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THE ROLE OF TECHNOLOGICAL SYSTEMS IN MANAGING AND EVALUATING THE LANGUAGE TEACHING PROGRAM Lalita Vistari; Rudi Hartono; Melfa Lamria Berliana Lumbantoruan
Wiralodra English Journal Vol. 9 No. 2 (2025): Wiralodra English Journal (WEJ)
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/wej.v9i2.406

Abstract

Innovative systems are changing modern language education from teaching and assessment to pedagogical strategies. This study explored the extent to which Learning Management Systems (LMS), Computer Assisted Language Learning (CALL) environments, and digital assessment tools impacted the organization and assessment of language programs. A qualitative research approach was utilized, and data was collected from forty participants (educators, learners, and administrators) through semi-structured interviews, anonymized surveys, and document analysis. Feedback from participants indicates that while organizational features of LMS platforms are one of the most utilized components, they are also highly effective (85%) for organizing course materials and communication. CALL tools provide interactive and personalized learning experiences (rated at 78%) but require better teacher training and technical know-how. Digital assessment tools are efficient (65%) for assessing language skills, but face challenges with evaluating nuanced language skills, such as fluency and creativity. The text emphasizes the importance of hybrid assessment methods that blend automated feedback with human input. Despite challenges like software issues, hardware access, and limited training, technology has enhanced learning and teaching. The study calls for thoughtful integration, continuous instructional design, and stronger teacher training, alongside improvements in infrastructure to support a more flexible, student-centred education system.
FROM DIGITAL PROFICIENCY TO COMMUNICATIVE CONFIDENCE: THE MEDIATING ROLE OF ATTITUDES IN AI-ASSISTED LANGUAGE LEARNING Lalita Vistari; Issy Yuliasri; Yuliati
English Review: Journal of English Education Vol. 14 No. 1 (2026)
Publisher : University of Kuningan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/englishreview.v14i1.126

Abstract

Artificial Intelligence (AI) is an influential factor in improving the speaking and communication skills of students in language learning. And yet, there is a knowledge gap in relation to students’ self-reported readiness levels for communication vis-à-vis their prediction on preparedness for AI-assisted digital learning, alongside their technological literacy and attitudes towards AI. The present study uses TAM for the context of digital learning and adopts a quantitative approach with a correlation research design using SEM. The subjects of the study were English education students in Indonesia, and several aspects, such as Technology readiness, Attitudes towards AI, & Communicative readiness, were measured using a structured questionnaire. The results highlighted the statistically significant direct and indirect links of technology readiness with positive AI attitudes, as well as communicative readiness. The standardized path estimates showed that students with high technical skills and strong attitudes towards the AI tool reported more communication-enhanced confidence. AI communication tools can contribute to the development of students’ communicative competence, but they are not simply a reflection of some specific purpose without emotional and cognitive engagement between learners and AI products. This research offers novelty by integrating TAM and TRI to test the mediation of attitudes towards AI on the communicative readiness of English language education students in Indonesia, filling an empirical gap in developing countries. State of the art highlights AI development, such as chatbots in Southeast Asia, but there is little exploration of the emotional roles and local infrastructure, which is completed by this validated SEM model. Yet, this study suggests that attention to students’ perceptions and readiness, including how they perceive ICT in their social networks and are ready for using ICT for learning, is a key factor to enhance digital learning environments. This study adds to this work by showing AI-enhanced technology can productively augment communicative competence when students are well-prepared and motivated.
Exploring Digital Transformation Readiness: Unveiling Hidden Patterns Through K-Means Clustering Lalita Vistari; Issy Yuliasri; Yuliati -; Adrallisman -; Melfa Lamria Berliana Lumbantoruan
Mimbar Ilmu Vol. 30 No. 3 (2025): December
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/mi.v30i3.104931

Abstract

The rapid digital transformation in higher education requires students to have advanced digital skills, ethical awareness, and effective communication. However, many studies overlook the diversity within student populations, particularly in terms of digital readiness. This research addresses this gap by examining students' digital construction variations through the use of K-Means clustering. The study adopts a mixed-methods approach, combining a survey on technology usage, attitudes, and communication with qualitative interviews. The analysis identifies two distinct student clusters: "Basic Learners," who demonstrate lower digital readiness, and "Digital Pioneers," who exhibit advanced digital skills. The validity of these clusters is confirmed through the Silhouette Score and ANOVA (p < 0.05), which reveal significant differences in digital readiness. The findings suggest that students with lower academic achievement perform better with moderately challenging digital tasks when provided with additional resources. In contrast, older students face more complex digital challenges. This highlights the need for higher education institutions to develop more inclusive, tailored strategies that address the diverse digital needs of students.