The purpose of the study is to present a bibliometric analysis of the academic publication trends of student performance in education computing. These data were collected from the Scopus database that was published from 2012 to 2022. In the bibliometric analysis, important visual map and tables were produced to show publication trends from five different viewpoints including annual publications, countries, authors, publication sources, and keywords. The analysis results showed that the number of publications had increased rapidly by year during 2015 to 2019. The top countries include the United States, China, and India. Most of these publications were conference papers, and there are also article journals. The keyword co-occurrence analysis revealed that the research hotspots highlighted in this field were educational data mining, academic performance, classification and data mining mechanisms. Through this bibliometric research work, it can be expected that more researchers or scholars concentrating on utilizing two important algorithms; machine learning and deep learning, for analysing and forecasting student performance in higher educational computing institutions.