THE THREE DIMENSIONS OF MULTIMEDIA TEACHING OF STATISTICS

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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

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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

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THE THREE DIMENSIONS OF TEACHING STATISTICS
Map these three dimensions onto the computer.
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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

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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

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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

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THE PRESENT SITUATION

• Transparencies
• An outline of the lectures in catch phrases
• Important formulas
• Graphic representations
• Examples -- few computer-based, presented by
  lecturer

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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

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THE PROPOSAL MMSTAT

• 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

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THE PROPOSAL MMSTAT

• 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

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• Table of Contents

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List of subtopics
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Lecture unit
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More information
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Lecture unit revisited
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Fully explained example
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Enhanced Example
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Interactive Example
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Table of Contents Revisited
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Computing Example
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Video
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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.
MathStats Newsletter, 21 - 24. Glasgow CTI
Statistics
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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

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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