Assessment and ML-based Prediction for Research Ability of Postgraduates

DOI

10.2991/978-94-6463-276-7_44How to use a DOI?

Keywords

education; research ability; machine learning (ML); principal component analysis (PCA); multiple linear regression

Abstract

The assessment and prediction of research ability are very important in education. This paper 1) proposes an assessment scheme based on principal component analysis (PCA), which assigns a reasonable score for a postgraduate, and 2) proposes a prediction model based on multiple linear regression, which suggests the research ability of a postgraduate based on indirectly related information. Data from some postgraduates in University of Electronic Science and Technology of China (UESTC) are used to evaluate the performance. Experiments show the effectiveness and reliability of the proposed scheme and model.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Hongcheng Liu
AU  - Wen Hu
AU  - Dong Sun
PY  - 2023
DA  - 2023/10/27
TI  - Assessment and ML-based Prediction for Research Ability of Postgraduates
BT  - Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023)
PB  - Atlantis Press
SP  - 410
EP  - 419
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-276-7_44
DO  - 10.2991/978-94-6463-276-7_44
ID  - Liu2023
ER  -