Exploring the Influence of Generative Artificial Intelligence on Students’ Independent Thinking and Knowledge Construction at University Level: A Case Study of Zimbabwe Open University.

Abstract

The rapid adoption of generative artificial intelligence (GenAI) is transforming teaching and learning into higher education, presenting both opportunities and challenges for students' independent thinking and knowledge construction. This study investigates the influence of GenAI on students' independent thinking and knowledge construction at the university level, using the Zimbabwe Open University (ZOU) as a case study. Guided by constructivist learning theory, the study employed a qualitative-dominant mixed-methods approach. Data was collected through semi-structured interviews, questionnaires, and document analysis of institutional policies and academic guidelines. The findings show that GenAI enhances learning by improving access to information, supporting conceptual understanding, facilitating idea generation, and increasing academic productivity. However, excessive reliance on AI-generated content may reduce students' critical engagement, originality, and capacity for independent knowledge construction. Participants also noted that the convenience of GenAI can encourage surface learning at the expense of analytical reasoning and reflective thinking. Furthermore, the study found that ZOU lacks comprehensive institutional policies and pedagogical frameworks to guide the ethical and effective integration of GenAI, resulting in inconsistent practices among lecturers and students. The study concludes that GenAI has a dual influence on higher education, serving as both a cognitive support tool and a potential barrier to independent thinking when used uncritically. The findings have important implications for higher education institutions by highlighting the need for AI governance frameworks, AI literacy, curriculum redesign, and assessment practices that foster critical thinking and authentic learning. The study recommends developing clear institutional policies, strengthening lecturer capacity, and adopting learner-centered pedagogies that promote the ethical, responsible, and reflective use of GenAI.