Student Predictive Analysis to Determine Program Interventions and Improve Student Performance

• In Event: Marriott Roundtable Session Two
  In Roundtable Session: Quality, Rigor, and Validity in Mixed-Methods Research (Table 3)

Abstract

With the prevalent use of Artificial Intelligence, the Academic Quality (AQ) unit of the Office of Strategic Planning and Academic Quality at the National Institute of Education embarked on a developmental project: creating a prototype Student Predictive Model. This Model is intended to be used as one of the ways to measure quality of NIE’s programmes and provide opportunity for NIE to identify areas for improvement. In addition, the Model would enable the programme offices to channel intervention efforts through the Model’s identification of at-risk students. The Model would be complementary to AQ’s existing measures of quality such as longitudinal and cross-sectional quantitative and qualitative studies.

Authors

• Nenny Aryanti Noorman, National Institute of Education - Nanyang Technological University
  Presenting Author

• Sean Chen Liu, National Institute of Education - Nanyang Technological University
  Presenting Author

• David Ng, Nanyang Technological University - National Institute of Education
  Non-Presenting Author