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Factors contributing to dropping out of adults' programming e-learning.

Aiste Dirzyte1,2, Aidas Perminas3, Lukas Kaminskis4

  • 1Faculty of Creative Industries, Vilnius Gediminas Technical University, Saulėtekio ave. 11, Vilnius 10221, Lithuania.

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Summary

Higher initial programming knowledge and specific motivators like reward and recognition are linked to completing computer programming courses. Lower extraversion and higher relatedness frustration correlate with dropping out, especially for female learners.

Keywords:
21st century skillsAdult learningApplications in subject areasDistance education and e-learningGender studies

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Area of Science:

  • Computer Science Education
  • Educational Psychology

Background:

  • Acquiring computer programming skills presents significant challenges, often leading to high dropout rates in e-learning environments.
  • Understanding factors contributing to attrition is crucial for improving retention in online technical education.

Purpose of the Study:

  • To investigate factors influencing dropout rates in an e-based computer programming course.
  • To identify predictors of course completion versus attrition among e-learners.

Main Methods:

  • A quasi-experimental design was employed, involving 305 participants who started and 94 who completed an e-based programming course.
  • Data were collected using a programming knowledge assessment, the Learning Motivating Factors Questionnaire, the Big Five-2 personality traits inventory, and the Basic Psychological Need Satisfaction & Frustration Scale.

Main Results:

  • Completers exhibited higher initial programming knowledge scores than dropouts.
  • Males who completed the course reported higher reward/recognition motivation than male dropouts.
  • Females who completed showed lower extraversion, and those who dropped out after the first assessment reported higher relatedness frustration.

Conclusions:

  • Initial programming knowledge is a key factor in e-course completion.
  • Personality traits (extraversion), motivational factors (reward/recognition), and psychological needs (relatedness) play a role in programming e-learning attrition.
  • Findings should be interpreted cautiously due to sample size and design limitations.