AI-supported course design for language proficiency development: Introducing the PPTTT framework

Abstract

Artificial intelligence (AI) offers significant potential for enhancing language instruction by personalizing learning experiences (Srinivasa et al., 2022) based on learner characteristics such as proficiency level and learning style (Ma, 2023), facilitating human-like interactions (Alawida et al., 2023; Klimova et al., 2024), demonstrating contextual understanding (Bansal et al., 2024), and creating opportunities for learners to engage with the target language in meaningful, real-world contexts. AI can also help increase engagement and motivation (Fuchs, 2023) and target the development of specific skills, including pronunciation and speaking. However, much of the existing work on AI in language education emphasizes individual tools or activities, with comparatively limited guidance on how AI can be systematically integrated into language course design. This paper addresses this gap by introducing the Planning, Preparing, Testing, Tailoring, and Treasuring (PPTTT) framework, a five-step AI-supported course design model developed for teaching Arabic as a foreign language. Building on established instructional design models such as ADDIE and the Holistic 4D Model, PPTTT positions AI as a co-designer throughout the planning, development, and refinement of language courses. The framework emphasizes learner profiling, proficiency-based outcomes, and the integration of communicative, culturally grounded tasks, with particular attention to pronunciation, fluency, and interaction. To illustrate the framework’s pedagogical potential, the paper presents a set of AI-mediated listening and speaking activities aligned with PPTTT stages. Although the framework is illustrated through Arabic, the pedagogical principles and AI applications are adaptable to a wide range of languages and instructional contexts.