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

Cognitive Learning01:21

Cognitive Learning

237
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...
237
Associative Learning01:27

Associative Learning

340
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
340
Vygotsky's Cognitive Development in Cultural Context01:22

Vygotsky's Cognitive Development in Cultural Context

65
Lev Vygotsky, a pioneering Russian psychologist, developed a theory of cognitive development that centers on the influence of social and cultural factors. Unlike Jean Piaget, who emphasized the child's direct interaction with the physical world as key to development, Vygotsky argued that cognitive growth is an interpersonal process that unfolds within a cultural context. For Vygotsky, a child's learning cannot be separated from their social environment, which includes the values,...
65
Observational Learning01:12

Observational Learning

166
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
166
Purposive Learning01:22

Purposive Learning

118
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
118
Steps in the Modeling Process01:14

Steps in the Modeling Process

200
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
200

You might also read

Related Articles

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

Sort by
Same author

Application of Cell-Free DNA Barcode-Enabled Single-Molecule Test for Non-Invasive Prenatal Testing of α-Thalassemia and β-Thalassemia.

Journal of clinical laboratory analysis·2026
Same author

<i>Dendrobium officinale</i> polysaccharide prevents liver injury via the regulation of Keap1/Nrf2 pathway and lipid metabolism in acute alcoholic liver injury mice.

Natural product research·2026
Same author

[Effect and mechanism of Ligustrum robustum extract in intervening in lipid metabolism pathways to reduce lipid levels in hyperlipidemic mice].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica·2026
Same author

AlGaN/GaN HEMT Hâ‚‚ sensor with integrated Wheatstone bridge and on-chip microheater for 0.1-ppm detection.

Microsystems & nanoengineering·2026
Same author

BLM as a potential therapeutic target in cutaneous malignant melanoma.

Biochemical pharmacology·2026
Same author

Deciphering the role of per- and polyfluoroalkyl substances in prostate cancer: a multi-omics and computational toxicology approach.

Frontiers in cell and developmental biology·2026

Related Experiment Video

Updated: Jun 25, 2025

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.3K

Psychological factors enhanced heterogeneous learning interactive graph knowledge tracing for understanding the

Zhifeng Wang1,2, Wanxuan Wu2, Chunyan Zeng3

  • 1Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, China.

Frontiers in Psychology
|May 27, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel knowledge tracing model (Psy-KT) that incorporates psychological factors and forgetting curves to predict student performance. The model enhances educational technology by providing more accurate insights into student learning behaviors.

Keywords:
Graph Neural NetworkItem Response Theoryknowledge tracinglearning processpsychological factors

More Related Videos

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

12.5K
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

8.4K

Related Experiment Videos

Last Updated: Jun 25, 2025

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.3K
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

12.5K
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

8.4K

Area of Science:

  • Educational Technology
  • Artificial Intelligence in Education
  • Cognitive Science

Background:

  • Online education is rapidly expanding, increasing demand for personalized learning experiences.
  • Knowledge tracing models predict student skill proficiency but often neglect psychological states.
  • Existing models overlook crucial factors like student frustration, confusion, concentration, and boredom.

Purpose of the Study:

  • To introduce a novel psychological factors-enhanced heterogeneous learning interactive graph knowledge tracing model (Psy-KT).
  • To address the limitations of current knowledge tracing models by incorporating psychological factors and the forgetting curve.
  • To improve the accuracy and interpretability of student performance prediction in educational settings.

Main Methods:

  • Developed a heterogeneous graph to model interactions between students, exercises, and skills.
  • Integrated four psychological factors: frustration, confusion, concentration, and boredom.
  • Incorporated the forgetting curve and Item Response Theory (IRT) for enhanced learning process modeling and performance prediction.

Main Results:

  • The Psy-KT model demonstrated superior performance in predicting future student performance across four public datasets.
  • Integration of psychological and forgetting factors significantly improved predictive accuracy.
  • The model offers a more comprehensive understanding of student learning behaviors.

Conclusions:

  • The Psy-KT model provides a more holistic approach to knowledge tracing by considering psychological states and learning dynamics.
  • Enhanced predictive accuracy enables educators to offer more targeted tutoring and personalized learning advice.
  • This research contributes to the advancement of adaptive learning systems in EdTech.