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

Schemata01:17

Schemata

123
A schema is a mental construct that organizes related concepts, allowing the brain to process information efficiently. Upon activation, schemata facilitate assumptions about people or objects.
Two types of schemata are:
123
Cognitive Learning01:21

Cognitive Learning

466
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...
466
Cluster Sampling Method01:20

Cluster Sampling Method

12.1K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.1K
Natural and Artificial Concepts01:24

Natural and Artificial Concepts

230
In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
230
Metacognition01:26

Metacognition

252
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...
252
Classification of Systems-I01:26

Classification of Systems-I

238
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
238

You might also read

Related Articles

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

Sort by
Same journal

Retraction Note: Online learning challenges in Thailand and strategies to overcome the challenges from the students' perspectives.

Education and information technologies·2026
Same journal

Quality of technology integration matters: Positive associations with students' behavioral engagement and digital competencies for learning.

Education and information technologies·2025
Same journal

Effects of adaptive feedback through a digital tool - a mixed-methods study on the course of self-regulated learning.

Education and information technologies·2024
Same journal

Measuring cyber wisdom: preliminary validation of a new four-component measure.

Education and information technologies·2024
Same journal

Online education of engineering students: Educational platforms and their influence on the level of academic performance.

Education and information technologies·2023
Same journal

Exploring the effects of sudden institutional coercive pressure on digital transformation in colleges from teachers' perspective.

Education and information technologies·2023

Related Experiment Video

Updated: Aug 8, 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

5.4K

Investigating online learners' knowledge structure patterns by concept maps: A clustering analysis approach.

Xiuling He1, Jing Fang2, Hercy N H Cheng3

  • 1National Engineering Laboratory For Education Big Data, Central China Normal University, Wuhan City, Hubei Province China.

Education and Information Technologies
|February 27, 2023
PubMed
Summary

Analyzing online learners

Keywords:
Clustering analysisConcept mapFlipped classroomKnowledge structureOnline learning

More Related Videos

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

3.6K
Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.2K

Related Experiment Videos

Last Updated: Aug 8, 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

5.4K
Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

3.6K
Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.2K

Area of Science:

  • Educational Technology
  • Online Learning
  • Knowledge Representation

Background:

  • Understanding online learners' knowledge levels is crucial for successful online learning.
  • Knowledge structures, visualized through concept maps, offer insights into learning.
  • Flipped classroom models present unique challenges for assessing online learner knowledge.

Purpose of the Study:

  • To investigate online learners' knowledge structures in a flipped classroom environment.
  • To identify patterns and types of online learners based on their knowledge structures.
  • To analyze the relationship between knowledge structure complexity and learning achievement.

Main Methods:

  • Collected 359 concept maps from 36 students over an 11-week semester.
  • Utilized clustering analysis to identify knowledge structure patterns and learner types.
  • Employed non-parametric tests to compare learning achievement across learner types.

Main Results:

  • Identified three knowledge structure patterns: spoke, small-network, and large-network.
  • Novice learners predominantly exhibited spoke patterns in the flipped classroom context.
  • Complex knowledge structures (large-network) correlated with significantly better learning achievement.

Conclusions:

  • Online learners' knowledge structures can be automatically analyzed using data mining.
  • More complex knowledge structures are associated with higher learning achievement in online settings.
  • Flipped classrooms may require specific instructional design to address learner knowledge preparedness.