skip to main content
10.1145/3330430.3333628acmotherconferencesArticle/Chapter ViewAbstractPublication Pagesl-at-sConference Proceedingsconference-collections
abstract

Scaffolding during Science Inquiry

Published:24 June 2019Publication History

ABSTRACT

Prior studies on scaffolding for investigative inquiry practices (i.e. forming a question/hypothesis, collecting data, and analyzing and interpreting data [21]) revealed that students who received scaffolding were better able to both learn practices and transfer these competencies to new topics than were students who did not receive scaffolding. Prior studies have also shown that after removing scaffolding, students continued to demonstrate improved inquiry performance on a variety of practices across new driving questions over time. However, studies have not examined the relationship between the amount of scaffolding received and transfer of inquiry performance; this is the focus of the present study. 107 middle school students completed four virtual lab activities (i.e. driving questions) in Inq-ITS. Students received scaffolding when needed from an animated pedagogical computer agent for the first three driving questions for the Animal Cell virtual lab. Then they completed the fourth driving question without access to scaffolding in a different topic, Plant Cell. Results showed that students' performances increased even with fewer scaffolds for the inquiry practices of hypothesizing, collecting data, interpreting data, and warranting claims; furthermore, these results were robust as evidenced by the finding that students required less scaffolding as they completed subsequent inquiry activities. These data provide evidence of near and far transfer as a result of adaptive scaffolding of science inquiry practices.

References

  1. R. S. Baker, J. Clarke-Midura, J. Ocumpaugh. 2016. Towards general models of effective science inquiry in virtual performance assessments. J Comp Assist Learn 32: 267--280. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Z. Chen, D. Klahr. 2008. Remote transfer of scientific-reasoning and problem-solving strategies in children. In Advances in child development and behavior. JAI, 419--470.Google ScholarGoogle Scholar
  3. J. Cohen. 1992. A power primer. Psychological Bulletin 112: 155--159.Google ScholarGoogle ScholarCross RefCross Ref
  4. J. D. Gobert, R. S. Baker, M. A. Sao Pedro. 2014. Inquiry skills tutoring system, U.S. Patent 9,373,082, Filed February 1, 2013, issued January 29, 2014.Google ScholarGoogle Scholar
  5. J. Gobert, R. Moussavi, H. Li, M. Sao Pedro, R. Dickler. 2018. Scaffolding students' on-line data interpretation during inquiry with Inq-ITS. In Cyber-Physical Laboratories in Engineering and Science Education. Springer.Google ScholarGoogle Scholar
  6. J. D. Gobert, M. Sao Pedro, J. Raziuddin, R. S. Baker. 2013. From log files to assessment metrics: measuring students' science inquiry skills using educational data mining. J Learn Sci 22: 521--563.Google ScholarGoogle ScholarCross RefCross Ref
  7. A. C. Graesser, D. S. McNamara, J. Kulikowich. 2011. Coh-Metrix: providing multilevel analyses of text characteristics. Educ Research 40: 223--234.Google ScholarGoogle ScholarCross RefCross Ref
  8. J. F. Hair Jr., R. E. Anderson, R. C. Tatham, W. C. Black. 1998. Multivariate data analysis. Prentice-Hall.Google ScholarGoogle Scholar
  9. C. E. Hmelo-Silver, R. G. Duncan, C. A. Chinn. 2006. Scaffolding and achievement in problem-based and inquiry learning: a response to Kirschner, Sweller, and Clark. Ed Psych 42: 99--107.Google ScholarGoogle ScholarCross RefCross Ref
  10. H. Kang, J. Thompson, M. Windschitl. 2014. Creating opportunities for students to show what they know: The role of scaffolding in assessment tasks. Science Ed 98: 674--704.Google ScholarGoogle ScholarCross RefCross Ref
  11. K. R. Koedinger, J. R. Anderson. 1998. Illustrating principled design: the early evolution of a cognitive tutor for algebra symbolization. Interactive Learning Environments 5: 161--180.Google ScholarGoogle ScholarCross RefCross Ref
  12. H. Li, J. Gobert, R. Dickler. submitted. Evaluating the transfer of scaffolded inquiry: What sticks and does it last?. Submitted to Conference on Artificial Intelligence in Education.Google ScholarGoogle Scholar
  13. H. Li, J. Gobert, R. Dickler. submitted. Testing the robustness of inquiry practices once scaffolding is removed. Submitted to Conference on Intelligent Tutoring Systems.Google ScholarGoogle Scholar
  14. H. Li, J. Gobert, R. Dickler. 2017. Automated assessment for scientific explanations in on-line science inquiry. In Proceedings of the 10th International Conference on Educational Data Mining. EDM Society, Wuhan, 214--219.Google ScholarGoogle Scholar
  15. H. Li, J. Gobert, R. Dickler, R. Moussavi. 2018. The impact of multiple real-time scaffolding experiences on science inquiry practices. In Lecture Notes in Computer Science. Springer, 99--109.Google ScholarGoogle Scholar
  16. N. D. Martin, C. D. Tissenbaum, D. Gnesdilow, S. Puntambekar. 2018. Fading distributed scaffolds: the importance of complementarity between teacher and material scaffolds. Instructional Science: 1--30.Google ScholarGoogle Scholar
  17. K. L. McNeill, J. S. Krajcik. 2011. Supporting grade 5-8 students in constructing explanations in science: the claim, evidence, and reasoning framework for talk and writing. Pearson.Google ScholarGoogle Scholar
  18. K. McNeill, D. J. Lizotte, J. Krajcik, R. W. Marx. 2006. Supporting students' construction of scientific explanations by fading scaffolds in instructional materials. J Learn Sci 15: 153--191.Google ScholarGoogle ScholarCross RefCross Ref
  19. R. Moussavi. 2018. Design, development, and evaluation of scaffolds for data interpretation practices during inquiry. Worcester Polytechnic Institute, Worcester.Google ScholarGoogle Scholar
  20. R. Moussavi, J. Gobert, M. Sao Pedro. 2016. The effect of scaffolding on the immediate transfer of students' data interpretation skills within science topics. In Proceedings of the 12th International Conference of the Learning Sciences. Scopus, Ipswich, 1002--1005.Google ScholarGoogle Scholar
  21. Next Generation Science Standards Lead States. 2013. Next generation science standards: for states, by states. National Academies Press.Google ScholarGoogle Scholar
  22. O. Noroozi, P. A. Kirschner, H. J. Biemans, M. Mulder. 2017. Promoting argumentation competence: extending from first-to second-order scaffolding through adaptive fading. Ed Psych Review: 1--24.Google ScholarGoogle Scholar
  23. J. Pallant. 2013. SPSS survival manual. McGraw-Hill Education.Google ScholarGoogle Scholar
  24. M. Sao Pedro. 2013. Real-time assessment, prediction, and scaffolding of middle school students' data collection skills within physical science simulations. Worcester Polytechnic Institute, Worcester.Google ScholarGoogle Scholar
  25. M. Sao Pedro, R. Baker, J. Gobert. 2013. Incorporating scaffolding and tutor context into bayesian knowledge tracing to predict inquiry skill acquisition. In Proceedings of the 6th International Conference on Educational Data Mining. EDM Society, 185--192.Google ScholarGoogle Scholar
  26. B. G. Tabachnick, L. S. Fidell. 1996. Using multivariate statistics (3rd. ed.). HarperCollins.Google ScholarGoogle Scholar
  27. I. Tabak, B. J. Reiser, B. J. 2008. Software-realized inquiry support for cultivating a disciplinary stance. Pragmatics & Cognition 16: 307--355.Google ScholarGoogle ScholarCross RefCross Ref
  28. W. R. van Joolingen, T. de Jong, A. W. Lazonder, E. R. Savelsbergh, S. Manlove, S. 2005. Co-Lab: research and development of an online learning environment for collaborative scientific discovery learning. Computers in Human Behavior 21: 671--688. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. V. S. Vygotsky. 1978. Mind in society: the development of higher psychological processes. Harvard University Press, Cambridge.Google ScholarGoogle Scholar
  1. Scaffolding during Science Inquiry

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      L@S '19: Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale
      June 2019
      386 pages
      ISBN:9781450368049
      DOI:10.1145/3330430

      Copyright © 2019 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 June 2019

      Check for updates

      Qualifiers

      • abstract
      • Research
      • Refereed limited

      Acceptance Rates

      L@S '19 Paper Acceptance Rate24of70submissions,34%Overall Acceptance Rate117of440submissions,27%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader