Manuscript received April 16, 2026; accepted September 23, 2026; published October 12, 2026.

Abstract—This work-in-progress developmental study designs and evaluates an Artificial Intelligence (AI)-based digital learning module for the linguistic training (Arabic grammar) course at Kuwait University. The study addresses persistent difficulties in applying grammatical rules and low engagement associated with conventional instruction characterized by limited interactivity and delayed feedback. The module integrates generative AI through NotebookLM and standardized prompt templates to provide adaptive explanations, scaffolded practice, immediate formative feedback, and self-paced review aligned with course learning outcomes. To account for Arabic linguistic complexity and potential inconsistencies in automated outputs, the module incorporates verification steps and instructor checkpoints to support responsible use. The study includes two phases: (1) a design and validation phase that analyzes course content, selects priority concepts and skills, and develops the module following a systematic instructional design model with an aligned assessment and feedback workflow; and (2) a quasi-experimental pretest–posttest phase in Semester 1 of the 2026–2027 academic year, comparing an experimental class using the module with a control class receiving conventional instruction. Data will be collected using a researcher-developed academic achievement test and a learning-motivation questionnaire administered before and after the intervention. Group differences will be analyzed at α = 0.05 using appropriate inferential statistics, and effect sizes will be reported to estimate practical impact. It is expected that the module will improve post-test achievement and motivation and will yield context-sensitive guidelines for responsible AI integration in Arabic grammar instruction, including academic integrity, data privacy, and instructor support considerations.
 
Keywords—linguistic training, Arabic grammar, Artificial Intelligence (AI)-based digital learning module, generative AI, NotebookLM, learning motivation, academic achievement

Cite: Amani A. Shaheen, Almothana Mustafa Gasaymeh, and Sahar Reyadh Hamza, "The Effect of an AI-based Digital Learning Module on Motivation and Achievement in a Linguistic Training (Arabic Grammar) Course at Kuwait University," International Journal of Learning and Teaching, Vol. 12, No. 4, pp. 302-305, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).