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A Data-Driven Precision Teaching Intervention Mechanism to Improve Secondary School Students' Learning Effectiveness

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Title: A Data-Driven Precision Teaching Intervention Mechanism to Improve Secondary School Students' Learning Effectiveness
Language: English
Authors: Yu-Jie Wang, Chang-Lei Gao, Xin-Dong Ye (ORCID 0000-0003-4187-0160)
Source: Education and Information Technologies. 2024 29(9):11645-11673.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 29
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Secondary Education
Elementary Education
Grade 7
Junior High Schools
Middle Schools
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement, Secondary School Students, Instructional Improvement, Learning Analytics, Prediction, Academic Achievement, Outcomes of Education, Grade 7, Data Analysis
DOI: 10.1007/s10639-023-12238-x
ISSN: 1360-2357
1573-7608
Abstract: The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and more attention should be paid to primary and secondary school students. This study proposed a data-driven precision teaching intervention mechanism combining EDM and LA technologies. The proposed mechanism aims to assist teachers in predicting students' academic performance and implementing corresponding interventions. This approach enables early warnings and reminders for students in crisis, and offers teaching assistance and support tailored to students at different levels. A quasi-experimental design was employed to examine the impact of the data-driven precision teaching intervention mechanism on secondary school students' learning outcomes. A total of 142 seventh-grade students participated in the intervention experiment, with an experimental group (50) receiving the data-driven precision teaching intervention, control group2 (48) receiving a group intervention stratified by teacher experience, and control group1 (44) receiving a traditional group intervention. Posttest data were collected after three rounds of intervention. Compared to the two control groups, students in the experimental group demonstrated superior academic achievement, intrinsic motivation, self-efficacy, and meta-cognitive awareness. These findings indicate that the data-driven precision teaching intervention approach positively impacted students' academic development, and effectively promoted their personalized learning. The findings provide pedagogical insights into the application of EDM in conjunction with LA prediction and actionable interventions.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1430146
Database: ERIC
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  Data: A Data-Driven Precision Teaching Intervention Mechanism to Improve Secondary School Students' Learning Effectiveness
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  Data: <searchLink fieldCode="AR" term="%22Yu-Jie+Wang%22">Yu-Jie Wang</searchLink><br /><searchLink fieldCode="AR" term="%22Chang-Lei+Gao%22">Chang-Lei Gao</searchLink><br /><searchLink fieldCode="AR" term="%22Xin-Dong+Ye%22">Xin-Dong Ye</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-4187-0160">0000-0003-4187-0160</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Education+and+Information+Technologies%22"><i>Education and Information Technologies</i></searchLink>. 2024 29(9):11645-11673.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: <searchLink fieldCode="EL" term="%22Secondary+Education%22">Secondary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Elementary+Education%22">Elementary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+7%22">Grade 7</searchLink><br /><searchLink fieldCode="EL" term="%22Junior+High+Schools%22">Junior High Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Middle+Schools%22">Middle Schools</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Precision+Teaching%22">Precision Teaching</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Use%22">Data Use</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Improvement%22">Educational Improvement</searchLink><br /><searchLink fieldCode="DE" term="%22Secondary+School+Students%22">Secondary School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Improvement%22">Instructional Improvement</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Analytics%22">Learning Analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction%22">Prediction</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Outcomes+of+Education%22">Outcomes of Education</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+7%22">Grade 7</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Analysis%22">Data Analysis</searchLink>
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  Data: 10.1007/s10639-023-12238-x
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  Data: 1360-2357<br />1573-7608
– Name: Abstract
  Label: Abstract
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  Data: The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and more attention should be paid to primary and secondary school students. This study proposed a data-driven precision teaching intervention mechanism combining EDM and LA technologies. The proposed mechanism aims to assist teachers in predicting students' academic performance and implementing corresponding interventions. This approach enables early warnings and reminders for students in crisis, and offers teaching assistance and support tailored to students at different levels. A quasi-experimental design was employed to examine the impact of the data-driven precision teaching intervention mechanism on secondary school students' learning outcomes. A total of 142 seventh-grade students participated in the intervention experiment, with an experimental group (50) receiving the data-driven precision teaching intervention, control group2 (48) receiving a group intervention stratified by teacher experience, and control group1 (44) receiving a traditional group intervention. Posttest data were collected after three rounds of intervention. Compared to the two control groups, students in the experimental group demonstrated superior academic achievement, intrinsic motivation, self-efficacy, and meta-cognitive awareness. These findings indicate that the data-driven precision teaching intervention approach positively impacted students' academic development, and effectively promoted their personalized learning. The findings provide pedagogical insights into the application of EDM in conjunction with LA prediction and actionable interventions.
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        Value: 10.1007/s10639-023-12238-x
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      – Text: English
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    Subjects:
      – SubjectFull: Precision Teaching
        Type: general
      – SubjectFull: Data Use
        Type: general
      – SubjectFull: Intervention
        Type: general
      – SubjectFull: Educational Improvement
        Type: general
      – SubjectFull: Secondary School Students
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      – SubjectFull: Instructional Improvement
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      – SubjectFull: Learning Analytics
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      – SubjectFull: Prediction
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      – SubjectFull: Academic Achievement
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      – SubjectFull: Outcomes of Education
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      – SubjectFull: Grade 7
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      – SubjectFull: Data Analysis
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