In 2024, ScaDS.AI Dresden/Leipzig welcomed Dr. Betty Mayeku as the second Ada Lovelace Distinguished Research Fellow at Leipzig University.

Dr. Betty Mayeku

Awarded through a DAAD scholarship, Dr. Mayeku holds a PhD in Computer Science from the University of Goettingen. Certainly, the doctoral thesis “Enhancing Personalization and Learner Engagement in Context-aware Collaborative Learning Environment – A Pedagogical and Technological Perspective,” reflects Dr. Betty Mayeku’s deep commitment to advancing educational technologies.

Dr. Betty Mayeku serves as a lecturer and researcher in the Department of Computer Science at Kibabii University in Kenya. The intersection of education and technology with particular focus on applied AI and Data Mining within the educational context pose the research interest. Furthermore, she is passionate about integrating AI technologies with pedagogy to create effective learning experiences, leveraging AI and Educational Data Mining (EDM) to improve educational outcomes, and promoting the responsible use of AI in education.

Research and Initiatives

Characterized by dedication to fostering innovation and excellence, Dr. Mayeku works in the field of educational technology. One of her research projects entails exploring how responsible development and application of AI within the education context can be approached from a holistic and integrated perspective. The motivation behind this work stems from the dual nature of AI technologies in academia. Although offering unprecedented opportunities, they are posing risks and challenges that reduce trust. The unique nature of higher education necessitates contextualizing the responsible development and application of AI to foster trust. Consequently, attempting to address these issues, some of the objectives of this work entail:

• Development of a Multidimensional Framework for Responsible AI in education that can guide developers, users, and stakeholders in creating and employing AI responsibly to establish a balanced, ethical, and practical educational AI experience
• Exploring approaches in fostering trust, more so in personalized and adaptive environments

To achieve these objectives, some of the topics, areas and approaches of interest to be explored include:

• Explainable AI
• Swarm Intelligence
• Participatory Design approach
• Exploring responsible AI through the lens of Learning models/theories/frameworks

Besides education, Dr. Betty Mayeku works on applications about comparative evaluation of deep learning algorithms for network-based cyber threat detection, Data Augmentation in enhancing predictive accuracy of HIV Risk Among People Who Inject Drugs (PWIDs) in Kenya and predicting terrestrial vegetation cover from land use and soil variables using machine learning approaches.

Key Publications and Contributions

• B. Mayeku, J. Kilwake, A. O. Mamai, E. K. Wamasebu (2024), Analysis and Prediction of Computer Science Students’ Performance Based on Core Foundational Courses Using Ensemble Machine Learning Methods. In IEEE Intelligent Systems (IS’24) Conference, August, Varna, Bulgaria.  DOI:10.1109/IS61756.2024.10705171
• B. Mayeku, D. Hogrefe and F. Wabwoba (2017), Influence of Social Personalization on Performance in Group Learning. In IEEE AFRICON’17 Conference, Cape Town, South Africa. DOI:10.1109/AFRCON.2017.8095573
• B. Mayeku and D. Hogrefe (2017), A Framework for Integrating Pedagogy and Technology in Context-Aware Learning Environment. International Conference on Web Learning (ICWL), Cape Town, South Africa. DOI:10.1007/978-3-319-66733-1_24