Students' perceptions of the use of artificial intelligence in language learning in Ghanaian higher education

Purpose This study investigates the role of artificial intelligence (AI) in language learning among Ghanaian tertiary students. It focuses on students' perspectives on the effectiveness of AI tools in enhancing language skills, patterns of use, the specific languages for which AI is employed, and the stages in their academic journey when they adopted these technologies. The study aims to provide insights into how Ghanaian students integrate AI into their multilingual learning experiences, both within and beyond the classroom. Design/methodology/approach The study adopted a quantitative design, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) and Constructivist Learning Theory. It was designed as a descriptive survey rather than a model-testing study. The use of UTAUT was purely to frame the discussion, not to operationalise constructs for hypothesis testing. The Constructivist perspective emphasised students' active engagement with AI to construct knowledge. Data were collected through structured questionnaires from 713 students from four selected Ghanaian tertiary institutions. Findings Ghanaian tertiary students view AI as a valuable tool for language learning, with most adopting it between 2020 and 2024. English and French are the most commonly learned languages, though some use AI for additional languages. AI is primarily used for assignments, research, and language learning, with moderate use in business and health. It was found that students see AI as a versatile tool that supports both academic and personal development. Research limitations/implications The study is limited by its use of self-reported data from a specific student population, which may not reflect broader experiences. It does not address ethical concerns, digital access issues, or varying digital skills. Additionally, it lacks analysis of AI's impact on specific language skills. Future research should use mixed or longitudinal methods to explore these areas more deeply and build on these findings by employing inferential or model-testing approaches to validate constructs and examine predictors of AI adoption in language learning. Originality/value This study is among the first of its kind to provide insight into AI's use in language learning in higher education in Ghana by offering practical perspectives into optimising AI integration in academic programmes. It highlights the need for educational institutions to incorporate AI-driven resources to enhance students' language learning skills and strategies.