This paper is from Session 8D: New Methods in the Age of Big Data
which comes under Topic 8: New approaches to research in statistics education
Paper 8D2 (Thursday 12th, 16:00-17:30)
Enhancing learning outcomes with 'big data' from pedagogy for conceptual thinking with Meaning Equivalence Reusable Learning Objects (MERLO) and Interactive Concept Discovery (INCOD)
Presenter
- Masha Etkind (Ryerson University, Canada)
Co-authors
- Theodosia Prodromou (University of New England, Australia)
- Uri Shafrir (University of Toronto, Canada)
Abstract
Learning outcomes of traditional pedagogy focus on memory of facts, problem-solving procedures, and multiple-choice or true/false questions. Pedagogy for conceptual thinking focuses on higher-order thinking skill, exploration of equivalence of meaning among ideas and relationships between statements that denote commonality of meaning across representations. MERLO assessments capture these important aspects of conceptual thinking. ‘Big data’ from the results of weekly formative MERLO quizzes reveal individual students' conceptual strengths and weaknesses, showing details of the evolution of deep understanding of each concept in the course. This allows the instructor to suggest corrective measures with Interactive Concept Discovery (InCoD) in the course’ digital Knowledge Repository (KR), conducted and discussed by individual students with their peers, and enhance learning outcomes in large undergraduate courses in statistics and mathematics.