Enhancing oral English learning through AI: a case study on the impact of AI-driven speaking applications among Chinese university students

AI has already changed education by making personalized practice platforms standard in many classrooms, reducing teacher time spent on differentiation and rubric creation, enabling 24/7 student support through AI chatbots, expanding access to tutoring for students who lack resources for private instruction, and reshaping academic integrity policies globally.

Documented negative impacts include increased academic dishonesty through AI-generated submissions, student over-reliance on AI that may weaken writing and critical thinking skills, privacy risks from student data processed by third-party AI vendors, equity gaps when premium AI tools are unavailable in under-resourced schools, and teacher uncertainty causing inconsistent implementation.

Research shows AI tutoring and adaptive learning platforms produce modest but consistent improvements in learning outcomes when used regularly. Carnegie Learning MATHia and Khan Academy have peer-reviewed evidence of effectiveness. The magnitude of gains depends heavily on implementation quality, teacher support, and whether students engage with AI guidance or bypass it.

AI can reduce the equity gap by providing every student access to personalized tutoring regardless of family income, but can also widen it if premium tools are unavailable in under-resourced schools, if AI systems embed biases that disadvantage certain student populations, or if reliable internet access required for AI tools remains unequally distributed.