On the afternoon of December 8, the 19th of “International Distinguished Lecture Series” in 2020 was held by the School of Foreign Languages. Professor Gavin Brown was invited to give an online lecture entitled “Educational Data: Challenging Analysis” via VooV Meeting. Professor Brown is Associate Dean Postgraduate Research and the Director of the Quantitative Data Analysis and Research Unit in the Faculty of Education and Social Work. Nearly 200 teachers and students from the School of Foreign Languages attended the lecture.

Before the lecture, Prof. Yang Chaojun, Dean of the School of Foreign Languages, welcomed and thanked Prof. Brown for giving this upcoming online lecture to faculty members and students, and briefly introduced the educational experience, research fields and academic achievements of Prof. Brown. The lecture was hosted by Associate Professor Mei Bing of Henan University.

At the beginning of the lecture, Prof. Brown pointed out, based on the experience in quantitative data analysis and research, he believed that statistical data was difficult to understand. If we want to discover the truth in educational activities, we should make greater efforts in statistical data analysis. First we need to start with the linear model, and then conduct further research. Prof. Brown mentioned that not all theories were correct. The theory of the laboratory may not apply to daily life. When faced with educational data analysis problems, we can use relevant data to design experiments or conduct surveys. Then, he also used the Hawthorne effect, John Henry effect, Pygmalion effect and other examples to introduce the precautions and possible problems of experimental design. Finally, Prof. Brown concluded, the educational data was chaotic and complicated. We need to make careful judgments and designs, use advanced techniques to explain data problems, and we need to treating every decision as a problem.

After the lecture, Prof. Brownanswered the questions raised bythe participants, and shared data analysis applications, such as jamovi.org and jasp-stats.org. This lecture helped the participants deepen their understanding of educational data analysis.

Contribution: School of Foreign Languages