Metacognition and Learning

, Volume 2, Issue 2–3, pp 89–105

SEEK Web tutor: fostering a critical stance while exploring the causes of volcanic eruption

  • Arthur C. Graesser
  • Jennifer Wiley
  • Susan R. Goldman
  • Tenaha O’Reilly
  • Moongee Jeon
  • Bethany McDaniel


We investigated the impact of a Web tutor on college students’ critical stance and learning while exploring Web pages on science. Critical stance is an aspect of self-regulated learning that emphasizes the need to evaluate the truth and relevance of information as the learner engages in systematic inquiry to answer challenging questions. The Web tutor is called SEEK, an acronym for Source, Evidence, Explanation, and Knowledge. The SEEK Tutor was designed to promote a critical stance through several facilities in a computer environment: spoken hints on a mock Google™ search page, on-line ratings on the reliability of particular Web sites, and a structured note-taking facility that prompted them to reflect on the quality of particular Web sites. We conducted two experiments that trained students how to take a critical stance and that tracked their behavior while exploring Web pages on plate tectonics to research the causes of the volcanic eruption of Mt. St. Helens. The SEEK Tutor did improve critical stance, as manifested in essays on the causes of the volcanic eruption, and did yield learning gains for some categories of information (compared with comparison conditions). However, many measures were unaffected by either the presence of the SEEK Tutor or by prior training on critical stance. We anticipate that robust improvements on critical stance and learning will require more training and/or some expert feedback and interactive scaffolding of critical stance in the context of specific examples.


SEEK Web Critical thinking Tutoring 


  1. AAAS (American Association for the Advancement of Science) (1993). Benchmarks for science literacy: Project 2061. New York: Oxford University Press.Google Scholar
  2. Azevedo, R. (2005). Computer environments as metacognitive tools for enhancing learning. Educational Psychologist, 40, 193–198.CrossRefGoogle Scholar
  3. Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students’ learning with hypermedia. Journal of Educational Psychology, 96, 523–535.CrossRefGoogle Scholar
  4. Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.) (2000). How people learn. Washington, DC: National Academy Press.Google Scholar
  5. Brem, S. K., Russell, J., & Weems, L. (2001). Science on the Web: Student evaluations of scientific arguments. Discourse Processes, 32, 191–213.CrossRefGoogle Scholar
  6. Britt, M. A., & Aglinskas, C. (2002). Improving student’s ability to use source information. Cognition and Instruction, 20(40), 485–522.CrossRefGoogle Scholar
  7. Chi, M. T. H., de Leeuw, N., Chiu, M., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439–477.CrossRefGoogle Scholar
  8. Chinn, C., & Brewer, W. (1993). The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science instruction. Review of Educational Research, 63, 1–49.CrossRefGoogle Scholar
  9. Corbett, A. T. (2001). Cognitive computer tutors: Solving the two-sigma problem. In User modeling: Proceedings of the eighth international conference (pp. 137–147). Berlin: Springer.Google Scholar
  10. Dodds, P., & Fletcher, J. D. (2004). Opportunities for new “smart” learning environments enabled by next-generation web capabilities. Journal of Educational Multimedia and Hypermedia, 13, 391–404.Google Scholar
  11. Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive developmental inquiry. American Psychology, 34, 906–911.CrossRefGoogle Scholar
  12. Goldman, S. R., Duschl, R. A., Ellenbogen, K., Williams, S., & Tzou, C. T. (2003). Science inquiry in a digital age: Possibilities for making thinking visible. In H. van Oostendorp (Ed.) Cognition in a digital age (pp. 253–283). Mahwah, NJ: Erlbaum.Google Scholar
  13. Goldman, S. R., & Murray, J. (1992). Knowledge connectors as cohesion devices in text. Journal of Educational Psychology, 84, 504–519.CrossRefGoogle Scholar
  14. Graesser, A. C., & Bertus, E. L. (1998). The construction of causal inferences while reading expository texts on science and technology. Scientific Studies of Reading, 2, 247–269.CrossRefGoogle Scholar
  15. Graesser, A. C., McNamara, D. S., & VanLehn, K. (2005). Scaffolding deep comprehension strategies through Point&Query, AutoTutor, and iSTART. Educational Psychologist, 40, 225–234.CrossRefGoogle Scholar
  16. Graesser, A. C., & Olde, B. A. (2003). How does one know whether a person understands a device? The quality of the questions the person asks when the device breaks down. Journal of Educational Psychology, 95, 524–536.CrossRefGoogle Scholar
  17. Graesser, A. C., & Person, N. K. (1994). Question asking during tutoring. American Educational Research Journal, 31, 104–137.CrossRefGoogle Scholar
  18. Hacker, D. J., Dunlosky, J., & Graesser, A. C. (Eds.) (1998). Metacognition in educational theory and practice. Mahwah, NJ: Erlbaum.Google Scholar
  19. Hadwin, A., & Winne, P. (2001). CoNoteS2: A software tool for promoting self-regulation. Educational Research and Evaluation, 7, 313–334.CrossRefGoogle Scholar
  20. Halpern, D. F. (2002). An introduction to critical thinking (4th ed.). Mahwah, NJ: Erlbaum.Google Scholar
  21. Linn, M. C., Davis, E. A., & Bell, P. (Eds.) (2004). Internet environments for science education. Mahwah, NJ: Erlbaum.Google Scholar
  22. Maki, R. H. (1998). Test predictions over text material. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.) Metacognition in educational theory and practice (pp. 117–144). Mahwah, NJ: Erlbaum.Google Scholar
  23. Mayer, R. E. (2005). Multimedia learning. Cambridge, MA: Cambridge University Press.Google Scholar
  24. McNamara, D. S. (2004). SERT: Self-explanation reading training. Discourse Processes, 38, 1–30.CrossRefGoogle Scholar
  25. Millis, K. K., & Graesser, A. C. (1994). The time-course of constructing knowledge-based inferences for scientific texts. Journal of Memory & Language, 33(5), 583–599.CrossRefGoogle Scholar
  26. Otero, J., & Kintsch, W. (1992). Failures to detect contradictions in a text: What readers believe versus what they read. Psychological Science, 3(4), 229–235.CrossRefGoogle Scholar
  27. Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.) Handbook of self-regulation (pp. 452–502). New York: Academic.Google Scholar
  28. Rouet, J.-F. (2006). The skills of document use: From text comprehension to web-based learning. Mahwah, NJ: Erlbaum.Google Scholar
  29. Sanchez, C., & Wiley, J. (2006). Effects of working memory capacity on learning from illustrated text. Memory & Cognition, 34, 344–355.Google Scholar
  30. Sanchez, C. A., Wiley, J., & Goldman, S. R. (2006). Teaching students to evaluate source reliability during internet research tasks. In Proceedings of the 7th international conference of the learning sciences (pp. 662–666). Bloomington, IN: ACM Digital Library.Google Scholar
  31. VanLehn, K., Graesser, A. C., Jackson, G. T., Jordan, P., Olney, A., & Rose, C. P. (2007). When are tutorial dialogues more effective than reading? Cognitive Science, 31, 3–62.Google Scholar
  32. Vosniadou, S., & Brewer, W. F. (1992). Mental models of the earth: a study of conceptual change in childhood. Cognitive Psychology, 24, 535–585.CrossRefGoogle Scholar
  33. White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition & Instruction, 16(1), 3–118.CrossRefGoogle Scholar
  34. Wiley, J. (2001). Supporting understanding through task and browser design. In Proceedings of the 23rd Annual Conference of the Cognitive Science Society (pp. 1136–1143). Hillsdale, NJ: Erlbaum.Google Scholar
  35. Wiley, J., Goldman, S. R., Graesser, A. C., Sanchez, C. A., Ash, I. K., & Hemmerich, J. (2007). Learning science from internet inquiry tasks: The importance of teaching students to discriminate and use reliable sources. Unpublished manuscript, University of Illinois at Chicago.Google Scholar
  36. Wiley, J., Griffin, T. D., & Thiede, K. W. (2005). Putting the comprehension in metacomprehension. Journal of General Psychology, 132(4), 408–428.CrossRefGoogle Scholar
  37. Wiley, J., & Myers, J. L. (2003). Availability and accessibility of information and causal inferences from expository text. Discourse Processes, 36, 109–129.CrossRefGoogle Scholar
  38. Wiley, J., & Voss, J. F. (1999). Constructing arguments from multiple sources: Tasks that promote understanding and not just memory for text. Journal of Educational Psychology, 91, 1–11.CrossRefGoogle Scholar
  39. Winne, P. H. (2001). Self-regulated learning viewed from models of information processing. In B. Zimmerman, & D. Schunk (Eds.) Self-regulated learning and academic achievement: Theoretical perspectives (pp. 153–189). Mahwah, NJ: Erlbaum.Google Scholar
  40. Zimmerman, B. (2001). Theories of self-regulated learning and academic achievement: An overview and analysis. In B. Zimmerman, & D. Schunk (Eds.)Self-regulated learning and academic achievement: Theoretical perspectives (pp. 1–37). Mahwah, NJ: Erlbaum.Google Scholar

Copyright information

© Springer Science + Business Media, LLC 2007

Authors and Affiliations

  • Arthur C. Graesser
    • 1
  • Jennifer Wiley
    • 2
  • Susan R. Goldman
    • 2
  • Tenaha O’Reilly
    • 3
  • Moongee Jeon
    • 1
  • Bethany McDaniel
    • 1
  1. 1.Department of Psychology & Institute for Intelligent SystemsUniversity of MemphisMemphisUSA
  2. 2.University of Illinois at ChicagoChicagoUSA
  3. 3.Educational Testing ServicePrincetonUSA

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