Embedded Files
A comparative case study to understand how three pioneering and prominent teachers have established makerspaces in their kindergarten classrooms.
Welcome!
The Systems Learning & Development Lab (SLDL) investigates how people of all ages understand, construct, and learn about complex systems through dynamic learning environments and epistemic tools. Directed by Prof. Sharona T. Levy at the Faculty of Education, University of Haifa, the lab spans research in science education, computational thinking, learning sciences, and complexity-informed design.
SLDL’s research focuses on three interrelated strands:
(a) Supporting learners’ reasoning about complex systems and emergent phenomena through model-based, participatory, and embodied learning — across science domains (e.g., chemistry, physics, biology, health), sports, traffic, and everyday life;
(b) Restructuring conceptual domains and instructional practices to promote deep understanding, epistemological growth, and inclusive access — including in early childhood, middle school, and nursing education;
(c) Designing inclusive, developmentally-attuned learning technologies and environments — such as sonified models for blind learners, unplugged computational thinking games for kindergarten, and embodied or VR-based simulations for health, science, and leadership.
As part of this work, SLDL has created and studied research-based learning environments including Connected Chemistry, Much.Matter.in.Motion, TrafficJams, Listening to Complexity, Biking with Particles and PILL-VR. These designs span formal and informal contexts, from kindergartens to nursing schools, and employ design-based research, microgenetic methods, and mixed-method evaluations to examine learning, inclusion, conceptual change, and identity.
Keywords: learning sciences, science education, constructionism, complex systems, agent-based modeling, computational thinking, model-based learning, epistemology of modeling, early childhood education, inclusion, sonification, embodiment, participatory simulations, makerspaces, leadership, curriculum design, health education, digital parenting
Much.Matter.in.Motion
Much.Matter.in.Motion
(Levy, Saba, Zohar & Hel-Or, 2018; 2022)
(Levy, Saba, Zohar & Hel-Or, 2018; 2022)
Much.Matter.in.Motion is a block-based modeling platform, which is geared towards middle- and high-school students. It is incorporated into chemistry and physics learning units that are concerned with systems, such as gases, electricity and chemical reactions. Its unique affordances are making prominent similarities between distinct phenomena in science and supporting a complexity-based perspective. It is very easy to start using as less important computational activities are replaced with drawing, and programming is at the micro-level of the system. It is based on a NetLogo (Wilensky, 1999) model we created, and blocks that were created with NetTango (Horn, Baker & Wilensky, 2020). MMM was developed and used as part of Janan Saba's dissertation, with Asnat Zohar and Nurit Berger Gil continuing the research.
Photosynthesis & Cellular Respiration in Plants (Levy, 2020)
Photosynthesis & Cellular Respiration in Plants (Levy, 2020)
This models shows how the chemical reactions in a plant's leaf cell can both transform light and molecules into glucose (photosynthesis), and how glucose further reacts to provide energy to the cell at the mitochondria (cellular respiration). It is based on a model-based framework we've been working on to investigate and provide consistent and mechanistic representations for biology learning, CEM: Cell-based Emergent Models.
It was used in Shani Goldstein's thesis, as part of a learning unit on the topic in eighth grade science class. Research showed how students' understanding of these two processes grew with respect to students studying with normative learning materials; and how the conceptual ecology both increased and became more connected, gradually including concepts such as processes taking place, and the identity of the micro-level organelles and molecules.
Flocking of birds is a fascinating phenomenon in which birds in motion remain together while flying across short and longer distances. Keeping together is an emergent phenomenon that results from many birds behaving according to very simple rules: approaching a flock, aligning with the flock and avoiding collisions. These rules can be explored with the NetLogo (Wilensky, 1999) Flocking model (Wilensky, 1998). Click the link to see the model.
Page updated
Report abuse