Comparing and contrasting within diagrams: An effective study strategy

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The study strategy of comparing-and-contrasting has been well validated for learning from text, but not from diagrams. As part of a semester-long study strategies intervention for undergraduate biology students, we created 4 short instructional videos demonstrating the strategy of comparing-and-contrasting within diagrams (CC DIA) and delivered these just before the first course exam. We hypothesized that this strategy would help students develop a deeper comprehension of the instructed biology content. Participants were 128 undergraduates in a 2nd semester introductory (molecular and cellular) biology course, who participated in exchange for extra course credit. Students who accessed our videos scored a significant 5.5% points higher on the first exam of the semester, compared to students in other conditions or non-viewers (d =.35). Our brief (approx. 10 min per week × 4 weeks) instruction in using diagrams to learn biology yielded significant gains in undergraduate achievement.

Original languageEnglish (US)
Title of host publicationDiagrammatic Representation and Inference - 10th International Conference, Diagrams 2018, Proceedings
EditorsGem Stapleton, Francesco Bellucci, Amirouche Moktefi, Peter Chapman, Sarah Perez-Kriz
Number of pages8
ISBN (Print)9783319913759
StatePublished - 2018
Event10th International Conference on the Theory and Application of Diagrams, Diagrams 2018 - Edinburgh, United Kingdom
Duration: Jun 18 2018Jun 22 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10871 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other10th International Conference on the Theory and Application of Diagrams, Diagrams 2018
Country/TerritoryUnited Kingdom


  • Biology
  • Compare-and-contrast
  • Strategy instruction

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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