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Integrating AI-Powered Digital English Textbook at Grade 12: Pakistani Students and Teachers' Perceptions

Title: Integrating AI-Powered Digital English Textbook at Grade 12: Pakistani Students and Teachers' Perceptions
Language: English
Authors: Muhammad Mooneeb Ali (ORCID 0000-0002-0356-320X); Shawana Fazal (ORCID 0000-0002-8565-8607); Ubaid ullah Ubaid; Muhammad Amir Sae; Sayyed Rashid Ali Shah
Source: International Journal of Adult Education and Technology. 2025 16(1).
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Peer Reviewed: Y
Page Count: 20
Publication Date: 2025
Document Type: Journal Articles; Reports - Research
Education Level: Grade 12; High Schools; Secondary Education
Descriptors: Artificial Intelligence; Electronic Books; Textbooks; Grade 12; English (Second Language); Second Language Instruction; Foreign Countries; High School Students; High School Teachers; Student Attitudes; Teacher Attitudes
Geographic Terms: Pakistan
DOI: 10.4018/ijaet.376488
ISSN: 2643-7996; 2643-8003
Abstract: In response to the global emergence of artificial intelligence (AI), the Government of Punjab, Pakistan, conducted a pilot project in 2024, introducing AI-powered digital textbooks for Grade 12 English learners. The project included 80 teachers and 400 learners from Lahore, Pakistan. The present study explores the perspectives of the learners and teachers who participated in this pilot initiative. A concurrent mixed-methods research design was employed, with a sample of 100 students and 40 teachers selected through simple random sampling. Structured questionnaires were used to collect quantitative data from students, while interviews were conducted with teachers. Quantitative data were analyzed using SPSS 27, and thematic analysis of qualitative data was carried out using Claude.ai. The findings revealed that students viewed AI-powered digital textbooks as a novel, dynamic, engaging, and impactful method for learning English. Similarly, teachers regarded AI-powered digital textbooks as highly beneficial for enhancing students' English language proficiency.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1471604
Database: ERIC