Potential Abstract:
This study investigates the use of flexible infrastructures, specifically Jupyter notebooks and cloud technologies, to enhance praxis in educational settings. Praxis, the integration of theory and practice, is a critical component of effective teaching and learning. However, traditional educational practices often struggle to integrate theory and practice seamlessly. This research explores the potential of using Jupyter notebooks, an open-source web application, and cloud technologies to create polytextual learning environments that facilitate praxis.
By enabling the integration of multiple forms of texts (e.g., text, code, images, and interactive visualizations), Jupyter notebooks offer a unique opportunity for students and educators to engage with complex educational content in a dynamic and interactive manner. These notebooks provide a flexible infrastructure that supports iterative and collaborative learning experiences. Furthermore, cloud technologies enable the seamless sharing and access to Jupyter notebooks, enhancing their potential impact on praxis.
To investigate this potential, a mixed-methods approach will be employed. The study will involve the design and implementation of polytextual learning activities using Jupyter notebooks in a secondary school setting. Data will be collected through observations, interviews, and surveys to gather insights into students’ and educators’ experiences, perceptions, and learning outcomes. Additionally, quantitative analysis will be conducted to examine the impact of Jupyter notebooks on students’ engagement, understanding, and transfer of knowledge.
The results of this study will contribute to the existing literature on flexible infrastructures, Jupyter notebooks, and cloud technologies in education. Specifically, it will provide insights into the affordances and challenges associated with integrating these technologies to support praxis. The findings will inform educators and policymakers about the potential of such technologies to enhance teaching and learning practices, particularly in the context of polytextual learning environments.
Potential References:
- Toward collaborative open data science in metabolomics using Jupyter Notebooks and cloud computing
- FEDGEN testbed: A federated genomics private cloud infrastructure for precision medicine and artificial intelligence research
- An interactive web-based analysis framework for remote sensing cloud computing
- Enabling interactive analytics of secure data using cloud kotta
- Models in the cloud: Exploring next generation environmental software systems
