Modelling Academic Performance: A Case Study on Engineering Courses
Resumo
Engineering education is of great importance to train future leaders and innovators in finding solutions for problems arising in our fast changing world. Due to the challenging nature of en- gineering education, an alarming number of undergraduate engineering students do not move to degree completion in curricular planned timeframes [1]. [...]
Downloads
Referências
Alize J Trinquet et al. “Student Grade Prediction Based Upon Prerequisite Lab or Topic Course Performance”. In: (2018).
Zafar Iqbal et al. “Machine learning based student grade prediction: A case study”. In: arXiv preprint arXiv:1708.08744 (2017).
Peggy C Boylan-Ashraf and John R Haughery. “Failure Rates in Engineering: Does It Have to Do with Class Size?” In: 2018 ASEE Annual Conference & Exposition. 2018.
Castro Gbememali Hounmenou, Kossi Essona Gneyou, and Romain Lucas GLELE KAKAÏ. “A Formalism of the General Mathematical Expression of Multilayer Perceptron Neural Networks”. In: (2021).
Davide Chicco. “Ten quick tips for machine learning in computational biology”. In: BioData mining 10.1 (2017), pp. 1–17.
Diederik P. Kingma and Jimmy Ba. “Adam: A Method for Stochastic Optimization”. In: CoRR abs/1412.6980 (2015).
