Research on innovative model of piano informatization teaching under the background of big data and soft computing

Abstract

The continuous emergence of new social media has promoted the interaction of data in life. In this context, big data technology has gradually become a type of technology with special value in the field of education. It realizes business decision-making through the collection and analysis of specific types of data. The application of technology to the field of education can realize the analysis of students’ learning needs and classroom teaching efficiency, while the application of big data technology to piano teaching can strengthen the combination of piano teaching and technology, and at the same time provide more data analysis and decision support for the whole process of piano teaching. Soft computing simplifies the calculation process by combining a variety of sophisticated algorithms. Soft computing is similar to human brain processing and perception. It can complete multi-variable complex calculations through low-cost and uncertain processes. With the continuous integration, the variables generated in the teaching process gradually increase, and the application of soft computing technology can effectively solve the complex calculation problems caused by many variables in the analysis of piano teaching. This paper first analyzes the basic theory of big data, soft computing and piano informatization teaching, and then obtains the problems existing in the current piano informatization teaching through questionnaire survey and analysis, and designs piano informatization, teaching innovation model based on big data and soft computing technology respectively. Through the post-investigation of the piano informatization teaching institutions combined with technical strategies, it is found that the degree of match between the piano informatization teaching content of the institution and the students’ learning needs, the evaluation accuracy of piano teachers’ teaching effects, and the students’ piano learning performance have improved.

Keywords

Big data soft computing piano information-based teaching innovation

1. Introduction

1.1 Big data

Data science continues to progress with the increase of online social data. Big data technology is a key technology in the field of data science. It can be divided into data collection, data processing, and data analysis categories, and each category contains a variety of Solution [1]. Usually, the methods in the data collection stage include Python crawlers, Java crawlers, and database data export, while the data processing stage usually includes processes such as SQL data filtering preprocessing and data condition screening [2, 3]. The requirements are displayed, usually combined with data visualization tools such as business reports [4]. The core function of big data technology is to provide users with data-based decision-making, and its application in piano informatization teaching can effectively improve the deficiencies in the traditional piano teaching process, and provide support tools for students’ learning needs analysis and teachers’ teaching situation analysis. Improve the efficiency and effect of piano informatization teaching [5, 6].

1.2 Soft computing

The concept of soft computing is proposed relative to hard computing. Hard computing requires the calculation process to be rigorous and deterministic, while soft computing considers the completion of system computing with a lower cost and an uncertain process. Soft computing is usually performed by annealing [7, 8]. Algorithms, brain neural simulation algorithms, fuzzy sets and other mathematical-related methods are combined to complete the calculation of a system with complex variables [9, 10]. The entire processing process is uncertain, but the calculation results can often be compared with hard calculations. Combining soft computing technology to solve complex system problems can often achieve environmental adaptation, that is, soft computing can automatically switch algorithms to complete the calculation according to the transformation of the problem, and finally achieve low-cost and high-efficiency computing [11, 12, 13].

1.3 Piano informatization teaching

In the era of rapid development of science and technology, information technology has played a leading role in human life, and in education and teaching, the learning effect that can be achieved by traditional oral teaching is far lower than the use of information-based teaching methods, so in the classroom The use of information technology has become the development trend of modern classrooms. At present, some developed countries abroad, such as the United States, Japan, the United Kingdom and other countries have not only issued many policies on popularizing information-based teaching, but the government has also allocated funds to schools in various regions to purchase information-based teaching equipment. Under the strong support of national policies and funds, the level of informatization teaching in these countries has been significantly improved. Using the Internet for classroom learning has become the norm for students to study, and these countries already have a complete set of informatization classroom management mechanisms. With the gradual expansion of my country’s information-based teaching strength, the country has focused on the training of teachers’ information-based education technology, and teachers’ construction of information-based teaching design before class has also become an important step to promote the development of information-based teaching. The informatization teaching classroom is conceived, the teaching links are standardized, the teaching method is adjusted, and the teaching mode is improved. Piano informatization teaching refers to the use of the Internet, the Internet of Things and other informatization-related technologies to achieve intelligent piano teaching [13]. For example, some piano sparring apps that are common in the field of view can complete online piano tutoring through external cameras and handheld devices [14, 15]. In addition, some pianos have built-in storage and sensors related to the Internet of Things, which can realize various interactions between the piano and the holder [16]. At present, the combination of artificial intelligence technology and some audio equipment can also provide more intelligent support for the piano teaching process, and emerging technologies such as big data and soft computing have gradually joined the wave of piano informatization teaching innovation in a special way [17, 18].

When piano students of different ages have some common problems in piano learning [16]. As a teacher, they should formulate corresponding piano learning standards and give appropriate praise according to the students’ situation, combined with the application of information technology and the latest technology [17]. Provide students with opportunities for continuous development, while giving hope and encouragement in the language of form [19, 20].

2. Questionnaire and analysis

In order to analyze the current situation of piano informatization teaching, 500 questionnaires were distributed to 50 piano teachers and 200 students in 25 piano education institutions. degree, the applications used in piano informatization teaching, the proportion of teacher-student communication time in piano lessons, and the accuracy of piano teachers’ teaching ability evaluation. Among them, 499 valid questionnaires were recovered, which met the standards of the questionnaire survey. Among them, the continuous development of piano education informatization has gradually complicated piano education. Piano teachers have also developed from traditional professional skills to multi-skilled models. The informatization application ability of piano teachers determines their role in teaching informatization. The contents of this questionnaire about the application ability of piano teachers’ informatization are shown in Table 1.

Table 1
Informatization application ability of piano teachers

Piano teacher	Ability type	Proportion of people with ability (0,1)
1	Programming	0.03
2	Internet of Things	0.05
3	Big Data	0.01

It can be seen from Table 1 that the current piano teachers have gradually fallen behind in the development of piano teaching informatization. Some of the abilities required by informatization teaching can only be mastered by very few piano teachers, and none of them have the relevant abilities. more than 5% of the total population.

Students’ interest in the learning content of piano courses is the basic guarantee for their learning efficiency and learning effect. Therefore, the pertinence of learning content in piano informatization teaching is more important. The specific situation is shown in Table 2.

Table 2

Students’ interest in learning

Student	Learning content	Interest (0,1)
A	X	0.33
B	Y	0.25
C	Z	0.42

It can be seen from Table 2 that the students of the current piano education institutions are not very interested in the teaching content of the piano courses in the institutions, which shows that the piano information teaching content of the piano education institutions does not match the needs of the students.

The applications used in piano informatization teaching are the embodiment of the development of piano informatization. At present, the analysis of the degree of informatization in various industries is based on the number of technologies used in the industry. Most industries still use computer software and APP to complete the process. Industry informatization, and piano informatization education is similar to the general industry, and its specific situation is shown in Table 3.

Table 3

Applications used in piano informatization teaching

Num	Application	Usage
1	APP	0.45
2	Smart wearable device	0.13
3	Other	0.42

From Table 3, it can be seen that the informatization applications used in the current piano informatization teaching are still relatively common. Still less applied. The proportion of other types of information-based teaching applications is slightly lower than that of APPs, but they are still relatively common. At present, key applications that are more in line with the development needs of the information age are needed.

Teacher-student communication in piano class is the key to promoting students’ learning in piano class, and the proportion of teacher-student communication time in piano class can show the specific situation of student-teacher interaction in piano class. The content of the teacher-student communication time in the class is shown in Table 4.

Table 4

The proportion of teacher-student communication time in piano lessons

Student	Communication time as a percentage of the total class	Interactive mode
A	0.35	Operation teaching
B	0.38	Dialogue
C	0.27	Other demos

From Table 4, it can be seen that there is a problem that the operation teaching process accounts for too little time in the current institutions. Piano is a course with strong practical operation. In the teaching process, teachers need to teach while operating, so that students can maximize the probability of teaching. The key knowledge has been acquired, and the data shown in Table 4 shows that the current students have less opportunities for interactive immersive learning in the classroom, so there may be a variety of piano operation problems left over, resulting in a lack of solid foundation and affecting students. The effect of piano learning.

The evaluation of the teaching ability of piano teachers can accurately analyze the teaching effect of teachers, and can also find problems through analysis, and provide improvement ideas for the later informatization teaching of piano teachers, the data about the accuracy of piano teachers’ teaching ability evaluation in this questionnaire survey are shown in Table 5.

Table 5

Accuracy of teaching ability evaluation of piano teachers

Teacher	Comment content	Evaluation accuracy
A	Information equipment operation ability	0.13
B	Ability to explain piano knowledge	0.42
C	Practical ability to operate the piano	0.45

From Table 5, it can be seen that the accuracy of the current piano teachers’ teaching ability evaluation is still low, especially the evaluation related to piano information teaching is still inaccurate. At present, it is necessary to improve the accuracy of the evaluation of piano teachers’ information teaching ability through other technologies.

3. An innovative model of piano informatization teaching based on big data

3.1 Improvement strategies of piano teachers’ informatization application ability based on big data technology

The combination of big data technology and recommendation algorithms in social media has successfully achieved accurate content push [21]. According to the teachers’ current informatization application ability obtained in the questionnaire, piano teachers generally lack the ability to use informatization applications [22]. Data technology can obtain the personal data and classroom teaching data of piano teachers to determine the missing part of their informatization application ability, combine the knowledge of informatization application ability existing in social media, and accurately push relevant knowledge to corresponding piano teachers, such as a certain piano teacher [23]. For piano teachers who are not familiar with earphone-type smart wearable devices, big data technology can be combined with recommendation algorithms to continuously push earphone-type smart wearable devices to them through the browser and social APP news interface according to the teacher’s teaching statistics and personal social media usage habits [24]. By constantly contacting the corresponding knowledge in life, the informatization application ability of institutional piano teachers can be gradually improved. Through the post-investigation of the research objects of piano institutions, it is found that the teacher’s informatization application ability has been greatly improved after combining with big data technology [25]. The specific situation is shown in Fig. 1.

Figure 1.

The informatization application ability of piano teachers combined with big data technology.

3.2 Strategies for improving students’ interest in piano learning based on big data technology

In the whole process of learning the piano, the application of knowledge involves a very wide range, such as: musical tone system, rhythm, rhythm, staff, interval, and chord. These basic knowledge are relatively boring and boring, but learning these basic knowledge in combination with information application can reduce the boring feeling, especially the learning content recommended for students’ interests [25].

All changes in piano informatization teaching are aimed at improving students’ learning effect and strengthening students’ interest in learning [26]. Learning interest is also the key to all subjects, and learning interest is often highly related to the content displayed in the classroom [27]. For students with low interest in learning, we can combine big data to analyze the personal information and hobbies registered by students when they enroll, and collect students’ classroom performance data through audio equipment, and then comprehensively analyze their learning interests based on students’ daily life and social media data, piano teaching is basically small class teaching, and the content of the class can be taught based on students’ learning interests [28]. For example, if a student has recently browsed the information of a musician on social media many times, the piano teacher can teach the musician in the classroom [29]. In order to stimulate students’ learning motivation and maximize their learning enthusiasm. Through the later investigation of the research objects of piano institutions, it is found that the students’ interest in piano learning has been greatly improved after combining with big data technology. The specific situation is shown in Fig. 2.

Figure 2.

Students’ interest in piano learning combined with big data technology.

3.3 Configuration strategy of piano informatization application based on big data technology

Combined with the analysis of the questionnaire survey, it is found that the current piano education institutions have insufficient information application configuration, which will directly affect the effect of piano information teaching. In the absence of equipment and facilities, piano teachers can only use poor equipment for teaching, thereby reducing teaching efficiency. Some piano education institutions lack the channels to obtain the latest applications of informatization teaching. Big data technology can obtain the latest piano informatization teaching applications in the current market based on social media data, and push the data to the piano in a reasonable way. Institutional equipment purchasers and decision makers, in order to stimulate the purchasing desire of decision makers, enhance the informatization application configuration of piano institutions, and improve the level of piano informatization teaching. Through the later investigation of the research objects of piano institutions, it is found that the configuration rate of piano informatization applications has been greatly improved after combining with big data technology. The specific situation is shown in Fig. 3.

Figure 3.

The deployment rate of piano informatization applications combined with big data technology.

4. An Innovative model of piano informatization teaching based on soft computing

4.1 Strategies for improving student immersion in piano lessons based on soft computing

Piano teaching is different from the teaching of culture class. In the process of piano teaching, the age, concentration and concentration of students, and the foundation of learning piano are all different, especially the special age group of children, who do not have special self-discipline. It is easy to be attracted by other things in the process of class, but children at the age of children have very strong imitation ability, teachers need to guide students to learn piano. For example, in the early stage of learning piano, students are generally young, and their comprehension ability and self-control are relatively weak. Most students often have errors in pitch, rhythm, fingering, etc. The spectrum speed is slow, the error frequency is high, and the hands are easily interrupted.

A detailed analysis of the questionnaire data found that the communication time between teachers and students in the current piano institution informatization teaching classroom accounted for a small proportion of the total classroom time. In the course of teaching or explaining knowledge, there is less time for hands-on teaching, so it is difficult for some students to obtain an immersive learning experience in piano teaching institutions. Soft computing technology is a relatively flexible multi-algorithm integration technology, which can be designed based on scene requirements, and can complete fast and low-cost computing of multi-complex variable systems. For the problem that students cannot effectively communicate with teachers in the piano informatization teaching classroom, the piano classroom teaching data can be obtained by using the audio collection equipment in the informatization classroom, and then based on the fuzzy set, neural network, annealing, etc. in the soft computing technology. The algorithm effectively calculates the interactive needs and questions generated by students in the piano informatization classroom, and makes corresponding knowledge fragments into VR and other headsets. At the end of the piano classroom teaching, students can quickly browse and analyze knowledge with the VR equipment. Students’ shortcomings in the informatization classroom, and timely provide solutions for the lack of interaction in the classroom, and further promote the optimization of teachers’ teaching plans, and finally achieve the effect that students can be efficient and focused in each piano informatization teaching class [30]. Through the post-investigation of the research objects of piano institutions, it is found that the students’ classroom experience and immersive learning time have been greatly improved after the combination of soft computing technology. The specific situation is shown in Fig. 4.

Figure 4.

Student immersion combined with soft computing technology.

4.2 Accuracy improvement strategy of piano teacher teaching ability evaluation based on soft computing

Due to the intelligent analysis and flexibility of various algorithms, soft computing is suitable for solving key problems in multi-variable complex systems. At present, soft computing has been applied in various data mining and data analysis. The application of soft computing in the field of education and teaching mainly includes the development prediction of students’ academic performance and the analysis of teacher fitness. The data analysis characteristics of soft computing also meet the needs of piano teachers’ teaching ability evaluation. Soft computing technology is used to improve Evaluation accuracy can simplify the complexity of the evaluation process and improve the efficiency of evaluation. The first step is the collection of teaching ability data, the selection of feature parameters, and the data discretization filtering; the second step is to combine the selected feature parameters with soft computing mathematical methods for further screening; the third step is to use the selected feature parameters. The data is classified into training and testing data, and the corresponding data training framework is constructed by combining methods such as neural network and SVM; the fourth step is to combine the parameters in the SVM method framework with the ant colony algorithm to complete the improvement; the fifth step is based on the third step. The test category information of the step is used to complete the teaching ability evaluation data test of the recognition model. The algorithm formula used is shown in Eqs (1)–(4).

$\displaystyle B_{1}=\frac{Q}{\sum\limits_{i}{q_{i}}a_{i}}$ (1) $\displaystyle B_{2}=\frac{1}{N}\sum{\frac{V_{a}}{V_{b}}}$ (2) $\displaystyle B_{3}=\left(\sum\limits_{i=1}^{n}{K_{i}}S_{i}/L_{i}\right)/n$ (3) $\displaystyle C_{2}=\frac{U}{G}$ (4)

Among them, $B_{1}$ is the matching degree of the teacher’s personal information; $Q$ is the amount of the teacher’s piano lessons; $q_{i}$ is the teacher’s i-type of ability evaluation; $a_{i}$ is the student’s i-type of evaluation choice. Among them, $B_{2}$ is the comfort level of students in piano class [31, 32]; Vb is the teacher’s informatization ability; Va is the teacher’s explanation speed in class; $N$ is the number of students included in the teacher’s teaching. Among them, B3 is the teacher’s evaluation accuracy coefficient; Ki is the i-th evaluation precision ratio [33].

Si is the i-th data accuracy; Li is the i-th evaluation method; $n$ is the number of evaluations. Among them, C2 is the total evaluation accuracy; $U$ is the individual evaluation coefficient; $G$ is the overall evaluation coefficient.

The test data of the teaching ability evaluation accuracy of piano informatization teaching teachers analyzed by Python programming software combined with soft computing technology were simulated. After the intelligent algorithm related to soft computing technology was found, the accuracy of teachers’ teaching ability evaluation was greatly improved. The specific situation is shown in Fig. 5.

Figure 5.

Accuracy of piano teachers’ teaching ability evaluation.

5. Conclusion

When piano teachers introduce in the classroom, through interesting forms such as cartoon animation playback, teachers can use fresh and interesting images to accurately and quickly grasp the focus of students’ attention when they are introduced in the classroom. The active atmosphere is introduced into the teaching difficulties in the classroom, and the students’ initiative is mobilized. In formal teaching, teachers can make use of the characteristics of students who like games, videos and pictures, and skillfully use the classroom activity system based on electronic whiteboard technology. Combining technologies such as big data and soft computing, the information-based classroom will become more targeted, especially in the direction of students’ learning interests and teachers’ teaching methods, and technologies such as big data can achieve personalized customization. Big data technology takes data as the core, filters and filters data based on various programming techniques, and then extracts the key information that analysts want to obtain. At present, big data has been widely used in medical, business, social media and other fields. With the continuous advancement of piano education informatization, there will be a variety of models combining big data and piano education in the future. As a branch of big data technology, soft computing technology is combined with neural networks and other algorithms to simplify complex computing processes. , the evaluation of teachers’ teaching efficiency and the analysis of students’ learning needs in the current process of piano information education involve a variety of complex variables, so soft computing can provide more support for piano information education. Since the country has vigorously promoted quality education, people have paid more and more attention to all-round development, and piano has become one of the important means of cultivating students’ personal quality. However, the traditional piano teaching methods are too single and rigid, students cannot be interested in piano learning, ignore the importance of students’ independent learning, and fail to achieve the expected teaching effect. How to cultivate interest is a long-term and complex problem. In this regard, every teacher should pay attention to the combination of theory and practice, and apply new technologies such as big data and soft computing to improve teaching efficiency and students’ interest in learning. This paper first analyzes the basic theory of big data, soft computing and piano informatization teaching, and then obtains the problems existing in the current piano informatization teaching through questionnaire survey and analysis, and designs piano informatization based on big data and soft computing technology respectively. Teaching innovation model, through the post-investigation of the piano informatization teaching institutions combined with technical strategies, it is found that the degree of match between the piano informatization teaching content of the institution and the students’ learning needs, the evaluation accuracy of piano teachers’ teaching effects, and the students’ piano learning performance have improved.

References

. Research on the innovation of piano informatization teaching in colleges and universities from the perspective of the Internet. Home Drama. 2022; 6: 178-179.

Zhang

. Action research based on information-based teaching in the teaching of piano group lessons for preschool children in secondary vocational schools. China National Expo. 2021; 20: 82-84.

Hou

. Research on piano informatization teaching strategy based on deep learning. Math Probl Eng. 2022; 2022; 5817752.

Feng

. A tentative exploration of the information-based teaching strategies for piano collective lessons in preschool education majors in secondary vocational schools. Talent. 2021; 30: 82-83.

Zhou

. Exploration of the new path of piano teaching in colleges and universities under the background of informatization. Artists. 2021; 8: 58-59.

Wang

. Piano information teaching mode based on deep learning algorithm. Wirel Commun Mob Com. 2022; 2022: 6205763.

. Piano performance teaching in colleges and universities under the background of the information age – Comment on “theory and practice of information-based teaching design”. Chin Sci Pap. 2021; 16(7): 803.

Liu

Huang

. Piano playing teaching system based on artificial intelligence – design and research. J Intell Fuzzy Syst. 2021; 40(2): 3525-3533.

Guo

. Exploration on piano teaching for preschool education majors in higher vocational colleges. Chin Lit Ar. 2021; 7: 119-120.

10.

. The application of information technology in the piano teaching of preschool education in secondary vocational education. Mod Vocat Educ. 2021; 29: 144-145.

11.

Ding

Huang

. Application of multimedia technology in online piano teaching. Mob Inf Syst. 2022; 2022: 1985546.

12.

. Optimization of online course platform for piano preschool education based on Internet cloud computing system. Comput Intel Neurosc. 2022; 2022: 6525866.

13.

Mei

. A new form of music development in colleges and universities from the perspective of education informatization 20.. Sci Educ Wenhui (Late Issue). 2021; 4: 64-65.

14.

Liu

. Research on the practice of informatization piano teaching in preschool normal colleges. Daguan (Forum). 2021; 4: 149-150.

15.

. Analysis of piano performance characteristics by deep learning and artificial intelligence and its application in piano teaching. Front Psychol. 2022; 12: 751406.

16.

Liu

. Research on micro-lecture teaching and the implementation strategy of “flipped classroom” in piano teaching in vocational colleges. Home Drama. 2021; 11: 101-102.

17.

Zhang

. Information penetration of piano teaching and performance in secondary vocational schools. Chin Handicraft. 2021; 2: 108-109.

18.

Fan

. Internet of Things remote piano information teaching system and its control method. J Sens. 2022; 2022: 4730550.

19.

. Research on piano informatization teaching in colleges and universities based on ideological and political perspectives. Educ Inf Forum. 2021; 3: 9-10.

20.

. Feasibility analysis of intelligent piano in piano teaching. Sci Programming-Neth. 2022; 2022: 5010428.

21.

Wang

. Research on the application of “micro-lecture” in college piano teaching under the background of “Internet +” era. Yangtze River Ser. 2021; 7: 36-38.

22.

. A brief discussion on the reform of piano accompaniment curriculum for preschool education majors. Yangtze River Ser. 2021; 3: 67-68.

23.

Liu

. Research on piano teaching under the information teaching mode. Educ Inf Forum. 2021; 1: 17-18.

24.

Wang

. Analysis of the application of new media technology in college music education. Daguan (Forum). 2020; 11: 116-117.

25.

. An analysis of the optimization model of piano teaching in higher vocational colleges. North Music. 2020; 18: 170-171.

26.

Zhang

. How to integrate modern information technology with the piano teaching mode of preschool education in secondary secondary schools. North Music. 2020; 14: 187-188.

27.

Zhai

. Analysis of the application of Chinese piano works in piano teaching in colleges and universities. Mod Vocat Educ. 2020; 27: 166-167.

28.

Ding

. Using piano teaching to improve students’ artistic accomplishment and spiritual quality: Reflections caused by multimedia information teaching in kindergartens. Artists. 2020; 5: 130-131.

29.

. Exploration of automatic piano distance teaching: Independence, sharing and cooperation. Home Drama. 2022; 7: 106-108.

30.

Wang

. AI technology assists the reform of piano education in rural revitalization. China Fruit Tree. 2021; (7): 110-111.

31.

. Research on the teaching innovation of piano collective lessons in colleges and universities in the era of artificial intelligence. Voice Yellow River. 2020; (19): 118-119.

32.

Gao

. The concept of piano teaching in the era of big data network: Taking Sichuan Junior College as an example. Contemp Music. 2020; (7): 36-37.

33.

Zhao

. Intelligent innovation path of distance education for piano performance major from the perspective of big data. Art Educ. 2020; (5): 59-62.

Research on innovative model of piano informatization teaching under the background of big data and soft computing

Abstract

Keywords

1. Introduction

1.1 Big data

1.2 Soft computing

1.3 Piano informatization teaching

2. Questionnaire and analysis

Table 1 Informatization application ability of piano teachers

3.1 Improvement strategies of piano teachers’ informatization application ability based on big data technology

4.1 Strategies for improving student immersion in piano lessons based on soft computing

References

Table 1
Informatization application ability of piano teachers