Enrollment Predictive Analytics

Enrollment Predictive Analytics is a computational methodology that applies statistical modeling and machine learning techniques to historical and contextual data to forecast student enrollment trends, distinguishing itself by its focus on anticipatory decision support in educational planning.

44

Publications

4.9K

Citations

119

Authors

59

Institutions

Publications per year

2017–2026

16

Authors

119

  1. WC
    William C. Weiler

    Stanford University, United States

    2 publications · 22 citations

    2

    h-index

  2. QS
    Qiang Song

    Tsinghua University, China

    2 publications · 2K citations

    2

    h-index

  3. BS
    Brad S. Chissom

    University of Alabama, United States

    2 publications · 2K citations

    2

    h-index

  4. NT
    Neil T. Heffernan

    Worcester Polytechnic Institute, United States

    2 publications · 130 citations

    2

    h-index

  5. IK
    I‐Hong Kuo

    National Taiwan University of Science and Technology, Taiwan

    2 publications · 324 citations

    2

    h-index

1–5 of 119

Venues

  1. Expert Systems with Applications

    4 publications · 434 citations

    4

    h-index

  2. Educational Data Mining

    Conference · 3 publications · 153 citations

    3

    h-index

  3. Fuzzy Sets and Systems

    3 publications · 3.2K citations

    3

    h-index

  4. New Directions for Institutional Research

    NDIR · 3 publications · 100 citations

    3

    h-index

  5. The Journal of Higher Education

    JHE · 2 publications · 22 citations

    2

    h-index

1–5