1. Dr. Brian M. Slator, Computer Science Department North Dakota State University Virtual Worlds for Education

2. NDSU WWWIC World Wide Web Instructional Committee WWWIC’s virtual worlds research supported by NSF grants DUE-9752548, EAR-9809761, DUE-9981094, ITR-0086142 and EPSCoR 99-77788 WWWIC faculty supported by large teams of undergraduate and graduate students. Paul JuellDonald Schwert Phillip McCleanBrian Slator Bernhardt Saini-EidukatAlan White Jeff Clark

3. MultiUser Exploration Spatially-oriented virtual worlds Practical planning and decision making Educational Role-playing Games “Learning-by-doing” Experiences

4. Balancing Pedagogy with Play Games have the capacity to engage! Powerful mechanisms for instruction Illustrate real-world content and structure Promote strategic maturity (“learning not the law, but learning to think like a lawyer”)

5. The Geology Explorer

6. The Virtual Cell

7. Work in Progress

8. Like-A-Fishhook Time Line 1839 1845 1862 1950 1890 2001 1930

9. Students can join from any remote locationStudents can join from any remote location They can log in at any time of day or nightThey can log in at any time of day or night Human tutors cannot be available at all times to helpHuman tutors cannot be available at all times to help Students can become discouraged or “lost” in the world and not know whyStudents can become discouraged or “lost” in the world and not know why In Virtual Environments: Tutors are Needed

10. Intelligent Software Tutoring Agents. (example: Diagnostic Tutors) 1. Equipment tutor 2. Exploration tutor 3. Science tutor Detects when a student makes a wrong guess and why (i.e. what evidence they are lacking); or when a student makes a correct guess with insufficient evidence (i.e. a lucky guess) Tutoring is Done by:

11. Rejects the notion of standardized multiple choice tests Pre-game narrative-based survey short problem-solving stories students record their impressions and questions Similar post-game survey with different but analogous scenarios Surveys analyzed for improvement in problem-solving Assessment Qualitative

12. Mean Post-Intervention Scenario Scores for 1998 Geology Explorer - NDSU Physical Geology Students GraderGraderGrader GroupNo.OneTwoThree Alternate 9529.3a27.0a42.6a Control19525.1a25.5a44.5a Planet Oit 7840.5b35.4b53.4b Within any column, any two means followed by the same letter are not significantly different at P=0.05 using Duncan’s multiple range mean separation test.