Over recent decades, the importance of collaborative learning has increased alongside the growing need for student-centered learning environments [1]. Collaborative learning involves small group activities and often occurs in the form of problem-based learning or team-based learning in medical education contexts. In collaborative learning, students are mutually engaged in a coordinated effort to solve a problem together and to maximize both their own and each other’s learning [2]. Previous research has reported that collaborative learning has positive effects on students’ academic performance [2]. However, merely placing students in a group does not guarantee that such social forms of learning will prove beneficial. Successful collaborative learning is facilitated through the process of interacting with others [3]. Therefore, group level variables that lead to the most favorable learning outcomes, such as collective efficacy and co-regulation, need to be concerned to understand the nature and emergence of productive interactions in collaborative learning.

Collective efficacy refers to a perceived belief in the performance capability of a group as a whole [4]. This is in contrast to self-efficacy, which involves an individual belief about his or her capacity in performing a specific task individually [4]. Self-efficacy, one of the most powerful components of motivation, is generally accepted as a positive predictor of student performance in educational settings [4]. Likewise, the meta-analysis of Stajkovic et al. [5] in collaborative learning indicates a significant positive relationship between collective efficacy and group performance, particularly when group goal attainment requires a significant interdependent effort among group members, such as complex authentic problem solving.

Co-regulation refers to interactions between two or more peers that coordinate their self-regulated learning processes in collaborative learning [3]. Self-regulation refers to metacognitive, motivational, and behavioral processes which individuals use to direct and control their learning, and this has been shown to relate positively to students’ performance [6]. In group learning contexts, a similar result is expected regarding co-regulation, as successful collaborative learning is facilitated by a group’s coordinated and co-regulated engagement to build and maintain a shared understanding of a problem. Zheng and Huang [7] have shown empirically that the co-regulated strategy can predict group performance to a high degree. However, research exploring the impact of co-regulation on students’ performance is a recent development, meaning more empirical research is necessary in order to understand the role of co-regulation in student performance in collaborative learning contexts.

Self-efficacy belief affects students’ regulatory process [8]. Therefore, collective efficacy is expected to have an influence in co-regulatory processes. Knowledge of regulated strategies on its own cannot promote learning. Students should be first motivated to use regulated strategies. Thus, these variables may work together to influence students’ performance, but the mechanism through which collective efficiency and co-regulation may be related to each other in facilitating students’ performance has not been specified in existing research.

Self-efficacy and self-regulated learning are variables that have often been examined in the context of medical education [8-10], but their group level counterparts have almost not been applied to this context. Thus, this study investigated the role of collective efficacy and co-regulation in terms of students’ performance during small group projects in a medical research program. As motivation is a precursor for students to use regulatory strategies, it is predicted that the effect of collective efficacy on students’ performance will be mediated by co-regulation. Given the increasing popularity of group approaches to learning in medical education fields, the results of this study can provide significant insights for enhancing students’ performance in small group or collaborative learning contexts.

Because more and more collaborative learning now occurs in medical education, and even in clinical skill acquisition, in which collaborative learning is usually not very common [14,15], identifying how productive forms of collective thinking and co-construction of understating arise from small group activities is critical. However, very limited attention has been paid to this important issue. Thus, this study examined the role of collective efficacy and co-regulation in terms of student performance in the context of a medical research program where students worked collaboratively in small groups. The results indicated that collective efficacy and co-regulation explained 26.61% of the variance in student performance, and, as seen in Fig. 1, the effect of collective efficacy on students’ performance is mediated by co-regulation.

Collective efficacy only indirectly affected student performance. Thus, collective efficacy can be said to influence student performance through co-regulation in group learning contexts. These results are consistent with previous studies showing that motivation is a prerequisite of using regulated strategies and has a positive impact on student performance [4,5,11].

Successful collaborative learning is inherently associated with a group’s co-regulated capabilities in group activities, but empirical research showing the relation between co-regulation and student performance is rare. This study adds empirical evidence regarding the positive impact of co-regulation on student performance in collaborative learning. This result is in line with that of a study by Volet et al. [3], who demonstrated that effective co-regulated strategies help learners to build productive and meaningful knowledge.

This study showed the positive relationship between collective efficacy and co-regulation in medical education contexts. Demirören et al. [8] demonstrated a positive relationship between self-efficacy and self-regulated learning skills in the context of problem-based learning in medical education. Although their research did not directly indicate a correlation between the group level variables, in the sense that both studies empirically show a correlation between motivation and regulatory processes, they show similar results.

The results of this study have several important implications. This study shows the mechanism through which collective efficiency and co-regulation are related to each other in facilitating students’ performance. Explicit instructional intervention for co-regulated strategies, such as instructing or demonstrating how to set learning goals, monitor, or evaluate their work while working in groups, may produce promising results in terms of student performance in much the same way explicit self-regulation intervention programs did [6]. In addition, collective efficacy is also an important target of effective collaborative learning. Collective efficacy is built on previous experience of collaborative learning, so successful group learning experience plays an important role in constructing collective efficacy [4]. For this, the instructors need to first ensure that learners are aware of the importance of productive interactions before they are involved in collaborative learning. In addition, it is also critical that they monitor group activity and provide feedback timely in order to promote successful collaborative learning [1]. Lastly, the research indicated that when students set clear, specific, and reasonable goals, they are more motivated to perform. By contrast, goals that are too difficult or broad lead to frustration, resulting in a degradation of their efficacy [9,16]. Thus, helping students set clear, specific, and reasonable goals, or, if necessary, intermediate goals (for example, writing a research question or finding related papers) should be promoted as an alternative to setting only one final goal (conducting research) in order to ensure effective collaborative learning experiences.

There are some limits to this study. Causal inference requires control of the temporal ordering of events, but, in this study, the two variables were measured at the same time although this seems to be a widespread issue regarding this type of research. In addition, this study was conducted with relatively a small number of subjects from only one medical school. It would be useful, therefore, to perform future studies using a longitudinal design with a larger number of subjects from a more diverse range of backgrounds.