Facilitating Professional Development with K-12 Computer Science Teachers in West Africa.

This project explores the challenges that K-12 computer science teachers experience in Western Africa and designs innovative solutions to foster context-relevant professional development.

 In prior work, we interviewed 25 computer science teachers and administrators from 10 middle schools in the Greater Accra Region of Ghana, gathering data on their experiences, skills, and teaching practices. We found only one school with adequate infrastructure and teacher expertise to teach the government-mandated computing curriculum. Despite teachers’ regular internet access and interest in continuous professional development, they struggle to find context-appropriate training materials while accounting for their own computing experience and resources, as well as their students.

This project particularly targets teachers at schools that cater to low-income and working-class families. Our partner schools include tuition-free public schools, and low-cost private schools (< 100 USD per semester tuition) in Ghana.

Most teachers in our study described their computer science skills as self-taught. They shared that they face struggles with finding training materials that allow them to teach the national curriculum while accounting for their teaching experience and infrastructural challenges. Teachers primarily focused their instruction on teaching parts of computers, and Microsoft Office Suites using textbooks and printed posters. Others with available computing resources aligned their instruction with their prior computing experience e.g., teachers with graphic design experience taught students Microsoft Paint, those with hardware experience have students take apart and assemble old computers, make 3D models etc. The figure below shows a variety of materials used for computer science instruction in Ghanaian classrooms.

This project seeks to address these challenges by curating a database of computer science training materials crowdsourced from teachers in diverse social and geographical contexts, and enhancing this database with an AI recommendation system to support teachers’ varied needs and the resource diversity in the schools they serve. We are investigating the following research questions: (1) What types of computer science training materials are most effective for student learning and engagement in low computing and group learning situations? (2) What features are relevant for training an AI language learning model to better understand and support teachers needs in this geographical and cultural context?