Student engagement during learning serves as a critical predictor of academic success and plays a pivotal role in nurturing interest and readiness for future careers.
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This paper reports perspectives of high school students and their teachers on how context-based learning can support students with varied educational and vocational aspirations to engage with and learn about emerging fields.
High school science and biomedical pathway teachers need effective strategies to build student data literacy and prepare them to conduct experiments.
What do high school students learn from a two-day datathon during which they tackle data to visualize the impact of biased data on healthcare decisions? How do they interact with their team of high school students, data scientists, clinicians, and teachers?
This paper presents an empirical study of high school teachers’ perspectives on context-based learning about Artificial Intelligence (AI) and data science. Four teachers were interviewed after they had enacted a curriculum contextualized in healthcare.
Student engagement is a key predictor of academic achievement and is closely linked to career awareness, interest, and preparedness. Measuring student engagement during STEM learning is challenging for teachers, given the dynamic and ever-changing nature of these learning environments.