YouTube's Impact on Students' Self-Directed Language Learning (SDLL): A Comprehensive Evaluation Based on the Knowledge-Skills-Attitude Trio

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Bibliographic Details
Title: YouTube's Impact on Students' Self-Directed Language Learning (SDLL): A Comprehensive Evaluation Based on the Knowledge-Skills-Attitude Trio
Language: English
Authors: Tran Thanh Nhan (ORCID 0000-0002-3253-9508), Pham Thi Ngoc Anh (ORCID 0009-0003-0516-7600), Nguyen Quynh Chi (ORCID 0009-0005-2734-0480), Ta Huong Giang (ORCID 0009-0004-3416-5054), Chu Thu Trang (ORCID 0000-0002-2583-7654)
Source: JALT CALL Journal. 2026 22(1).
Availability: JALT CALL SIG. 1-6-1 Nishiwaseda Shinjuku-ku, Tokyo, 169-8050, Japan. e-mail: journal!jaltcall.org; Web site: https://jaltcall.org
Peer Reviewed: Y
Page Count: 26
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Social Media, Independent Study, Second Language Learning, Multimedia Materials, Influence of Technology, English (Second Language), Instructional Effectiveness, Video Technology, Technology Uses in Education, Instructional Films, Foreign Countries, Higher Education, College Students
Geographic Terms: Vietnam
ISSN: 1832-4215
Abstract: YouTube has undeniably become a ubiquitous and influential multimodal media for recreational and educational purposes among Generation Z students. These "digital natives" have acquired increasingly more self-efficacy to lead their learning via this virtual immersion. Their self-directed language learning (SDLL) is hailed as a game changer in cultivating learners' ability to activate their language acquisition device when encountering comprehensible input (Chomsky, 1965; Krashen, 1982). Therefore, the current study aims to identify the effects of YouTube on students' SDLL and propose solutions to optimize this self-regulated process. Quantitative and qualitative data were collected through a survey with 361 participants from a high-ranking language-major university. The data was analyzed descriptively and inferentially via Microsoft Excel Analytical Pack with the analysis of variance (ANOVA). The results indicate a significant relationship between learning time on YouTube and overall study results. YouTube has a considerable impact on their autonomous learning (M = 3.60) regarding eight aspects: vocabulary (M = 3.73), grammar (M = 3.18), pronunciation (M = 4.12), listening (M = 3.44), reading (M = 3.27), speaking (M = 3.24), writing (M = 4.06), and their attitudes (M = 4.10). The study also reports student-raised suggestions to maximize the effectiveness of their SDLL.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506615
Database: ERIC
Description
Abstract:YouTube has undeniably become a ubiquitous and influential multimodal media for recreational and educational purposes among Generation Z students. These "digital natives" have acquired increasingly more self-efficacy to lead their learning via this virtual immersion. Their self-directed language learning (SDLL) is hailed as a game changer in cultivating learners' ability to activate their language acquisition device when encountering comprehensible input (Chomsky, 1965; Krashen, 1982). Therefore, the current study aims to identify the effects of YouTube on students' SDLL and propose solutions to optimize this self-regulated process. Quantitative and qualitative data were collected through a survey with 361 participants from a high-ranking language-major university. The data was analyzed descriptively and inferentially via Microsoft Excel Analytical Pack with the analysis of variance (ANOVA). The results indicate a significant relationship between learning time on YouTube and overall study results. YouTube has a considerable impact on their autonomous learning (M = 3.60) regarding eight aspects: vocabulary (M = 3.73), grammar (M = 3.18), pronunciation (M = 4.12), listening (M = 3.44), reading (M = 3.27), speaking (M = 3.24), writing (M = 4.06), and their attitudes (M = 4.10). The study also reports student-raised suggestions to maximize the effectiveness of their SDLL.
ISSN:1832-4215