1. The Virtual Cell: A Role-Based Virtual Environment for Learning Cell Biology
Alan R. White
Phillip E. McClean
Brian M. Slator
Lisa Daniels
Jeff Terpstra
North Dakota
State University
Fargo, ND

2. World Wide Web Instructional Committee
NDSU WWWIC
World Wide Web Instructional Committee
Paul Juell Donald Schwert
Phillip McClean Brian Slator
Bernhardt Saini-Eidukat Alan White
Jeff Clark Lisa Daniels
Jeff Terpstra
WWWIC faculty supported by large teams of undergraduate and graduate students.
WWWIC’s virtual worlds research supported by:
NSF grants DUE , EAR , DUE , ITR and EPSCoR ;
US Dept of Educ. FIPSE P116B000734, FIPSE P116B011528; FIPSE P116B030120

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

4. Educational Role-playing Games “Learning-by-doing” Experiences
Problem solving
Scientific method
Real-world content
Mature thinking

5. Advantages of Virtual Worlds
Collapse virtual time and distance
Allow physical or practical impossibilities
Participate from anywhere
Interact with other users, virtual artifacts, and software agents
Multi-user collaborations and competitive play

6. Technical Approaches Networked, internet-based, client-server
MultiPlayer
Simulation-based
Implemented in Java applets

7. Technical Approaches MUD = Multi User Domain
MOO = Object Oriented MUD Multi-user database for implementing objects and methods to represent rooms, containers and agents

8. Technical Approaches
MUDs and MOOs are typically task-oriented with keyboard interactions
Ours are also graphically-oriented, point & click interfaces

9. The Virtual Cell The Geology Explorer The Projects Dollar Bay
Like-a-Fishhook Village
Digital Archive for Archaeology
Blackwood – Old West Town

10. The Virtual Cell User Interface

11. The Virtual Cell Rendered in VRML (Virtual Reality Modeling Language)

12. You are a biologist who can “fly around” inside the cell.

13. Users are assigned specific goals For example: Identify 5 different organelles

14. A Virtual Laboratory is attached

15. The Cell User movements are tracked by MOO software.

16. Users set up experiments in the Cell to accomplish their assigned goals.

17. The Virtual Cell User Interface

19. The Virtual Cell: Assessment Protocol Text-Based Virtual Cell
Pre-course Assessment:
400+ students
Computer Literacy Assessment:
Divide by Computer Literacy
and Biology Lab Experience
Text-Based
Control Group:
(150 students, approx.)
Virtual Cell
Treatment Group:
(125 students)
Web-Based
Alternative Group:
(125 students)
Post-course Assessment:
400 students

20. Mean Post-Intervention Scenario Scores
Module:
Group No. Organelle ID Cellular Resp.
Text a 10.6a
Web b 13.7b
VCell c 17.3c
Within any column, any two means followed by the same letter are not significantly different at P=0.05 using the LSD mean separation test.

21. What we have found:
Virtual Cell is currently a supplement to Introductory Biology lectures.
It has the potential to replace certain sections of a course.
It can also be used in laboratory settings.
Virtual Cell does provide an authentic experience.

22. Cell Biology Animations
Visualization in 3D aids learning
Animations are effective visualization tools for novice learners
Animations enhance long-term memory retention
Animations reveal the complexity of dynamic processes

23. Virtual Cell Animations

24. Virtual Cell Animations
First Look

25. Virtual Cell Animations
Advanced Look

26. Virtual Cell Animations
Transcription
Translation
Bacterial gene expression (Lac Operon)
Protein import to organelle
Cellular respiration
Biological gradients & ATP synthesis
RNA processing
mRNA splicing

27. Virtual Cell Animations
Translation Animation

28. Virtual Cell Animations
Classroom Experiment
Education 321 – Introduction to Teaching
Diverse class of pre-service teachers
Pre-Test Multiple Choice Protein Synthesis
Treatment Lectures and individual study about protein synthesis
Post-Test Multiple Choice Protein Synthesis

29. Virtual Cell Animations
Classroom Experiment
Treatments:
A (n=14) Animation Lecture
Individual Study of Animation
B (n=14) Individual Study of Text
Animation Lecture
C (n=15) Overheads Lecture
D (n=12) Individual Study of Text
Overheads Lecture

30. Virtual Cell Animations
Group
PostTest Mean
Difference
A Animation Lecture
Individual Animation
3.54
2.54
B Individual Text
Animation Lecture
2.73
1.50
C Overheads Lecture
2.50
1.20
D Individual Text
Overheads Lecture
2.07
1.67

31. Virtual Cell Animations
Comparison
P Value
Means Comparison
Difference
A vs B
0.0442*
0.0237*
A vs C
0.0150*
0.0036*
A vs D
0.0004*
0.0046*
B vs C
0.5612
0.4881
B vs D
0.0823
0.4669
C vs D
0.2824
0.9409

32. Virtual Cell Animations
Conclusions
Animation used both during lecture and individual study significantly improves content retention.

33. Acknowledgements Graphic Artists Christina Johnson, Roxanne Rogers,
Rob Brantseg, Kellie Martindale, Mark Rose
Aaron Bergstrom
Programming
Brad Vender, Mei Li, Jacob Halvorson,
Daniel Small, Kellie Erickson,
Ganesh Padmanabhan, John Opgrande
Education
Brian Meier, Jill Hockemeyer, Richard Danielson
Kim Addicott, John Reber

34. To visit WWWIC Projects:
vcell.ndsu.edu
wwwic.ndsu.edu
Supported by: National Science US Dept of Educ.
Foundation FIPSE

36. Outcomes:. Cell Biology Content. Learning-by-Doing. Problem Solving
Outcomes: Cell Biology Content Learning-by-Doing Problem Solving Hypothesis Formation Deductive Reasoning Mature Thinking

37. Virtual Cell Animations
Classroom Experiment - Results

38. Works in Progress
Photosystem II