Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Social Cognitive Perspective on Personality01:30

Social Cognitive Perspective on Personality

723
Social cognitive perspectives on personality emphasize the importance of conscious awareness, beliefs, expectations, and goals in shaping behavior. These perspectives incorporate behaviorist principles, such as learning through reinforcement and conditioning, but extend beyond them by highlighting human reasoning and planning. Unlike traditional behaviorist views, social cognitive theory focuses on how individuals reflect on their past experiences and plan for future outcomes by considering...
723
Cognitive Learning01:21

Cognitive Learning

709
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
709
Personality Theory by Eysenck and Eysenck01:29

Personality Theory by Eysenck and Eysenck

749
Hans and Sybil Eysenck developed a widely recognized theory of personality, which emphasizes the role of temperament and genetically based differences in shaping individual traits. Their theory posits that biological factors primarily determine personality and can be understood through two main dimensions: extroversion/introversion and neuroticism/stability.
In the extroversion/introversion dimension, highly extroverted people are sociable, outgoing, and easily connect with others. In contrast,...
749
Cattell's 16 Personality Factors01:24

Cattell's 16 Personality Factors

1.5K
Raymond Cattell's trait theory offers a structured framework for understanding personality by distinguishing between two critical traits: surface and source traits. Surface traits are observable patterns of behavior, such as indecisiveness, anxiety, and irrational fears. These traits are less stable, varying across situations and over time. This means that they are less helpful in understanding the deeper aspects of an individual's personality.
In contrast, source traits are the...
1.5K
Self-Report Tests of Personality01:22

Self-Report Tests of Personality

502
Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.
502
Metacognition01:26

Metacognition

326
Metacognition is a conscious process where individuals are aware of their cognitive and executive processes, such as planning before solving a problem or self-monitoring during reading. For instance, a writer may need help with composing a piece. The situation involves a writer who is working on a piece of writing, but while doing so, they realize that something is missing. They notice that their characters lack depth or details. This realization occurs because the writer is reflecting on their...
326

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Lithuanian children's trauma characteristics and correlates: comparison of clinical and non-clinical samples.

Frontiers in psychiatry·2026
Same author

Psychological, social, and sociocultural factors related to disordered eating behaviour during pregnancy: A systematic review.

Journal of health psychology·2026
Same author

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

Heliyon·2023
Same author

The impact of appearance comments by parents, peers and romantic partners on eating behaviour in a sample of young women.

Health psychology report·2023
Same author

Law Enforcement Officers' Ability to Recognize Emotions: The Role of Personality Traits and Basic Needs' Satisfaction.

Behavioral sciences (Basel, Switzerland)·2022
Same author

Associations between Leisure Preferences, Mindfulness, Psychological Capital, and Life Satisfaction.

International journal of environmental research and public health·2022

Related Experiment Video

Updated: Oct 18, 2025

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
13:57

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

Published on: July 1, 2015

12.8K

Computer Programming E-Learners' Personality Traits, Self-Reported Cognitive Abilities, and Learning Motivating

Aiste Dirzyte1,2, Aivaras Vijaikis2, Aidas Perminas3

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

Brain Sciences
|September 28, 2021
PubMed
Summary

Computer programming e-learners show lower extraversion and motivation scores compared to other e-learners. Personality traits significantly predict motivation, while cognitive abilities have a negligible impact on programming e-learning success.

Keywords:
cognitive abilitiescomputer programminge-learningmotivationpersonality

More Related Videos

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
12:55

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Published on: September 27, 2020

8.6K
Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

4.1K

Related Experiment Videos

Last Updated: Oct 18, 2025

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
13:57

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

Published on: July 1, 2015

12.8K
Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
12:55

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Published on: September 27, 2020

8.6K
Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

4.1K

Area of Science:

  • Educational Psychology
  • Cognitive Science
  • Computer Science Education

Background:

  • Programming education is crucial but challenging for students globally.
  • Understanding factors influencing programming learning is essential for effective e-learning.
  • This study investigates personality traits, cognitive abilities, and motivation in computer programming e-learners.

Purpose of the Study:

  • To identify personality traits, self-reported cognitive abilities, and learning motivation factors of computer programming e-learners.
  • To compare these factors between computer programming e-learners and other e-learners.
  • To explore the predictive relationships between personality, cognitive abilities, and motivation in programming e-learning.

Main Methods:

  • Survey administered to 444 e-learners (189 in computer programming).
  • Instruments used: Learning Motivating Factors Questionnaire, Big Five Inventory-2, and SRMCA.
  • Structural Equation Modeling (SEM) analysis was employed to examine relationships.

Main Results:

  • Computer programming e-learners scored significantly lower in extraversion and specific motivating factors (individual attitude, reward, punishment).
  • No significant differences in self-reported cognitive abilities were found between groups.
  • Personality traits (extraversion, conscientiousness, negative emotionality) significantly predicted motivation (attitude, clear direction); cognitive abilities had negligible impact.

Conclusions:

  • Personality traits are significant predictors of learning motivation in computer programming e-learners.
  • Self-reported cognitive abilities do not appear to be a major factor in programming e-learning success.
  • Future research should incorporate neurocognitive methods to validate self-reported findings.