Abstract
This article presents two studies investigating how computer interface affordances influence basic cognition, including ideational fluency, problem solving, and inferential reasoning. In one study comparing interfaces with different input capabilities, students expressed 56% more nonlinguistic representations (diagrams, symbols, numbers) when using pen interfaces. A linear regression confirmed that nonlinguistic communication directly mediated a substantial increase (38.5%) in students' ability to produce appropriate science ideas. In contrast, students expressed 41% more linguistic content when using a keyboard-based interface, which mediated a drop in science ideation. A follow-up study pursued the question of how interfaces that prime nonlinguistic communication so effectively facilitate cognition. This study examined the relation between students' expression of nonlinguistic representations and their inference accuracy when using analogous digital and non-digital pen tools. Perhaps surprisingly, the digital pen interface stimulated construction of more diagrams, more correct Venn diagrams, and more accurate domain inferences. Students' construction of multiple diagrams to represent a problem also directly suppressed overgeneralization errors, which were the most common inference failure. These research results reveal that computer interfaces have communications affordances which elicit communication patterns that can substantially stimulate or impede basic cognition. Implications are discussed for designing new digital tools for thinking, with an emphasis on nonlinguistic and especially spatial representations that are most poorly supported by current keyboard-based interfaces.
- ANOTO. 2011. http://www.anoto.com/. (Last accessed 10/11).Google Scholar
- Bangert-Drowns, R. 1993. The word processor as an instructional tool: A meta-analysis of word processing in writing instruction. Rev. Edu. Res. 63, 69--93.Google ScholarCross Ref
- Barrows, H., Norman, G., Neufeld, V., and Feightner, J. 1982. The clinical reasoning of randomly selected physicians in general medical practice. Clin. Invest. Med. 5, 49--55.Google Scholar
- Bauer, M. and Johnson-Laird, P. 1993. How diagrams can improve reasoning. Psychol. Sci. 4, 6, 372--378.Google ScholarCross Ref
- Bloom, P., Peterson, M., Nadel, L., and Garrett, M., Eds. 1996. Language and Space. MIT Press, Cambridge, MA.Google Scholar
- Crowne, S. 2007. Harnessing Technology Review 2007: Progress and Impact of Technology on Education (BEC1-15506). Coventry: Becta Reviews.Google Scholar
- Darves, C. and Oviatt, S. 2004. Talking to digital fish: Designing effective conversational interfaces for educational software. In Evaluating Embodied Conversational Agents, Z. Ruttkay, C. Pelachaud, Eds. Kluwer, Dordrecht, 7, 271--292. Google ScholarDigital Library
- Gibson, J. 1977. The theory of affordances. In Perceiving, Acting and Knowing, R. Shaw, J. Bransford, Eds. Erlbaum, Hillsdale, NJ, 3, 67--82.Google Scholar
- Guilford, J. P. 1956. The structure of intellect. Psychol. Bull. 53, 267--293.Google ScholarCross Ref
- Haas, C. 1989. Does the medium make the difference? Two studies of writing with pen and paper and with computers. Hum. Comput. Interac. 4, 149--169. Google ScholarDigital Library
- Johnson-Laird, P. 1999. Space to think. In Language and Space, P. Bloom, M. Peterson, L. Nadel, and M. Garrett, Eds. MIT Press, Cambridge, MA, 437--462.Google Scholar
- Kahneman, D., Slovic, P., and Tversky, A., Eds. 1982. Judgment Under Uncertainty: Heuristics and Biases. Cambridge University Press, NY.Google Scholar
- Kirk, R. 1995. Experimental Design: Procedures for the Behavioral Sciences, 3rd Ed., Brooks/Cole Publishing. Pacific Grove, CA.Google Scholar
- Larkin, J. and Simon, H. 1987. Why a diagram is (sometimes) worth ten thousand words. Cognit. Sci. 11, 65--99.Google ScholarCross Ref
- LIVESCRIBE. 2011. Livescribe home page. http://www.livescribe.com. (Last accessed 10/11).Google Scholar
- Levinson, S. 2003. Space in Language and Cognition: Explorations in Cognitive Diversity, Language, Culture and Cognition. Cambridge University Press, Cambridge, U.K.Google Scholar
- Luria, A. 1961. The Role of Speech in the Regulation Normal and Abnormal Behavior. Liveright, New York, NY.Google Scholar
- ONENOTE. 2011. Microsoft One Note. http://www.microsoft.com/office/onenote/. (Last accessed 10/11).Google Scholar
- Oviatt, S. To appear. The Future of Educational Interfaces. Routledge Press, London, U.K.Google Scholar
- Oviatt, S., Arthur, A., Brock, Y. and Cohen, J. 2007. Expressive pen-based interfaces for math education. In Proceedings of the Conference on Computer Supported Collaborative Learning 2007: Of Mice, Minds and Society, International Society of the Learning Sciences, C. Chinn, G. Erkens S. Puntambekar, Eds. Vol. 8, Part 2, 569--578. Google ScholarDigital Library
- Oviatt, S., Arthur, A., and Cohen, J. 2006. Quiet interfaces that help students think. In Proceedings of the 19th Annual ACM Symposium on User Interface Software and Technology, 191--200. Google ScholarDigital Library
- Oviatt, S. and Cohen, A. 2010a. Toward high-performance communications interfaces for science problem-solving. J. Sci. Educ. Technol. 19, 6, 515--531.Google ScholarCross Ref
- Oviatt, S. and Cohen, A. 2010b. Supporting students' thinking marks: Designing accessible interfaces for science education. In Proceedings of the American Educational Research Association Conference.Google Scholar
- Roth, W. M. 2005. Talking Science: Language and Learning in Science Classrooms. Rowman and Littlefield, Toronto.Google Scholar
- Ruths, D., Nakhleh, L. Ivengar, M., Reddy, S., and Ram, P. 2006. Graph-theoretic hypothesis generation in biological signaling networks. J. Comput. Biol. 13, 1546--1557.Google ScholarCross Ref
- Schwartz, D. and Heiser, J. 2006. Spatial representations and imagery in learning. In Cambridge Handbook of the Learning Sciences, R. Sawyer, Ed. Cambridge University Press, New York, NY, 19, 283--298.Google Scholar
- Smith, M., Wood, W., Adams, W., Wieman, C., Knight, J., Guild, N., and Su, T. 2009. Why peer discussion improves student performance on in-class concept questions. Science 323, 122--124.Google ScholarCross Ref
- Stieff, M. and Raje, S. 2010. Expert algorithmic and imagistic problem solving strategies in advanced chemistry. Spatial Cogn. Comput. 10, 53--81.Google ScholarCross Ref
- Suthers, D. and Hundhausen, C. 2003. An experimental study of the effects of representational guidance on collaborative learning. J. Learn. Sci. 12, 183--219.Google ScholarCross Ref
- Sweller, J., van Merrienboer, J., and Paas, F. 1998. Cognitive architecture and instructional design. Edu. Psychol. Rev. 10, 251--257.Google Scholar
- Tversky, B. and Suwa, M. 2009. Thinking with sketches. In Tools for Innovation, A. Markman, Oxford University Press, Oxford, U.K. 75--84.Google Scholar
- Vvygotsky, L. 1962. Thought and Language. MIT Press, Cambridge, MA.Google Scholar
- Weber, E., Bockenholt, U., Hilton, D., and Wallace, B. 1993. Determinants of diagnostic hypothesis generation. Effects on information, base rates, and experience. J. Exp. Psychol. Learn. Memory Cognit. 19, 1151--1164.Google ScholarCross Ref
- van Merrienboer, J. and Sweller, J. 2005. Cognitive load theory and complex learning: Recent developments and future directions. Educ. Psychol. Rev. 17, 2, 147--177.Google ScholarCross Ref
- Zhang, H. and Linn, M. 2008. Using drawings to support learning from dynamic visualizations. In Proceedings of the Annual Meeting of the American Educational Research Association (AERA), New York, NY.Google Scholar
Index Terms
- The impact of interface affordances on human ideation, problem solving, and inferential reasoning
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