In this episode, Lily and David discuss transforming challenges in low-resource educational environments into opportunities. David shares his experiences in leveraging limited funding and facilities, advocating for individual initiative, and generating agency among students and staff.

In this episode, Santiago and David discuss the idea of personalised education within standardised education. They explore the challenges and opportunities of using adaptive learning technologies to customize educational materials for individual needs to thrive in standardised systems. They also touch on the historical context and future potential of educational tools.

Lucie and David discuss a $7,000 grant from Float, funding internships to support tech projects in West Africa and Kenya. The initiative will advance community tech in agroecology and prepare for a larger $45,000 workshop, emphasizing IDEMS' focus on capacity building and collaboration.

In this podcast episode, Santiago and David discuss IDEMS’ strategy for sustainable growth through Social Enterprise Impact Bonds. They revisit the concept of 'fundamentally profitable', emphasizing the need for financial sustainability to support impactful projects. The conversation highlights their unique funding model, offering ethical and secure returns for investors, aimed at fostering social impact while avoiding high-risk ventures.

Lucie and David discuss their recent workshops in Niger, Burkina Faso, and Mali, focusing on teaching effective research visualizations to diverse stakeholders within the Global Collaboration for Resilient Food Systems. They highlight the importance of visual storytelling, the challenges faced, and the inspiring engagement of local teams.

How can we transform complex data into understandable information? In this episode, Lily and David discuss the concept of factors in data analysis. They consider the historical context of factors, their importance in grouping data, and how they revolutionise statistical thinking.

How can we incentivise student learning? Santiago and David discuss various educational technologies and innovations, focusing particularly on SmileyCoin and the SmileyTutor system from Iceland. David shares insights from his collaboration with Gunnar Stefánsson, who developed a unique system that uses multiple choice questions to enhance student learning, and integrates a cryptocurrency designed to incentivise learning by rewarding students financially.

Santiago and David provide an in-depth look at PreTeXt, an open-source authoring tool designed to separate the roles of authors and publishers. David recounts his early interactions with PreTeXt founder Rob Beezer and discusses the evolution and principles behind the tool. They highlight the importance of modularity, separating content from presentation, and emphasize the tool's relevance for creating interactive, adaptable educational resources. The discussion also touches on PreTeXt's integration with other tools like STACK and the broader vision of combining multiple open-source technologies to address diverse educational needs.

Santiago and David discuss the innovative “five quiz” model – an educational framework designed to improve student learning outcomes. Conceived during the pandemic, this model includes five types of quizzes: prerequisites, instructional, mastery, testing, and extension quizzes. Santiago and David explore how this framework, originally conceptualised for online courses, addresses various educational contexts and learning needs, from low-resource environments to high-resource institutions like Caltech.

Lily and David Stern discuss the history and impact of Computer Assisted Statistics Textbooks (CAST), developed by New Zealand lecturer Doug Sterling. The discussion highlights the interactive and assessment-driven nature of CAST, recounting how its use in Kenyan classrooms led to significant improvements in student performance. They reflect on the technological challenges that led to CAST's decline and extract key lessons for designing sustainable educational resources.

What happens if statistics teaching starts from data rather than methods? In this episode, Lily and David explore the idea that statistics education should prioritise data analysis over traditional methods-first approaches, discussing the benefits and challenges of this paradigm shift. Highlighting examples from New Zealand's education system and their own experiences, they argue that a data-first approach can provide more practical and widely applicable skills for students, despite the structural challenges it may pose.

For those unfamiliar with STACK, consider searching the podcast backlog for previous episodes on the subject. In this episode, Santiago and David discuss the latest developments with STACK in Africa. They highlight various recent developments, including: tailored data course trainings in Niger, Burkina Faso, and Mali; the inaugural African official STACK conference set for 2026 in Kenya; the establishment of an African STACK Center at Masinde Muliro University; impressive outcomes from the use of STACK in Kenyan schools and technical colleges; the new PreTeXt textbook initiative for Ethiopian universities, impacting over 4,000 students; and additional efforts in Namibia, Tanzania, Somalia, and South Sudan.

Michele Pancera and David Stern critically discuss a recent Google paper on AI-augmented textbooks. They consider the paper's proposal of AI-generated personalised learning materials and how it compares to existing deterministic tools like STACK. The conversation highlights the differences between surface-level and deep personalisations, the importance of human involvement in AI processes, and the potential of AI in supporting teachers and enhancing education systems globally. They explore the vision of a customisable, community-driven textbook ecosystem that leverages AI to reduce educational inequalities while maintaining high-quality human interaction. Access the paper from Google here: https://arxiv.org/abs/2509.13348

Lily and David discuss the often misunderstood concepts of “open” and “open source.” They discuss the origins of these terms within the programming community and how they have expanded into areas such as open data, open science, and educational resources. The conversation focuses on the various types of licenses, including Creative Commons, and their implications for use and reuse.

In this special two-year anniversary episode David and Kate reflect on their journey, from improving audio quality to hosting more expert guests. They explore the essence of IDEMS' work, emphasizing the combination between the IDEMS Collaboratory and CommonTech, as a breakthrough in IDEMS’ narrative, highlighting the challenge of communicating a complex, collaborative vision.

In this episode, Santiago and David delve into the two of IDEMS’ staffing principles: Individual Initiative and Collective Responsibility. They discuss how these principles support a culture where team members can take initiative while sharing responsibility collectively. Highlighting real examples, they introduce a recent breakthrough in implementation of these principles in the form of a tool designed to visualise and manage these principles effectively.

Michele and David discuss the Turing test, and its relevance today. They explore various philosophical questions about intelligence, the limitations of the Turing test, and the ethical dilemmas posed by AI, particularly in the context of self-driving cars. David emphasises the vital role of human observation in the Turing test and expresses skepticism about society's ability to make responsible choices regarding AI regulation.

Michele and David discuss the impact of AI in low resource environments. They discuss the complexities surrounding AI technology, the hype versus the actual value, and the potential for AI to either widen or reduce global inequalities. They consider the need for robust infrastructural and social frameworks, the promise of small language models, and the importance of local ownership in AI development.

Lily and David explore a powerful framework for data analysis: Explore, Describe, Present. They discuss the importance of exploring data to understand its structure, describing data in the context of specific objectives, and effectively presenting insights to various audiences. Highlighting the challenges of modern data analysis, including the role of AI and the influence of tools like the tidyverse and R-Instat, they emphasise the need for structured approaches to make sense of complex datasets.

David talks to Rikin Gandhi from Digital Green to discuss the organisation's innovative approach to integrating AI with farmer support systems. They discuss Digital Green’s approach to working with AI, including the importance of human-in-the-loop systems, the benefits of using multimodal inputs like voice, text, and images, and the advantage of open-source data for tuning AI models to meet local agricultural needs. They also explore the potential and challenges of leveraging small language models to provide tailored support to farming communities and the critical role of local expertise in enhancing AI's effectiveness.