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All Journal Information Technology Education Journal Journal of Applied Artificial Intelligence in Education
Fitra Ramadani
Universitas Negeri Makassar
Computer Science & IT Education

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Analyzing the Continuance Intention to Use AI News Anchors for Daily Information Needs: An Expectation Confirmation Theory Approach Alyah Rahayu; Andika Isma; Fitra Ramadani
Journal of Applied Artificial Intelligence in Education Vol 1, No 1 (2025): July 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v1i1.2

Abstract

Artificial intelligence (AI) has begun reshaping news broadcasting through AI-based news anchors that can deliver information efficiently and consistently, yet public acceptance, emotional connection, and accountability for potential errors remain open concerns. This study aimed to analyze users’ continuance intention to use AI news anchors for daily information needs through an Expectation Confirmation Theory, focusing on trust/acceptance, news-delivery quality, and perceived innovation. A quantitative cross-sectional survey was conducted among students aged 18–24 as digitally active users; data were collected via an online Likert-scale questionnaire (15 items across three aspects) and analyzed descriptively to summarize response patterns. The results indicate generally moderate-to-positive evaluations across all aspects: trust and acceptance showed an overall mean of 2.65, news-delivery quality 2.62, and innovation/technology 2.45. At the item level, respondents reported moderate comfort with AI-delivered news (M = 2.51) and moderate belief in accuracy/reliability (M = 2.54); delivery clarity was rated similarly (M = 2.54), while visual appeal showed a relatively stronger influence on viewing interest (M = 2.73). Respondents also expressed interest in AI-related technological advances (M = 2.52) and generally viewed AI news delivery as a positive media direction, while still noting that improvements are needed before AI can fully replace human presenters. These findings imply that media organizations and developers should prioritize more natural and emotionally engaging delivery, strengthen audio-visual realism, and address ethical/regulatory safeguards, concluding that AI news anchors are broadly acceptable to younger audiences but should be positioned as a complement to human presenters rather than a complete substitute.
Extending the Technology Acceptance Model (TAM) to Predict Student Learning Outcomes in GNS3 Based Networking Education Ummul Khaeri Masna; Agus Salim; Fitra Ramadani; Fadhlirrahman Baso
Information Technology Education Journal Vol. 5, No. 1, February (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i1.265

Abstract

Purpose – This study investigates the factors influencing network simulator acceptance and its direct impact on learning outcomes within the Department of Informatics and Computer Engineering. It addresses the gap between technology adoption and actual academic success in a technical vocational context. Design/methods/approach – A quantitative approach using the Technology Acceptance Model (TAM) was applied. Data from 187 students were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0, employing a 5,000-resample bootstrapping procedure. Findings – Results confirm that Perceived Usefulness significantly drives Behavioral Intention (β= 0.774, p < 0.001), while Perceived Ease of Use is non-significant (β = 0.150, p = 0.166). Crucially, Behavioral Intention strongly predicts Learning Outcomes (β = 0.849, p < 0.001). The model exhibits substantial predictive power, explaining 83% of the variance in intention (R2 = 0.830) and 72.1% in learning outcomes (R2 = 0.721). Research implications/limitations – Engineering pedagogy should prioritize demonstrating the industrial utility of simulators over interface simplicity. Limitations include the cross-sectional design and reliance on self-reported data within a single department, which may affect generalizability. Originality/value – This research empirically bridges technology acceptance with tangible academic performance in the Indonesian technical education context. It provides a validated framework for enhancing technical competencies through strategic tool integration.
Co-Authors Agus Salim Alyah Rahayu Andika Isma Fadhlirrahman Baso Ummul Khaeri Masna