Determinants of Learners’ Continuance Intention in Informal Video Learning: Evidence from YouTube

Informal video platforms support self-directed learning, yet the determinants of learners’ continuance intention to use YouTube for informal learning remain insufficiently integrated. This study addressed two questions: how the hypothesized structural relationships in an extended expectation–confirmation model explain Thai learners’ continuance intention and which determinants are necessary for high continuance intention. A sequential exploratory mixed-methods design was employed. Fuzzy e-Delphi with 23 experts retained 33 measurement items; survey data from 797 Thai learners were analyzed using covariance-based structural equation modeling, bootstrapped specific indirect effects, and Necessary Condition Analysis (NCA). The model explained 74% of the variance in continuance intention. Satisfaction was the strongest direct predictor (β = 0.559), followed by perceived enjoyment and trust. All 12 hypothesized structural relationships and eight indirect effects were statistically significant, revealing interconnected roles for confirmation, content quality, subjective norm, perceived enjoyment, perceived usefulness, satisfaction, and trust. NCA identified satisfaction and content quality as the principal necessary conditions, with smaller supporting roles for perceived usefulness and perceived enjoyment. Theoretically, the findings extend the expectation–confirmation model to voluntary informal video learning and distinguish contributing relationships from necessary constraints. Practically, they support prioritizing high-quality content and satisfactory learning experiences while strengthening perceived usefulness and perceived enjoyment.

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Publication Details

Journal
Behavioral Sciences
Published
2026-09-04
DOI
https://doi.org/10.3390/bs16091574
Primary Topic
Online and Blended Learning
Type
article
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article

Determinants of Learners’ Continuance Intention in Informal Video Learning: Evidence from YouTube

Sumaman Pankham, Somchai Lekcharoen, Tewarit Khanmolee
Behavioral Sciences
Online and Blended Learning
article

Determinants of Learners’ Continuance Intention in Informal Video Learning: Evidence from YouTube

Sumaman Pankham, Somchai Lekcharoen, Tewarit Khanmolee
article en

Abstract

Informal video platforms support self-directed learning, yet the determinants of learners’ continuance intention to use YouTube for informal learning remain insufficiently integrated. This study addressed two questions: how the hypothesized structural relationships in an extended expectation–confirmation model explain Thai learners’ continuance intention and which determinants are necessary for high continuance intention. A sequential exploratory mixed-methods design was employed. Fuzzy e-Delphi with 23 experts retained 33 measurement items; survey data from 797 Thai learners were analyzed using covariance-based structural equation modeling, bootstrapped specific indirect effects, and Necessary Condition Analysis (NCA). The model explained 74% of the variance in continuance intention. Satisfaction was the strongest direct predictor (β = 0.559), followed by perceived enjoyment and trust. All 12 hypothesized structural relationships and eight indirect effects were statistically significant, revealing interconnected roles for confirmation, content quality, subjective norm, perceived enjoyment, perceived usefulness, satisfaction, and trust. NCA identified satisfaction and content quality as the principal necessary conditions, with smaller supporting roles for perceived usefulness and perceived enjoyment. Theoretically, the findings extend the expectation–confirmation model to voluntary informal video learning and distinguish contributing relationships from necessary constraints. Practically, they support prioritizing high-quality content and satisfactory learning experiences while strengthening perceived usefulness and perceived enjoyment.

Behavioral SciencesVol. 16(9)
Rangsit University (TH)
Quality Education
Openalex Percentile: Top 2%
Online and Blended Learning
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