Emergency Remote Teaching and Programme Intervention: Towards a Human-Machine Pedagogy Based on Interactive Learning Documents

Abstract

Teaching restrictions, due to the COVID-19 pandemic, have rapidly shifted the global learning environment demanding educators to implement technology-based solutions in their instruction. In this case study, we discuss how Interactive Learning Documents (ILDs), based on R-Markdown and R-Shiny technologies can contribute to building student confidence in their transition from secondary to tertiary education under the conditions of Emergency Remote Teaching. We propose a human-machine based active learning pedagogy to be implemented in a stage one Introductory Statistics course delivered to social science students. Our results show that Interactive Learning Documents contribute to alleviating student’s transition to university education. Three factors contribute to this result: 1) ILDs help students reduce statistics anxiety, 2) ILDs help learning by efficiently organising large quantities of complex learning material, and 3) ILDs effectively engage students by providing them with a variety of dynamic interactions with the subject.