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Designing and evaluating a big data analytics approach for predicting students’ success factors

Effectiveness of data augmentation to predict students at risk using deep learning algorithms

An innovative big data analytics method for decision makers in the higher education sector to address student attrition

  • Creator: Fahd, Kiran
  • Resource Type: thesis
  • Date: 2022

Knowledge graph model development for knowledge discovery in dementia research using cognitive scripting and next-generation graph-based database: a design science research approach

An innovative framework for online examination in a higher education setting : a response to the COVID-19 crisis

Application of machine learning in higher education to assess student academic performance, at-risk, and attrition: A meta-analysis of literature

Integrating design science research and design based research frameworks for developing education support systems

Predicting student performance in a blended learning environment using learning management system interaction data

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