Concepedia

Data-informed Completion Analytics

Data-Informed Completion Analytics is a scholarly framework that systematically integrates empirical educational data with analytical methodologies to identify, monitor, and predict student progression and completion patterns within academic institutions, distinguishing itself through its reliance on evidence-based decision-making to inform targeted interventions and institutional policy.

1

Publications

16

Citations

3

Authors

1

Institutions

Publications per year

2017–2026

0

Parents

Publications

1

1–2 of 1

Authors

3

  1. GL
    Gregory L. Heileman

    University of New Mexico, United States

    1 publications · 16 citations

    1

    h-index

  2. CT
    Chaouki T. Abdallah

    University of New Mexico, United States

    1 publications · 16 citations

    1

    h-index

  3. TB
    Terry Babbitt

    University of New Mexico, United States

    1 publications · 16 citations

    1

    h-index

  4. BL
    Benjamin Lascaud

    ConocoPhillips (Canada), Canada

    1 publications · 10 citations

    0

    h-index

  5. HZ
    Hui Zhou

    ConocoPhillips (Canada), Canada

    1 publications · 10 citations

    0

    h-index

1–5 of 3

Institutions

1

  1. University of New Mexico

    Albuquerque, United States

    1 h-index

    1 publications

    16 citations

  2. ConocoPhillips (Canada)

    Calgary, Canada

    1 publications

    10 citations

1–2 of 1

Venues

  1. Change The Magazine of Higher Learning

    1 publications · 16 citations

    1

    h-index

1–2