Evaluating the transfer of scaffolded inquiry: What sticks and does it last?

Haiying Li, Janice Gobert, Rachel Dickler

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

9 Scopus citations


The Next Generation Science Standards [1] expect students to master disciplinary core ideas, crosscutting concepts, and scientific practice. In prior work, we showed that students benefited from real time scaffolding of science practices such that students’ inquiry competencies both improved over time and transferred to new science topics. The present study examines the robustness of adaptive scaffolding by evaluating students’ inquiry performances at a very fine-grained level in order to investigate what aspects of inquiry are robust over time once scaffolding was removed. 108 middle school students in grade 6 used Inq-ITS and received adaptive scaffolding for three lab activities in the first inquiry topic they completed (i.e. Animal Cell); they then completed 10 activities without scaffolding across three new topics. Results showed that after removing scaffolding, student’s inquiry performance generally improved with slight variations in performance across driving questions and over time. Overall, these findings suggest that adaptive scaffolding may support students’ inquiry learning and transfer of inquiry practices over time and across topics.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings
EditorsSeiji Isotani, Eva Millán, Amy Ogan, Bruce McLaren, Peter Hastings, Rose Luckin
PublisherSpringer Verlag
Number of pages6
ISBN (Print)9783030232061
StatePublished - 2019
Event20th International Conference on Artificial Intelligence in Education, AIED 2019 - Chicago, United States
Duration: Jun 25 2019Jun 29 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11626 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference20th International Conference on Artificial Intelligence in Education, AIED 2019
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


  • Growth in inquiry performance
  • Scaffolding
  • Science inquiry


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