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

10178 Berlin

Germany

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

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.

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

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

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

GOALS

THE PRESENT SITUATION

Transparencies:

• An outline of the lectures in catch phrases

• Important formulas

• Graphic representations

• Examples -- few computer-based, presented by lecturer

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

THE PRESENT SITUATION

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

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

THE PROPOSAL: MM*STAT

Table of Contents:

List of subtopics:

Lecture unit:

More information:

Lecture unit revisited:

Fully explained example:

Enhanced Example:

Interactive Example:

Table of Contents Revisited:

Computing Example:

Video:

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.), 77 - 88. Heidelberg: Physica-Verlag

Müller, M. (1998). Teaching Statistics with XploRe. Math&Stats Newsletter, 21 - 24. Glasgow: CTI Statistics

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.), 408 - 414. 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.), 461 - 466. Heidelberg: Physica- Verlag

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, 7 - 10, Turkey