Exploring music students' resistance to innovation as a moderator in the relationship between e‐learning adoption and academic performance.

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Title: Exploring music students' resistance to innovation as a moderator in the relationship between e‐learning adoption and academic performance.
Authors: Bai, Xueer1 (AUTHOR) 20210118@nuc.edu.cn
Source: Psychology in the Schools. Jun2024, Vol. 61 Issue 6, p2612-2633. 22p.
Subject Terms: *Music students, *Digital learning, *Chinese-speaking students, *Academic achievement, *Student attitudes, *Mobile learning
Geographic Terms: Beijing (China)
Abstract: A teaching strategy known as an "e‐learning system" involves the use of electronic technology to encourage and assist learning in a classroom setting. According to the increasing rise in the number of pupils using modern communication technologies, alterations to the e‐learning system are now feasible. The study aims to explore the relationship between e‐learning adoption, attitude, and academic performance in the regulations of students' resistance to innovation from the perspective of Chinese students. Recognizing the mediating impact of e‐learning adoption (ELAD) as well as the regulating function of resistance to innovation (RTI) is crucial for completely comprehending how e‐learning attitude (ELAT) influences music student performance (SP). The objective of this study is to find an association between ELAT and students' performance and to find out the association between ELAD and students' performance. A random sampling technique was utilized quantitatively. Data were collected from 293 music education students in China using a questionnaire method. The study obtained data were analyzed through descriptive statistics using SPSS statistical software. The research was conducted in Chinese music educational institutions in Beijing. PLS‐SEM stands for Partial Least Squares Structural Equation Modeling. It's a statistical method used for analyzing relationships between variables. Partial Least Squares (PLS) software is chosen for its versatility in handling complex relationships with small sample sizes. PLS is known for its ability to handle multicollinearity, making it a robust choice for research requiring accurate and stable predictions with limited data. The study analyzes the connection between music student performance and e‐learning attitude. The findings of the study indicate the regulating role of objections to innovation and the mediation effect of e‐learning adoption. The study suggests that a positive attitude toward e‐learning adoption enhances students' work performance. The findings underline the significance of ELAT and ELAD and offer useful policies for improving students' performance. Practitioner Points: Importance of e‐learning attitude (ELAT): Recognize the crucial role ELAT plays in influencing music student performance.Mediating Impact of e‐learning adoption (ELAD): Understand how ELAD mediates the relationship between ELAT and student performance.PLS‐SEM for Robust Analysis: Utilize Partial Least Squares Structural Equation Modeling for accurate analysis of complex relationships with small sample sizes in the context of music education. [ABSTRACT FROM AUTHOR]
Copyright of Psychology in the Schools is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Exploring music students' resistance to innovation as a moderator in the relationship between e‐learning adoption and academic performance.
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  Data: <searchLink fieldCode="AR" term="%22Bai%2C+Xueer%22">Bai, Xueer</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 20210118@nuc.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Psychology+in+the+Schools%22">Psychology in the Schools</searchLink>. Jun2024, Vol. 61 Issue 6, p2612-2633. 22p.
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  Data: *<searchLink fieldCode="DE" term="%22Music+students%22">Music students</searchLink><br />*<searchLink fieldCode="DE" term="%22Digital+learning%22">Digital learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Chinese-speaking+students%22">Chinese-speaking students</searchLink><br />*<searchLink fieldCode="DE" term="%22Academic+achievement%22">Academic achievement</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+attitudes%22">Student attitudes</searchLink><br />*<searchLink fieldCode="DE" term="%22Mobile+learning%22">Mobile learning</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Beijing+%28China%29%22">Beijing (China)</searchLink>
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  Label: Abstract
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  Data: A teaching strategy known as an "e‐learning system" involves the use of electronic technology to encourage and assist learning in a classroom setting. According to the increasing rise in the number of pupils using modern communication technologies, alterations to the e‐learning system are now feasible. The study aims to explore the relationship between e‐learning adoption, attitude, and academic performance in the regulations of students' resistance to innovation from the perspective of Chinese students. Recognizing the mediating impact of e‐learning adoption (ELAD) as well as the regulating function of resistance to innovation (RTI) is crucial for completely comprehending how e‐learning attitude (ELAT) influences music student performance (SP). The objective of this study is to find an association between ELAT and students' performance and to find out the association between ELAD and students' performance. A random sampling technique was utilized quantitatively. Data were collected from 293 music education students in China using a questionnaire method. The study obtained data were analyzed through descriptive statistics using SPSS statistical software. The research was conducted in Chinese music educational institutions in Beijing. PLS‐SEM stands for Partial Least Squares Structural Equation Modeling. It's a statistical method used for analyzing relationships between variables. Partial Least Squares (PLS) software is chosen for its versatility in handling complex relationships with small sample sizes. PLS is known for its ability to handle multicollinearity, making it a robust choice for research requiring accurate and stable predictions with limited data. The study analyzes the connection between music student performance and e‐learning attitude. The findings of the study indicate the regulating role of objections to innovation and the mediation effect of e‐learning adoption. The study suggests that a positive attitude toward e‐learning adoption enhances students' work performance. The findings underline the significance of ELAT and ELAD and offer useful policies for improving students' performance. Practitioner Points: Importance of e‐learning attitude (ELAT): Recognize the crucial role ELAT plays in influencing music student performance.Mediating Impact of e‐learning adoption (ELAD): Understand how ELAD mediates the relationship between ELAT and student performance.PLS‐SEM for Robust Analysis: Utilize Partial Least Squares Structural Equation Modeling for accurate analysis of complex relationships with small sample sizes in the context of music education. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Psychology in the Schools is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/pits.23181
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      – Code: eng
        Text: English
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        PageCount: 22
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    Subjects:
      – SubjectFull: Music students
        Type: general
      – SubjectFull: Digital learning
        Type: general
      – SubjectFull: Chinese-speaking students
        Type: general
      – SubjectFull: Academic achievement
        Type: general
      – SubjectFull: Student attitudes
        Type: general
      – SubjectFull: Mobile learning
        Type: general
      – SubjectFull: Beijing (China)
        Type: general
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      – TitleFull: Exploring music students' resistance to innovation as a moderator in the relationship between e‐learning adoption and academic performance.
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            – D: 01
              M: 06
              Text: Jun2024
              Type: published
              Y: 2024
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