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Jordanian English Language Learners' Engagement with AI-Supported Self-Regulated Learning

Title: Jordanian English Language Learners' Engagement with AI-Supported Self-Regulated Learning
Language: English
Authors: Omar Ali Al-Smadi; Radzuwan Ab Rashid; Raed Awad Al-Ramahi; Marwan Harb Alqaryouti; Holmatov Shakhriyor Zokhidjon Ugli; Abdurakhmon Norinboev Vokhidovich
Source: Research in Learning Technology. 2025 33.
Availability: Association for Learning Technology. Gipsy Lane, Headington, Oxford OX3 0BO, UK. e-mail: enquiries@alt.ac.uk; Web site: https://journal.alt.ac.uk
Peer Reviewed: Y
Page Count: 18
Publication Date: 2025
Document Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Descriptors: Foreign Countries; Metacognition; Second Language Learning; Second Language Instruction; Artificial Intelligence; Computer Software; Technology Integration; Higher Education; Educational Experience; Undergraduate Students; Student Attitudes; Majors (Students); English (Second Language); Technological Literacy; Teaching Methods; Inclusion; Independent Study; Learner Engagement
Geographic Terms: Jordan
ISSN: 2156-7069; 2156-7077
Abstract: In the dynamic landscape of higher education, the integration of artificial intelligence (AI) into learning has emerged as a transformative force, ushering in tailored, adaptive, and immersive educational experiences for undergraduate university students. This study employed a thematic analysis to scrutinize focus group discussions with 25 undergraduate participants majoring in English language at a university in Jordan to examine how these learners engage with AI-supported self-regulated learning. The findings revealed five prominent themes: accessibility and inclusivity, adaptive feedback mechanisms, impact on learning habits, technological proficiency and preparedness, and social dynamics in AI-infused learning. Within these themes, diverse student views were categorized according to Ab Rashid and Yunus' (2016) framework of perception evaluation: the Avid Category (very positive perception), the Analytic Category (enthusiast but critical), the Anxious Category (enthusiast but with worries and fear), and the Agnostic Category (negative view). These varied views collectively reveal the profound implications of AI integration in reshaping the educational landscape. This study contributes to the discourse on AI in education by highlighting the importance of integrating AI tools with pedagogical approaches that foster independent learning and critical engagement. Recommendations include combining AI feedback with peer reviews and instructor guidance, enhancing digital literacy programs, and ensuring robust support measures. By addressing these areas, educational institutions can create more inclusive and effective AI-supported learning environments that cater to diverse student needs and promote a balanced approach to technology in education.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1478394
Database: ERIC