Learning Ecologies: Connecting Social Constructivism and Distance Learning
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Social constructivist teaching practices are understood to foster deep learning through socio-cultural interactions, asserting that individual learning is limited in comparison to what can be learned as a community. Social constructivist principles are embedded within Saskatchewan curricula with little mention of how that might be achieved in asynchronous distance learning. The lack of direct connections places a burden on distance learning teachers, policymakers, and course designers to discover how to actualize social constructivist education practices, within an asynchronous learning environment. This mixed methods study used an online survey and semi-structured interviews to understand teachers’ experiences with social constructivist practices in high school asynchronous distance learning within Saskatchewan. Through the reflexive thematic analysis of the semi-structured interviews and the open-ended survey questions, three themes were constructed. The “Teacher as Catalyst” theme identified the dynamic role that teachers take on to be responsive to student learning needs (e.g., creating flexible learning paths, increasing resources, and strengthening relationships). The theme “Student Agency” represents two key teacher perspectives regarding students’ reluctance to take part in collaborative learning with peers. Namely, student readiness and student buy-in. The final theme, “Alignment of Purpose, Pedagogy, and Person” depicts how the learning ecosystem influences pedagogical decisions and the learning experiences of students. The findings support the integral role of student-teacher relationships to support learning and suggest that under the right conditions, the intent and stance of the Saskatchewan curricula can be achieved in asynchronous distance learning environments provided there is an alignment in purpose, pedagogy, and person. However, the research findings did not support a strong student desire for social constructivist practices.
DegreeDoctor of Philosophy (Ph.D.)
CommitteeWallin, Dawn; Koole, Marguerite; Schwier, Richard; Brenna, Beverley
Copyright DateApril 2022
deep learning, asynchronous