Student Retention in Online and Traditional Course Settings: Motivation and Interaction between Sett

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Student Retention in Online and Traditional
Course Settings Motivation and Interaction
between Setting and Gender

• Dianna J. Spence
• North Georgia College and State University
• SSCEL
• September 30, 2006

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Research Setting

• Studies of several traditional and online
  sections of the same courses
• Across settings trends common to both
• Between settings differences found
• Developmental mathematics courses
• State supported two year college in the Southeast

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Two Studies Conducted

• Factors Associated with Student Engagement and
  Achievement
• Both settings
• Quantitative study
• Theoretical framework Social cognitive theory

• Nature of Student Experience Using Computer-Based
  Learning Tools
• Both settings
• Qualitative study
• Line of inquiry factors mediating effectiveness
  of courseware

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Emerging Theme Retention

• What sort of retention issue?
• Students who stop coming to class after course
  withdrawal deadline
• Why examine this retention issue?
• Not the initial focus of either study
• Practical issue in retaining research
  participants in both studies
• Identified as a barrier to student achievement in
  both studies

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Details of Student Attrition after Withdrawal
Deadline

• Withdrawal deadline is mid-semester
• Drop before deadline grade is WStop attending
  later grade is F
• Midterm exam score and other course feedback are
  given to student before withdrawal deadline
• In quantitative study, 18 of 182 participants
  stopped attending class after mid-term withdrawal
  deadline

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Quantitative Study Variables

• Gender
• Course setting (online or traditional)
• Motivation Variables
• Achievement Goals
• Computer Self-Efficacy
• Self-Efficacy for Self Regulation

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Course Setting

• Online
• Students meet only for orientation, midterm and
  final exam
• Web-based learning software is primary mechanism
  of instruction
• Traditional
• Students meet in classroom for instruction
• Same web-based learning software available as
  optional supplement

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Achievement GoalsOverview

• Mastery Goals Desire to learn content for its
  own sake
• Performance Goals
• Performance Approach Desire to appear competent
• Performance Avoid Desire not to appear
  incompetent
• Behaviors associated with achievement linked more
  with mastery goals than with performance goals.

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Achievement GoalsFindings

• Students who finished course
• Performance avoid goals M 2.42

• Students who did not finish course
• Performance avoid goals M 2.94

• Statistically significant mean difference in
  performance avoid goals
• Performance approach and mastery goals no
  significant differences detected

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Computer Self-Efficacy Overview

• Computer Self-EfficacyA persons belief in
  his/her ability to use a computer

Findings
No significant differences detected in computer
self-efficacy between those who finished and
those who did not
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Self-Efficacy for Self-RegulationOverview

• Self Regulation Monitoring or regulating ones
  thoughts and behaviors while attempting a task
• Self Regulated Learning Using self-regulating
  strategies to achieve academic success (goal
  setting, self-monitoring, learning strategies)
• Self-Efficacy for Self-Regulation Persons
  belief in his/her ability to use self-regulated
  learning strategies

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Self-Efficacy for Self-RegulationFindings

• Students who finished course
• Self-efficacy for self-regulation
• M 4.24

• Students who did not finish course
• Self-efficacy for self-regulation
• M 3.57

• Statistically significant mean difference in
  self-efficacy for self-regulation
• Self-efficacy for self-regulation predicted
  student engagement with online courseware,
  whereas computer self-efficacy did not.

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Course Setting and GenderFindings

• Setting
• 9 of 86 online students did not finish
• 9 of 96 traditional students did not finish
• No significant association between setting and
  decision not to finish
• Gender
• 12 of 139 women did not finish (8.6)
• 6 of 43 men did not finish (14.0)
• Chi-square test revealed no significant
  association (gender and not finishing)

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Setting and Gender InteractionGender Association
in Each Setting
(results did not reach significance)
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Setting and Gender InteractionGender Association
in Each Setting
p lt .01
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Setting and Gender InteractionSetting
Association for Each Gender
(results did not reach significance)
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Setting and Gender InteractionSetting
Association for Each Gender
p lt .05
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A Prediction Model

• Logistic Regression
• Binary outcome
• Finish yes/no
• Only two factors were significant predictors
• RL2 analogous to R2 for predictive value of model
• Gamma indicates this model lowers prediction
  error by 61 over random prediction

p lt .05
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Interpreting the Logistic Regression

• Self-Efficacy for Self-Regulation overshadows
  Computer Self-Efficacy in predicting student
  persistence
• Female students in traditional classes had higher
  likelihood of finishing
• than did traditional male students
• than did online female students

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Examining Gender and SettingQualitative Findings

• Female students placed more emphasis on the
  importance of contact with a human instructor,
  even in online environments
• Availability by phone or e-mail
• Personal interaction
• Videos of instruction for online viewing
• Gender differences in perceived role of
  instructor
• Men Content Expert, Leader, Enforcer
• Women Helper, Guide, Nurturer

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Implications and Suggestions

• Set student expectations for self-regulated
  learning
• Give prospective online students the
  self-efficacy for self-regulation survey
• Communicate role of self-regulation in success,
  particularly in online setting
• Be aware of students varying needs for
  contact/interaction with instructor
• Possible gender differences

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Questions and Discussion