The IDEMS Podcast

Lucie and Roger discuss the intricacies and applications of crop simulation models in agricultural research. Roger explains the historical development of these models since the 1980s and provides a detailed explanation of how crop simulation models work, such as the DSAT and APSIM systems, which are used extensively in the United States and Australia. The discussion underscores the models' value in complementing traditional field experiments, especially in understanding long-term agricultural dynamics. They also touch on the challenges of implementing these models in Africa due to climatic data availability.

Santiago and David discuss how aspects of education could be “gamified” in order to improve outcomes. They explore various real-world examples of how games are used to enhance learning, including platforms like Kahoot and innovative projects like SmileyCoin. As well as the benefits, they consider the potential downsides, such as excessive screen time and the impact of dopamine release on student concentration.

As part of their continuing conversations around research methods for agriculture, Lucie and Roger discuss the utility of conducting research trials over multiple years. They consider the importance of understanding climate variability, and the value of pilot experiments as well as the implications of adapting research methods based on initial findings and the benefits of engaging farmers extensively in the research process.

How do we understand the material living conditions of people on Earth today? In this episode of the IDEMS podcast, Lily and David discuss the influential book “Factfulness” by Hans Rosling. They explore Rosling's key concepts about global development, particularly the categorisation of the world into four income levels instead of the binary “developing” and “developed” terms.

Social impact scientist and anthropologist Lucie Hazelgrove Planel joins Roger Stern to discuss the intricate process of designing agricultural experiments. Using a real-world example involving 10 maize varieties and a field with 12 plots, they explore the challenges of fitting theoretical models to practical scenarios.

How do you present research data in a compelling way? In this episode, Lucie and David discuss the intricacies of creating impactful visualisations for projects. They consider the distinctions between descriptive, exploratory, and presentation graphs. They emphasise the importance of understanding your audience, whether it's scientific, agricultural, or policy-making, and how to adapt visualisations accordingly to tell compelling stories.

In order to collect research data, we need to take measurements. As part of their continuing conversations, Lucie and statistician Roger consider this critical topic of measurements in agricultural research. They explore various types of measurements, such as context measurements, objective-related measurements, and those that help explain variability, using examples from agricultural trials and anthropological studies. The conversation highlights the nuanced nature of collecting quality data and calls for thoughtful planning and pilot studies.

Santiago and David discuss recent advancements and challenges in educational technology, looking at the integration of the STACK electronic assessment system with the PreTeXt tool for textbook authoring. Reflecting on a successful African STACK Conference held in Ethiopia, they consider the broader impact of these innovations on education in Ethiopia and potentially other African countries, emphasising the importance of making technology accessible at the student, lecturer, and institution levels.

In their continuing conversations on Research Methods for Agriculture, Lucie and Roger discuss the importance and application of controls in agricultural research. They consider the importance of controls in general, and consider examples from both agricultural and medical experiments, emphasising the importance of ethical considerations when using controls. Roger shares insights on how to make controls meaningful, how to adjust experiments based on intermediate findings, and the potential pitfalls of rigidly adhering to control rules.

AI tools can be helpful in analysing quantitative data, but their potential utility in qualitative analysis might be less obvious, or even concerning. In this episode of the IDEMS Podcast, data scientist Lily Clements and social impact scientist Lucie Hazelgrove Planel discuss the usage of generative AI in analysing qualitative data. They explore the ethical implications, the importance of context, and the challenge of addressing biases in AI-generated analyses, as well as the evolving intersection of AI with traditional qualitative research methods.