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GAISE in the Online Course

GAISE in the Online Course. Michelle Everson, University of Minnesota Sue B. Schou, Idaho State University Patti B. Collings, Brigham Young University Jamis Perrett, Texas A & M University. Six GAISE Recommendations. 1) Emphasize statistical literacy and develop statistical thinking

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GAISE in the Online Course

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  1. GAISE in the Online Course Michelle Everson, University of Minnesota Sue B. Schou, Idaho State University Patti B. Collings, Brigham Young University Jamis Perrett, Texas A & M University

  2. Six GAISE Recommendations 1) Emphasize statistical literacy and develop statistical thinking 2) Use real data 3) Stress conceptual understanding rather than mere knowledge of procedures 4) Foster active learning in the classroom 5) Use technology for developing conceptual understanding and analyzing data 6) Use assessments to improve and evaluate student learning

  3. Using Technology to Emphasize Statistical Literacy and Enhance Software Instruction Michelle Everson Department of Educational Psychology University of Minnesota Email: gaddy001@umn.edu

  4. Who I am and what I do • I’ve been teaching online for 5 years and I helped develop several online courses in my department • Currently, I teach the following online courses: • EPSY 3264: Basic and Applied Statistics • EPSY 5261: Introductory Statistical Methods • EPSY 5262: Intermediate Statistical Methods • EPSY 5271: Becoming a Teacher of Statistics • Class sizes are typically around 30 students • Students come from a variety of disciplines (Education, Nursing, Social Sciences) • WebVista is the classroom management system used • Collaboration, group discussion, and activity are big parts of all courses

  5. Example Course Site

  6. Example Weekly Module

  7. Snapshot of Discussion Rooms

  8. Using Technology in the Online Course • Are there ways we might use technology to emphasize statistical literacy? • If we want students to become savvy and critical consumers of statistics used in the media and in published research studies, what types of assignments and activities might we want to use in our courses? • What are some things that might really motivate and engage students, or entice them to be on the lookout for uses and misuses of statistics in the real world? • How can technology be used to enhance software instruction? • Students who must learn to use statistical software in an online course may need extra support • Detailed handouts do not always work • Available software tutorials sometimes fall short • Students may benefit from opportunities to witness their own instructor model the thinking and reasoning process involved in exploring and analyzing data

  9. Project #1: The Great Statistics Twitter Experiment • Students are asked to set up a Twitter account and to follow the instructor (www.twitter.com/MGEverson) • Students (and the instructor) “tweet” about a variety of things • News articles that include statistical information • Cartoons related to statistics • Poll results • Misleading graphs or news report • Online sites that can help individuals learn statistics • Good data sets • Students must include the link to what they have found and a short description/critique (followed by #epsy5261) • Currently, this is an EXTRA CREDIT assignment

  10. Project #2: SPSS Tutorials • Project supported by a Technology Enhanced Learning Grant (through the University of Minnesota Digital Media Center) • Collaborator: Yelena Yan • Goals: • To use real data sets • To go beyond simply walking through steps and procedures; to help students form connections among different topics and ideas • To model (for students) how to think about and reason through different problems • To foster more of a sense of community in the online course by providing students with opportunities to see and hear their instructor

  11. Rationale for Statistics Tutorials How to Use Statistics Tutorials Develop Research Questions Collect Data Data Exploration Making Inferences about Population Confidence Intervals for a Single Mean Entering data One Sample t - test Describing a Single Quantitative Variable Two Sample t - test Paired t - test Comparing groups on a Single Quantitative Variable Correlation Chi-square Linear regression

  12. Preliminary Feedback about SPSS Tutorials • Students are watching the tutorials, often more than once • The tutorial with the most “hits” is about confidence intervals • Students like: • The overall design and pacing of tutorials • Seeing and hearing the instructor • Accompanying handouts/data sets • Being able to pause and go back to sections over and over • Students don’t like: • Pacing (some say tutorials are slow and too long) • Not having opportunities to stop and practice what they are learning • Feeling as if tutorials will not be useful beyond the course

  13. Some Lessons Learned • It’s important to think about how you might “sell” your students on the use of various technological tools in your course • Relate the use of such tools to the learning goals of the course • Try to ensure students can access these tools and that they feel comfortable using them • Think carefully about the software you’ll need to use to create different tools (such as tutorials) and about whether the time and effort will be worth it in the long run • If the statistical software you are using in the course is constantly changing, is it worth it to create tutorials, or would well-labeled and illustrated handouts suffice?

  14. Incorporating GAISE in Online Instruction: A Business Perspective Sue B. Schou Idaho State University Email: schosue@isu.edu

  15. Background • Two semester undergraduate business statistics courses • Taught within the College of Business • Use Minitab 15 statistical software • Emphasis on writing and interpretation • Use Moodle as the learning management system (Adobe Presentations, Minitab video instruction) • Class size ranges from 30 to 40 students

  16. Using Real Data • Collect survey data from students in the course using web survey tool • Have students formulate questions • Place the questions as written into the web questionnaire • Give students web address to respond • Provide Excel spreadsheet for analysis • Use the world SARS data (very skewed)—could easily change to H1N1 flu data • Source: Mathematics Teacher, September 2004

  17. Using Real Data • Projects • Sampling from a real data source online • www.dunes.com • www.autotrader.com • www.apartments.com • www.realtor.com • First course uses data for hypothesis testing • Second course uses data for building a multiple regression model

  18. Projects in Online Setting • Wiki • Group assignment • Can track each student’s contribution • Saves all drafts • Google Docs • Students must set up using their gmail accounts • Allows editing • Disadvantage in that instructor cannot see work in progress

  19. Discussion Forums in MoodleActive Learning • Grading rubric for discussions available to students • Assign groups for discussions initially • First discussion forum: introduce yourself to your group • Use this environment to introduce myself to the class • Type I/Type II error • http://www.intuitor.com/statistics/T1T2Errors.html website includes an interactive applet

  20. Discussion Forums in MoodleActive Learning • Require How to Lie with Statistics in the first course • Require Super Crunchers in the second course • Reading assignments then discussion • Provide questions to direct the thought process • Example: wedding article

  21. Problems with Forums • Lack of student participation • Solution is to make it percentage of overall grade • Simply reiterating other students’ responses • Use Q&A forum in Moodle • Student low quality response • Requires some encouragement from the instructor to think more deeply • Poor writing skills • Include in grade and ensure is discussed in grading rubric

  22. Assessment • Proctored exams (testing center, local library, etc.) • Mostly free response • Some multiple choice (often from ARTIST website) • Unproctored portion to check Minitab skills • Sometimes use this portion for interpretation questions during proctored exams; submission at exam center • Sometimes require a memo that discusses the results and gives recommendation for business; submission online

  23. Assessment • End of semester proctored computer lab exam • First course requirement to ensure each student is developing adequate technology skills • Gives student raw data to input then analyze • One hypothesis test from (one sample t-test, 2 sample t-test, paired t-test, ANOVA, one proportion, two proportion, Test for equal variance, and Chi-squared test of independence) • Two additional problems from the remainder of topics (probability, descriptive statistics, graphs, etc.)

  24. Promoting Conceptual Learning in Online Classes Patti B. Collings Brigham Young University Email: collingsp@stat.byu.edu

  25. Who am I and What I Do • Have taught online for 6 years • Developed three versions of intro stat • Independent Study: ≈1000 students per year • Hybrid (half in class and half out of class: ≈400 students per semester • Hybrid (activity once a week): ≈500 students per semester • All online (question/answer period once a week): ≈250 students per semester

  26. What I do (cont.) • Used Blackboard in the past • Now use Moodle • Department chair mandated that online course be exactly like in class course

  27. Course Materials • Textbook: Basic Practice of Statistics by David S. Moore, 4th edition • StatsPortal • StatTutor lessons (tutorials) • Pre- and Post-Quizzes for each chapter • Applets • Open labs

  28. Assessment • 15 question practice quiz and 15 question credit quiz due every Monday, Wednesday and Friday • Open book, open notes, open neighbor • Immediate feedback • Three proctored midterms • Proctored final

  29. Learning Outcomes • Use ethical judgment to assess statistical results in the honest search for truth. • Communicate how statistics facilitates the discovery, understanding, quantification and modeling of truth about the world. • Understand the importance of how data should be collected, and how data collection dictates the appropriate statistical method and acceptable inference.

  30. Learning Outcomes • Understand and communicate using technical language about probability and variation. • Interpret and communicate the outcomes of estimation and hypothesis tests in the context of a problem.

  31. Screen Shot of Moodle

  32. Typical Lesson

  33. Sample Quiz Question • Identify when association is not causation.

  34. Sample Quiz Question • Give appropriate interpretations of statistical values • Real stories; real data

  35. Sample Quiz Question • Recognize type of study: experiment versus observational study • Recognize that causation can only be concluded from experiment with randomization

  36. Sample Quiz Question • Recognize need for properly collected data for inference

  37. Activity Screen Shot

  38. Activity Screen Shot

  39. Applet • Understanding sum of squared deviations

  40. Applet • Understanding relationship between a and power

  41. What I’ve learned • Students need frequent deadlines • Students only do what counts for credit • Some students view hybrid classes as an opportunity for less class time • Students learn best if they work together • Changing student expectations is a challenge

  42. Graduate Online Instruction Jamis Perrett Texas A & M University Email: jamis@stat.tamu.edu

  43. Example 1: Online course in statistical methods for Ph.D. nursing students • 30 years experience as a nurse. • 30+ years since last stats/math class. • 30+ years since last college course. • More mature, not in the education mode, nervous about statistics, not very familiar with computers.

  44. Institutional Support • Lots of new online programs requesting introductory stats courses. • Lots of webinars available for sharing ideas. • No one else was interested in teaching online. • Perception (true or false) that online education is inferior.

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