Introduce participants to the tools and skills needed to work on collaborative no code app builders. These techniques can be used to develop apps for educational innovation and improve student learning opportunities. Participants will gain hands-on experience in setting up, configuring, and customizing apps while working collaboratively to learn teamwork and encourage innovation.
Introduce learners to data skills. Through practical activities, learners will explore, organise, clean, and visualise data.
Equip learners with the skills and methodologies necessary to collaboratively create, manage, and disseminate open educational resources (OER) specifically tailored for mathematics education.
Introduce students to the role of data and artificial intelligence (AI) in driving development outcomes. Students will engage with case studies to understand the ethical and practical implications of using data and AI in development, building foundational skills in data interpretation, with a particular focus on socially responsible decision-making.
Equip students with the skills needed to create meaningful visualisations from their data. By focusing on the Grammar of Graphics, the course prepares learners to uncover insights and patterns in data.
Equip learners with the skills to interpret variability in data and its implications for statistical analysis and modelling. The goal is to help learners understand how to select the appropriate statistical model and the appropriate technique to account for variability in their context.
Provide knowledge and skills to do research in social development contexts, with an emphasis on alignment of methods with purposes.
Introduce students to the principles of statistical modelling and machine learning. The course is a practical course, focussed on running models and algorithms and interpreting the output.