Developing SMART-EEI with the ADDIE Framework: AI-Assisted E-Book for Export-Import English and 4C Skills in Indonesian Universities
Year: 2026
Type: article
Abstract: Artificial intelligence (AI) offers new possibilities for interactive and professionally relevant English for Specific Purposes (ESP) in Indonesian higher education. However, many Export-Import English resources remain static and provide limited support for authentic trade communication, individualised feedback, competency monitoring, and twenty-first-century skills. This study identified students’ learning needs and industry expectations and translated them into the pedagogical and technological design of Smart English for Export-Import (SMART-EEI). The analysis and design phases of the ADDIE framework were employed with 378 undergraduates from six Indonesian universities, six English lecturers, and five export-import industry stakeholders. Questionnaires, semi-structured interviews, and document analysis generated quantitative and qualitative data, which were analysed descriptively and thematically. Students prioritised business communication (M = 3.89, SD = 0.21), export-import documentation (M = 3.87, SD = 0.25), and digital trade and AI tools (M = 3.86, SD = 0.24), while industry stakeholders rated business communication (M = 3.95, SD = 0.12) and documentation (M = 3.94, SD = 0.14) highest. These convergent needs informed a design comprising validated multimodal content, competency-based assessment, bounded AI functions, learning analytics, and authentic trade tasks. The five-stage SMART sequence integrates self-directed exploration, multimodal engagement, guided AI practice, reflective improvement, and authentic transfer while operationalising critical thinking, communication, collaboration, and creativity. SMART-EEI thus offers a context-responsive design framework that can strengthen professionally relevant, technology-enhanced ESP and inform adaptable digital learning innovation beyond the Indonesian setting.
Institutions: Universitas PGRI Sumatera Barat, Politeknik Negeri Ambon
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7224992177