Exploring the Impact of Predictive Analytics and AI in STEM Education
The demand for STEM education is rising globally, yet high attrition rates among underrepresented groups remain a significant challenge. This paper explores the potential of predictive analytics and learning analytics (LA) to enhance student retention and success in STEM fields. Predictive analytics...
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| Format: | Article |
| Language: | English |
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The Institute of Research and Community Services, Universitas Terbuka
2025-05-01
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| Series: | International Journal of Research in STEM Education |
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| Online Access: | https://jurnal-fkip.ut.ac.id/index.php/ijrse/article/view/1758 |
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| _version_ | 1849727274845208576 |
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| author | Tai Ki Kim |
| author_facet | Tai Ki Kim |
| author_sort | Tai Ki Kim |
| collection | DOAJ |
| description | The demand for STEM education is rising globally, yet high attrition rates among underrepresented groups remain a significant challenge. This paper explores the potential of predictive analytics and learning analytics (LA) to enhance student retention and success in STEM fields. Predictive analytics, leveraging vast datasets including academic performance, engagement metrics, and demographic variables, allows educators to identify at-risk students early and implement targeted interventions. Recent advancements in artificial intelligence (AI) have further transformed these predictive models, enabling real-time adaptation of learning materials and personalized support. However, ethical concerns regarding data privacy, algorithmic bias, and equitable access must be addressed to ensure all students benefit from these innovations. Through a systematic literature review of studies published between 2020 and 2023, this paper highlights the effectiveness of predictive analytics in improving STEM education outcomes while emphasizing the importance of inclusive practices. Ultimately, this research underscores the potential of predictive analytics to revolutionize STEM education, fostering a more equitable and supportive learning environment for all students.
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| format | Article |
| id | doaj-art-c8bc860d241d45c29caae9a2addf33d6 |
| institution | DOAJ |
| issn | 2721-3242 2721-2904 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | The Institute of Research and Community Services, Universitas Terbuka |
| record_format | Article |
| series | International Journal of Research in STEM Education |
| spelling | doaj-art-c8bc860d241d45c29caae9a2addf33d62025-08-20T03:09:54ZengThe Institute of Research and Community Services, Universitas TerbukaInternational Journal of Research in STEM Education2721-32422721-29042025-05-017110.33830/ijrse.v7i1.1758Exploring the Impact of Predictive Analytics and AI in STEM EducationTai Ki Kim0The Institute for Educational Research, Yonsei UniversityThe demand for STEM education is rising globally, yet high attrition rates among underrepresented groups remain a significant challenge. This paper explores the potential of predictive analytics and learning analytics (LA) to enhance student retention and success in STEM fields. Predictive analytics, leveraging vast datasets including academic performance, engagement metrics, and demographic variables, allows educators to identify at-risk students early and implement targeted interventions. Recent advancements in artificial intelligence (AI) have further transformed these predictive models, enabling real-time adaptation of learning materials and personalized support. However, ethical concerns regarding data privacy, algorithmic bias, and equitable access must be addressed to ensure all students benefit from these innovations. Through a systematic literature review of studies published between 2020 and 2023, this paper highlights the effectiveness of predictive analytics in improving STEM education outcomes while emphasizing the importance of inclusive practices. Ultimately, this research underscores the potential of predictive analytics to revolutionize STEM education, fostering a more equitable and supportive learning environment for all students. https://jurnal-fkip.ut.ac.id/index.php/ijrse/article/view/1758STEMPredictive AnalyticsLearning AnalyticsPersonalized LearningAI |
| spellingShingle | Tai Ki Kim Exploring the Impact of Predictive Analytics and AI in STEM Education International Journal of Research in STEM Education STEM Predictive Analytics Learning Analytics Personalized Learning AI |
| title | Exploring the Impact of Predictive Analytics and AI in STEM Education |
| title_full | Exploring the Impact of Predictive Analytics and AI in STEM Education |
| title_fullStr | Exploring the Impact of Predictive Analytics and AI in STEM Education |
| title_full_unstemmed | Exploring the Impact of Predictive Analytics and AI in STEM Education |
| title_short | Exploring the Impact of Predictive Analytics and AI in STEM Education |
| title_sort | exploring the impact of predictive analytics and ai in stem education |
| topic | STEM Predictive Analytics Learning Analytics Personalized Learning AI |
| url | https://jurnal-fkip.ut.ac.id/index.php/ijrse/article/view/1758 |
| work_keys_str_mv | AT taikikim exploringtheimpactofpredictiveanalyticsandaiinstemeducation |