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Melissa Dark Purdue University

Increasing Preservice Teachers' Capacity for Technology Integration Through the Use of Electronic Models. Melissa Dark Purdue University. Background. 70% of teachers report not feeling well prepared to use technology Even new teachers feel ill-equipped to integrate technology

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Melissa Dark Purdue University

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  1. Increasing Preservice Teachers' Capacity for Technology IntegrationThrough the Use of Electronic Models Melissa Dark Purdue University

  2. Background • 70% of teachers report not feeling well prepared to use technology • Even new teachers feel ill-equipped to integrate technology • Growth in ideas about, and confidence for, technology integration have not kept pace with growth in skills

  3. Why is Integration Hard to Achieve? • Teachers don’t know what technology integration should look like or how to accomplish it • They lack confidence for achieving something they have neither observed nor experienced • Teachers need information about why and how to use technology in meaningful ways

  4. Increasing Capacity for Technology Integration • Increase Ideas • Create a vision • Delineate strategies • Increase Self-Efficacy • Personal mastery • Vicarious experiences • Social persuasion • Physiological indicators

  5. Vicarious Experiences: A Powerful Option • Personal experiences are difficult to arrange • Use of models provides information about how to accomplish the task • Observing models can also increase confidence for performing similarly

  6. Should We Use Electronic Models? • Avoid logistical problems associated with real-time observations • Guarantee that certain performances are observed • Multimedia capability can bring models “to life” • Will learners feel removed or isolated from classrooms observed electronically?

  7. Methods • Pretest-posttest research design • Examined preservice teachers’ ideas about, and self-efficacy for, technology integration before and after interacting with electronic models of exemplary technology-using teachers • Quantitative data triangulated with qualitative data

  8. Participants • 69 students enrolled in 6 sections of a one-credit undergraduate technology course • Age Range: 18-25 (x = 20) • Gender: 65% female • Class: 71% Sophomores or Juniors • Major: 60% Elementary Education

  9. Description of Modeling Tool VisionQuest • CD-ROM tool incorporating video, audio, text, and electronic artifacts • Illustrates the beliefs and practices of six classroom teachers • Allows users to explore teachers’ classrooms one at a time or thematically

  10. VisionQuest: Main Menu

  11. VisionQuest: Sample Screen

  12. VisionQuest: Sample Page

  13. Procedures—Timeframe • Week 1 • Demographic information and consent obtained • Week 10 • Students completed (pre) idea and self-efficacy surveys • Students evaluated VQ using a software evaluation form • Week 11 • Students used VQ to learn about classroom organization issues • Students completed (post) idea and self-efficacy surveys

  14. Data Sources • Demographic Questionnaire • Online Surveys (pre and post) • Ideas: “I have specific ideas about how to use one computer effectively during large group instruction.” • Self-Efficacy: “I am confident I can use one computer effectively during large group instruction.” • Software Evaluation Questions • Observations and Interviews

  15. Data Analysis • Frequencies and percentages • Paired t-tests • Pearson correlations • Qualitative pattern seeking

  16. Results-Changing Ideas and Efficacy • Two-tailed paired t (df = 68) indicated significant increase in students’ ratings of perceived ideas (t = 8.85; p < .0000) from pre- to post survey • Two-tailed paired t (df = 68) indicated significant increase in students’ ratings of confidence (t = 3.34; p < .000) from pre- to post survey

  17. Results-Relationships among Variables • Significance level set at p < .0005 (critical r = .35) • No significant relationships among demographic characteristics (age, gender, class) and pre- and post- ideas and efficacy • No significant relationships among ratings of computer skills (novice, beginner, etc.) and pre- and post- ideas and efficacy

  18. Significant Relationships • Ideas for technology integration, pre and post, were significantly correlated (r = .61) • Confidence for technology integration, pre and post, was significantly correlated (r = .50) • Perceptions of ideas and confidence were significantly correlated, pre (r = .72) and post (r = . 84)

  19. Students’ Perceptions of Learning from Electronic Models • On a scale from 1 (low) - 5 (high), students rated the classroom activities observed as realistic (x = 4.46) • On a scale from 1-5, students rated the video examples observed as relevant (x = 4.31) • Student interview comments were overwhelmingly positive

  20. Students’ New Ideas Included: • Using new assessment techniques • Organizing group work • Using different activities to teach same content • Using HyperStudio in a music class • Establishing a good climate • Using stations

  21. Discussion • Electronic models can be used to increase ideas and self-efficacy for technology integration • Models were considered realistic and relevant • Medium - high levels of skills do not translate into ideas or confidence • Increasing teachers’ specific ideas for technology use may be one way to increase confidence

  22. Implications • VisionQuest can be used as the “textbook” for technology integration courses. • Within a “one-computer classroom,” VisionQuest can be used to provide visual classroom scenarios for discussion or analysis. • Individually or collectively, students could investigate different portions of VisionQuest within a lab-setting.

  23. Limitations/Future Research • Lack of control group • Homogeneous group of participants • Perceptions may not translate into action • Long-range benefits are unknown

  24. Conclusion • Many teachers lack ideas and confidence for integrating technology into their classrooms • Self-efficacy theory suggests that observing models can serve informational and motivational functions • Electronic models increase educators’ options for providing future teachers with exemplary models

  25. Questions?

  26. For more information: • Melissa Dark <dark@cerias.purdue.edu> Paper available at: http://www.edci.purdue.edu/ertmer/conferences

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