Productive Action In Online Learning Of Data And Media Literacy

Abstract

The article examines the adolescents' potential for productive action at various stages of the data research cycle. The hypothesis was that the technically intricate phases of data research cycle, which require mathematical and computational skills can be performed by students at a reproductive level following the patterns, whereas the stages requiring data understanding and research design, can be executed creatively and productively. The hypothesis was tested during the online bootcamp aiming to enhance media and data literacy among 8-11 grade students. 53 students aged 14 to 18 from 26 Russian cities took part in the research. Throughout the course students examined textual socio-humanitarian data in geographically distributed teams. Their learning outcomes were compared to those obtained earlier from similar bootcamps on technical and engineering data. Contrary to widespread belief, the main challenge the school students face while learning the basics of data science and machine learning is not the complexities of programming or Math statistics. When dealing with the socio-humanitarian object of research, students successfully coped with computational tasks, but they encountered challenges producing the research design and interpreting results. The study shows that the development of the students' competencies in the basics of scientific research methodology should be considered as a necessary and critical component of educational programs that involve data inquiry. The findings of this study were used for the development of a competency model of data literacy.