Nurhayati et al. (2018) focused on big data technology for a comparative study of k-means and fuzzy c-means algorithms performance. Hadoop and Hive were chosen as the big data technology (Nurhayati et al., 2018). Zhou et al. (2019) discussed improving students’ research-based learning ability and establishing a new type of effective student-centered teaching model for college English education with the help of English classic reading. Sun et al. (2020) focused on verifying whether the integration of reading and writing is helpful to the improvement of college students’ ability through comparative experiment and a random sampling method, and they put forward an integrated learning mode of online reading and writing based on a data algorithm. Zhen (2021) studied English teaching ability evaluation based on the big data fuzzy K-means clustering algorithm and used the fuzzy membership method to describe the probability that the sample belongs to a certain class. To study the impact of big data on education activities and English teaching activities, Kong et al. (2021) proposed an improvement scheme of online teaching by personalized recommendation technology integrated with a big data cloud storage platform. Li (2021) designed a college English teaching ability evaluation system based on the establishment of the constraint parameter index analysis model, carried out the ability evaluation of the big data information model, and extracted the ability constraint function information. Zhang and Yuan (2021) introduced a BP neural network method and a hill climbing algorithm. Jiang (2022) analyzed, researched, and applied the diagnostic evaluation model using data gathered during system use.