Music Learning Research Articles

The Effectiveness of Direct Instruction Model in Teaching Solfeggio for Beginners

The background of this study was rooting down from the students music learning circumstances, of which they have low skill and knowledge of solfeggio, low ability of transferring solfeggio automatically into a new context although they have learned it, unavailability of learning material, syllabus, and lesson plan, standardized method and media of learning. Based on the problems stated above, it is very important to design a research dealing with learning solfeggio which lasting and producing a complete, practical, reliable and valid curricula of solfeggio. The basis model of development is using ADDIE theory. This research belongs to R & D research. The subject of the research is the students of art and music department, FBS Padang State University. The instrumentation of data gathering was using interview, questionnaire, tryout, performance-test. To analyze the raw data to see the level of reliability and practicality the researcher used the formula of Rho Spearman Brown, and the result is that r-obtain 1.2 exceeds r-table within significance level of 95% (0.05) it is 0.349 or by (0,01) it is 0.449. To prove the effectiveness of the product of this research ( the model of learning solfeggio ), the writer distinguish the data of pre-test to post-test by accumulating the scores the students obtained by using match t-test, and the result is that t-obtain 9.311 exceeds t-table 1.697. It means that, the model of learning solfeggio as the product of this research is much more effective significantly since the result of the match t-test is so high exceeding the number of the t-tab. It can be concluded that this model is very useful for the lecturers and the students as well in learning solfeggio at the music department of FBS Padang State University.

Pelaksanaan Pembelajaran Seni Budaya Musik Tradisional (Talempong Pacik) Siswa Kelas VIII-1 SMP Negeri 43 Padang

. This study aims to describe the process of implementing Talempong Pacik Music learning in grades VIII-1 at SMP Negeri 43 Padang. This type of research is qualitative research with descriptive methods. This research instrument is the researcher himself and is assisted by supporting instruments in the form of stationery and cameras. This research data uses primary data and secondary data. Data are collected through literature study, observation, interviews, documentation. The steps of analyzing data are data classification, analyzing data, and inferring data. The results showed that the implementation of learning Traditional Music Culture Arts (Talempong Pacik) in Grades VIII-1 SMP Negeri 43 Padang consisted of 4 meetings, namely initial activities, core activities and closing activities. The scores of students after the implementation of Traditional Music Culture (Talempong Pacik) learning activities are still many who have not reached KKM, there are 15 students who have not reached KKM and 8 students can only achieve predetermined KKM standard scores and there are 9 students who get scores that exceed KKM. The learning process has not fully obtained satisfactory learning results. Teacher limitations in using teaching aids and limited time in practical activities, teachers continue to try to motivate students, so that students continue to be enthusiastic in the process of learning activities, students still look rigid in carrying out learning activities including in the process of traditional music learner practice activities, so that there are still many student scores below KKM, and the rest only reach the KKM limit. So it is known that students have not received maximum grade results.

MatheMusical Virtual Museum: Virtual Reality application to explore Math-Music World

Virtual Reality is a promising tool for pedagogy in teaching music, and the MatheMusical Virtual Museum takes this promise to a new level. This study aims to share and describe the project's concept and advancement, including expertise and collected experiences in MatheMusic. Mathemusic is the scientific field that studies the relations between math and music; the Society for Mathematics and Computation in Music regroups worldwide researchers in the field. The Mathemusical Virtual Museum is an interactive virtual experience that premiered at the Museum of Design in Atlanta (Moda) in June 2022 (Baroin & de Gérando, 2022). It contains a growing set of interactive models based on the research issued by our society. Mathemusicians have always produced models for understanding, analyzing, or computing music. Visualizing some on paper, theater, or computer screens is expected. Even if it is in a multidimensional space (3D-4D), the viewer ends up with a 2D picture or a movie while displaying these models on a computer screen. Planar projection limits the perception in the era of virtual reality nowadays. This study proposes tools and solutions to apprehend these models better and improve the viewer's immersive experience. Since the beginning of the project, user experiences were collected. Besides desperately unfit users for VR, we noticed that kids are highly engaged and immersed in the learning environment; music learners are not just improving their knowledge but also feeling inspired and hopeful about the future of music education; mathematicians and researchers are feeling like they are finally entering their creation and contributing to improving the project, thereby making significant contributions to their respective fields. Keywords: Virtual Reality, Mathemusic, Visualization, Pedagogy, Learning Strategy Received Date: January 31, 2024Revised Date: March 14 , 2024Accepted Date: April 25, 2024

E-learning and speech dynamic recognition based on network transmission in music interactive teaching experience

The research adopts the network transmission technology to realize the framework of e-learning, and combines the speech dynamic recognition technology to improve the interactive music teaching experience. By establishing an online learning platform, the network is used to transmit learning resources such as audio, video and text. In the application of speech dynamic recognition technology, the modern speech recognition algorithm and artificial intelligence technology are used. Let students sing or play on a device such as a microphone or a mobile phone and transmit their sound signals to the system. Through speech dynamic recognition technology, students 'audio is analyzed and processed in real time, and students' singing or performance is evaluated and feedback. The system can analyze students' intonation, rhythm, timbre and other musical elements, and evaluate and guide them according to the preset scoring standards, so as to help students improve their playing skills. Through the combination of network transmission technology and speech dynamic recognition technology, students can enjoy a more personalized and interactive teaching experience in music learning. The systematic real-time evaluation and guidance function can also help students adjust their performance skills in time and provide targeted learning suggestions.

Research on VR e-learning based on load balancing algorithm in intelligent music education system

This paper aims to explore the application of virtual reality (VR) electronic learning based on load balancing algorithm in the simulation of intelligent music education system. This paper designs and implements an intelligent music education system simulation, which uses load balancing algorithm and virtual reality (VR) technology to provide the convenience of e-learning and personalized learning experience. The load balancing algorithm allocates and manages multiple tasks or requests in the system to ensure the balanced utilization of resources and the efficient operation of the system. In the intelligent music education system, the load balancing algorithm can be used to manage user requests, allocate appropriate resources and services, and ensure that the system can respond quickly and provide a stable learning environment. This paper introduces the architecture and implementation details of the system, including the design and optimization of load balancing algorithm and the application of VR technology. The results show that we point out that VR e-learning based on load balancing algorithm has potential in the simulation of intelligent music education system, which can provide high-quality personalized music learning experience and provide useful enlightenment for innovation in the field of music education.

Application of recommendation system based on fuzzy logic in music culture communication and music teaching management

Music has been utilized throughout history as a medium for cultural communication and artistic expression, embodying various nations’ and societies’ ideologies and experiences. Music culture communication is crucial for encouraging cultural diversity and understanding and developing social cohesion and community building among people. Music teaching management is the process of setting up, arranging, and executing music education programs in a manner that successfully teaches students the essential skills and information necessary for becoming proficient musicians. Users’ exact preferences for various areas of attraction cannot be determined, nor are users’ choices for traditional music recommendations sufficiently accurate. A recommender system estimates or anticipates people’s preferences and offers appropriate recommendations. First, the sparsity problem emerges when insufficient data is accessible for the recommendation, and the coverage is one of the key drawbacks of social labeling. Cold start issues might be difficult since new music learners might not have given sufficient details about their musical tastes. Hence, the Hybridized Fuzzy logic-based Content and Collaborative Music Recommendation (HFC2MR) system is proposed to create personalized music teaching plans that are effective and engaging for each student based on their music preferences and learning outcomes. Enhanced Fuzzy C-Means clustering is used in collaborative recommendations to group users based on their shared musical tastes and to provide each user with more individualized, accurate music recommendations based on other users’ listening habits and preferences in the same cluster. Subsequently, an assessment of the recommender system using parameters like accuracy, precision, f1-score, and recall ratio is shown with optimal cluster selection. The coverage ratio is used to compare experimental data based on skill capacity covered through the assessment of music teaching. RMSE metric is used to evaluate the accuracy of students’ performance based on music attributes related to teaching goals.

The CrazySquare project for music learning in Italian school-age pre-adolescents: integrating technology into educational practice

The CrazySquare project for music learning in Italian school-age pre-adolescents: integrating technology into educational practice

Kaleidoscope of Inclusion: Mapping Music Learning Methods through the Lens of Contemporary Early Childhood Education Literature

The use of music learning methods in inclusive schools is considered as an innovative way to create an inclusive environment that stimulates children's holistic development. Even so, not many are aware of the urgency of music as a tool to achieve this inclusion, so a more in-depth study is needed. This study aims to analyze the role of music learning methods in inclusive early childhood education (ECE) in the contemporary era. Using a Systematic Literature Review (SLR) approach, this research aims to collect, review and analyze literature related to the use of music learning methods in inclusive ECE. Data collection techniques involve conducting a structured and comprehensive search on trusted databases. The data analysis process involved selecting literature based on inclusion and exclusion criteria, considering the relevance of articles and the necessary information. The results of the literature analysis found that music learning methods play an important role in creating an inclusive environment that stimulates early childhood participation and development. Music can open doors of communication, increase social interaction, and stimulate the creativity of inclusive children.

Quality Assessors’ Feedback and Recommendations on Music Education in Hong Kong Kindergartens

In Hong Kong, quality assessors from the Education Bureau (EDB) visit kindergartens to conduct Quality Review (QR) assessments. Their written reports, therefore, reflect the official local perspective of quality kindergarten education. We conducted a content analysis of 323 QR reports focusing on the positive and negative feedback and recommendations for improvement regarding music education. Two coding schemes were developed using an inductive approach. High inter-reliability was obtained. The most frequently mentioned positive feedback codes were related to sufficient exposure to music and enjoyable musical learning experiences. In contrast, there were negative feedback codes pointing out that children’s musical exposure was insufficient at Kindergarten 3 (children aged 5–6 years), and some musical activities were poorly prepared and/or designed. Children’s music learning outcomes were rarely mentioned in the reports. The analyses indicate that the local understanding of kindergarten music education strongly emphasizes exposing children to enjoyable musical activities, with a lower focus on the nature and quality of musical learning. We conclude that the QR reports reflect a teacher-centric view of music education. Findings may inform curriculum designers and teacher educators about EDB’s expectations in the area of music education. Future research should explore the perspectives of other kindergarten stakeholders such as teachers, principals, and teacher educators.

Investigation and Analysis of the Application of Efficient Classroom Model in High School Music Appreciation Course

In China, the efficient classroom teaching model is also known as the "6+1" teaching model, which was first applied to cultural courses, such as math, chemistry and English."6+1" refers to the six segments of classroom teaching, including "guide", "think", "discuss", "show", "assess", "check"; the second part is the "1" in the efficient 6+1 model, which is called "use", which is a learning segment carried out in the self-study after class (Ma, 2023). It emphasizes the students' subject position and focuses on cultivating students' independent learning ability and innovative thinking. But whether this teaching mode is suitable for high school music appreciation courses has not yet been researched in a targeted way. The cultivation and improvement of independent learning ability has become an important symbol of deepening teaching reform (Du, 2020). Therefore, the efficient classroom mode was adopted for classroom teaching in the high school music appreciation course, and after four weeks of teaching practice, questionnaires on music learning attitudes, learning styles, and learning goals as the main content were administered to teachers and students respectively. The results of the study showed that after the teaching of the efficient classroom model, teachers were positive about the instructional model, and students' learning attitudes became more positive. Students also listen to more musical works on their own. The results of the study are expected to provide some useful references and lessons for the reform and development of high school music education in China.

E-learning application in immersive music entertainment teaching system based on genetic network algorithm

The problem of traditional music teaching is that students' interest and participation in learning are not high, which leads to the decline of teaching effect. Therefore, this study proposes an e-learning approach based on genetic network algorithms, aiming to enhance students' learning experience and engagement through an immersive music entertainment teaching system. The research has established an immersive music entertainment teaching system, which combines virtual reality technology to provide an immersive music learning environment. A genetic network algorithm is then used to optimize the e-learning modules in the system to improve the personalization and interactivity of the learning process. By collecting students' learning data and feedback information and using it as input to genetic network algorithms to update the parameters and structures in the learning module. The results show that e-learning based on genetic network algorithm has achieved remarkable results in an immersive music entertainment teaching system. When using the system for music learning, students showed higher enthusiasm and investment in learning, and achieved better academic performance. Students' experience and satisfaction with the system were also improved.

Exploring music learning needs of working-age individuals in Thailand

This quantitative study delves into the music learning needs of working-age individuals in Thailand, focusing on those aged 21 to 59 years outside the music profession. The research, conducted in October 2023, collected responses from 503 participants through an online structured questionnaire. The findings revealed that “As a hobby/for relaxation” emerged as the primary motivation for enrolling in music classes, among currently enrolled, previously enrolled, and prospective participants. Desired learning contexts revealed “Onsite learning” with a “Very High” mean score for current ( x− = 4.89) and past enrollees ( x− = 4.58), while those aspiring to enroll rated this and “Hybrid Learning” in a “High” level. “Private learning” earned a “High” rating across groups, and “Small group learning” received a “High” rating for prospective and past enrollees. Exploring learning styles, participants consistently rated items at a High Level, encompassing “Involvement in learning choices,” “Prioritizing adaptation over theory,” “Using metaphor,” “Visual learning,” “Auditory learning,” and “Kinesthetic learning.” Barriers to music learning, including “Time management” and “Memory,” were notably high among past enrollees. These insights offer valuable guidance for tailoring music activities or lessons to the specific needs of adult learners.

Enhancing Learning Efficacy for Chinese Undergraduates Majoring in Music — A Constructive Approach

In 1977, the American psychologist Albert Bandura first proposed the concept of Self-efficacy. Once proposed, this concept has had an impact on several research fields. In the field of music learning, self-efficacy, as the intrinsic psychological motivation in the process of music learning, is an important factor affecting students' music learning. This paper examines the self-efficacy status of undergraduates majoring in Music in China using both quantitative and qualitative approaches. Based on the results of 50 questionnaires and 6 interviews, this study further proposed possible strategies to enhance students' self-efficacy from a constructivist approach. Constructivism learning theory emphasizes the dynamic nature of knowledge, the richness and difference of students' experience, and the active construction of learning, social interaction and situation, which has certain theoretical value and practical significance for college music education. This paper is expected to provide future researchers and educators in music education with research-driven theoretical support on how to facilitate undergraduates' music learning.

Fuzzy control algorithm for analyzing the effects of vocal music on college students’ social and emotional learning

Vocal music training for college students impacts the social and emotional aspects of better learning. This impact must be classified progressively to improve the social and musical connectivity coinciding with real-time emotions. Therefore, an intermittent analysis of music learning is required for augmenting socio-emotional changes to the learning method. This article introduces Impact-centric Learning Analysis (ILA) using the Fuzzy Control Algorithm (FCA) for the purpose above. The control algorithm operates in two linear stages: in the first stage, the socio-emotional impact of the learning on the students is analyzed, pursued by the learning changes in the second stage. This first stage inputs student activity scores based on real-time implications. The lowest scores are classified independently in the second stage, and learning changes are carried out. The learning change is targeted to meet the maximum (optimal) impact score from the first stage using fuzzy differentiations based on training sessions and student performance. Therefore, the proposed algorithm generates an optimal impact for the considered features (socio-emotional), preventing trivial vocal music sessions.

Fuzzy logical system for personalized vocal music instruction and psychological awareness in colleges using big data

Traditional psychological awareness relating to vocal musical instruction often disregards the impact of earlier experiences on music learning could result in a gap in meeting the needs of individual students. Conventional learning techniques of music related to psychological awareness for each individual has been focused on and addressed in this research. Technological upgrades in Fuzzy Logic (FL) and Big Data (BD) related to Artificial Intelligence (AI) are provided as a solution for the existing challenges and provide enhancement in personalized music education. The combined approach of BD-assisted Radial Basis Function is added with the Takagi Sugeno (RBF-TS) inference system, able to give personalized vocal music instruction recommendations and indulge psychological awareness among students. Applying Mel-Frequency Cepstral Coefficients (MFCC) is beneficial in capturing variant vocal characteristics as a feature extraction technique. The BD-assisted RBF can identify the accuracy of pitch differences and quality of tone, understand choices from students, and stimulate psychological awareness. The uncertainties are addressed by using the TS fuzzy inference system and delivering personalized vocal training depending on different student preference factors. With the use of multimodal data, the proposed RBF-TS approach can establish a fuzzy rule base in accordance with the personalized emotional elements, enhancing self-awareness and psychological well-being. Validation of the proposed approach using an Instruction Resource Utilization Rate (IRUR) gives significant improvements in engaging students, analyzing the pitching accuracy, frequency distribution of vocal music instruction, and loss function called Mean Square Error(MSE). The proposed research algorithm pioneers a novel solution using advanced AI algorithms addressing the research challenges in existing personalized vocal music education. It promises better student outcomes in the field of music education.

Effects of altered sensory feedback on piano performance errors: An exploratory study

Music performance is an intensive sensorimotor task that involves the generation of mental representations of musical information that are actively accessed, maintained, and manipulated according to the demands of the performance. Internal representations and external information interact through feedback and feedforward processes that adjust the musician’s motor behavior to optimize a musical performance. This study aimed to examine the relationship between altered sensory feedback and performance errors. Seventeen experienced pianists aged between 33 and 54 years performed Hanon Exercise N°1 from memory under four different conditions: (1) normal (normal sensory feedback); (2) closed fallboard (altered haptic and auditory feedback); (3) blindfolded (altered visual feedback); and (4) combined (blindfolded and closed fallboard; altered haptic, auditory, and visual feedback). Performance errors were quantified based on a video analysis of the performances. Results indicated that compared with normal performance, participants made significantly more note errors in the blindfolded condition and more bar-adding errors per trial in the closed fallboard condition. The comparison between the normal condition and the three altered sensory feedback conditions revealed the impact of altering sensory feedback in musical performance. These findings are discussed in the context of music learning.

Exploring the relationships among music performance anxiety, teaching anxiety, and self-efficacy of Chinese preservice music teachers.

This quantitative study aimed to explore the relationships among music performance anxiety (MPA), teacher anxiety (TA), and self-efficacy (SE) through a survey study of Chinese preservice music teachers (N = 237). We also examined gender, grade, primary instrument, secondary instrument, music learning time length, and time spent in four activities: peer teaching, practicum, internship, and private teaching as potential predictors of MPA, TA, and SE. Results indicated that the higher the self-efficacy, the lower music performance anxiety and teaching anxiety; Simultaneously, the increased music performance anxiety was associated with an increased teaching anxiety. Partial correlation results indicated a significant but negative correlation between TA and SE with MPA controlled. Teaching anxiety, followed by primary piano, was the strongest predictor of MPA. MPA, followed by SE and peer teaching, was the strongest predictor of TA. TA, followed by grade level, was the strongest predictor of SE. The results from the multivariate analysis of variance revealed that the SE of male preservice music teachers were significantly higher than their female counterparts. As a study implication, music teacher educators may consider interventions and support mechanisms that address both types of anxiety simultaneously to improve overall teacher preparedness.

Focus of attention in musical learning and music performance: a systematic review and discussion of focus instructions and outcome measures.

The topic of attentional focus (focus of attention, FOA) in musical learning and performance has recently received increasing interest, as the growing number of empirical studies inspired by the established FOA paradigm in sports by Wulf and colleagues in 1998. The current systematical review aims at collecting, abstracting, and categorizing relevant data to show which kinds of FOA instructions were applied in experimental designs and what kinds of dependent variables were used to measure the effects of FOA instruction on musical performance. The three main inclusion criteria in the selection process were experimental design, detailed descriptions of FOA instructions, and outcome measures (OMs). A systematic search was conducted with a complex search term in four scientific databases in March 2023. For presenting and synthesizing results, we used data collection and an inductive-deductive data categorization. Fifteen studies with a total sample size of 401 participants were included out of 387 records initially identified. We collected 53 different FOA instruction citations from the 15 studies and classified them into 9 FOA subcategories, of which the most applied were bodily focus (21%), sound focus (15%), and visual focus (14%). Selected studies used 63 OMs that were abstracted to 10 different OM categories with expert ratings (27%) and acoustical analysis (22%) as the most applied dependent variables. Data categorization and abstraction of additional study information show multiple combinations of FOA instructions, OMs, participants' instruments and expertise, and musical tasks. Finally, studies show no consistent results of superiority of either external or internal or otherwise different FOA considering positive effects on musical performance. Limitations of the review lie in the small study sample, possible criticism of applied eligibility criteria, and subjectivity of data categorization. We propose a research agenda with a more exploratory approach that comprehensively and qualitatively examines the dimensions of musical goals to create a database that could provide a foundation for developing a music-specific FOA model.

Intelligent Construction of University Music Education Teaching System Based on Artificial Intelligence Technology

The university music education teaching system plays a vital role in nurturing aspiring musicians and music enthusiasts by providing a comprehensive framework for musical learning and development. This system typically encompasses a diverse range of courses, workshops, and performance opportunities designed to cultivate students' musical talents, theoretical knowledge, and practical skills. Through a combination of classroom instruction, ensemble rehearsals, private lessons, and hands-on experiences, students receive a well-rounded musical education that covers various genres, styles, and traditions. Moreover, university music education teaching systems often incorporate state-of-the-art facilities, including rehearsal rooms, recording studios, and performance venues, to support students' artistic growth and creative expression. This paper presents an innovative approach to the intelligent construction of university music education teaching systems, leveraging artificial intelligence (AI) technology with Intelligent Fuzzy Regression Classification (IFRC). Recognizing the complexity and diversity of music education, this research aims to optimize teaching methodologies and enhance learning outcomes through AI-driven strategies. The proposed approach integrates AI technology, particularly IFRC, into the design and implementation of university music education teaching systems. IFRC combines fuzzy logic with regression analysis and classification techniques to model and predict complex relationships within music education datasets, enabling the system to adapt and respond dynamically to student needs and preferences. The IFRC-enhanced teaching system can generate personalized learning pathways, recommend tailored resources, and provide real-time feedback to students and instructors alike. This intelligent adaptation to individual learning styles and progress fosters a more engaging, effective, and inclusive music education environment. The IFRC-enhanced teaching system achieves an average improvement of 25% in student performance compared to traditional teaching methods. Moreover, specific musical skills, such as sight-reading, ear training, and music theory comprehension, exhibit notable enhancements, with average score increases of 30%, 20%, and 35%, respectively.

Integrating Narrative Characters in Early Childhood Music Learning: A Study of Mozart Mouse and Beethoven Bear Impact on Early Learners

Integrating Narrative Characters in Early Childhood Music Learning: A Study of Mozart Mouse and Beethoven Bear Impact on Early Learners