Engagement with Music Technology in Special Educational Settings for Children with Disabilities ^†

Abstract

In line with the broader learning of integrating technology into science, there is growing demand for educational learning to apply electronic technologies in educational practice. Despite a handful of accounts indicating the advantages of this equipment and these tools, objective empirical research on their role in learning and their application in the learning process is lacking. Over the past ten years, studies have proven the Holistic Music Educational Approach for Young Children (HMEAYC) to be an effective method to assist in the learning and development of children with special needs. HMEAYC and technology integrated into instruction are both learning modes that expect learners to achieve learning orientation through musical expression. This study aimed to measure children with specific needs’ language comprehension and self-conduct abilities when HMEAYC was combined with technology integrated into instruction in curriculum design. The research, conducted at an early-intervention center in central Taiwan, included 389 children aged between 4 and 6 years old with specific needs. These participants’ traits of learning and developing more slowly than typical children of the same age were referred to as “specific needs” for this study. They all participated in one 40 min session per week for a total of 16 weeks. The research results showed that HMEAYC combined with music technology could enhance the development of language comprehension and the self-conduct of children with specific needs.

1. Introduction

Over the past ten years, research has proven the Holistic Music Educational Approach for Young Children (HMEAYC) to be an effective method for assisting in the learning and development of children with special needs [1,2,3,4]. The musical activity evidence base assists with early language and behavior development. Music can enhance learning motivation, which helps induce a different learning trigger whereby music has a positive effect on growth, making learning lively and dynamic. This article begins with an overview of HMEAYC and music technology in children with specific needs’ education today, its history, and its current status. The applications of science and technology, multi-sensory equipment, and traditional instruments are mentioned. Technology equipment in music courses designed for assisted instruction is established. Research on young children and music technology is conducted, with references to work performed on integrating technology into science.

1.1. Child Music Course Models in Taiwan

For over 20 years in Taiwan, HMEAYC has commonly been accepted as an excellent practice for music education in the area. As a model, HMEAYC encourages training and experience in early childhood music [1] and shows that music is an excellent medium for young children’s learning development [2,3]. Previous studies have shown positive effects in implementation experiments on the development of young children with developmental delays; the interaction of preschool children with developmental delays with musical technology instruments, whereby they learn the effectiveness of comprehension, physical movement, and social skills, can be improved by musical performances. Music addresses difficulties in children with disabilities, such as emotional, health, social interaction, intellectual, language, and creative [4]. Singing, rhymes, musical games, and instruments are all effective ways for young children to learn [5,6,7,8]. A significant finding is that HMEAYC positively affects young children with developmental delays.

Reviewing the research in the literature means finding positive results in learning efficiency [9], including improvements in language communication and physical and emotional abilities in children with special needs [5,10]. In addition to improvements in children with developmental delays, positive outcomes have been found in learning effectiveness through HMEAYC for all young children [11]. It is confirmed by research studies conducted on young children with developmental delays to enhance language comprehension and self-control. In other studies, the focus is on establishing particular musical elements, such as rhythmic and movement performance [12,13,14] and music image technology [10], to meet rehabilitation and treatment needs. Another evidence-based finding regarding the issue of children with developmental delays was that music could best enable children to process information visually. On a pragmatic note, the special preschool needs environment represents an obtainable source field, making opportunities to integrate music technology into education for young children with special needs easily accessible.

With the growth of research emphasizing the importance of early education for children with specific needs, educators face challenges in incorporating teaching practices. These practices focus less on the information technology integrated into instruction. HMEAYC and technology integrated into instruction are both learning modes that expect learners to achieve learning orientation through musical expression. This study aimed to measure children with specific needs’ language comprehension and self-conduct abilities when HMEAYC was combined with technology integrated into instruction in curriculum design.

1.2. Current Study on Young Children with Developmental Delays in Music Technology

HMEAYC is a decades-old innovative education model that combines modern science and technology, multi-sensory equipment, and traditional instruments with creative music [9,15]. HMEAYC is a positive-enhancement course model. Its effects on the learning levels of young children with developmental delays were investigated by monitoring their participation in musical activities. Children with developmental delays improved their learning process via rhythmic and movement performance, demonstrating that music with technology effectively promotes learning [16,17,18,19,20].

2. Method

This study was designed with a pretest–post-test control group quasi-experimental research method. The research, conducted at an early-intervention center in central Taiwan, included 389 children aged between 4 and 6 years old with specific needs. These participants’ traits of learning and developing more slowly than typical children of the same age were referred to as “specific needs” for this study. All the young children with developmental delays from one group were used in the experimental group, and all participants from the other group were determined to be the control group. The music image technology embedded into the HMEAYC course was utilized with the experimental group for 40 min weekly over 16 weeks.

The study was conducted in an educational institution in central Taiwan in a non-profit early-intervention center that frequently received young children with progression through predictable developmental phases of varying degrees, such as developmental delay. Gay et al. proposed that different student groups be selected as the experimental and control groups to reduce the interaction between the groups during the experimental intervention process and increase internal validity. All children between 4 and 6 years with developmental delays in the group in which the first author worked as a music teacher were chosen as the experimental group. All the participants in the other group were selected as the control group. In the research design, to examine participants’ experiences in the experimental and control group through quantitative data, a structured assessment form was used.

3. Findings and Results

This study is based on the HMEAYC and technology integrated into instruction learning modes. Seven indices were selected for overall model evaluation. In the chi-square test, the p-value = 0.000. In this study, χ2 and the df ratio of the model are smaller than 5 (3.96). The GFI and AGFI of this model are 0.95, respectively. In this study, the RMSEA is 0.087. The CFI acceptable standard should be >0.9, and CFI for this study model is 0.95. The above results indicate that this study model is acceptable (Figure 1 and

Table 1. Empirical results of research hypotheses on language comprehension (LC).

Path Relationship	Path Coefficients	Support for Hypothesis
1. LC→ look at each other properly when talking.	0.84	Yes
2. LC→ listens carefully when others speak to him.	0.76	Yes
3. LC→ could adequately express their inner thoughts.	0.76	Yes
4. LC→ could respond to the content of the conversation.	0.70	Yes
5. LC→ could actively participate in group activities.	0.83	Yes
6. LC→ could relay the matters explained by teachers.	0.89	Yes
7. LC→ could refuse the improper request of others.	0.87	Yes
8. SC→ could maintain the cleanliness of personal appearance.	0.87	Yes
9. SC→ will dress according to the weather changes.	0.88	Yes
10. SC→ could adequately manage their belongings.	0.85	Yes
11. SC→ when the requirements are unmet immediately, appropriate measures will be taken to deal with them.	0.87	Yes
12. SC→ could cooperate with the daily routine of kindergarten.	0.89	Yes
13. SC→ ability to work independently.	0.87	Yes
14. SC→ try to do it by yourself before asking for help.	0.89	Yes
15. SC→ can deal with the disruptive behavior of others.	0.88	Yes

).

The study results are divided into two sections. Language comprehension and self-conduct are learning path coefficients, and music technology’s effects account for 72% of their variance. The estimated reliability of the music technology’s effects on learning in children with specific needs is 0.72. The squared multiple correlations can be interpreted as follows.

• First, in Hypothesis 1, the path value, 0.84 (p < 0.05), reaches a significant level, indicating support for the hypothesis that participants have more positive scores for “look at each other properly when talking.”
• The path value of Hypothesis 2, 0.76 (p < 0.05), does reach a significant level, and it gives support to the hypothesis that a participants have more positive “listens carefully when others speak to him” scores.
• In Hypothesis 3, the path value, 0.76 (p < 0.05), reaches a significant level. The hypothesis “could adequately express their inner thoughts” is supported, with more participants receiving positive scores in both learning modes.
• In Hypothesis 4, the path value, 0.70 (p < 0.05), does reach a significant level, and it gives support to the hypothesis of more positive “could respond to the content of the conversation” scores.
• In Hypothesis 5, the path value, 0.83 (p < 0.05), does reach a significant level, and it gives support to the hypothesis of more positive “could actively participate in group activities” scores.
• The path value of Hypothesis 6, 0.89 (p < 0.05), does reach a significant level and gives support to the hypothesis of more positive “could relay the matters explained by teachers” scores.
• In Hypothesis 7, the path value, 0.87 (p < 0.05), reaches a significant level, indicating support for the hypothesis that participants have more positive “could refuse the improper request of others” scores.
• Then, in Hypothesis 8, the path value, 0.87 (p < 0.05), reaches a significant level, indicating support for the hypothesis that participants receive more positive scores for “could maintain the cleanliness of personal appearance.”
• The path value of Hypothesis 9, 0.88 (p < 0.05), does reach a significant level and gives support to the hypothesis of more positive “will dress according to the weather changes” scores.
• In Hypothesis 10, the path value, 0.85 (p < 0.05), reaches a significant level.
• In Hypothesis 11, the path value, 0.87 (p < 0.05), does reach a considerable level, and it gives support to the hypothesis of more positive “when the needs are unmet immediately, appropriate measures will be taken to deal with them” scores. The assumption “could adequately manage their belongings,” is supported, with more participants receiving positive scores and benefitting from both learning modes.
• In Hypothesis 12, the path value, 0.89 (p < 0.05), does reach a significant level, and it gives support to the hypothesis of more positive “could cooperate with the daily routine of kindergarten” scores.

4. Conclusions and Recommendations

This study demonstrates that the test depends on an observed variable called earning, which could be interpreted as an underlying ability (language comprehension and self-conduct) that is not directly observed. According to the model, performance in the two tests depends on this ability. The research results showed that HMEAYC combined with music technology could enhance the development of language comprehension and the self-conduct of children with specific needs.

5. Discussion and Conclusions

This research found that music image technology effectively promoted participants’ language comprehension. The results show that the model fit was adequate after adding error covariances between the pre- and post-tests in the hypothesis model for participants. The study suggests that music image technology significantly increased scores for young children with developmental delays in HMEAYC.

This study proved that there was an increase in the experimental group’s language comprehension in the music image technology post-test scores. The post-test results were higher for young children with developmental delays in the control group than the pretest results. When the groups were compared, more significant improvements were observed in language comprehension in the experimental group due to the experimental intervention (the music image technology). In the end, all measurements showed a significant relationship with comprehension. The results of this study demonstrated that more activity using music technology related to educational practice is needed. At the same time, attention is given to methods and strategies to make more music technology accessible to various learners [2,7,17].

As a result of the experiments, we concluded that the significant relationships between language comprehension and self-control in the pretest and post-test are consistent with previous studies. From a language comprehension perspective, it was established that music image technology [4,5,9,12,14,18] was influential in language comprehension and promoted higher scores in the experimental group than the control group with statistical significance. This study’s findings resemble previous experimental participants’ findings regarding music technology in the language learning literature.

When participants understand the group rule, they demonstrate group-normative behavior in musical activities. As can be seen from this study, music is an excellent medium for young children’s learning development [1,4,12,13]. The participants showed that the music image technology led to a positive change in learning behaviors, increased course engagement, and positive changes in interactive communication [10,11,20]. Within the limitations of these results, music image technology could likely contribute to evidence of language comprehension development in young children with developmental delays.