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A Framework for Teaching Empathy to Data Scientists: Building Human-Centered and Responsible Data Science Through Empathy
| Nome: | Descrição: | Tamanho: | Formato: | |
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| 1.51 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
This study presents a holistic framework for integrating empathy into data science education,
highlighting its crucial role in promoting people-centered and responsible data science.
Recognizing the increasing complexity of socio-technical challenges faced by data scientists,
the research establishes the necessity of empathy as a key skill in their education. The
methodology employs a qualitative, multi-layered approach, including a scoping literature
review to map existing knowledge on fostering empathy in STEM and design education, a
benchmarking of top data science programs to examine current curricula, and in-depth
interviews with educators and practitioners for practical insights. Findings reveal significant
gaps, including the lack of a unified empathy definition, as well as a discrepancy between
theoretical ideals versus their actual practice in education. The research advocates for a nontraditional, multidisciplinary, and hands-on educational approach that combines technical
proficiency with empathetic understanding, viewed through communicational, relational, and
ethical lenses. Conceptualizing empathy as both a process and an outcome, this study suggests
that empathic teaching, learning, and practice can better prepare data scientists to engage
more effectively with diverse stakeholders and address responsibility dimensionsinformed by
social empathy. The proposed framework seeks to both improve educational outcomes and
advance a human-centered approach to data-driven systems, aligning with core values and
societal needs.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management
Palavras-chave
Empathy in Data Science Education Human-Centered Data Science Social Responsibility in Data Science Soft Skills in STEM STEMpathy SDG 4 - Quality education SDG 12 - Responsible production and consumption SDG 17 - Partnerships for the goals