Food Production and Biodiversity

Students debug and build a concept map regarding the consequences of different ways of farming on biodiversity. The prototype aims to support the development of 12-14 year old students’ systemic thinking as they explore the nature and relationships of ecosystems. By clicking this link https://youtu.be/3yThjwe8s38, you accept that your browser will send information to YouTube to view the video. YouTube privacy policy Prototype Availability Software websites: Information on DynaLearn itself can be found via: https://www.dynalearn.nl/ (however, this website is being updated) (see also Denker project https://denker.nu/) Using the software online you need to go to: https://create.dynalearn.nl/ (use the Chrome browser) Follow the instructions in the workbook: Additional Information for Researchers Mapping activities inherently involve abductive, inductive, and deductive reasoning, particularly when children collaboratively create, modify, or debug concept maps in response to new information. Concept maps function as external representations that make children’s reasoning visible, revealing how they select concepts, establish relationships, integrate new information into partially developed maps, and combine multiple sources (e.g., text, video, diagrams). When used as communication tools, concept maps provide strong evidence of how children compare, synthesize, and organize information to explain what they have learned, especially in collaborative contexts such as jigsaw activities. From a research perspective, integrating GenAI tools into concept mapping offers opportunities to examine how AI can support constructivist learning approaches and scientific reasoning. Such prototypes can help researchers explore how children interact with AI while developing concept maps, how GenAI scaffolds reasoning and sense-making across heterogeneous information sources, and how young learners develop AI-related skills within carefully designed educational contexts, particularly around socioscientific issues. Possible research questions: What kinds of abductive, inductive, and argumentative reasoning do children express when creating, modifying, or debugging concept maps in response to new sources of information? How do children decide which concepts to include as entities in a concept map? For example, do they identify and connect concepts that appear across multiple sources (e.g., linking ideas shared by a video and a text), and does this reflect hypothesis generation or evidence-based reasoning? How do children incorporate new information into partially developed (“half-baked”) concept maps? What strategies do they use to reorganize, refine, or replace existing connections when confronted with new or conflicting information? How GenAI scaffolds children’s reasoning during concept map creation and revision. How interaction with GenAI tools supports the development of AI-related competencies in young learners. How carefully designed GenAI-supported activities around socioscientific issues influence students’ scientific reasoning and sense-making processes. Additional Information for Educators Before the start of the activity, educators should ensure that the GenAI tool students will use is properly configured for age-appropriate interaction and adheres to ethical and safety standards. For example, before students access the tool, the teacher should prompt it to use child-friendly language, avoid inappropriate or sensitive topics, provide supportive and respectful responses, and refrain from collecting or requesting personal information from students. Publications Bredeweg, B., Liem, J., Linnebank, F., Bühling, R., Wißner, M., Del Río, J. G., … & Gómez Pérez, A. (2010, June). Dynalearn: Architecture and approach for investigating conceptual system knowledge acquisition. In International Conference on Intelligent Tutoring Systems (pp. 272-274). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-13437-1_42 Gkreka, C., & Bredeweg, B. (2024). GenAI in primary education: The case of ChatGPT and concept mapping with DynaLearn. In ICERI2024 Proceedings (pp. 9024-9032). IATED. https://library.iated.org/view/GKREKA2024GEN Learning Goals Address and discuss misconceptions regarding the impact of different ways of farming on biodiversity. Disciplines Environmental Education Science Topics Biodiversity Sustainable farming Multi and single cropping Water scarcity Land exploitation/pollution Learner Levels: Lower Secondary Target Audience: Educators and Researchers Communities of Interest CoI 1 – AI to Support Exploratory Learning Emerging Technologies: GenerativeAI