With the advent of the era of big data, a brand-new vision and broad thinking have been provided for the evaluation of college physical education teaching. This article mainly studies the analysis of college tennis teaching scientific research literature under the background of big data. In order to ensure the credibility of the survey content, the retest method was used to test the reliability of the questionnaire during the survey. Thirty students in the public sports tennis class were selected, and the same questionnaire was distributed and tested at intervals of 2 weeks. After the recovery, the correlation analysis with the previous questionnaire was carried out. This article uses SPSS17 statistical software to perform mathematical statistics on the experimental results. Among them, the independent sample T test is mainly used to carry out mathematical statistics on the cultural class scores and motor skills assessment after the experiment. The statistical results include the average score, standard deviation, variance between groups (F) and coefficient significance test (sig). The data input and statistics are strictly operated in accordance with the requirements of the SPSS software to ensure the accuracy and practicality of the results. The data shows that 22%, 84%, 88% and 88% of the students think that they are required, like, adapt to the social requirements and improve their tennis skills, while 17%, 86%, 88% and 75% of the students in the control class. The results show that it is feasible to apply big data to college tennis teaching evaluation.

Huifen Yang, Yu Wei. University Tennis Teaching and Scientific Research Documents under the Background of Big Data. International Journal of Educational Curriculum Management and Research (2021), Vol. 2, Issue 2: 1-7. https://doi.org/10.38007/IJECMR.2021.020201.

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