authentic discovery projects in statistics gctm conference october 16, 2009 dianna spence ngcsu...
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Authentic Discovery Projectsin Statistics
GCTM ConferenceOctober 16, 2009
Dianna Spence
NGCSU Math/CS Dept, Dahlonega, GA
NSF Grant Project Overview• Grant Title:
“Authentic, Career-Specific Discovery Learning Projects in Introductory Statistics”
• Project Goals: Increase students’... knowledge & comprehension of statistics perceived usefulness of statistics self-beliefs about ability to use and understand
statistics
• Tasks: Develop Instruments Develop Research Constructs and Projects Develop Materials and Train Instructors Measure Effectiveness
Instructional Model: Discovery Learning in Statistics• Authentic Research Projects
Experiencing the Scientific Method
Discovering Statistical Methods in Context• Design of Research Question
• Definition of Variables
• Demographic Data
• Representative Sampling Issues
• Data Collection
• Appropriate Analyses of Data
• Interpretation of Analyses
Project Format
• Linear regression Variables
• student selects• often survey
based constructs Survey design Sampling Regression analysis
• t-tests Variables
• may use data previously collected
Designs• Independent
samples• Dependent
samples Hypotheses
Interdisciplinary Team
• Disciplines Represented Biology/Ecology Criminal Justice Psychology Sociology
• Tasks of Team Members Identify authentic research constructs Define instrument/measurement of construct Suggest simple statistical research projects
Nursing Physical Therapy Education Business
Online Resource:Instructional Materials Homepage
• Instructor GuideProject overview
• Timelines• Implementation tips• Best practices
Handouts for different project phases
Evaluation rubricsLinks to student resources
http://radar.ngcsu.edu/~rsinn/nsf/
Online Resource:Instructional Materials Homepage
• Student GuideOverall Project Guide
• Help for each project phaseTechnology GuideVariables and Constructs
http://radar.ngcsu.edu/~rsinn/nsf/
Common Questions
• How long will the projects take?
• How do I fit this in with the content I am supposed to teach?
• How should I go about organizing and facilitating these projects?
• What are the student “deliverables”?
• How do I assess the students’ work?
• How much should this count in determining student grades?
Project Phases• Form Teams
• Generate Research Ideas
• Develop Constructs and Variables
• Develop Surveys or Other Instruments
• Project Proposals
• Data Collection
• Data Analysis
• Project Report
• Team Presentations
Finding Time for the Project
• Make the projects the vehicle through which students learn course content
• Selecting projects to use as class examples current students’ projects (work in progress) example project(s) you have made up former students’ projects (when you have them)
• Leverage sample projects Gives students an idea what
should be included in their project Helps students connect course
content and put it in context
Aligning Course Content with Project Phases
Phase Class Topic
Define variables Independent/dependent variablesDevelop surveys Types of biasData collection Sampling methodsData analysis Appropriate statistical analyses
Example: Exploring slope of regression line“One team examined the relationship between
number of vegetable servings consumed in a week and number of hours spent exercising in a week. Their regression equation was ___?___. What is the slope and what does it mean?”
Considerations and Options: Forming Teams• Team Size
• Assigned Members vs. “Pick Your Own”
• Grouping by Common Interests
• Giving Team Members Specific Roles
Considerations and Options: Project Proposals
• Formal vs. Informal
• IRB or Similar Entity
• Other Permissions Required?
• Require instructor approval before data collection begins!
Considerations and Options: Data Collection• Dialog About Sampling
StrategiesRandomStratified Convenience
• Dialog About Representative Samples
• Assist Students with Organization and Data Entry
Considerations and Options: Data Analysis• Linear Regression Projects
ScatterplotCorrelation Coefficient rRegression LineRegression EquationSlopeR2 and Explanatory Value of Model
Height and Shoe Size
y = 0.4198x - 18.921
R2 = 0.7684
4
6
8
10
12
14
55 60 65 70 75 80
Height
Sh
oe
siz
e
Considerations and Options: Data Analysis
• t-Test Comparison ProjectsAppropriate Design
• Two Independent Samples• Dependent Samples/Matched Pairs
Appropriate Hypotheses• One-tailed (and which tail)• Two-tailed
Significance LevelInterpretationImplications of Type I & II Errors
Considerations and Options: Project Report
• Content RequirementsOutlinesTemplatesSample ReportsScoring Rubrics
(Students can use as checklist)• Other Requirements
Writing StandardsSubmission of Technology FilesReflections
Considerations and Options: Team Presentations
• Presentation GuidelinesContent and ScopeAestheticsPace and OrganizationTime Limit & Enforcement
• Audience AccountabilityEvaluations1-2 Sentence Recap of Points
Assessment
• RubricsAdvantages
• Consistency• Manageability• Communicate expectations
Encompass All Project Components• Grade milestones along the way
Explicit vs. HolisticResources for Rubrics
• Use one of ours• Customize your own
Assessment
• Team Member Grades Accountability of Individual Members
• Shared Team Grade• Individual Contribution• Other “Tricks”
• Weight of Projects
Exploratory StudyFall 2007
• Instrument Validation and Concept “Trial Run”
• Based on 10 sections of Introductory Stats
• 4 experimental sections Used authentic discovery projects n=113 participants out of 128 students
• 88% participation rate
• 6 control sections Did not use authentic discovery projects n = 164 participants out of 192 students
• 85% participation rate
Exploratory Results: Content Knowledge• Instrument
21 multiple choice items KR-20 analysis: score = 0.63
• Results control mean: 8.87; experimental mean = 10.82 experimental mean 9 percentage points higher experimental group significantly higher (p < .0001) effect size = 0.59
• Instrument shortened to 18 items for full study
Exploratory Results: Perceived Usefulness of Statistics
• Instrument 12-item Likert style survey; 6-point scale 5 items reverse scored score is average (1 – 6) of all items Cronbach alpha = 0.93
• Results control mean: 4.24; experimental mean = 4.51 experimental group significantly higher (p < .01) effect size = 0.295
• Instrument unchanged for full study
Exploratory Results: Statistics Self-Beliefs• Beliefs in ability to use and understand statistics
• Instrument
15-item Likert style survey; 6-point scale
score is average (1 – 6) of all items
Cronbach alpha = 0.95
• Results
control mean: 4.70; experimental mean = 4.82
difference not significant (1-tailed p = .1045)
effect size = 0.15
• Instrument unchanged for full study
Full Study: Pilot of Developed Materials
• 3 institutions 1 university (6 undergraduate sections)
1 2-year college (2 sections)
1 high school (3 sections)
• 5 instructors
• Quasi-Experimental Design Spring 2008: Begin instructor “control” groups
Fall 08 - Fall 09: “Experimental” groups
Pilot Results• Varied by Instructor
• Overall results given here
• Instrument Perceived Usefulness
• Pretest: 50.42• Posttest: 51.40• Significance: p = 0.208
Self-Beliefs for Statistics• Pretest: 59.64• Posttest: 62.57• Significance: p = 0.032**
Content Knowledge• Pretest: 6.78• Posttest: 7.21• Significance: p = 0.088*
Attitudes and Beliefs• Statistics Self-Beliefs
Self-beliefs improved significantly overall• Significant Gains
– for regression techniques ( p = 0.035 )– for general statistical tasks ( p = 0.018 )
• Little or No Improvement– for t-test techniques ( p = 0.308 )
• Perceived Utility for Statistics Student perceptions of the usefulness of
statistics improved slightly but not significantly No sub-scales on this instrument
• Overall Perceived Utility ( p = 0.208 )
Performance Gains
• Concept Knowledge: 3 Components Regression Techniques
• Moderately Significant ( p = 0.086 ) T-test Usage
• Moderately Significant ( p = 0.097 ) T-test Inference
• No gain
For more information
• Project Website http://radar.ngcsu.edu/~djspence/nsf/
• Instructional Materials Home http://radar.ngcsu.edu/~rsinn/nsf/