Understanding the Advisor-advisee Relationship via Scholarly Data Analysis

TL;DR

This study analyzes how advisors' academic experience and level influence advisees' performance in computer science, revealing patterns of growth, decline, and the impact of advisor expertise on advisee success.

Contribution

It uncovers the correlation between advisors' academic characteristics and advisees' performance, highlighting the influence of advisor experience and expertise.

Findings

Advisees' performance initially improves with advisors' academic age.

High-level advisors mentor more successful advisees.

High-level advisors elevate advisees' h-index rankings.

Abstract

Advisor-advisee relationship is important in academic networks due to its universality and necessity. Despite the increasing desire to analyze the career of newcomers, however, the outcomes of different collaboration patterns between advisors and advisees remain unknown. The purpose of this paper is to find out the correlation between advisors' academic characteristics and advisees' academic performance in Computer Science. Employing both quantitative and qualitative analysis, we find that with the increase of advisors' academic age, advisees' performance experiences an initial growth, follows a sustaining stage, and finally ends up with a declining trend. We also discover the phenomenon that accomplished advisors can bring up skilled advisees. We explore the conclusion from two aspects: (1) Advisees mentored by advisors with high academic level have better academic performance than the rest; (2) Advisors with high academic level can raise their advisees' h-index ranking. This work provides new insights on promoting our understanding of the relationship between advisors' academic characteristics and advisees' performance, as well as on advisor choosing.