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Do OnLine Students Analyze, Synthesize And Evaluate Better Than FaceToFace Students Preliminary Evid

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Title: Do OnLine Students Analyze, Synthesize And Evaluate Better Than FaceToFace Students Preliminary Evid


1
Do On-Line Students Analyze, Synthesize And
Evaluate Better Than Face-To-Face Students?
Preliminary Evidence
  • Drs. Steven C. Myers Michael A. Nelson
  • myers_at_uakron.edu
  • Department of Economics - The University of Akron
  • Online at http//gozips.uakron.edu/myers/online

2
Acknowledgments
  • Grant from
  • Carnegie Teaching Academy
  • Scholarship of Teaching, Assessment and
    Learning Funds
  • Institute for Teaching and Learning
  • The University of Akron
  • Data collected under signed informed consent from
    our students subject to the Institutional
    Research Board for the Protection of Human
    Subjects at The University of Akron.
  • Very few failed to give informed consent
  • Data collection instruments validated by a number
    of independent reviewers and created by MA grad,
    Michael Lovette.

3
Research Questions
  • (1) Does the mode of delivery (face-to-face or
    web-based) have an influence on learning
    outcomes? 
  • (2) Are students in an online environment as
    likely to do as well as in face-to-face classes?
    Will they be able to equal the complex problem
    solving of the face-to-face students?

4
Course under study
  • Introduction to Economic Analysis
  • One-semester principles of economics
  • 3 cr. General education course
  • Required for engineering majors
  • Both face-to-face and on line
  • The online course is similar to a graduate course
    offered since Fall 2001

5
Comparison
  • Face-to-face
  • Offered by Michael Nelson
  • Regular class times
  • Lecture and active learning collaborative
    techniques
  • Better than the norm of 83 chalk and talk
    (Becker and Watts)
  • Some minor web-enhancements such as online
    gradebook
  • Online
  • Offered by Myers (F02) / Nelson (S03)
  • No face-to-face meetings
  • Mastery competency based learning
  • High professor-student interaction
  • No student to student interaction
  • Full use of the WebCT environment

6
Student Characteristics
  • Face-to-face Students
  • More likely
  • To be male
  • To be a freshman
  • To be undecided in their major
  • To spend less time gathering business and
    economic news.
  • Online Students
  • More likely to be
  • To be older
  • To be non-white
  • To be female
  • To have taken more credits
  • To be decided in their major
  • More favorably disposed to economics

7
The online course design has influenced grades,
but learning?
  • Grades Distribution

MC Learning Assessment Breakdown / Online
8
Research design
Students success f( students initial
endowments, awareness of the
economy, attitudes about economics, course
modality, student characteristics)
Pre-test scores total on recall and
recognition on simple application problems on
complex problems GPA Previous attempt of course
9
Research design
Survey of economic facts 20 questionson trends
and facts in the economy. 2 questions How does
the student collect business and economic
news. How many hours per week does the student
spend collecting news
Students success f( students initial
endowments, awareness of the
economy, attitudes about economics, course
modality, student characteristics)
10
Research design
  • Three Survey Questions
  • Level of student report of being interested in
    economics.
  • Level of student report of liking this economics
    course.
  • Level of student report about likelihood of
    taking more economics courses.

Students success f( students initial
endowments, awareness of the
economy, attitudes about economics, course
modality, student characteristics)
5strongly agree 4agree 3indifferent/no
opinion 2disagree 1strongly disagree
11
Research design
Students success f( students initial
endowments, awareness of the
economy, attitudes about economics, course
modality, student characteristics)
Online or face-to-face Major Level, e.g.,
freshman Credits completed Age Gender Ethnicity
12
Dependent Variable Student Success Outcome
Measures
  • examscore on first 6 chapters
  • In class exam for face-to-face class
  • Average of first three module quizzes for online
    class
  • Final examination
  • (FE, FE_recog, FE_apply, FE_complex)
  • First 3 or 4 levels of Blooms Taxonomy
  • Writing assignment
  • writing2
  • 4th to 6th level of Bloom
  • Regular Grades in class

13
Blooms Taxonomy (from Carla Lane)
  • Knowledge arrange, define, duplicate, label,
    list, memorize, name, order, recognize, relate,
    recall, repeat, reproduce state.
  • Comprehension classify, describe, discuss,
    explain, express, identify, indicate, locate,
    recognize, report, restate, review, select,
    translate,
  • Application apply, choose, demonstrate,
    dramatize, employ, illustrate, interpret,
    operate, practice, schedule, sketch, solve, use,
    write.
  • Analysis analyze, appraise, calculate,
    categorize, compare, contrast, criticize,
    differentiate, discriminate, distinguish,
    examine, experiment, question, test.
  • Synthesis arrange, assemble, collect, compose,
    construct, create, design, develop, formulate,
    manage, organize, plan, prepare, propose, set up,
    write.
  • Evaluation appraise, argue, assess, attach,
    choose compare, defend estimate, judge, predict,
    rate, core, select, support, value, evaluate.

14
Results
  • Students Initial Endowments
  • All prior expectations are met
  • Higher pretest and higher GPA are positive on
    examscore, writing2 and less so on FE.
  • Higher complex pretest scores and higher GPA are
    positive for writing2 and FE_Complex

15
Results
  • Economic Awareness Attitudes
  • Survey is weakly positive for examscore and
    writing2, but has no effect on FE.
  • No combination of News gathering is ever
    significant.
  • Attitudes are strongly significant for
    examscore and writing2, but no effect on FE
  • When attitudes matter
  • take_more econ gt interest in econ gt will like
    econ

16
Results
  • Student characteristics
  • Those with an undeclared or undecided major do
    much worse than engineering majors for examscore
    and FE.
  • Older students do worse on examscore, no effect
    on writing2 and strongly positive on FE
  • Females do better in writing2 (strongly
    significance), but do worse on FE (almost
    significant)

17
Results
  • Online Students
  • Do much better on examscore
  • Show no significance difference in scoring on
    analytical and complex reasoning tasks.
  • Insignificant coefficients in writing2
  • Insignificant and small coefficients in
  • FE
  • FE_recog
  • FE_Apply
  • FE_complex
  • There is some evidence of a possible interaction
    with females
  • Weak suggestion in the data that
  • Men in online classes do better and
  • Women in online classes do worse all things equal

18
Design of the online course
  • Built in modules
  • Modules completed in order
  • Competency based testing
  • Use student feedback
  • For student learning enhancement
  • For modifying improving the course

19
CourseDesign
  • DL requires planning for contingencies
  • 14 Content Modules
  • Active Learning vs. Passive Learning

20
Pre-class and Module 1 Preparing Students to
Learn
  • Email me! http//gozips.uakron.edu/myers/online/
  • Is Distance Learning for Me?
  • VARK testing learning styles
  • Orientation Module How to logon to WebCT
  • Orientation Module How to Use WebCT
  • Syllabus
  • Graduate course
  • Undergraduate course

21
Pre-class and Module 1Additional Orientation
  • How to Communicate with Dr. Myers
  • How to access your online text
  • http//www.economicsplace.com/econ5e/
  • Rules of the game
  • Building a relationship
  • Breakdown the anonymity
  • Survey Tell me about yourself

22
Content Modules 2-15
  • Module Introduction Objectives
  • Chapter Introductions
  • Content
  • Supportive Materials
  • Assessment of Learning - Quizzes on objectives
    with multiple trials
  • Evaluation

23
2 Research Writing Assignments some objectives
  • Practice and experience in reflecting on a topic
    in the current economy.
  • Practice in analysis of economic trends.
  • Gaining of confidence about talking about the
    economy.
  • Ability to know and use the resources of economic
    commentary, prior analysis and data.

24
Introductions Content
  • Mostly Passive
  • Learner Centered
  • Students progress without intervention
  • Micro Modules 2-8
  • Macro Modules 9-15

25
GradedAssessment
  • Competency based
  • Everyone strives to get a perfect 10 (Mastery)
  • Three attempts, 15 min. time limit
  • Questions a mix of (1) Recognition, (2)
    Conceptual, (3) Analytic70 CA
  • Random intervention by Professor

26
Role of Module Evaluation
  • Planned intervention
  • Forced contact
  • Focus on the learning
  • Professorial encouragement
  • Decreases dropout rates
  • Process repeats

27
Module EvaluationA Classroom Assessment
Technique from Angelo and Cross (1993) tested
by Chizmar and Ostrosky (1998)
  • What comments do you have on this module and your
    experience in completing it?
  • What main point have you learned that you did not
    fully understand before?
  • What questions Include any points that still
    remain muddy or unclear. Do consider posing the
    muddy points to your fellow students in the
    discussions.
  • What recommendations do you have for us as we
    continue to change and enhance the course?

28
Student Comments / online
  • The fact that this course was completely
    internet based, had no bearing on the level of
    knowledge I gained from the course. I think I
    learned as much, or even more, than I would have
    in a traditional classroom. I contribute this
    most to the way the instructor organized the
    course.

29
Student Comments / online
  • I believe that the benefits of web-based courses
    far outweigh any disadvantages such as lack of
    face-to-face interaction--at least in this
    particular course. Dr. Myers' course was, of the
    four I took this semester over the web,
    truthfully the best organized, most well-adapted
    to the web (by his efforts) of them all.

30
Do On-Line Students Analyze, Synthesize And
Evaluate Better Than Face-To-Face Students? The
answer is NOand they dont do any worse either.
  • Contact Steve Myers myers_at_uakron.edu
  • The University of Akron
  • Or get this paper and presentation
  • Online at http//gozips.uakron.edu/myers/
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