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 skills, exploration of equivalence of meaning among ideas, and relationships between issues that denote commonality of meaning across representations. MERLO learning assessments capture these important aspects of conceptual thinking. In this chapter, we will look at how MERLO generates big data that can be used to assist teaching. ‘Big data’ for each student in large undergraduate class, include scores of MERLO CIFD weekly quizzes, mid-term tests, and final exams in individual courses. This data shows details of the evolution of deep understanding of each concept in the course, from weekly formative MERLO quizzes that reveal individual students’ conceptual strengths and weakness. This allows the instructor to suggest individual corrective measures with Interactive Concept Discovery (InCoD) in the course digital Knowledge Repository (KR), that are conducted and discussed by individual students with their peers, and enhance learning outcomes.
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Etkind, M., Prodromou, T., Shafrir, U. (2021). Enhancing Learning Outcomes with ‘Big Data’ from Pedagogy for Conceptual Thinking with Meaning Equivalence Reusable Learning Objects (MERLO) and Interactive Concept Discovery (INCOD). In: Prodromou, T. (eds) Big Data in Education: Pedagogy and Research . Policy Implications of Research in Education, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-030-76841-6_6
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DOI: https://doi.org/10.1007/978-3-030-76841-6_6
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