Task-Based Language Teaching Dan Model ARCS Dalam Meningkatkan Motivasi Belajar Bahasa Inggris: Tinjauan Literatur Sistematis

Abstract

English speaking proficiency is an essential need for Informatics Engineering students, both for accessing literature, engaging in international collaboration, and preparing for careers in the global industry. However, learning motivation is often a major challenge due to low second-language exposure and rigid curricula. This article aims to systematically examine the effectiveness of Task-Based Language Teaching (TBLT) integrated with the ARCS motivational model (Attention, Relevance, Confidence, Satisfaction) in enhancing motivation, engagement, and speaking confidence. A systematic literature review of 40 Scopus-indexed articles published between 2022 and 2026 was conducted through identification, screening, and thematic analysis stages. The findings show that TBLT consistently strengthens intrinsic and instrumental motivation, reduces speaking anxiety, and enhances self-efficacy, particularly when supported by adequate teacher training, a supportive classroom environment, and technology integration such as virtual reality (VR) and artificial intelligence (AI). Integrating the ARCS model into the TBLT task cycle strengthens learners' attention, relevance, confidence, and satisfaction. Nevertheless, systemic barriers such as rigid curricula, large classes, and limited facilities still constrain implementation effectiveness, particularly in the Indonesian higher education context. This article recommends strengthening lecturer training, aligning curricula with industry needs, and developing technology-based authentic tasks to optimize English learning motivation among Informatics Engineering students.