Overview
Our research endeavors are driven by a passion for capacity building for the full range of human development, for an education system overhaul and to leverage technology and AI to improve student’s learning creatively.
Our research projects are dedicated to evidence-based problem solving in education, integrating research findings and learning sciences into product and service innovation to improve learning outcomes, and understanding product impact on education stakeholders. We see our research advancing us as a thought leader, guiding and influencing the education system and the AIED private sector in the UAE and the broader MENA region.
Where Generative AI Fits Within and in Addition to Existing AI K12 Education Interactions: Industry and Research Perspectives
Xin Miao Richard Brooker Samantha Monroe
Recent developments in Generative AI have led capital market, industry, and research institutions to explore its education applications as solutions to K12 challenges. However, there is currently a gap of analytical review of these trends. This chapter attempts to review and analyze predominant Generative AI education efforts within and in addition to existing AI education (...)
View Details
Adoption of Artificial Intelligence in Schools: Unveiling Factors Influencing Teachers‘ Engagement
Mutlu Cukurova (University College London) Xin Miao Richard Brooker
The slow adoption of AI-based adaptive learning platforms in schools prompts concerns about identifying and predicting factors influencing teachers' engagement, leading to the development of a reliable instrument measuring holistic adoption factors; results reveal the importance of factors such as workload, ownership, trust, support mechanisms, and ethical considerations alongside knowledge, confidence, and product quality, concluding (...)
View Details
AI Applications and Implications in the UAE K12 Sector: Industry Experience from Alef Education
Xin Miao Joe El Sebaaly
"This paper explored the impact of AI and globalization on education systems, particularly in the UAE, highlighting the need to prepare children for future jobs, train teachers and school leaders for emerging technology trends, and understand the tasks and skills influenced by AI within the education system, presenting insights from Alef Education`'s AI applications and (...)
View Details
Explaining transformer-based models for automatic short answer grading
Andrew Poulton Sebas Eliens
Recent advancements in natural language processing have made advanced language models easily accessible, but achieving infallible Automatic Short Answer Grading (ASAG) systems remains challenging; this work proposes a framework to select the most accurate and intuitive models for ASAG by evaluating popular transformer-based models with explainability methods on the Semeval-2013 benchmark dataset.
View Details
Modeling the Learning That Takes Place Between Online Assessments
Ryan S. Baker Sujith M. Gowda Eyad Salamin
This paper introduces a variant of the Bayesian Knowledge Tracing algorithm, called BKT-PL, which assumes that learning primarily occurs during the use of declarative content, demonstrating improved predictive ability compared to traditional algorithms in adaptive learning systems, and offering insights into the effectiveness of different types of declarative content for iterative redesign.
View Details
Evidence and Promises of AI Predictions to Understand Student Approaches to Math Learning in Abu Dhabi K12 Public Schools
Xin Miao Pawan Kumar Mishra Ali Nadaf
“To improve math performance in Abu Dhabi public schools and support UAE‘s education transformation, this study utilizes machine learning to identify key factors, including self-system, metacognitive skills, and instructional language, that impact student approaches to math learning, revealing a latent relationship with math diagnostic test performance, leading to potential targeted interventions and refined education policies. "
View Details
Machine learning evidence from PISA 2018 data to integrate global competence intervention in UAE K–12 public schools
Xin Miao Ali Nadaf Zhuotong Zhou
“This paper investigated the significance of global competence in UAE K12 education, finding that three key indicators of global competence contribute to student academic performance, suggesting targeted interventions for boys and girls in areas such as self-efficacy and intercultural communication, and highlighting the importance of integrating global competence interventions with efforts to close achievement gaps (...)
View Details
Grit and Academic Resilience During the Covid-19 Pandemic
Daniel L. Chen (University of Toulouse Capitole) Seda Ertac (Koc University) Theodoros Evgeniou (INSEAD) Xin Miao Ali Nadaf Emrah Yilmaz
This paper demonstrates that grit, a non-cognitive skill associated with perseverance and passion for long-term goals, predicts academic resilience during the Covid-19 pandemic, using a behavioral dataset from a digital learning platform in the UAE; findings suggest that pre-pandemic behavioral data can explain a significant portion of the variance in academic resilience compared to survey-based (...)
View Details
Insights into Contextual Factors Related to Social Emotional Learning (SEL) in UAE Public Schools
Samantha Monroe Ali Nadaf Xin Miao
This paper explored enabling factors for Social Emotional Learning (SEL) skills in UAE students and identified a correlation between student wellbeing, school-related stressors, and academic performance, emphasizing the importance of SEL interventions to mitigate the impact of stress on students' abilities.
View Details
Interpretable-Machine-Learning Evidence for Importance and Optimum of Learning Time
Ali Nadaf Sebas Eliens Xin Miao
This study applies a boosted tree model and the SHapley Additive exPlanations (SHAP) approach to analyze the 2018 PISA data, revealing the importance of various features in predicting cognitive achievement, including instruction time which exhibits a non-linear relationship and suggests potential issues in the student population related to learning time or other factors.
View Details
A Study of Adaptive Learning in Large Class Sizes and the Enabling Conditions for Student Self-Regulated Learning in the UAE
Xin Miao Pawan Kumar Mishra Richard John Brooker Samantha Monroe
This study conducted a pilot program in the UAE to explore the use of an adaptive learning system in larger class sizes, aiming to mitigate challenges related to teacher shortages and turnover. Findings indicate that increasing the teacher-student ratio did not have a negative impact on student academic performance, and in certain cases, it even (...)
View Details
Exploring The Relationship Between Parental Engagement and Social Emotional Learning in UAE Public Schools
Samantha Monroe
This paper explores the intricate dynamics of parental engagement, Social Emotional Learning (SEL) skills, and academic performance in UAE K12 public schools. The study seeks to shed light on the current status quo of parental involvement in the UAE, examining both the home and school environments. Furthermore, it explores the correlation between parental competencies, including (...)
View Details
Can Computer-Based Learning Environments Mitigate Large Class Size?
Ryan S. Baker (University of Pennsylvania) Aishah Al Yammahi Joe El Sebaaly Ali Nadaf Tina Kapp Seth Adjei (Northen Kentucky University)
In this paper, we study the impact of class size in several schools in the United Arab Emirates using a computer-based learning environment as part of their regular classroom practice. Within this study, we compare larger and smaller classes in terms of both learning and time on task. Classes in the same school are compared (...)
View Details
Learning Factors for TIMSS Math Performance Evidenced through Machine Learning in the UAE
Ali Nadaf Samantha Monroe Sarath Chandran Xin Miao
This paper investigated the use of machine learning techniques, specifically the SHapley Additive exPlanations (SHAP) approach, to understand the key learning factors affecting UAE students' math performance on the TIMSS 2019 assessment, providing insights for evidence-based policy making and informed education interventions to enhance UAE student mathematics learning and improve TIMSS math performance.
View Details
Redefining opportunities to better harness technology and financial capital in education in the Middle East
Xin Miao
The global shift towards digital globalization, accelerated by the Covid-19 pandemic, emphasizes the importance of utilizing opportunities brought by the digital era, aligning leadership vision, and fostering collaboration in research and development to effectively leverage government policies, technology, and financial resources for positive impact, particularly in the Middle East, while ensuring the execution of planned (...)
View Details