Preparing Middle Schoolers for a Machine Learning-Enabled Future Through Design-Oriented Pedagogy

Abstract

Machine learning (ML) literacy has recently been identified as one of critical skills students need to succeed as future creators and innovators. While the significance of introducing ML basics at kindergarten to twelfth grade (K-12) levels is increasingly acknowledged, there is limited research that focuses specifically on collaborative design of ML applications with middle school students. We posit that engaging young children to co-invent and make concrete prototypes improves their ideas, encourages them to become active participants, and allows them to establish the implications of the technology in their everyday lives. In order to lay the foundation for middle school ML education, we collaboratively designed and prototyped ML applications with 43 eighth grade students (ages 11 to 14) in a Nigerian school. The ideas generated by the students indicate that they began to identify the applicability of ML to their daily lives and as a solution to a plethora of societal challenges. This study provides learners' input and preliminary insights into approaches that could be adopted to promote ML within the compulsory level of education in an African setting. The research contributes to the limited body of knowledge available on effectively teaching ML to young learners using design-oriented pedagogy, especially in the context of an emerging country.

Blended Learning for Machine Learning-based Image Classification

“…To foster collaboration and knowledge exchange, an online forum was established where students could discuss concepts, share resources, and seek assistance from peers and instructors [50]. Collaborative projects were also introduced, encouraging participants to work together on ML-based image classification tasks [51]. This collaborative aspect aimed to simulate real-world scenarios where teamwork and shared insights contribute to the success of machine learning projects [52].…”