The main benefit of using Cram in language teaching lies in its capacity to foster autonomous vocabulary learning through repeated exposure in a motivating, game-like format. By allowing students to access their study sets anytime, monitor their progress, and collaborate by sharing decks, the tool promotes self-regulated learning and responsible digital practices, in line with the digital engagement principles outlined in DigCompEdu (Redecker, 2017). Cram also supports multimodal learning by enabling the combination of images and words, which strengthens memory and comprehension, particularly at the remembering and understanding levels of Bloom’s Taxonomy (Bloom, 1956), and can extend to application when students use newly acquired vocabulary in meaningful contexts. From a technological integration perspective, Cram aligns with the SAMR model (Puentedura, 2006), functioning as substitution when digital flashcards replace paper ones and reaching modification when learners collaborate and interact online. Furthermore, its use reflects the TPACK framework (Mishra & Koehler, 2006), as it combines technological knowledge with pedagogical strategies and content knowledge to enhance vocabulary development, potentially supported by AI-based tools such as large language models (OpenAI, 2025) to generate contextualized examples and practice activities.