Showing 1,101 - 1,120 results of 1,747 for search 'Machine learning education model', query time: 0.19s Refine Results
  1. 1101
  2. 1102
  3. 1103

    Benefits and risks of ChatGPT in future education by Baltezarević Radoslav, Baltezarević Ivana

    Published 2024-01-01
    “…ChatGPT analyses enormous volumes of data using machine learning (ML) to offer the necessary content and simply respond to queries in a conversational manner. …”
    Get full text
    Article
  4. 1104
  5. 1105

    Workplace Preference Analytics Among Graduates by Sin-Yin Ong, Choo-Yee Ting, Hui-Ngo Goh, Albert Quek, Chin-Leei Cham

    Published 2023-09-01
    “…To address this challenge, this study has employed feature selection and machine learning approach to help graduates identify desired company type and sector based on their preferences and preferred location. …”
    Get full text
    Article
  6. 1106
  7. 1107
  8. 1108
  9. 1109
  10. 1110
  11. 1111
  12. 1112
  13. 1113
  14. 1114

    Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding by Milan Lazic, Earl Woodruff, Jenny Jun

    Published 2025-01-01
    “…AU patterns associated with each phase were then identified through the application of six supervised machine learning algorithms. Distinct AU patterns were found for all five phases, with gradient boosting machine and random forest models achieving the highest predictive accuracy. …”
    Get full text
    Article
  15. 1115

    Readability Formulas for Elementary School Texts in Mexican Spanish by Daniel Fajardo-Delgado, Lino Rodriguez-Coayahuitl, María Guadalupe Sánchez-Cervantes, Miguel Ángel Álvarez-Carmona, Ansel Y. Rodríguez-González

    Published 2025-06-01
    “…These findings underscore the potential of combining machine learning with interpretable modeling techniques and highlight the importance of linguistic and curricular adaptation in readability assessment tools.…”
    Get full text
    Article
  16. 1116

    Decoding disease–specific ageing mechanisms through pathway-level epigenetic clock: insights from multi-cohort validationResearch in context by Pan Li, Jijun Zhu, Shenghan Wang, Haowen Zhuang, Shunjie Zhang, Zhongting Huang, Fuqiang Cai, Zhijian Song, Yuxin Liu, Weixin Liu, Sebastian Freidel, Sijia Wang, Emanuel Schwarz, Junfang Chen

    Published 2025-08-01
    “…Methods: We conducted a cross-sectional study using genome-wide DNA methylation data from 10,615 individuals across 19 cohorts and 3413 Han Chinese participants, along with transcriptomic data from 3384 samples. A two-stage machine learning model aggregated CpG sites into GO or KEGG pathway-level features to predict chronological age. …”
    Get full text
    Article
  17. 1117
  18. 1118
  19. 1119
  20. 1120