Motivation, inclusivity, and realism should drive data science education.
F1000Res
; 12: 1240, 2023.
Article
en En
| MEDLINE
| ID: mdl-38764793
ABSTRACT
Data science education provides tremendous opportunities but remains inaccessible to many communities. Increasing the accessibility of data science to these communities not only benefits the individuals entering data science, but also increases the field's innovation and potential impact as a whole. Education is the most scalable solution to meet these needs, but many data science educators lack formal training in education. Our group has led education efforts for a variety of audiences from professional scientists to high school students to lay audiences. These experiences have helped form our teaching philosophy which we have summarized into three main ideals 1) motivation, 2) inclusivity, and 3) realism. 20 we also aim to iteratively update our teaching approaches and curriculum as we find ways to better reach these ideals. In this manuscript we discuss these ideals as well practical ideas for how to implement these philosophies in the classroom.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Ciencia de los Datos
/
Motivación
Límite:
Humans
Idioma:
En
Revista:
F1000Res
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos