The Use of Digital Annotation Tools in Assisting Reading English for Science and Technology Academic Texts among L2 Learners in Higher Institutions
Year: 2025
Type: article
Abstract: Since more academic reading resources are becoming digitally available, second language (L2) learners at higher institutions are confronted with more obstacles than in the past. Despite this, the abundance of internet resources available to support reading has made reading a more engaging activity. This research examined L2 learners' usage of digital annotation tools (DAT) in a Learning Management System (LMS) to aid the reading of English for Science and Technology (EST) materials in a blended course. The data was collected from a sample of 55 students who were enrolled in a variety of Science and Technology courses at a public institution in Malaysia. The data was gathered through online annotation and focus group interviews and subsequently subjected to thematic analysis using the NVivo software program. The validation of the thematic analysis was conducted through the utilisation of Cohen's Kappa analysis, resulting in a score that approached near perfection. This outcome serves as evidence for the credibility and accuracy of the collected data. Findings revealed that digital annotation tools improved L2 learners' lexical recognition and comprehension. Highlighting and annotating texts showed learners could summarise, justify, reproduce, and rephrase concepts. These annotation analyses supported interview data, showing that learners developed cognitive skills by paraphrasing and synthesising EST academic texts online. This study suggested facilitating successful best practices in online reading settings, where DAT is important in subject content areas for higher education students. This matters because DAT improves L2 learners' cognitive and social development by improving English reading comprehension . Keywords: English for Science and Technology; Online Reading; Digital Annotation Tools; Learning Management Systems; higher institution
Authors: Ruhil Amal Azmuddin, Nur Ainil Sulaiman, Mazura Jamalai @Jamali, Anis Nadiah Che Abdul Rahman, Farah Hani Roslan
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $300
OpenAlex ID: W4408877907
