Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

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

Abstract

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.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2

References

  1. AAAS (American Association for the Advancement of Science) (1993). Benchmarks for science literacy: Project 2061. New York: Oxford University Press.

  2. Azevedo, R. (2005). Computer environments as metacognitive tools for enhancing learning. Educational Psychologist, 40, 193–198.

  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.

  4. Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.) (2000). How people learn. Washington, DC: National Academy Press.

  5. Brem, S. K., Russell, J., & Weems, L. (2001). Science on the Web: Student evaluations of scientific arguments. Discourse Processes, 32, 191–213.

  6. Britt, M. A., & Aglinskas, C. (2002). Improving student’s ability to use source information. Cognition and Instruction, 20(40), 485–522.

  7. Chi, M. T. H., de Leeuw, N., Chiu, M., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439–477.

  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.

  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.

  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.

  11. Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive developmental inquiry. American Psychology, 34, 906–911.

  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.

  13. Goldman, S. R., & Murray, J. (1992). Knowledge connectors as cohesion devices in text. Journal of Educational Psychology, 84, 504–519.

  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.

  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.

  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.

  17. Graesser, A. C., & Person, N. K. (1994). Question asking during tutoring. American Educational Research Journal, 31, 104–137.

  18. Hacker, D. J., Dunlosky, J., & Graesser, A. C. (Eds.) (1998). Metacognition in educational theory and practice. Mahwah, NJ: Erlbaum.

  19. Hadwin, A., & Winne, P. (2001). CoNoteS2: A software tool for promoting self-regulation. Educational Research and Evaluation, 7, 313–334.

  20. Halpern, D. F. (2002). An introduction to critical thinking (4th ed.). Mahwah, NJ: Erlbaum.

  21. Linn, M. C., Davis, E. A., & Bell, P. (Eds.) (2004). Internet environments for science education. Mahwah, NJ: Erlbaum.

  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.

  23. Mayer, R. E. (2005). Multimedia learning. Cambridge, MA: Cambridge University Press.

  24. McNamara, D. S. (2004). SERT: Self-explanation reading training. Discourse Processes, 38, 1–30.

  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.

  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.

  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.

  28. Rouet, J.-F. (2006). The skills of document use: From text comprehension to web-based learning. Mahwah, NJ: Erlbaum.

  29. Sanchez, C., & Wiley, J. (2006). Effects of working memory capacity on learning from illustrated text. Memory & Cognition, 34, 344–355.

  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.

  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.

  32. Vosniadou, S., & Brewer, W. F. (1992). Mental models of the earth: a study of conceptual change in childhood. Cognitive Psychology, 24, 535–585.

  33. White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition & Instruction, 16(1), 3–118.

  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.

  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.

  36. Wiley, J., Griffin, T. D., & Thiede, K. W. (2005). Putting the comprehension in metacomprehension. Journal of General Psychology, 132(4), 408–428.

  37. Wiley, J., & Myers, J. L. (2003). Availability and accessibility of information and causal inferences from expository text. Discourse Processes, 36, 109–129.

  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.

  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.

  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.

Download references

Acknowledgements

This research was supported by the National Science Foundation (REC 0126265, ITR 0325428, REESE 0633918). Any opinions, findings and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of NSF. We would like to thank Brian Haynes, Brandon King, and Kristy Tapp for assisting us in developing the computer software, collecting data, and analyzing the data.

Author information

Correspondence to Arthur C. Graesser.

Additional information

This work was conducted while Tenaha O’Reilly was a postdoctoral fellow at the University of Memphis.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Graesser, A.C., Wiley, J., Goldman, S.R. et al. SEEK Web tutor: fostering a critical stance while exploring the causes of volcanic eruption. Metacognition Learning 2, 89–105 (2007). https://doi.org/10.1007/s11409-007-9013-x

Download citation

Keywords

  • SEEK
  • Web
  • Critical thinking
  • Tutoring