Teaching Statistics Online CAUSEweb Webinar December 12, 2006 - PowerPoint PPT Presentation

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Teaching Statistics Online CAUSEweb Webinar December 12, 2006

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Title: Teaching Statistics Online CAUSEweb Webinar December 12, 2006


1
Teaching Statistics OnlineCAUSEweb
WebinarDecember 12, 2006
  • Michelle Everson
  • University of Minnesota

2
Overview
  • About the course
  • Structure of the course website
  • Description of student assignments and
    assessments
  • What do students think about the course?
  • Things for the online instructor to consider
  • Some lessons learned

3
The GAISE Recommendations
  • According to the GAISE (2005) recommendations,
    introductory statistics courses at the college
    level should
  • Emphasize statistical literacy and develop
    statistical thinking
  • Use real data
  • Stress conceptual understanding
  • Foster active learning
  • Use technology
  • Integrate assessments that are aligned with
    course goals

4
Research on Teaching Statistics Online
  • How can collaborative activities and technology
    can be integrated into an online statistics
    course?
  • Student-to-student interaction and collaboration
  • Weekly chats (e.g., Dereshiwsky, 1998)
  • Project work (e.g., Davis Chao, 2004 Prater
    MacNeil, 2002 Suanpang, Petocz, Kalceff, 2004)
  • Regular group discussions (e.g., Grandzol, 2004
    Jones, 2003)
  • Technology
  • Courses have used Excel, SPSS, Minitab,
    Cyberstats, and ActivStats (e.g., Davis Chao,
    2004 Dutton Dutton, 2005 Grandzol, 2004
    Harrington, 1999 Lawrence Singhania, 2004
    Mills Xu, 2005 Prater MacNeil, 2002 Utts et
    al., 2003 Zhang, 2004)

5
EPSY 3264 Basic and Applied Statistics
  • This is a 3-credit, semester-long, upper-level
    undergraduate course
  • Students who take the course come from all over
    campus most take the course to fulfill a general
    education requirement
  • The course covers the following topics data
    collection and description, normal distributions,
    sampling distributions, methods of statistical
    estimation and inference, correlation, and simple
    linear regression
  • The course uses the textbook Mind on Statistics
    (3rd ed., by Utts Heckard), bundled with Minitab

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Course Assignments
  • Grades are based on
  • Small-group Discussion Assignments (7)
  • Homework Assignments (8)
  • Quizzes (4)
  • Project (1)
  • Students also have the opportunity to complete
    non-graded practice activities and extra credit
    assignments

17
More on Grades
18
Collaborative Group Assignments
  • Each student is assigned to a discussion group at
    the beginning of the semester
  • Seven small-group discussion assignments are
    completed
  • Assignments involve discussing concepts and
    answering questions as a group
  • Students must post their own thoughts (by
    midnight on Wednesday) AND respond in a
    meaningful way to what at least one group member
    has posted
  • One student volunteers to lead each discussion
    and submit a summary to the instructor by
    midnight on Monday
  • Grading 3 points for initial posting, 3 points
    for responding, 1 point if group summary is
    submitted on time

19
Group Assignment 1 Designing an experiment
  • Students read a 1998 New York Times article about
    a Therapeutic Touch experiment conducted by
    11-year-old Emily Rosa
  • Students spend some time critiquing the study
    (i.e., discussing sampling issues, possible
    confounding variables, etc.)
  • Students then design a new experiment in order to
    assess the efficacy of the Therapeutic Touch
    method

20
Group Assignment 4 Sampling Distributions
  • Students work independently through a lab in
    which they use the Sampling SIM program (delMas,
    2001)
  • Students then attempt to answer a series of
    questions about the lab as a group
  • They talk about what they feel a sampling
    distribution is and why it is important.
  • They talk about why they think the sampling
    distribution has the characteristics that it
    does.
  • They work as a group to answer a question that
    involves applying knowledge of sampling
    distributions.

21
Group Assignment 6 Hypotheses tests
  • Each student posts a research question that
    he/she is interested in and that can be addressed
    using either a one-sample, two-sample, or paired
    t-test procedure
  • Students talk about
  • Why they are interested in this question
  • What their null and alternative hypotheses will
    be
  • What procedure is most appropriate to use and why
  • After students have posted their own research
    question, they each must choose one other
    research question to critique

22
More on Homework Assignments
  • Students complete 8 homework assignments, each
    worth 10 points
  • Assignments involve answering instructor-generated
    questions
  • Most assignments involve using Minitab or other
    technology (e.g., Java applets)
  • For some assignments, student data is analyzed
    (i.e., data from a class survey that students
    fill out during Week 1 of the course)
  • Assignments are submitted as Word attachments
    through WebCT e-mail
  • The TA grades each assignment and sends
    individual feedback to the student within one week

23
More on the Project
  • Each student completes a project that involves
    gathering data from two groups and
    describing/analyzing the data using Minitab
  • The project is submitted in parts
  • Part 1 Project idea
  • Part 2 Project data
  • Part 3 Introduction and description of data
  • Part 4 Inference (confidence intervals and
    hypothesis testing) and summary/conclusion

24
Quizzes
  • Every four weeks (25 points each)
  • Quizzes are administered online through the WebCT
    quiz tool
  • Available from noon on Fridays until noon on
    Mondays
  • Students have up to three hours to complete the
    quiz (in one sitting)
  • Quizzes consist almost entirely of short-answer
    questions
  • The BIG question How do you administer quizzes
    online and ensure that students are not cheating?
    Can you do this????

25
Trying to Prevent Cheating
  • If all of your quizzes will be online (like they
    are in this course), you can do different things
    to prevent cheating
  • Change assessments from semester to semester
  • Insist that students complete the quiz in one
    sitting, within a certain period of time
  • Use open-ended questions where students must
    explain their answers
  • You can also randomize the order in which
    questions are presented to each student
  • Ask that students adhere to an honor code of
    some kind

26
Student Feedback (Spring and Fall, 2006)
  • Students are asked to complete a Midterm Feedback
    Survey during Week 9 and indicate how they feel
    different assignments are contributing to their
    understanding of statistics

27
Teaching Online Issues to Consider
  • What kind of support will you get in developing
    the course? How much autonomy do you want to
    have?
  • How large will your class be? Will you get some
    TA support?
  • How will you ensure that students know what is
    expected of them in the online course?
  • What do you want YOUR role in the course to be?
  • Are you willing to be online often?
  • Are you comfortable providing feedback or
    explaining concepts to students via e-mail?
  • If you use discussion groups, will you
    participate in group discussions?

28
Some Lessons Learned
  • Teaching online can be a big time commitment
  • Online courses are NOT for everyone!
  • You get to know your students in a much different
    way when teaching online
  • Students appreciate timely communication with the
    instructor/TA, organization, and consistent
    deadlines
  • Online discussion assignments can be a great way
    to learn more about student difficulties/misconcep
    tions
  • They motivate ALL students to participate
  • Discussions can be monitored for ALL GROUPS from
    start to finish
  • Set deadlines discourage students from waiting
    until the last minute to participate

29
Thank you!!!!
  • Contact information
  • Dr. Michelle Everson
  • Department of Educational Psychology
  • University of Minnesota
  • gaddy001_at_umn.edu
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