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Enhancing Learning Outcomes with 'Big Data' from Pedagogy for Conceptual Thinking with Meaning Equivalence Reusable Learning Objects (MERLO) and Interactive Concept Discovery (INCOD)

  • Masha Etkind
  • , Theodosia Prodromou
  • , Uri Shafrir

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

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.

Original languageEnglish
Title of host publicationBig Data in Education: Pedagogy and Research
EditorsTheodosia Prodromou
Place of PublicationCham, Switzerland
PublisherSpringer
Pages125-139
Volume13
Edition1
ISBN (Print)9783030768416, 9783030768409, 9783030768430
DOIs
Publication statusPublished - 2021

Publication series

NamePolicy Implications of Research in Education
PublisherSpringer
Number13
ISSN (Print)2543-0289
ISSN (Electronic)2543-0297

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