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Training Teachers to Use Authentic Discovery Learning Projects in Statistics

Training Teachers to Use Authentic Discovery Learning Projects in Statistics. AMTE January 30, 2010 Robb Sinn Dianna Spence Department of Mathematics & Computer Science North Georgia College & State University Dahlonega, Georgia. Agenda. Overview of Project Scope and Tasks – Dianna

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Training Teachers to Use Authentic Discovery Learning Projects in Statistics

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  1. Training Teachers to Use Authentic Discovery Learning Projects in Statistics AMTE January 30, 2010 Robb Sinn Dianna Spence Department of Mathematics & Computer Science North Georgia College & State University Dahlonega, Georgia

  2. Agenda • Overview of Project Scope and Tasks – Dianna • Teaching Model and Sample Workshop Activities – Robb • Research Design and Initial Findings – Dianna • Directions and Discussion – All of Us

  3. 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 • Tasks: • Develop Instructional Materials for Projects • Develop Instruments • Train Instructors to Use Materials • Measure Effectiveness

  4. Student Projects • t-tests • Variables • student selects • Designs • Independent samples • Dependent samples • Linear regression • Variables • student selects • often survey based constructs • Survey design • Sampling • Regression analysis

  5. Materials Developed(Web-Based) Instructor Guide Project overview Timelines Best practices Student handouts Evaluation rubrics • Student Guide • Project Guide • Help for each project phase • Technology Guide • Variables and Constructs

  6. Teacher Training – Pilot Instructors • Took place before pilot of materials • Half a day training • Follow-up meetings • Work sessions • Individual Mentoring

  7. Teacher Training WorkshopFor Secondary Teachers “Make It Real” • 1 day workshop • Follow-up online assignments • PLU credit available

  8. Make It Real Training for Inservice Teachers of AP Statistics

  9. Workshop Goals • Participants created surveys: • Developed quality research ideas • Designed their variables and constructs • Practiced writing good questions • A team of students worked during the lunch break with the combined surveys: • Administered surveys in 6 NGCSU classrooms • Entered and compiled all data • Participants returned after lunch to analyze their research findings

  10. Capstone Experience • Team presentations • Occurred in late afternoon session • Presented findings and their own learning outcomes • A final session reviewed their day’s experience and asked them to critique the training. They reported: • Creating their own surveys was both fun and empowering • More than 75% felt sure they could adapt the discovery learning projects to their own classroom needs

  11. 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

  12. Learning to Discover? • We did “make it real” • Hands on experiences • Simulated student projects • Discovery is often messy • We learn by watching discovery happen • We learn by watching experienced users of discovery learning facilitate • We will NOT learn from a lecture • So why are you lecturing to me?

  13. Question 1 How much K-12 teaching experience do you have? Less than 2 years Between 2 and 5 years Between 5 and 10 years Between 10 and 20 years More than 20 years

  14. Question 2 How much experience do you have teaching classes for inservice and preservice teachers? Just starting Taught between 3 and 5 courses / sections Taught between 5 and 10 courses / sections Taught more than 10 courses / sections

  15. Activity 1 • Consider the following survey-study variable idea: • How much did you study last week _____ ? • 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 • Suggest answer format • Closed vs. open • If closed, give categories

  16. Variable Constructs Our NSF grant supported the development a variables and constructs student help guide Depression example Answer Choice Format: Rarely Often Always I do not get much pleasure or joy out of life. Sometimes I feel sad, blue, or unhappy. I often find it difficult to get out of bed in the morning. Sometimes I feel like life is not going my way. Sometimes I feel like crying. I am not sure my life will improve in the future. I often feel like my life really doesn’t matter.

  17. Interesting Variable Ideas • Number of text messages sent during class • Age when you had your first real kiss • 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

  18. 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 good ideas and revise • You have about 2 minutes

  19. Next Step • Turning students’ research ideas into a high quality surveys • We have found that teaching others to facilitate this portion of discovery is • The most difficult task • The most important task • 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

  20. 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 2 minutes

  21. Research Instrumentation Data Collection Initial Results

  22. 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 pilot

  23. 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 pilot

  24. 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 pilot

  25. Phase I Data Collection: Pilot of Developed Materials • 3 institutions • university (3 instructors) • 2-year college (1 instructor) • high school (1 instructor) • Quasi-Experimental Design • Spring 2008: Begin instructor “control” groups • Fall 08 - Fall 09: “Experimental” groups

  26. 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*

  27. 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 )

  28. Subscales: Content Knowledge • Regression Techniques • Moderate Gains ( p = 0.086 ) • T-test Usage • Moderate Gains ( p = 0.097 ) • T-test Inference • No Gain

  29. Multivariate Analysis: Content Knowledge

  30. Multivariate Analysis: Statistics Self-Efficacy

  31. Multivariate Analysis: Perceived Usefulness of Statistics

  32. 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

  33. Up For Discussion Because results vary by instructor, we’d like to focus on improving… • Instructor Preparation • Instructor Assessment • Curriculum Materials

  34. Up For Discussion Instructor Preparation • What could be included in teacher workshops to foster instructor success in implementing these projects?

  35. Up For Discussion Instructor Assessment • In what ways can instructors be assessed… • to gauge their propensity for success with these projects? • to identify areas in which their skills could be refined?

  36. Up For Discussion Curriculum Materials • What should be included in the instructional materials? • Aspects to consider • Content • Organization • Style • Features for what stakeholders? • Instructors • Students

  37. For more information • Project Website • http://radar. northgeorgia.edu/~djspence/nsf/ • Instructional Materials Home • http://radar.northgeorgia.edu/~rsinn/nsf/ • Contact Us • Robb: robb.sinn@northgeorgia.edu • Dianna: dianna.spence@northgeorgia.edu • Brad: brad.bailey@northgeorgia.edu

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