Abstract:

Students' academic performance has traditionally been linked to aspects centred on their personal abilities, such as cognitive skills, hours spent studying or personal motivation. However, in recent years, some research in the literature have begun to highlight the role that students' social interactions play in their performance (Johnson and Johnson 1993; Baldwin et al. 1997). These interactions create informal trust-based networks that facilitate knowledge exchange between students and enhance their learning (Gašević et al. 2013).

A number a of contributions have recently found a direct relationship between students' position in these knowledge networks and their academic performance (Cho et al. 2007; Smith and Peterson 2007; Hommes et al. 2012). On the other hand, this position has also been linked to opportunities to obtain new knowledge from external sources and to creative skills. (Tomás-Miquel et al., 2016). However, in this paper, far from this static vision, we delve deeper into the dynamic view of knowledge networks among students in order to understand the academic influence exerted in university environments by students on their peers. Specifically, this paper aims to answer the following research question: do the peers of higher-achieving students improve their performance over time?

To answer this question, this paper applies a stochastic actor-oriented model (SAOM) to a sample of 50 students of the Business Administration and Management bachelor’s degree at the Campus of Alcoy of the Universitat Politècnica de València in Spain.

The results obtained confirm the positive influence of higher-achieving students on their lower-graded peers. Thus, lower-achieving students perform better over time as they increase their academic relationships with higher-achieving students. These results highlight the importance for universities of attracting higher-ability students, as well as mixing students into heterogeneous work groups in terms of academic performance. This would make it easier to improve the performance of less proficient students, thus preventing them from dropping out of the university. Therefore, these findings may have relevant implications for both university policy and classroom learning management.

Keywords:

Academic performance, student relationships, student networks, classmate selection, University studies.