Utilizing a Digital Library to Teach Introductory Statistics

1
Utilizing a Digital Library to Teach Introductory
Statistics

• Joint Fall Conference, TMTA and MTMT

2
Utilizing a Digital Library to Teach Introductory
Statistics

• Lisa Bloomer Green, Ph. D.
• Scott McDaniel, Ed. D.
• Ginger Holmes Rowell, Ph. D.
• Megan Duffey, Ileah McKee
• Undergraduate Students
• Middle Tennessee State University

3
Outline

• CAUSE and CAUSEweb
• Using Internet Resources throughout the Learning
  Cycle
• Specific Examples
• Your Ideas

4
CAUSE

• Consortium for the Advancement of
  Undergraduate Statistics Education

5
CAUSEweb Resources

Digital Library for Undergraduate Statistics
Education www.CAUSEweb.org
6
CAUSEweb Searching Browse Categories

• Lecture Examples
• Laboratories
• Out-of-class
• Teaching Tips
• Datasets
• Analysis Tools
• Curriculum
• Humor
• Building Blocks
• Multimedia

7
CAUSEweb Advanced Search
8
Advanced Searching

• Conditional probability
• Keyword
• Filter by math level
• Hypothesis testing
• Keyword
• Math level
• Lecture presentation

9
Case Study Example
Teachers Viewpoint

• Case Study Case Teaching Notes

a Ready-To-Go Classroom Lesson
10
Finding Related Items

• Related (or Companion) Items are Identified

11
Outline

• CAUSE and CAUSEweb
• Using Internet Resources throughout the Learning
  Cycle
• Specific Examples
• Your Ideas

12

• PowerPoint slides
• Reference Materials
• History
• Demonstrations
• Applets
• Videos
• Simulations

• Data Sets
• Case Studies
• Guided Demos
• Simulations
• Laboratories
• Applets
• Tutorials

• Teacher-directed assessments
• Laboratories
• Homework Problems
• Self-directed assessments
• Immediate Feedback

13
Outline

• CAUSE and CAUSEweb
• Using Internet Resources throughout the Learning
  Cycle
• Specific Examples
• Your Ideas

14
To help students understand the use of
conditional probability, a teacher can lead a
demonstration of the Monty Hall Problem using one
of the many available Internet applets.
Tutorials, such as Mrs. Glossers Math Goodies
Lesson on Conditional Probability, can be given
to students who miss a class or students that
would like additional instruction.
In some self-assessment tools like Trees and
Conditional Probability from Tutorials for Finite
Math, students receive immediate feedback when
answering questions including hints for incorrect
answers and steps to correct solutions.
15
To help students understand the use of
conditional probability, a teacher can lead a
demonstration of the Monty Hall Problem using one
of the many available Internet applets.
16
Whatever applet we choose goes here. Pause to do
a worksheet.
Applet
http//www.shodor.org/rcogan/interactivate/activi
ties/index.htmlpro
17
To help students understand the use of
conditional probability, a teacher can lead a
demonstration of the Monty Hall Problem using one
of the many available Internet applets.
Tutorials, such as Mrs. Glossers Math Goodies
Lesson on Conditional Probability, can be given
to students who miss a class or students that
would like additional instruction.
18
http//www.mathgoodies.com/lessons/vol6/conditiona
l.html
19
To help students understand the use of
conditional probability, a teacher can lead a
demonstration of the Monty Hall Problem using one
of the many available Internet applets.
Tutorials, such as Mrs. Glossers Math Goodies
Lesson on Conditional Probability, can be given
to students who miss a class or students that
would like additional instruction.
In some self-assessment tools like Trees and
Conditional Probability from Tutorials for Finite
Math, students receive immediate feedback when
answering questions including hints for incorrect
answers and steps to correct solutions.
20
http//people.hofstra.edu/faculty/Stefan_Waner/Rea
lWorld/tutorialsf3/frames6_5B.html
21
http//ocw.mit.edu/OcwWeb/Mathematics/18-05Spring-
2005/CourseHome/index.htm
22
Introduction to Probability and Statistics
23
This slide from Sampling Distributions can help a
teacher guide a discussion on when the sample
mean can be assumed to be normally distributed.
This applet from Statistical Java demonstrates
the convergence implied by the central limit
theorem by allowing students to manipulate sample
size, number of samples, and underlying
distribution.
This guided applet activity from Wise includes
assessment questions that, when answered
correctly, allow students to proceed to new
concepts.
24
This slide from Sampling Distributions can help a
teacher guide a discussion on when the sample
mean can be assumed to be normally distributed.
25
http//www.stat.psu.edu/resources/ClassNotes/hrm_
08/sld018.htm
26
This slide from Sampling Distributions can help a
teacher guide a discussion on when the sample
mean can be assumed to be normally distributed.
This applet from Statistical Java demonstrates
the convergence implied by the central limit
theorem by allowing students to manipulate sample
size, number of samples, and underlying
distribution.
27

• Applet

Applet
http//kitchen.stat.vt.edu/sundar/java/applets/CL
TApplet.html
28
This slide from Sampling Distributions can help a
teacher guide a discussion on when the sample
mean can be assumed to be normally distributed.
This applet from Statistical Java demonstrates
the convergence implied by the central limit
theorem by allowing students to manipulate sample
size, number of samples, and underlying
distribution.
This guided applet activity from Wise includes
assessment questions that, when answered
correctly, allow students to proceed to new
concepts.
29
An in-class activity from the STAR Library can
help introduce the concept of regression.
Applets like this one from SticiGui Java Tools
allow students to explore changes in the data to
see how they affect the regression line.
Using self-tests like this one from Biometry
Statistics for Ecology, students can submit their
answers and receive immediate feedback regarding
questions answered correctly and questions or
topics needing improvement.
30
An in-class activity from the STAR Library can
help introduce the concept of regression.
31
http//www.causeweb.org/repository/StarLibrary/act
ivities/buskirk_young2001/
32
An in-class activity from the STAR Library can
help introduce the concept of regression.
Applets like this one from SticiGui Java Tools
allow students to explore changes in the data to
see how they affect the regression line.
33
Regression
applet
http//stat-www.berkeley.edu/stark/Java/Html/Corr
elation.htm
34
An in-class activity from the STAR Library can
help introduce the concept of regression.
Applets like this one from SticiGui Java Tools
allow students to explore changes in the data to
see how they affect the regression line.
Using self-tests like this one from Biometry
Statistics for Ecology, students can submit their
answers and receive immediate feedback regarding
questions answered correctly and questions or
topics needing improvement.
35
http//aerg.canberra.edu.au/cgi-bin/tiegen?/share/
www/envirostats/bm/L6/ffq12.tie
36
DIGSTATS contains examples and data sets, like
the one below about Acid Rain.
The Intuitor site contains an introduction to
hypothesis testing, relating it to what happens
at a criminal trial.
The ARTIST database contains questions classified
by topic and learning outcomes.
37
The Intuitor site contains an introduction to
hypothesis testing, relating it to what happens
at a criminal trial.
38
http//www.intuitor.com/statistics/T1T2Errors.html
39
DIGSTATS contains examples and data sets, like
the one below about Acid Rain.
The Intuitor site contains an introduction to
hypothesis testing, relating it to what happens
at a criminal trial.
40
http//www.cvgs.k12.va.us/DIGSTATS/Sitemap.html
41
(No Transcript)
42
Acid Rain Activity
43
Acid Rain Data
44
DIGSTATS contains examples and data sets, like
the one below about Acid Rain.
The Intuitor site contains an introduction to
hypothesis testing, relating it to what happens
at a criminal trial.
The ARTIST database contains questions classified
by topic and learning outcomes.
45
https//ore.gen.umn.edu/artist/index.html
46
Outline

• CAUSE and CAUSEweb
• Using Internet Resources throughout the Learning
  Cycle
• Specific Examples
• Your Ideas

47

• Lisa Green
• lbgreen_at_mtsu.edu
• Scott McDaniel
• smcdanie_at_mtsu.edu
• Ginger Holmes Rowell
• rowell_at_mtsu.edu