Complementary AI in higher education: behavioral, cognitive, and ethical implications of ChatGPT and DeepSeek

The present mixed-methods study integrates a systematic review of 51 studies (2024-2025) with qualitative findings from eight participants, who were asked to complete a semi-structured questionnaire, to comprehend the complementary functions, pedagogical tasks, and ethical concerns associated with ChatGPT and DeepSeek in tertiary education. ChatGPT enhances creativity, language learning, and motivational participation, while DeepSeek excels in analytical accuracy and domain-specific performance, particularly in STEM and medical education. Evidence from both phases indicates that their integration underpins a twin-function pedagogy that couples generative fluency and systematic reasoning. Yet threats still exist, such as hallucination-induced errors, academic fraud, and a decline in critical thinking in the absence of metacognitive scaffolding and ethical regulation. Six thematic categories-personalized education, academic honesty, metacognition, model performance, adoption patterns, and domain-specific use-emerged in parallel with three cross-cutting patterns highlighting cognitive trade-offs, equity-related matters, and neurobehavioral dynamics. Together, these results suggest that interdisciplinary cooperation is crucial in developing AI-human co-regulation models, ethics-informed curricula, and deployment scenarios tailored to diverse environments. ChatGPT and DeepSeek are not rival technologies but complementary cognitive agents whose prudent integration can enhance creativity, accuracy, and ethical resilience in higher education.