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Helping Real Kids Learn Via Virtual Environments

Helping Real Kids Learn Via Virtual Environments. Chris Dede Harvard University. “Next Generation” Interfaces for Distributed Interaction. World to the Desktop: Accessing distant experts and archives for knowledge creation, sharing, and mastery

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Helping Real Kids Learn Via Virtual Environments

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  1. Helping Real Kids LearnViaVirtual Environments Chris Dede Harvard University

  2. “Next Generation” Interfacesfor Distributed Interaction • World to the Desktop:Accessing distant experts and archives for knowledge creation, sharing, and mastery • Ubiquitous Computing:Wearable wireless devices coupled tosmart objects for “distributed cognition” • Multi-User Virtual Environments:Immersion in virtual contexts withdigital artifacts and avatar-based identities

  3. What is a MUVE? • A representational container that enablesmultiple simultaneous participants to accessvirtual spaces configured for learning. • A place where learners represent themselves through graphical avatars (persona)to communicate with other learnersas well as with experts of various types. • A learning context that provides activitiesin support of classroom curriculum.

  4. River City Figure 2: River water sampling Figure 1: Lab equipment inside the University

  5. River City Figure 3: Screen Shot of an “agent” giving information. Smithsonian artifact on the right.

  6. Educational Objectives • To help students learn the skills necessaryfor scientific inquiry, with the emphasison experimental design and the typesof investigation in science fair projects • To help students learn biology and ecology content related to national science standards • To motivate students to learnscience content and inquiry skills • To enhance students’ self-imageas science learners

  7. Pedagogical Capabilitiesof Learning Technologies • facilitating guided, reflective inquiry through extended projects thatgenerate complex products • utilizing modeling and visualization as powerful means of bridgingbetween experience and abstraction • involving students in virtualcommunities-of-practice

  8. Students

  9. Modeling Across the Curriculum • IERI federal funding • Five types of modeling tools over 3 years • Focus on causal understanding, transfer, epistemology of models, modeling skills • Longitudinal growth modelingas a research method • “Conditions for success” a crucial issue

  10. BioLogica (Concord Consortium)

  11. Model-It (Univ. of Michigan)

  12. Research Objectives • To create and evaluate graphical Multi-User Virtual Environments (MUVEs)that use digitized museum resources • To study how MUVE learning experiences affect motivation and educational outcomes for middle school students, particularly those in the bottom-third of achievement • To examine the process needed to successfully integrate MUVEsin typical classroom settings

  13. Research Questions - Motivation • How do MUVE experiences affectstudents’ motivation to learn about science? • Will students voluntarily accessthese shared virtual learning environmentsoutside their classroom setting? • What types of content and interactiondo students find most interesting?

  14. Research Questions - Learning • To what extent do museum-related MUVEs aid students’ performance on assessments related to the district’s science curriculum and to national science standards? • Do students gain skills in experimental design that generalize to settingssuch as science fair projects? • Do bilingual MUVEs aid studentsin mastering both languages?

  15. Research on Learning Styles How are participants’ learning and motivation related to their individual characteristics (e.g., prior experience with computers, knowledge about and interest in science, gender, ethnicity, linguistic proficiency in English)?

  16. Research Questions - Design • What types of science-related knowledge and skills are best incorporatedinto MUVE settings? • How are participants’ learning and motivation related to design characteristics of the MUVEs? • What instructional design strategies generalize beyond this project to other uses of shared virtual environments in education?

  17. Research on Museum Learning • Does using museum-based MUVEs for learning science alter students’ patternsof museum usage? • Do MUVE participants who visit Smithsonian science exhibits have different patterns of motivation and learningabout science than those who do not? • Do students’ reactions to MUVEs suggest design strategies for improvingmuseums’ physical exhibits?

  18. Research on Implementation • How usable in classroom settingsare MUVEs? • What problems with implementation and curriculum/assessment integrationdo teachers encounter?

  19. Methods and Analysis • One sixth and one seventh grade classroomin schools with diverse student populations, including many free and reduced lunch pupils • Control classrooms arranged witha similar, but technology-free curriculum • 45 students in the two experimental classes,and 36 in the control, evenly split by gender • The quantitative data analyzed with SAS • Descriptive statistics, correlations and regression models run using a significance level of p < .05

  20. Data • Qualitative and quantitative data were collected from students and teachers over the three-week implementation • Quantitative data, pre and post intervention: • Patterns for adaptive learning survey (Midgley, 2000) • Content test, (modified from Tobin, 1999) • Demographic data • Teacher expectations of student success • Observational data • Pre-intervention teacher questionnaire on pedagogyand technology comfort • Post-intervention teacher narratives on their perceptionsof the curriculum and the technology

  21. Results: Content and Motivation • 6 out of 7 experimental students scoringless than 35% on the content pre-testimproved their content knowledge above that level, while only 2 of 5 control students did so • In one seventh grade classroom, five different hypotheses were chosen,with causes rangingfrom population density to immigrationto water pollution • The experimental group, on average, hadmore positive changes in motivation mastery(as measured by the PALS assessment)than did the control group,controlling for collaboration and science interest

  22. Results: Student Efficacy • Experimental group students perceived their academic efficacy increasing by one point (out of 5) on average as opposed to the control groups’ decrease of .31. (significant at t=3.36, p<.05) • The control group, over the course of the study, increased their view that their teacher pressed them for understanding, while the experimental group decreased theirs • This might indicate the switch from ‘sage on the stage’ to ‘guide on the side’ that this technology promotes,

  23. Results: Inquiry

  24. Results: Student Characteristics • 7th grade experimental students showed approximately 5 points more improvementat all levels of content pretest scoresthan did 6th grade students,controlling for both technology interest and use • Despite the fact that over 50% of the studentswere ESL, language was not a significant factor • The MUVE seemed to have the most positive effects for students with high perceptions of their thoughtfulness of inquiry (TI). These students, on average, scored higher on the post content test, controlling for SES, science GPA, ethnicity and content pre-test score

  25. Summary of Significance • MUVEs seem quite feasible as an addition to more conventional kinds of computer-based instruction. • Preliminary results indicate the MUVE is motivating for all students, including those of lower achievement. • The MUVE seemed to have the most positive effects for students with high perceptions of thoughtfulness of inquiry. • We found that students did perceive multi-variate problems in the MUVE. • Language was not a barrier to success. • There are some indications that the MUVE with embedded guidance can support students’ growth towards self-responsibility in learning.

  26. So What?Why Should Teachers Care? • enhancing motivation (challenge, curiosity, beauty, fantasy, fun, social recognition) • reaching learners who don’t do well in conventional classroom settings • building fluency in distributed modes of communication and expression -- rhetoric • rich, authentic representations(e.g., MedievalWorld)

  27. Evolving towardDistributed Learning • Sophisticated Methods of Learning and Teaching • guided construction of knowledge and meaning • apprenticeships and mentoring • infusion of research into teaching • Orchestrated across classrooms, homes, workplaces, community settings • On demand, just-in-time • Collaborative distributed across space, time, media

  28. Conditions for Successin Technological Innovation • High-quality learning tools and materials • Extensive professional development • Strong technical infrastructure • Organizational shifts to enabledeeper content, powerful pedagogies • Equity in Content and Servicesas well as Access and Literacy • Stakeholder Involvement

  29. “Systemic” Reform Implementation • transforming standard practices for curriculum, pedagogy, assessment, incentives, management and organization, professional development, and educational research • achieving success with all students • involving parents, employers, community,colleges, and schools as full partners in the educational process boundaries of “system” aroundthe school and the community

  30. References • Website: http://www.virtual.gmu.edu/muvees/. • Partners: Harvard's Graduate School of Education, the Virtual Environments Lab at George Mason University, the Smithsonian's National Museum of American History (NMAH), and Thoughtful Technologies, Inc. • Midgley, C., Maehr, M. L., Hruda, L. Z., Anderman, E., Anderman, L., Freeman, K. E., Gheen, M., Kaplan, A., Kumar, R., Middleton, M. J., Nelson, J., Roeser, R., & Urdan, T. (2000). Manual for the patterns of adaptive learning scales (PALS), Ann Arbor, MI: University of Michigan. • Tobin, Mark (1999). Improving student retention through the use of technology. Unpublished Master’s thesis, Saint Xavier University.

  31. What are the MUVERs investigating? • The potential of MUVE-based museum-related “participatory historical situations” to aid motivation and learning in science. • How the design characteristicsof these learning experiences affectstudents' motivation and educational outcomes. • The extent to which museum-related MUVEs can aid pupils' performance on conventional assessments related to national science standards. • How MUVEs aid bilingual andmulticultural learning.

  32. What is Special about MUVEES? • Interesting things: many MUVEs lack interesting artifacts for interaction.The Smithsonian partnership affordsaccess to millions of artifactsand their associated histories. • Motivational capabilities drawn from strategies used by the entertainment industry. • Direct relationship to national science standards and other classroom activities.

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