Abstract
This study was designed to theoretically articulate and empirically assess the role of computer scaffolds. In this project, several examples of educational software were developed to scaffold the learning of students performing high level cognitive activities. The software used in this study, Artemis, focused on scaffolding the learning of students as they performed information seeking activities. As 5th grade students traveled through a project-based science unit on photosynthesis, researchers used a pre-post design to test for both student motivation and student conceptual understanding of photosynthesis. To measure both variables, a motivation survey and three methods of concept map analysis were used. The student use of the scaffolding features was determined using a database that tracked students’ movement between scaffolding tools. The gain scores of each dependent variable was then correlated to the students’ feature use (time and hits) embedded in the Artemis Interface. This provided the researchers with significant relationships between the scaffolding features represented in the software and student motivation and conceptual understanding of photosynthesis. There were a total of three significant correlations in comparing the scaffolding use by hits (clicked on) with the dependent variables and only one significant correlation when comparing the scaffold use in time. The first significant correlation (r = .499, p < .05) was between the saving/viewing features hits and the students’ task value. This correlation supports the assumption that there is a positive relationship between the student use of the saving/viewing features and the students’ perception of how interesting, how important, and how useful the task is. The second significant correlation (r = 0.553, p < 0.01) was between the searching features hits and the students’ self-efficacy for learning and performance. This correlation supports the assumption that there is a positive relationship between the student use of the searching features and the students’ perception of their ability to accomplish a task as well as their confidence in their skills to perform that task. The third significant correlation (r = 0.519, p < 0.05) was between the collaborative features hits and the students’ essay performance scores. This correlation supports the assumption that there is a positive relationship between the student use of the collaborative features and the students’ ability to perform high cognitive tasks. Finally, the last significant correlation (r = 0.576, p < 0.01) was between the maintenance features time and the qualitative analysis of the concept maps. This correlation supports the assumption that there is a positive relationship between the student use of the maintenance features and student conceptual understanding of photosynthesis.
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Abbas JM (2001). Smoothing the information-seeking path: removing representational obstacles in the middle school digital library environment. Unpublished doctoral dissertation, University of North Texas
Aleven V, Stahl E, Schworm S, Fischer F, Wallace R (2003) Help seeking and help design in interactive learning environments. Rev Educ Res 73(3):277–320
Blumenfeld PC, Soloway E, Marx RW, Krajcik JS, Guzdial M, Palincsar A (1991) Motivating project-based learning: sustaining the doing, supporting the learning. Educ Psychol 26(3–4):369–398
Bransford JD, Brown AL, Cocking RR (1999) How people learn: brain, mind, experience, and school. National Academy Press, Washington, DC
Bruner J (1986) Actual minds, possible worlds. Harvard University Press, Cambridge, MA
Freiberg HJ, Driscoll A (2000) Universal teaching strategies, 3rd edn. Allyn and Bacon, Boston
Goldsmith TE, Johnson PJ, Acton WH (1991) Assessing structural knowledge. J Educ Psychol 83(1):88–96
Jones BF, Valdez G, Nowakowski J, Rasmussen C (1999) Plugging in: choosing and using educational technology. NEKIA Communications, North Central Regional Educational Laboratory, Washington, DC
Krajcik JS, Blumenfield PC, Marx RW, Soloway E (1994) A collaborative model for helping teachers learn project-based instruction. Elem School J 94:483–497
Krajcik JS, Blumenfield PC, Marx RW, Bass KM, Fredricks J, Soloway E (1998a) Inquiry in project-based science classrooms: initial attempts by middle school students. J Learn Sci 7(3&4):313–350
Krajcik JS, Soloway E, Blumenfield PC, Marx RW (1998b) Scaffolding technology tools to promote teaching and learning in science. In: Dede C (ed) ASCD yearbook: learning & technology. Association for Supervision and Curriculum Development, Alexandria, VA, pp 31–45
Lumpe AT, Butler KA (2002) The information seeking strategies of high school science students. Res Sci Educ 32(4):549–566
Marx RW, Blumenfield PC, Krajcik JS, Soloway E (1997) Enacting project-based science: challenges for practice and policy. Elem School J 97:341–358
McClure JR, Bell PE (1990) Effects of an environmental education-related STS approach instruction on cognitive structures of preservice science teachers (ERIC Document Reproduction Service No. ED 341582)
National Board Professional Teaching Standards for Science: Adolescence/Young Adulthood (2003). http://www.nbpts.org/candidates/guide/whichcert/19AdolYoungScience.html. Retrieved 12 September 2003
National Education Technology Standards for Students (2005). http://cnets.iste.org/students/s_stands.html. Retrieved 12 September 2005
National Research Council (1996) National science education standards. National Academy Press, Washington, DC
Novak JD, Gowin DR (1984) Learning how to learn. Cambridge University Press, New York
Pinrich PR, Smith DA, Garcia T, McKeachie WJ (1991) A manual for the motivated strategies for learning questionnaire (MSLQ). The Regents of the University of Michigan, Ann Arbor, MI
Wallace R, Soloway E, Krajcik J, Bos N, Hoffman J, Hunter H, Kiskis D, Klann E, Peters G, Richardson D, Ronen O (1998) ARTEMIS: Learner-centered design of an information seeking environment for K-12 education. In: Proceedings of ACM CHI, pp 195–202
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This material is based upon work supported by the National Science Foundation (REC9980055). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Butler, K.A., Lumpe, A. Student Use of Scaffolding Software: Relationships with Motivation and Conceptual Understanding. J Sci Educ Technol 17, 427–436 (2008). https://doi.org/10.1007/s10956-008-9111-9
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DOI: https://doi.org/10.1007/s10956-008-9111-9