequal variances			0.564	57.865	0.712	0.674	1.526	-3.327	2.145
Spectrum recognition ability	Equal variances	0.255	0.994	0.492	58	0.935	0.569	1.358	-3.641	2.412
Spectrum recognition ability	Unequal variances			0.492	57.907	0.935	0.569	1.358	-3.641	2.412
Basic piano skills	Equal variances	1.556	0.212	-0.767	58	0.159	-1.164	1.505	-1.862	3.826
Basic piano skills	Unequal variances			-0.767	57.643	0.159	-1.164	1.505	-1.862	3.826
Performance techniques	Equal variances	0.004	0.945	1.673	58	0.163	1.525	0.758	-0.019	2.832
Performance techniques	Unequal variances			1.673	57.794	0.163	1.525	0.758	-0.019	2.832

As can be seen from Table 2, the Sig.(2-tailed) values in the four dimensions of music theory knowledge, music literacy, basic piano skills and performance techniques are 0.712, 0.935, 0.159, 0.163, respectively, which are greater than the standard value of 0.05. It indicates that there is no significant difference between the scores of the experimental group and the control group in the various dimensions in the piano professional competence before carrying out the teaching experiments, that is, the The selected samples are homogeneous and meet the requirements of the experiment.

4.1.2

Comparison of piano professional ability of the experimental group before and after the experiment

In order to compare whether there is a significant difference between the students in the experimental group after the experiment and before the experiment in terms of piano professional ability, a paired-sample t-test was conducted on the experimental data, and the paired-sample t-test results of the experimental group before and after the experiment are shown in Table 3.

Table 3.

T test results of paired samples in the experimental group

Project	Experimental group(M±SD)		t	P
Project	Before the experiment	After the experiment	t	P
Musical knowledge	18.41±4.037	27.23±2.598	-2.953	0.000
Spectrum recognition ability	19.03±5.258	26.25±3.124	-2.431	0.004
Basic piano skills	15.69±2.654	22.34±4.986	-2.354	0.011
Performance techniques	17.38±3.125	23.16±5.312	-2.069	0.024

As can be seen from Table 3, the p-values of the paired samples t-test of the performance of the experimental group before the experiment and the experimental group after the experiment in the four items of music theory knowledge, music reading ability, basic piano skills and performance techniques are 0.000, 0.004, 0.011 and 0.024 respectively, all of which are less than 0.05, and there is a significant difference. Among them, the music theory knowledge dimension showed the largest increase, with an average score increase of 8.82 points, which was very significantly different from both the score recognition ability dimension (P<0.01). It can be seen that the teaching mode based on the innovative application strategy of multimedia technology offers significant advantages in multimedia piano teaching. It not only fully mobilizes students’ enthusiasm and stimulates their love for piano art, but also significantly improves their piano professional skills.

4.1.3

Comparison of piano expertise in the control group before and after the experiment

At the same time, in order to prove the superiority of the teaching mode of this paper compared with the traditional teaching mode, a paired-sample t-test was conducted on the piano professional ability of the control group students before and after the experiment, and the results of the paired-sample t-test for the control group are shown in Table 4.

Table 4.

T test results of paired samples in the control group

Project	Control group(M±SD)		t	P
Project	Before the experiment	After the experiment	t	P
Musical knowledge	18.23±3.615	23.36±3.417	-2.145	0.035
Spectrum recognition ability	18.92±5.049	22.15±4.058	-2.014	0.042
Basic piano skills	16.12±2.733	19.41±3.874	-1.926	0.052
Performance techniques	16.85±3.346	18.53±4.562	-1.899	0.071

Table 4 shows that before and after the teaching experiment, there are significant differences between the control group in the two dimensions of music theory knowledge and score recognition ability (P<0.05), while there are no significant differences in the basic piano skills and performance techniques (P>0.05). This indicates that the traditional multimedia teaching mode adopted by the control group improved the students’ abilities mainly in the aspect of theoretical knowledge, but less in the aspect of practical skills. Among them, the greatest improvement was in the knowledge of music theory, which increased by 5.13 points, a significant increase.

4.1.4

Comparative Analysis of Piano Professional Competence after Experimentation

In order to further test the teaching effect of the piano multimedia teaching mode in this paper, at the end of the experiment, the two groups were post-tested for piano professional ability, and the results of the independent sample t-test of the experimental post-test are shown in Table 5.

Table 5.

Independent sample T test results after the experiment

Project	Levin variance equivalence test				Average equivalent T test
	Assumption	F	Sig.	t	df	Sig.(2-tailed)	Mean difference	Std. error difference	95% CI
	Assumption	F	Sig.	t	df	Sig.(2-tailed)	Mean difference	Std. error difference	Lower limit	Upper limit
Musical knowledge	Equal variances	8.364	0.005	2.423	58	0.037	2.083	1.128	-4.245	-0.356
Musical knowledge	Unequal variances			2.423	57.796	0.037	2.083	1.128	-4.245	-0.356
Spectrum recognition ability	Equal variances	4.235	0.346	0.849	58	0.024	3.042	1.464	-5.273	-2.268
Spectrum recognition ability	Unequal variances			0.849	57.754	0.024	3.042	1.464	-5.273	-2.268
Basic piano skills	Equal variances	6.147	0.027	1.526	58	0.042	1.954	1.441	-3.252	-1.981
Basic piano skills	Unequal variances			1.526	57.934	0.042	1.954	1.441	-3.252	-1.981
Performance techniques	Equal variances	2.517	0.521	1.828	58	0.028	1.616	0.947	-2.326	-1.722
Performance techniques	Unequal variances			1.828	57.673	0.028	1.616	0.947	-2.326	-1.722

As can be seen from Table 5, there are significant differences between the experimental group and the control group in the four dimensions of piano professional ability: music theory knowledge, music reading ability, basic piano skills and performance techniques (P<0.05). Combined with Table 3 and Table 4, it can be seen that the increase of each dimension in the experimental group is greater than that of the control group, which indicates that the piano teaching mode based on the innovative application strategy of multimedia proposed in this paper is significantly better than the traditional multimedia teaching mode, and has a better teaching effect in improving the students’ professional competence in piano.

4.2

Analysis of student acceptance

In this paper, Kano’s model was used to study students’ acceptance and satisfaction with innovative multimedia application strategies in piano teaching, aiming to find out whether the new teaching mode can be quickly trusted and willingly used by students.

4.2.1

Kano model questionnaire design

This part of the questionnaire was set up for students majoring in music at the University of H. The sample size was enlarged by random sampling to include 60 students in the teaching experiment, including students from all grades in the four majors of Piano Performance, Music Education, Piano Accompaniment, and Musicology. Respondents were first asked to answer some basic information questions, as well as the purpose and frequency of their piano studies, in order to categorize students according to different criteria. Next, they filled out a questionnaire about their acceptance and satisfaction with four innovative multimedia applications for piano teaching: virtual piano classroom, digitized sheet music with automatic accompaniment, interactive teaching software, and virtual reality and augmented reality technologies. All questions were asked using the Kano method in a positive and negative way, with five levels of options, namely “liked it a lot” “deserved it” “didn’t care” “Barely accept” and “Dislike it a lot” for the students to rate. The basic information of the interviewed students is shown in Table 6.

Table 6.

Student basic information statistics

Primary dimension	Secondary dimension	Frequency	Proportion
Gender	Male	112	34.78%
Gender	Female	210	65.22%
Majors	Piano performance	76	23.60%
	Musical education	84	26.09%
	Piano accompaniment	72	22.36%
	Musicology	90	27.95%
Grade	Freshman	112	34.78%
	Sophomore	90	27.95%
	Junior year	78	24.22%
	Senior four	42	13.05%
Attitude towards the course	Highly valued	176	54.66%
	No taken seriously	20	6.21%
	Generally valued	126	39.13%

Table 6 shows that the overall proportion of female students among the interviewed students was higher, at 65.22%. Students majoring in the four categories of Piano Performance, Music Education, Piano Accompaniment, and Musicology accounted for 23.60%, 26.09%, 22.36%, and 27.95% respectively, which is a relatively even classification of majors. The number of freshmen, sophomores, juniors and seniors were arranged in descending order, accounting for 34.78%, 27.95%, 24.22% and 13.05% respectively. In terms of teaching effectiveness, lower grades begin with weaker piano proficiency, and the teaching effect is more noticeable, thus the sample selection is more reasonable. As for the importance attached to the course, those who attached great importance and general importance accounted for 54.66% and 39.13% respectively, and those who did not attach importance only accounted for 6.21%, which made the selection more reasonable.

A total of 360 questionnaires were distributed and 344 questionnaires were recovered. Including suspicious results and invalid questionnaires, 322 valid questionnaires were obtained, with an effective recovery rate of 89.4%. The results of the questionnaire were statistically analyzed in this paper using SPSS software. Considering the Cronbach’s α coefficient, the forward questionnaire is 0.916, and the reverse questionnaire is 0.964, which are higher than 0.8, and the questionnaire reliability is good. Considering the KMO value, the forward questionnaire was 0.915 and the reverse questionnaire was 0.932. The significance of the Bartlett’s ball test was 0.000 in both cases, and the validity of the questionnaire was good.

4.2.2

Statistical results based on KANO modeling

Applying the Kano model analysis method to identify the students’ acceptance of innovative multimedia application strategies in this paper, it was found that students in different majors accepted them as shown in Table 7.

Table 7.

Acceptance of different professional students

Application mode	Majors	Demand attribute				SI	DSI
Application mode	Majors	M	O	A	I	SI	DSI
Virtual piano classroom	Piano performance	25	29	16	6	0.59	-0.71
	Musical education	23	36	21	4	0.68	-0.71
	Piano accompaniment	24	25	17	6	0.58	-0.68
	Musicology	25	41	19	5	0.67	-0.73
Digital sheet music & automatic accompaniment	Piano performance	18	21	33	4	0.71	-0.51
	Musical education	29	38	12	5	0.60	-0.80
	Piano accompaniment	14	34	22	2	0.78	-0.67
	Musicology	25	44	17	4	0.68	-0.77
Interactive teaching software	Piano performance	15	39	19	3	0.76	-0.71
	Musical education	18	42	19	5	0.73	-0.71
	Piano accompaniment	16	20	32	4	0.72	-0.50
	Musicology	14	27	40	9	0.74	-0.46
VR & AR	Piano performance	12	38	20	6	0.76	-0.66
	Musical education	9	32	41	2	0.87	-0.49
	Piano accompaniment	11	22	34	5	0.78	-0.46
	Musicology	14	23	45	8	0.76	-0.41

As shown in Table 7, the attitudes of students in different majors towards different multimedia application methods varied. Compared to students majoring in piano performance and piano composition, students majoring in music education and musicology are more receptive to the virtual piano classroom and can generate higher satisfaction. For digitized sheet music and automatic accompaniment, the satisfaction coefficient of the piano composition majors was 0.78, and their acceptance was significantly higher than those of the other majors. As for VR and AR, the acceptance of music education majors was significantly higher than that of students from other majors. In terms of interactive teaching software, there is a small difference in acceptance between students from various majors. Overall, the acceptance of the multimedia innovative application strategy by students of all majors is high, which proves the effectiveness of the strategy presented in this paper.

The acceptance of students at different grade levels is shown in Table 8.

Table 8.

Acceptance of students of different grades

Application mode	Grade	Demand attribute				SI	DSI
Application mode	Grade	M	O	A	I	SI	DSI
Virtual piano classroom	Freshman	12	50	34	16	0.75	-0.55
	Sophomore	16	34	28	12	0.69	-0.56
	Junior year	10	26	13	18	0.58	-0.54
	Senior four	4	16	10	10	0.65	-0.50
Digital sheet music & automatic accompaniment	Freshman	24	65	20	3	0.76	-0.79
	Sophomore	18	51	17	4	0.76	-0.77
	Junior year	12	28	31	7	0.76	-0.51
	Senior four	9	12	15	6	0.64	-0.50
Interactive teaching software	Freshman	21	54	27	10	0.72	-0.67
	Sophomore	19	42	25	4	0.74	-0.68
	Junior year	12	24	36	6	0.77	-0.46
	Senior four	11	25	4	2	0.69	-0.86
VR & AR	Freshman	6	32	65	7	0.88	-0.35
	Sophomore	12	25	48	5	0.81	-0.41
	Junior year	8	26	35	9	0.78	-0.44
	Senior four	5	16	18	3	0.81	-0.50

As can be seen from Table 8, the acceptance of this paper’s multimedia innovative application strategy is generally high among students of different grades. In the virtual piano classroom, the satisfaction coefficient of freshmen students is 0.75, which is significantly higher than the acceptance of students in other grades. As for digitized sheet music with automatic accompaniment and interactive teaching software, the acceptance of the fourth-year students was relatively low compared to students of other grades, with satisfaction coefficients SI of 0.64 and 0.69, respectively. For VR and AR, the acceptance of the first-year students was the highest among students of all grades, with an SI of 0.88, and the least acceptance was that of the third-year students (SI = 0.78). Overall, the acceptance of this paper’s innovative multimedia use strategy was higher for all grades, and more pronounced in the lower grades.

To summarize, the innovative application strategy of multimedia technology in piano teaching designed in this paper has a better teaching effect, and the students have a higher acceptance of the strategy.

5

Conclusion

This paper realizes the design of the innovative application strategy of multimedia technology in piano teaching and evaluates the implementation effect of the strategy and students’ acceptance of the strategy by using the two-sample t-test method and Kano model.

First of all, this paper designed a controlled teaching experiment, where the experimental group used the piano teaching model based on the innovative application strategy of multimedia technology in this paper, and the control group used the traditional piano multimedia teaching model. In the pre-test, there was no significant difference between the experimental group and the control group in the four dimensions of music theory knowledge, music literacy, basic piano skills and performance techniques (P>0.05), and the samples were homogeneous. Post-experiment measurement, there are significant differences between the experimental group and the control group in each specific dimension of piano professional ability (P<0.05), and the increase in the performance of the experimental group in each dimension after the experiment is greater than that of the control group, which indicates that the multimedia-based innovative application strategy proposed in this paper can significantly improve the effect of piano multimedia teaching, which is significantly better than the traditional piano multimedia teaching mode.

Secondly, this paper assessed the students’ acceptance of the strategy by calculating the satisfaction index (SI) based on the Kano model. The results show that the satisfaction coefficient (SI) values of students of different majors and grades for the specific dimensions of the four multimedia innovative application strategies, namely, virtual piano classroom, digitized sheet music and automatic accompaniment, interactive teaching software, and VR&AR, are all greater than 0.5, i.e., the students have a high acceptance of the strategies in this paper.

Langue:: Anglais

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A Study on the Innovative Application of Multimedia Technology in Piano Teaching and Students’ Acceptance

Wei Zheng

Zhihui Yu

Publié en ligne: 17 mars 2025

Reçu: 01 nov. 2024

Accepté: 02 févr. 2025

DOI: https://doi.org/10.2478/amns-2025-0322

Mots clés<kwd>Two-sample t-test</kwd>, <kwd>Kano model</kwd>, <kwd>Piano teaching</kwd>, <kwd>Multimedia technology</kwd>

© 2025 Wei Zheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
<kwd>Two-sample t-test</kwd>, <kwd>Kano model</kwd>, <kwd>Piano teaching</kwd>, <kwd>Multimedia technology</kwd>