1. THE THREE DIMENSIONS OF MULTIMEDIA TEACHING OF STATISTICS
Nathaniel Derby, Wolfgang Härdle, and Bernd Rönz
Institute for Statistics and Econometrics
Economics Department
Humboldt University of Berlin
Spandauer Straße 1
Berlin
Germany

2. THE NEED FOR MORE ADAPTIVE TEACHING METHODS
Most students find statistics difficult and uninspiring:
Conflicts with pre-conceived ideas about chance and data analysis
Increasingly complex statistical data structures
Complex mathematical formulas
Instruction still dependent on blackboard-based lectures and paper-and-pencil homework

3. THE THREE DIMENSIONS OF TEACHING STATISTICS
The Third Dimension: Jumping between frames of the sequence (context)
3.3
3.2
3.1 1 2 3 4
The First Dimension: The sequence of the lesson (storyline)
The Second Dimension: Examples
and more information (deepening)
Map these three dimensions onto the computer.

4. WHY A NET-BASED SOLUTION?
Web browser the only connection between different platforms
Easy access to real data sets
allows for the use of web-based tools

5. GOALS
For the teacher:
1. Move from classroom examples to more elaborate statistical data analysis
2. Handle more data and examples in the instruction
3. Emphasize more statistical critical thinking
4. Demonstrate the assumptions connected with various statistical methods and models
5. Concentrate more on the students’ difficulties

6. GOALS For the student (three dimensions):
1. Review the lectures at his/her own pace
2. Perform examples with several data sets and view the results
3. Discover relations between the course subjects

7. THE PRESENT SITUATION Transparencies:
An outline of the lectures in catch phrases
Important formulas
Graphic representations
Examples -- few computer-based, presented by lecturer

8. THE PRESENT SITUATION Teaching material for the students:
Outline of the lectures
Selected textbook references
Collection of the formulas
Printed versions of transparencies
Prepared exercises with solutions
Limited computer use, not stressed by the lecturer

9. THE PROPOSAL: MM*STAT Hypertext functionality throughout all pages
More information
Examples (Fully explained, enhanced, interactive, programmable)
Multiple choice questions at the end of paragraphs
Glossary
Introductory page with general explanations
Help system
Video sequences
Sound

10. THE PROPOSAL: MM*STAT Ideas for future development:
Question-answer page
Page for notes
Page for the timing of the lecture
Links to other subject areas for more information

11. Table of Contents:

12. List of subtopics:

13. Lecture unit:

14. More information:

15. Lecture unit revisited:

16. Fully explained example:

17. Enhanced Example:

18. Interactive Example:

19. Table of Contents Revisited:

20. Computing Example:

21. Video:

22. REFERENCES
Härdle, W., Klinke, S., and Marron, J. (1999). Connected Teaching of Statistics, recently submitted to the Journal of Statistical Planning and Inference.
Müller, M. (1998). Computer-Assisted Statistics Teaching in Network Environment. COMPSTAT 1998 Proceedings in Computational Statistics (ed. Payne, R., Green, P.), Heidelberg: Physica-Verlag
Müller, M. (1998). Teaching Statistics with XploRe. Math&Stats Newsletter, Glasgow: CTI Statistics

23. REFERENCES
Redfern, E.J., Bedford, S.E. (1994). Teaching and Learning through Technology: The Development of Software for Teaching Statistics to Non-Specialist Students. COMPSTAT 1994 Proceedings in Computational Statistics (ed. Dutter, R., Grossmann, W.), Heidelberg: Physica-Verlag
Sonderforschungsbereich staff and projects
Talbot, M. (1998). Statistics Training and the Internet. In: COMPSTAT 1998 Proceedings in Computational Statistics (ed. Payne, R., Green, P.), Heidelberg: Physica- Verlag

24. REFERENCES
Tufte, Edward, The Visual Display of Quantitative Information, Graphics Press, New Haven, 1983
West, R.W. (1997). Statistical Applications for the World Wide Web. In: Bulletin of the International Statistical Institute, 51st Session Proceedings Book 2, , Turkey