Learning Factors for TIMSS Math Performance Evidenced Through Machine Learning in the UAE

A Nadaf, S Monroe, S Chandran, X Miao - International Conference on …, 2022 - Springer
Understanding how the UAE K12 education system performs with data-driven evidence is
key to inform better policy making to support UAE vision to upskill human capital growth for …

Evidence and Promises of AI Predictions to Understand Student Approaches to Math Learning in Abu Dhabi K12 Public Schools

X Miao, PK Mishra, A Nadaf - Gulf Education and Social Policy …, 2021 - knepublishing.com
Transforming the education system and building highly skilled human capital for a
sustainable and competitive knowledge economy have been on the UAE's top policy …

Interpretable Machine Learning Models for PISA Results in Mathematics

I Gómez-Talal, L Bote-Curiel… - Available at SSRN … - papers.ssrn.com
Abstract The Programme for International Student Assessment (PISA) 2022 provides a
canvas to explore educational achievements across the globe. Our study focuses on Spain's …

[PDF][PDF] IMPACT OF INSTRUCTIONAL APPROACH ON MATHEMATICAL REASONING AND SELF-EFFICACY BELIEFS: A BAYESIAN ANALYSIS FOR VARIABLE …

RI Quintero-Sánchez, VV Pineda-Romero - researchgate.net
Instructional and assessment approaches play a fundamental role in the effectiveness of
mathematics education. Literature is well-stocked with studies confirming that teachers need …

[PDF][PDF] Interpretable-machine-learning evidence for importance and optimum of learning time

A Nadaf, S Eliëns, X Miao - International Journal of Information and …, 2021 - ijiet.org
This study uses a machine learning technique, a boosted tree model, to relate the student
cognitive achievement in the 2018 data from the Programme of International Student …

The mediating role of learning analytics to improve student academic performance

S Kosasi, U Kasma, IDAE Yuliani - 2020 2nd International …, 2020 - ieeexplore.ieee.org
Recent indicators of the success of every college graduate still refer to the cumulative
academic achievement index. The era of disruption of the digitalization of education has …

Leveraging Artificial Intelligence to Predict Student Performance: A Comparative Machine Learning Approach

A Maulana, GM Idroes, P Kemala… - Journal of …, 2023 - heca-analitika.com
This study explores the application of artificial intelligence (AI) and machine learning (ML) in
predicting high school student performance during the transition to university. Recognizing …

Finding the contextual impacts on Students' Mathematical performance using a Machine Learning-based Approach

Z Khoudi, M Nachaoui, S Lyaqini - … JOURNAL: A PUBLICATION OF …, 2024 - real.mtak.hu
An extensive dataset for examining Moroccan eighth-grade pupils' mathematical prowess
was made available by the 2019 Trends in Mathematics and Science Study (TIMSS). The …

An interactive learning analytics tool to support higher education stakeholder to more explain and interpret predictive student's failure or success

B KHELIL, SIDA SAHD - 2023 - dspace.univ-tiaret.dz
Learning Analytics has great potential for improving student learning and pre-diction making
about the probability of their success or failure. However, these machine learning algorithms …

Predicting and interpreting student performance using ensemble models and shapley additive explanations

H Sahlaoui, A Nayyar, S Agoujil, MM Jaber - IEEE Access, 2021 - ieeexplore.ieee.org
In several areas, including education, the use of machine learning, such as artificial neural
networks, has resulted in significant improvements in predicting tasks. The opacity of these …