This study focused on the assessment of the use of computer vision in the teaching and learning of English language education. The use of computer vision in the teaching and learning of language education has become a novel approach that has attracted varying attentions in recent times. In this study, descriptive analysis was used to provide a coherent view of the use of computer vision in implementing knowledge-based systems for the teaching and learning of English Language Education. The language education tasks that were analysed comprised of image captioning, human-machine interaction, video captioning, visual attributes, visual retrieval and visual question answering. The study also looked at the approaches that could be used to incorporate computer vision and the teaching and learning of English language education courses, with particular reference to models as an integrated topic of distributional semantics. The researchers made an analysis of computer vision and English Language teaching and learning, using distributional semantics as both words and imagery. An integrated view of the subject matter was clearly presented and useful suggestions were made for promising future guidelines. The study also x-rayed the usefulness of computer vision for effective teaching and learning of language education and suggested novel approaches that could be used in incorporating computer vision in developing knowledge-based system for effective teaching and learning of the English language.