Classroom Expectations

Document Sample

```					     Authentic Discovery Learning
Projects in Statistics
NCTM Conference
April 23, 2010

Dianna Spence
Robb Sinn

Department of Mathematics & Computer Science
North Georgia College & State University
Dahlonega, Georgia
Agenda
• Overview of Project Scope and Tasks
– Dianna

• Sample Classroom Activities
– Robb

• Findings: Student Outcomes (Phase I)
– Dianna

• Curriculum Materials Developed
– Robb

• Future Directions
– Dianna
NSF Grant Project Overview
•   NSF CCLI Phase I Grant:
“Authentic, Career-Specific Discovery Learning
Projects in Introductory Statistics”
•   Goals: Increase students’...
 knowledge & comprehension of statistics
 perceived usefulness of statistics
 self-beliefs about ability to use and understand
statistics
 Develop Instructional Materials
 Develop Instruments
 Measure Effectiveness
Student Projects
•   Linear regression        •   t-tests
 Variables                   Variables
•   student selects          •   student selects
•   often survey            Designs
based constructs         •   Independent
 Survey design                    samples
 Sampling                     •   Dependent
samples
 Regression analysis
Make It Real
Sample Activities from
Our Workshop for
Teachers of AP Statistics
Workshop Goals:
Mirroring Phases of the Project

• Participants create surveys:
 Develop quality research ideas
 Design their variables and constructs
 Practice writing good questions
• Surveys compiled, administered, and entered
into Excel while participants are at lunch
• Participants return after lunch to analyze their
research findings
• Participant teams present their findings and
their own learning outcomes to the group
Points of Learning

• Scientific Method
 Where survey-based research fits
 Students become researchers
• Technology – Excel
• Statistics
 Regression analyses and analyzing relationships
 Presenting t-Test findings within context of
discovery learning
• Brainstorming sessions on:
 Collaborative groups
 Assignment sheets, timelines, grading rubrics
Activity 1

• Consider the following survey-study variable
idea:
1. How much did you study last week _____ ?
2. How many hours did you study last night?
0 1 – 2 3 – 4 5 – 6 7 – 8 10+
•   What are some flaws?
•   Design your own “study” variable.
 Write a terse, clear question
•   Closed vs. open
•   If closed, give categories
Variable Constructs
•   Our NSF grant supported the development a variables
and constructs student help guide
•   Depression example
Answer Choice Format:         Rarely       Often       Always

1.   I do not get much pleasure or joy out of life.
2.   Sometimes I feel sad, blue, or unhappy.
3.   I often find it difficult to get out of bed in the morning.
4.   Sometimes I feel like life is not going my way.
5.   Sometimes I feel like crying.
6.   I am not sure my life will improve in the future.
7.   I often feel like my life really doesn’t matter.
Interesting Variable Ideas

• Number of text messages sent during class
• Number of songs on your I-Pod / MP3 player
• Minutes spent getting ready each morning
• Number of “years old” for the car you drive most
often
 Appears to measure SES
 Used in “Rich Kids” study ideas
Activity 2

• Develop a t-test study idea
 Brainstorm a variable you think will be different
for two groups of students (at your school)
 Be ready to explain why you expect to find
differences
• We give our students (and the workshop
participants) these “rules of brainstorming”
 Lots of talking must occur
 Throw out 5 or 6 ideas: “popcorn”
 Choose a couple of good ideas and revise
• You have about 3 minutes
Next Step

• Turning students’ research ideas into high
quality surveys
 We have found that teaching others to facilitate
this portion of discovery is
 We both are adept at operationalizing opinions,
activities, obsessions, and preferences
• High quality surveys
 Multiple drafts
 Tested with a few peers
 Critiqued at least twice by an instructor
Activity 3

• For the chosen topic, try operationalizing the
variable idea
 Talk with 2 – 3 folks nearby
 Be clear and terse
 Suggest an appropriate answer format
• You have about 3 minutes
Research and Findings
• Design of the Study
• Student Outcomes
Phase I Research
Exploratory Study
• Compared student groups, AY 2006-2007
• Conducted prior to development of materials
• Used to validate instruments
Main Pilot of Materials
• 3 institutions
 university (3 instructors)
 2-year college (1 instructor)
 high school (1 instructor)
• Quasi-Experimental Design
 2007-2008: Control groups by instructor
 2008-2009: Treatment groups by instructor
Instruments Developed:
Content Knowledge
• Instrument
 21 multiple choice items
 KR-20 analysis: score = 0.63
• Exploratory Results
 treatment group significantly higher (p < .0001)
 effect size = 0.59
• Instrument shortened to 18 items for main pilot
Instruments Developed:
Perceived Usefulness of Statistics
• Instrument
 12-item Likert style survey; 6-point scale
 Cronbach alpha = 0.93

• Exploratory Results
 treatment group significantly higher (p < .01)
 effect size = 0.295
• Instrument unchanged for main pilot
Instruments Developed:
Statistics Self-Efficacy
• Beliefs in ability to use and understand statistics
• Instrument
 15-item Likert style survey; 6-point scale
 Cronbach alpha = 0.95

• Exploratory Results
 gains realized, but not significant
(1-tailed p = .1045)
 effect size = 0.15

• Instrument unchanged for main pilot
Pilot Results: t-Tests
• Perceived Usefulness
 Pretest:      50.42
 Posttest:     51.40
 Significance: p = 0.208
• Self-Efficacy for Statistics
 Pretest:        59.64
 Posttest:       62.57
 Significance: p = 0.032**
• Content Knowledge
 Pretest:      6.78
 Posttest:     7.21
 Significance: p = 0.088*
Subscales: Statistics Self-Efficacy

• Strong Gains
 SE for Regression Techniques ( p = 0.035 )

 SE for General Statistical Tasks ( p = 0.018 )

• Little or No Improvement
 SE for t-test Techniques ( p = 0.308 )
Subscales: Content Knowledge

• Regression Techniques
 Moderate Gains ( p = 0.086 )

• T-test Usage
 Moderate Gains ( p = 0.097 )

• T-test Inference
 No Gain
Multivariate Analysis:
Content Knowledge
Multivariate Analysis:
Statistics Self-Efficacy
Qualitative Findings:
Participating Instructor Observations

•    Students need guidance with research question
•    Set Student Expectations
 Students underestimate time/effort required
 Students often unclear on exactly what to do once
they have collected the data
 Students should be prepared for results that may be
weak, non-significant, etc.
• realistic view of statistics
• avoid too much disappointment
Qualitative Findings:
Student Feedback
Student Quotes Shared by Instructors
“While our results did not meet our initial expectations,
this is not an utter disappointment. Before this project,
statistics looked simple enough for anyone to sit down
and do, but now it is evident that it requires more creativity
and critical thinking than initially expected. Overall, it was
an edifying experience.”

“The main thing that we have learned is that
statistics take time. They cannot be conjured
up by a few formulas in a few minutes. The
time and effort that is put into a small
research project such as this is significant.
On a large scale, one can quickly understand
the kind of commitment of money and time
that is required just to obtain reasonable
data.”
Materials Developed
(Web-Based)

• Instructor Guide      • Student Guide
Project overview       Project Guide
• Timelines             • Help for each
• Best practices          project phase
Student handouts       Technology Guide
Evaluation rubrics     Variables and
Constructs

Future Directions

NSF CCLI Type II Grant
•   Proposal Submitted January 2010
•   Goals Include:
 Nation wide pilot
 Vertical Integration to early secondary
 Revisions to Materials
•   Increased flexibility
•   Accommodate early high school grades
 Qualitative Component
•   More insight into instructor impact
 Advisory Panel of Statisticians & Educators

• Project Website
• Instructional Materials Home