assig 3

Taking a Free Ride: How Team Learning Affects Social Loafing

Catherine Gabelica1, Sven De Maeyer2, and Michaéla C. Schippers3 1 Department of People, Organizations and Negotiation, IESEG School of Management

2 Department of Training and Education Sciences, University of Antwerp 3 Department of Technology and Operations Management, Rotterdam School of Management (RSM), Erasmus University Rotterdam

Although collaboration is increasingly required in today’s academic and work contexts, there are many ways in which teamwork can be impaired by dysfunctional inefficiencies and process loss. An important form of process loss is the tendency for individual members of a team to exert less effort than their fel- low team members (i.e., social loafing). Since teams need to sustain the effort of team members as a col- laborative resource, it is imperative to understand factors that shape social loafing in team tasks. This study examines simultaneously the degree to which goal orientation and changes in team learning (i.e., shifts in collective knowledge) affect social loafing. The authors use a multiwave design to explain changes in social loafing tendencies of 675 students working in teams. They conduct linear mixed effects modeling to show that individual team members who belong to teams that score higher than other teams on team learning throughout 9 weeks of teamwork experience a decrease in social loafing. Although learning and performance orientations are significantly related to initial self- or peer-rated social loafing, they cannot explain ensuing changes in social loafing. Results highlight the importance of considering team-level dynamic properties when explaining fluctuations of motivation in teams.

Educational Impact and Implications Statement Even though small group work has gradually progressed to being one of the dominant approaches in the domain of learning and instruction and professional development, research shows that large numbers of team members exhibit unco-operative behaviors such as social loafing (i.e., individuals’ tendency to expend less effort than their fellow team members). The results of a nine-week longitu- dinal study with 675 students working in teams reveal that teams experiencing a steeper shift in team’s collective knowledge (i.e., team learning) than other teams show a decrease in social loafing tendencies over time. Additionally, they show that the learning and performance orientations of individual members predict social loafing at the start of the collaboration. These findings help us better understand how dynamic team-level properties can prevent individual members from engag- ing in dysfunctional behaviors.

Keywords: teams, co-operative learning, collaboration, social loafing, team learning

In the past few decades, classroom instructors and professional practitioners increasingly have used teams to improve learning and achievement (Johnson & Johnson, 2015; Salas et al., 2007). Both team and collaborative learning research are rooted in the principle that to be effective, teams must collaborate to overcome barriers to their interpersonal processes (Mathieu et al., 2019). That is, team success depends on team members’ contributions to team out- comes, such that low contributions to teamwork and motivational losses are associated with low achievement (Kirschner, 2009).

Although many studies have investigated the factors that explain how and why some teams outperform other teams (e.g., Kozlowski & Ilgen, 2006), only a relatively smaller body of literature consid- ers and explains social motivation losses, such as “social loafing” (Kozlowski & Bell, 2013). Social loafing, which occurs when peo- ple expend less effort than their fellow team members in team con- texts (Karau & Williams, 1993), is common in classroom settings. Most college graduates likely can recall instances in which they worked collectively on projects that were graded on a team basis, yet some team members “slacked off” and failed to put an equal share of effort into achieving the team outcomes.

Social loafing theory (also known as collective effort theory) (Karau & Williams, 1993) proposes explanations for why loafing occurs, most of which cite structural reasons for withheld inputs or team set-up factors, such as group size. While situational and dis- positional variables can both drive social motivation (Toma & Butera, 2015), relatively few social loafing models incorporate team members’ individual differences, which may account for the fact that the research evidence to date is limited and mixed (Karau

This article was published Online First October 25, 2021. Catherine Gabelica https://orcid.org/0000-0003-0096-6940 Sven De Maeyer https://orcid.org/0000-0003-2888-1631 Michaéla C. Schippers https://orcid.org/0000-0002-0795-5454 Correspondence concerning this article should be addressed to Catherine

Gabelica, Department of People, Organizations and Negotiation, IESEG School of Management, Rue de la Digue 3, 59000 Lille, France. Email: [email protected]

716

Journal of Educational Psychology

© 2021 American Psychological Association 2022, Vol. 114, No. 4, 716–733 ISSN: 0022-0663 https://doi.org/10.1037/edu0000713

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

& Wilhau, 2020). Differences in goal orientations (learning vs. performance) are expected to drive social motivation as they can influence the extent to which individual members generally value certain tasks (Karau & Wilhau, 2020). When team members hold certain goal orientations (i.e., situated orientations for action in an achievement task, Dweck, 1986), they are expected to display and sustain low social loafing when they collaborate, specifically when they attach value to task mastery, understanding, and growth (i.e., learning orientation). Individual members who focus on demon- strating ability (i.e., performance orientation) might start their col- laborative task with low social loafing because they seek to gain favorable judgments from others. However, performance orienta- tion might relate to increased social loafing over time, due to the reception of team feedback and therefore, lower individual identi- fiability (Karau & Wilhau, 2020). Research in this area is even scarcer at the team level of analy-

sis. In a team, communication is directed toward a twofold pur- pose: (a) to develop the interpersonal relations within the team, and (b) to build a collective knowledge pool. However, most stud- ies focus on the socioemotional side of teamwork (e.g., creation and maintenance of cohesiveness and a sense of community; Kreijns et al., 2003), while there is a larger gap in our understand- ing of the influence of important sociocognitive mechanisms, such as team learning, on social loafing. As teamwork enables individu- als to merge their individual knowledge and skills to reach a com- mon goal, it is characterized by the phenomenon of team learning. Through team learning, defined as “a change in the team’s collec- tive level of knowledge and skill produced by the shared experi- ence of the team members” (Ellis et al., 2003, p. 822), individual members’ knowledge is transformed and integrated into a collec- tive knowledge pool (Van den Bossche et al., 2011). Thereby, by progressively acquiring more complex knowledge and skills, teams can overcome motivational barriers such as social loafing (Raes et al., 2015; van Dick et al., 2009). In this sense, team learn- ing and team motivation are closely related (Bell et al., 2012). Importantly, social loafing develops over time during collabora-

tion. As such, time is a key factor. As team members socially interact and initiate momentum on team tasks, they increase their collective knowledge pool, which is expected to decrease social loafing over time because of the whole team being involved in maintaining a shared conception of problems they encounter. However, the time factor is underresearched (Fransen et al., 2013; Hofmann & Jones, 2005). Although many researchers have stud- ied how groups develop into functional teams in organizational settings (Kozlowski & Bell, 2013), data about why teams develop differently and how different aspects of interaction are related are limited (Fransen et al., 2013). Research studying teams in educa- tional settings proposes that high-learning teams likely follow a linear progressive development (Fransen et al., 2013; Johnson et al., 2002) because of their specific features (e.g., restricted dura- tion of teamwork, valence of deadlines and grades, low expertise at the start of a collaboration). Accordingly, we expect student teams to follow a linear progression, on average. However, build- ing upon group socialization theory supporting that the relation- ship between a team and its members also changes over time, we propose that time spent in teams is not sufficient to explain increases or decreases in social loafing. Teams also need to learn

(Bell et al., 2012). Consequently, we expect high-learning teams to experience downward shifts in individual social loafing.

We first extend social loafing research by testing the impact of the emergence of, and change in, team learning on social loafing trajectories. We then connect these variables to person-related fac- tors (i.e., goal orientations), moving back to the more proximal in- dependent variables of our model. That is, we propose it is change in learning during the collaborative process, rather than team learning measured at a static point in time, and initial levels of individual differences, that decrease social loafing over time. This study makes several contributions to team motivation and team learning literature by (1) investigating interdependent contexts of naturally occurring teams; (2) using a multilevel, interactive framework to analyze social loafing tendencies in teams that incor- porates important but under-researched individual and team-level factors; and (3) adopting a multiwave, multisource design to check for patterns in how social loafing evolves over time and account for differing perspectives on individual behavior in teams.

Literature Review and Hypotheses

Concept of Social Loafing

A team is a collection of individuals who work interdependently to achieve a common goal and share responsibility for team out- comes (Cohen & Bailey, 1997; Michaelsen et al., 2004). Individu- als, in co-operative as opposed to competitive and individualistic situations, tend to engage in more on-task behaviors and less off- task, disruptive behaviors (Johnson & Johnson, 2015). However, placing individuals in teams and having them work together does not necessarily lead to co-operative efforts. Teamwork can also generate dysfunctional inefficiencies such as “social loafing.” According to the collective effort model (CEM), social loafing refers to individuals’ behavioral tendencies to put forth less effort than their teammates (Karau & Williams, 1993). It is believed to occur in teams as a result of the presence of others as coactors who combine their efforts on a collective task (Karau & Wilhau, 2020).

Social psychologists and organizational behavior researchers conceptualize social loafing as an individual motivational con- struct that operates in team contexts (Karau & Wilhau, 2020). They categorize team motivation losses due to social loafing into “interpersonal processes” in most team interaction classification systems (Kozlowski & Bell, 2013; Mathieu et al., 2008). Interest- ingly, in the literature on student engagement in educational psy- chology, the notion of effort is included in definitions of both cognitive and behavioral engagement (Fredricks et al., 2004). In the definition of social loafing mentioned above, the notion of effort is primarily behavioral, a matter of doing the work (or a fair share of the work), and less of learning and mastering the task. We could hence stipulate that social loafing is closer to the concept of behavioral (dis)engagement (i.e., individuals’ active participation, involvement and persistence in a learning activity) but applied to team settings and with a strong notion of relative efforts (relative to fellow team members) that is not specifically mentioned in the engagement literature (Fredricks et al., 2004; Skinner et al., 2009).

Compared with the volume of research on individual motivation, relatively little work has directly addressed social motivation and social loafing in teams (Kozlowski & Bell, 2013). Prior research

TAKING A FREE RIDE 717

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

showed that social loafing leads to several negative team processes and outcomes. It evokes distrust, lowered morale, and low team cohesion and performance (Duffy & Shaw, 2000; Jassawalla et al., 2008). Of moderate magnitude, it appears to be generalizable across tasks and subject populations (Karau & Williams, 1997). Because teams that display detrimental processes are likely to

sustain such negative interaction patterns over time (Webb & Cull- ian, 1983), literature on teams has implicitly regarded social loafing as a static rather than temporal variable (Aggarwal & O’Brien, 2008; Hofmann & Jones, 2005). However, we propose that social loafing may be more dynamic than previously conceptualized. In this article, we posit that social loafing is not a single, discrete act; rather, individual team members may be inclined to contribute their fair shares at different times or according to different tasks. Hence, we view social loafing as a time-varying phenomenon that follows different trajectories over time. Whereas the focus of prior work has been on identifying the causes of social loafing at one point in time, we oppose the idea of social loafing as a static phenomenon and examine whether and how social loafing changes over time.

Operationalization of Social Loafing

To date, researchers have tended to capture the social loafing tendencies of individual team members from a single-source per- spective. Most previous studies on social loafing use self-ratings of loafing; only a few studies have used peer ratings (e.g., Price et al., 2006), and only one study, to our knowledge, has used both peer and self-ratings (Stark et al., 2007). Karau and Williams (1993) and Jassawalla et al. (2008) suggest

social loafing occurs without self-awareness and that loafers gen- erally find it socially undesirable to admit they loafed on complet- ing collective tasks; the authors’ argument draws on sources other than team members themselves, that is, their teammates. Arguably, according to human behavior concepts and theories (e.g., attribu- tion theory, decision making, performance appraisal; Ilgen et al., 1994), attitudes and behaviors depend largely on perceptions. We can argue that social loafing starts to exert influence in a team when other members perceive that some member who relies too much on his or her teammates to accomplish his or her portion of the work takes advantage of them while “unfairly” enjoying and/ or sharing the team outcome equally well with less work (Jassa- walla et al., 2008; Schippers, 2014). This proposal is often used as a main argument for measuring “perceived social loafing of others” (i.e., an individual’s assessment of the others’ relative con- tribution to the team; Piezon & Ferree, 2008; Zhu et al., 2019). At the same time, some researchers (e.g., Cheng & Warren,

1999) question the reliability of peer evaluations, suggesting peer ratings may suffer from a halo effect (Loughry et al., 2007), leni- ency effect, or lack of skill in differentiating teammates. For exam- ple, Davison et al. (2014) find that only high performers are able to deliver evaluations of teammates that differentiate between those who perform well and those who perform poorly. Peer rat- ings also may be biased by friendships or personal dislikes (Bar- clay & Harland, 1995). These limitations could lead to the use of self-ratings of social loafing. For example, Price and colleagues (2006) found in their study using both peer and self-ratings that individuals were more inclined to highlight their own loafing than the loafing of others. Another argument in favor of self-assessment purports that questioning one’s own relative contribution to the

team can lead to disclosure of one’s beliefs about him or herself as a team member (McCardle & Hadwin, 2015) and self-awareness of one’s antisocial behavior (Simms & Nichols, 2014). Finally, Conway and Lance (2010) claim that there are two major miscon- ceptions about self versus other-ratings. The first misconception is that other-report is superior to self-report measures. The second is that relationships between self-reported constructs are always upwardly biased. They contend that “rather than providing a more accurate estimate of true relationships among constructs, relation- ships estimated using different methods tend to be more attenuated and less accurate as compared to same-method correlations” (Con- way & Lance, 2010, p. 327). In sum, thus far, prior outcomes are mixed with regard to which source best assesses social loafing.

Social Loafing and Contextual Factors

Researchers offer multiple explanations for why social loafing takes place, with early work indicating that characteristics of the sit- uation and individual members’ situational interpretations often drive social loafing (Williams et al., 1981). Specifically, the social loafing literature proposes that people engage in social loafing mostly because of a decreased perceived accountability and increased dispensability of effort experienced by team members (Harkins, 1987; Price et al., 2006). Similarly, co-operative learning research also demonstrates that positive goal interdependence and individual responsibility and accountability are likely to reduce social loafing (Buchs et al., 2015; Johnson & Johnson, 2009).

The robust presence of social loafing in teams has led research- ers to identify not only its antecedents but also variables that might moderate the tendency to engage in social loafing (Kozlowski & Bell, 2013). Most authors note the influence of set-ups or work designs to minimize social loafing (Erez & Somech, 1996; Koz- lowski & Bell, 2013; Stark et al., 2007). For example, social loaf- ing can be reduced by improving task management and reward structures (George, 1992; Pearsall et al., 2010). Other strategies that reduce individual tendencies to loaf include increasing team familiarity and identifiability of individual members and decreas- ing ‘team size’ (Erez & Somech, 1996; Lam, 2015). However, we propose that work-design factors are not sufficient to explain social loafing tendencies, because they also reside in individual team members. Accordingly, individual-level factors may explain individual differences in social loafing.

Social Loafing and Individual Differences

Individual differences have received less attention in social loaf- ing research (Stark et al., 2007). As early as 1995; Comer began to integrate team members’ attitudes and individual differences into social loafing frameworks (Comer, 1995), but empirical evidence and understanding of these factors remain relatively limited and are mostly derived from laboratory settings (Karau & Wilhau, 2020). There is increasing evidence that individual differences can explain the extent to which team members loaf (Bolin & Neuman, 2006; Morgeson et al., 2005); for example, those who believe they are better than others (Huguet et al., 1999) are more likely to loaf, whereas those with high levels of winning orientations and prefer- ences for group work (Stark et al., 2007) and conscientious, agree- able team members (Schippers, 2014; Tan & Tan, 2008) are less likely to loaf.

718 GABELICA, DE MAEYER, AND SCHIPPERS

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

This angle of individual differences points to a need for addi- tional hypotheses that include person-based factors that can pre- vent or lower the occurrence and magnitude of social loafing throughout team collaborations. A person-related motivational factor that appears to have

received little research attention in the social loafing literature is goal orientations, including learning orientation and performance orientation (cf. Gagné & Zuckerman, 1999).

Learning Orientation and Performance Orientation

Work on goal orientations in team contexts is rooted in research arguing that how people change a given situation into an effective situation depends on their social motivation (Forgas et al., 2005; Schippers, & Scheepers, 2020). Social motivation theories are concerned with goal-directed behaviors that are aimed at, or cen- tral to, social interaction (Carver & Scheier, 1998; De Dreu et al., 2008). An assumption of social motivation is that one’s tendency to collaborate and interact with others is largely driven by individ- ual differences, in particular achievement goals (De Dreu et al., 2008). In accordance with this premise, we can hypothesize that goal orientations have important consequences for interpersonal interactions and for behavior change, more specifically change in social loafing. Since the purpose of the present article is to investi- gate antecedents of social loafing viewed as a dynamic behavior that emerges in social contexts, we expect members to bring their behavior in line with their initial goals. Much research on motivation in individual settings has examined

the basic concept of “goal” that accounts for how people intend to behave (Locke et al., 1981). Goal-related motivation theories and research have given rise to Achievement Goal Theory (AGT) that focuses on the psychological features of goals and individuals’ intention beyond a goal (i.e., goal orientation, Pintrich, 2000). Sev- eral goal structure models have emerged to explain the reasons for achievement behaviors (Kaplan & Maehr, 2007). In early work, goal structure is conceptualized as two-dimensional (Elliot, 2005). Specifically, these models stipulate that people’s goals focus on increasing competencies via learning (i.e., learning or mastery goals) versus obtaining affirmative judgments about their competencies (i.e., performance goals; Dweck, 1986, 1999). Despite the varying terminologies, mastery versus performance goal orientations are closely related to learning versus performance orientations. Later research on achievement goal orientations proposes to con-

sider whether achievement goal orientations lead individuals to approach or avoid a task (e.g., Elliot & Church, 1997). In the trichoto- mous achievement goal framework, the performance goal orientation construct is divided into a performance-approach goal orientation and a performance-avoidance goal orientation. Individuals who are per- formance-avoidance oriented are concerned with avoiding demon- strating low ability, mostly in comparative terms (Urdan & Kaplan, 2020). Following this logic, Elliot and McGregor (2001) later pro- pose a 2 3 2 model that adds a fourth goal orientation, a mastery- avoidance orientation, whereby a learner’s goal is to avoid misun- derstandings and mistakes. It implies a fear of failure that is rooted in an intrapersonal rather than an interpersonal perspective. Mastery or learning orientations generally relate to interest, per-

sistence, positive emotions, use of deep learning approaches, and, under certain conditions, to achievement. In contrast, perform- ance-avoidance goals relate to negative emotions, disengagement

in the face of obstacles, and low achievement. Performance- approach goals are associated with higher achievement, and under different circumstances, with more and less adaptive and maladap- tive emotions and learning strategies (Payne et al., 2007; Rolland, 2012; Ramos et al., 2021; Urdan & Kaplan, 2020). Mastery-avoid- ance goals have received less scrutiny than the other goals. Although patterns of relations between mastery-avoidance goals and outcomes are inconsistent, they are generally associated with maladaptive outcomes (Madjar et al., 2011).

There is a growing number of studies incorporating AGT in team and collaborative learning research (Poortvliet et al., 2009). However, to understand how those operate in the context of team- work, further empirical studies are needed (Lim & Lim, 2020). In collaborative learning research, studies consistently show that mastery orientation has positive effects on individual-level cogni- tive and affective outcomes such as cognitive processing (e.g., Pat- rick et al., 2008) and a handful of studies similarly demonstrate positive effects on team behaviors such as other-regulation (Grei- sel et al., 2018; Lee et al., 2010; Lim & Lim, 2020; Volet & Mans- field, 2006) or feedback-seeking (Payne et al., 2007). By contrast, inconsistent relationships have been found between performance orientation and other-regulation. For example, some studies show that performance orientation has negative (Lee et al., 2010), posi- tive (Greisel et al., 2018), and no significant relationships (Lim & Lim, 2020) with other-regulation, and feedback-seeking (Cellar et al., 2010; Payne et al., 2007). Further, in situations of team prob- lem solving, Poortvliet and colleagues (Poortvliet et al., 2007; Poortvliet et al., 2012) show that performance orientation is related to information retention and even thwarting behavior. Most studies find no significant effects of the performance-avoidance goal ori- entation on team constructs. Payne et al. (2007) find a negative correlation with feedback-seeking in nonteam settings, whereas Cellar et al. (2010) conclude that there is no significant relation between the two constructs.

In the present study, we decided to focus exclusively on the approach variants of the achievement goals because these are pre- dictive of process variables in the collaborative learning literature, while the avoidance goals have been less studied and seem to nei- ther hinder nor promote collaboration (Lim & Lim, 2020). For the sake of parsimony, we include learning and performance orienta- tions in our multivariate approach, as the goal of our study is to investigate whether the significant relationships found in this liter- ature reproduce at the team level.

As stated, studies to date suggest that team members scoring high on learning orientation tend to engage more in adaptive col- laborative learning than members scoring low on this orientation. However, the results on the effects of performance orientations in collaborative contexts are mixed. Further, what is not yet clear in this strand of research is how different goal orientations induce differences in social loafing trajectories (Skinner et al., 2009).

Because they attach great value to hard work for its own sake, achievement or personal growth, team members who are learning oriented are also more likely to place value in specific collabora- tive tasks, and hence, are less likely to loaf. This task value propo- sition is consistent with the Collective Effort model that suggests that individuals who view tasks as meaningful, important, or intrinsically interesting are less likely to engage in social loafing (Karau & Wilhau, 2020). Furthermore, individuals scoring high on learning orientation seek more help from, and exchange more

TAKING A FREE RIDE 719

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

information with, their peers (Newman & Schwager, 1995). Engaging in such help-seeking and information-sharing behaviors implies that this team member lacks a particular skill that others might have (Veenman et al., 2005). Thus, a learning orientation likely encourages collaboration and discourages social loafing (Poortvliet et al., 2009), such that it should associate positively with a willingness to participate in a team activity, regardless of effort identifiability. We propose that those with a high learning orientation are less likely to loaf at the start and over the course of collaborations.

H1: Team members with a higher learning orientation are less suscep- tible to display social loafing throughout the collaboration.

Similarly, when the pursuit of performance goals is driven by need for achievement, these goals might stimulate high relative contribution in a team (Lim & Lim, 2020). Specifically, since team members who endorse performance goals tend to strive to demonstrate their competence to others, performance orientation could be an effective motive in the short term, and hence, at the start of a team project. However, this effect might change in the long term (Brophy, 2005). In teams that have co-operative reward structures (e.g., team scores), members with high levels of per- formance orientation may not be able to use interpersonal stand- ards, such as performance relative to their peers, to assess competence in achievement situations (Elliot & McGregor, 2001; Pintrich, 2000). Also, in teams, their individual efforts may not be identifia- ble, and feedback is generally provided at the team level. Since reward and recognition are important for such people (Reeve, 2015), they might consequently develop a lowered sense of accountability and thus greater tendencies to loaf over time. Addi- tionally, if individuals compete with their teammates to establish their abilities, they are less likely to collaborate, which may gener- ate less harmonious social relations or augment disruptive behav- ior (Butler, 1995; Midgley et al., 2001). Accordingly, it is likely that a performance orientation does not encourage teamwork in the long term but does elicit the growth of antisocial tendencies such as social loafing (Poortvliet et al., 2009).

H2: Team members with a higher performance orientation are (a) less susceptible to display social loafing at the start of a team collaboration, (b) more susceptible to display social loafing over time.

Social Loafing and Team-Level Factors

Traditionally, psychological theories have mostly focused on indi- vidual variables (e.g., personality traits, attitudes, values) in their attempts to explain individual behavior, the underlying assumption being that the causes of an individual’s behavior are inside the indi- vidual. Social interdependence theory, on the other hand, postulates that individual behavior can be explained by the interactions among individuals that are inherently dynamic (Johnson & Johnson, 2015). As such, this theory recognizes the critical role played by team fac- tors in the completion of a team task for individual members. There is a growing body of literature that recognizes the importance of team-level factors during collaboration (Johnson & Johnson, 2009). Despite this growing interest, in contrast to research on individual- level antecedents of social loafing, there is much less information

about team-level factors that enable team members to resist social loafing or decrease its intensity over time.

The collaborative learning literature supports that team commu- nication can serve two complementary purposes,(a) building a pos- itive and cohesive socioemotional climate (Bakhtiar et al., 2017; Isohätälä et al., 2020) and (b) facilitating team cognitive processes (Järvelä et al., 2016; Rogat & Linnenbrink García, 2011).

A few studies on social loafing focus on the socioemotional aspects of teams, and they typically rely on laboratory work to reveal, for example, that group cohesiveness reduces or eliminates social loafing (e.g., Duffy & Shaw, 2000; Lam, 2015). This result was replicated in field studies that affirm that social loafing in teams relates to low team cohesiveness (Høigaard et al., 2006; Liden et al., 2004). This finding usually is explained by high levels of member identification with teams and concerns about team welfare.

However, much less is known about the sociocognitive factors that could substantially lower or even eliminate social loafing (Erez & Somech, 1996; Lam, 2015). Whereas empirical work on social loafing implies that team members simply add their individ- ual inputs to produce team outcomes, teams are social systems that evolve and create multiple solutions that stem from ongoing knowledge sharing (Jassawalla et al., 2008). Despite this observa- tion, there is a paucity of evidence on the extent to which team- level differences in team learning during collaborative learning, can explain differences in individual loafing behavior. The present study aims to address this gap.

Social Loafing and Team Learning

In response to the lack of research on team sociocognitive fac- tors, we propose that individual team members reduce their loafing tendencies when their teams increase their collective learning. According to Wilson et al. (2007), team-level learning represents a change in a team’s collective level of knowledge and skills. We conceptualize team learning as an output of shared experience of the team members, and more specifically, as a newly shared under- standing of how the team should function and develop new knowl- edge and skills about the team tasks (Ellis et al., 2003; Van den Bossche et al., 2011).

We hence view team learning from a social constructivist per- spective, according to which people create knowledge during social interactions (Boud et al., 2001; Oliveira & Sadler, 2008). Team learning is frequently compared with collaborative and co-operative learning, though the concepts are not mutually exclu- sive. In this article, team learning is not conceived as a structured peer learning method but shares some conceptual similarities with the two other constructs. As variations of “peer learning”, they all incorporate features such as shared experiences and responsibil- ities, positive interdependence, individual accountability, and pro- motive interaction (Johnson & Johnson, 1999; Slavin, 2011). However, team learning, typically studied in work settings, also encompasses (a) the production of team-level outcomes, such as collective knowledge (i.e., knowledge held by the team as its own united entity) and team performance, (b) the main goal of success- fully completing a given task, and (c) mutual accountability for these outcomes (Dochy et al., 2014). While research on co-operative and collaborative learning has recently shifted its attention to the group as the unit of analysis, it has traditionally focused on outputs at

720 GABELICA, DE MAEYER, AND SCHIPPERS

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

the individual level (e.g., what do students learn?) (Fransen et al., 2013; Vangrieken et al., 2016; Weinberger et al., 2007). As such, both research lines complement each other when building an understanding of the extent to which team members converge toward increased collective knowledge.

Dynamics of Social Loafing and Team Learning

Teams are not static entities, but instead change in dynamic ways over time. To clarify the determinants of social loafing, it is there- fore necessary to consider temporal aspects of teams, which include team development (i.e., changes in the team as a whole) and team socialization (i.e., changes in the relationship between the team and its members; Arrow et al., 2000; Levine & Moreland, 1994). Group socialization theory stipulates that both the team and its

members are “potential influence agents” (Levine & Moreland, 1994, p. 306). This perspective purports that people change as a function of the team that they join. Traditionally, small group research focuses on the team perspective and overlooks how rela- tions between a team and its members develop over time (Mathieu et al., 2019). This theory recognizes that individual members’ con- tribution levels change over time and that it can, in turn, change the relationship between the team and its members. As such, the effects of the team on an individual’s behavior can depend on team socialization, reflecting changes over time. If changes in con- tribution occur, this can result in divergence and the potential exclusion of the individual from the team. However, the team can also resocialize the individual (Levine et al., 2001). In line with this theory, we posit that when contribution levels become increas- ingly unequal, it creates a tension that can be repaired through knowledge creation. The team can hence change the individual so he or she can exert more effort toward the team goals. We hence propose that the development of new knowledge and skills has the potential to raise the satisfaction of the loafers’ needs. Furthermore, there is a consensus across disciplines that teams as

a whole develop or change over time (Fransen et al., 2013; Hommes et al., 2014; Kozlowski & Bell, 2013). Since team learn- ing requires interactions between individuals, inherently, it is emer- gent and dynamic and involves developmental progression (Kozlowski & Bell, 2013). It supposes a shift in knowledge state— a knowledge trajectory over time. As teams develop and evolve from groups of individual members to become collectivities with well-mapped repertoires of adaptive skills, the learning that emerges is not only inextricably connected to the fundamentals of social motivation but also changes over time (Goodman & Dabbish, 2011; Wiese & Burke, 2019). Recently, more promising research efforts adopt a regulatory

approach to team learning. In this view, team learning takes a reg- ulatory role. Team members respond to goal progress, adjust their efforts and strategies and create newly shared understandings. In turn, this role should benefit motivational processes (Bell et al., 2012; Chen et al., 2009). However, the regulatory perspective on team learning requires further consideration, especially with regard to its relationship to motivation in team contexts. Using this theoretical model, we posit that dynamics inherent to team learn- ing shape motivational states that emerge over time. By increasing team learning, teams can increase their effort and attention to team goal accomplishment and strategies and thereby reduce process losses in the form of social loafing. A steeper change in collective

knowledge is expected to lower social loafing because it would ne- cessitate that the whole team devotes attention to integrating indi- vidually held information into the team’s collective knowledge state and maintaining a shared conception of a problem.

To join emerging efforts to explore the dynamic relationships between team learning and social loafing, both conceptually and empirically, we formulate and test the following hypothesis:

H3: An increase in team learning leads to a decrease in social loafing, even when controlling for individual goal orientations.

In summary, though prior work on social loafing offers important theoretical foundations pertaining to the reasons for social loafing and the limiting conditions of its effects, several significant theoreti- cal and practical gaps remain. First, it has traditionally conceptualized social loafing as a stable rather than a dynamic construct. Second, it has mostly focused on structural reasons and set-up factors to explain social loafing. Relatively fewer studies have investigated other rea- sons related to individual differences and team-level factors. Third, even though goal orientation theory and social motivation theory pos- tulate interrelations between goal orientations and motivation, the effects of goals orientations on social loafing development have not been closely examined. Fourth, research on team-level factors, and more specifically on team sociocognitive factors, is even scarcer in the social loafing literature. Furthermore, building upon social inter- dependence theory and a regulatory approach of team learning (for theoretical considerations) as well as on group socialization theory and team development models (for temporal considerations), team learning appears as a promising yet underexplored emergent socio- cognitive mechanism that can initiate a downward shift in individual social loafing. So far, however, there has been little discussion about the power of team learning growth on change in social loafing. Fifth, studies have tended to collect data from single sources, leaving room for same-source biases. To address these research gaps on social loaf- ing, our goal is to identify individual and team factors, namely goal orientations and team learning, that together make up for this process loss; to do so, we use a multilevel framework and research design (Kozlowski & Klein, 2000), a repeated-measure design, and multiple assessors of social loafing tendencies.

Method

Data and Sample

Participants in our study (n = 675) were first-year business stu- dents attending a Research Methods course in their first trimester at a Dutch university. They were required to form three- or four- person teams (n = 195 teams, 105 three-person teams, 90 four-per- son teams) to complete tasks. The course used a self-selection approach in which students selected their own teams for the entire trimester. At the start of the course, students completed an online survey measuring the independent variables, that is, learning ori- entation and performance orientation (T0). Throughout the trimes- ter, they were required to complete three team assignments, which counted toward their final grade. Just before they turned in each assignment, students were contacted by e-mail and were asked to fill out the online surveys individually to measure team learning (T1, T2, T3) and social loafing (T1, T2, T3). They were briefed

TAKING A FREE RIDE 721

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

that the questionnaire was referring to the team assignments they had just completed collaboratively. The assignments varied in dif- ficulty. The first task consisted of choosing a research topic from a list, reading the accompanying case, conducting a literature search using different databases (e.g., Google Scholar, JSTOR), making an inventory of relevant articles, and comparing their results. Most students already were acquainted with literature search in data- bases, so this task was not difficult. The second task, of greater dif- ficulty, involved reading and analyzing a scientific article, building a complex conceptual model of the variables measured in the arti- cle, and formulating research hypotheses. The task was additive in nature: it lacked structure, there were no clear strategies, and more than one correct solution was possible. Finally, the third task, of moderately high difficulty, required teams to read a case, compose a research question, and answer scientific reasoning questions. According to their research question, students had to select and justify the most appropriate research method (e.g., experiment, case study, survey study); define whether the aim of the study would be to explore, explain, or describe (e.g., theory building vs. theory testing); and justify which research strategy would be least suitable for answering the research question. Teams also had to formulate recommendations according to the case. In total, they worked together for about nine weeks to complete these three team assignments. All members received the same grade on their assignments irrespective of individual effort, and performance standards were clearly communicated. The response rate for the first survey was 94.43% (729 stu-

dents); for the second survey, it was 91.58% (707 students); and for the third survey, it was 88.60% (684 students). We omitted from the analysis teams for which the data of two or three mem- bers were missing. The final sample consisted of 675 students dis- tributed in 195 teams. Of these respondents, 70.80% were men, 28.90% were women, and for .30%, information about gender was missing. The mean age of the participants was 18.76 years (stand- ard deviation [SD] = 1.48); 68.80% were Dutch, 24.60% indicated non-Dutch nationality, and 6.60% did not indicate any nationality.

Procedure

Data were collected with an online survey, sent by two research assistants. None of the authors nor the assistants were involved in teaching the Research Methods class. Moreover, the teachers were not aware of the purposes of the research. Because students filled out the questionnaires before they received their grades for their tasks, feedback on how well they did on the task did not affect their percep- tions of the measured variables. Participants were briefed about the purpose of the research and given the opportunity to opt out, but none of the students did so, and the final sample remained unchanged.

Measures

Team Learning

To assess team learning, we used a 5-item scale from the input- mediator-output-input (IMOI) model to grasp team dynamics, as described by Ilgen et al. (2005) and adapted by Schippers et al. (2013). Items included, for instance, “We learned from our mistakes in our tasks,” “We learned how to improve at our tasks,” and “We developed new knowledge or skills about our tasks” (1 = “strongly

disagree;” 5 = “strongly agree”). Team members rated these items individually. Their responses were aggregated to the team level to obtain team learning scores for each team at the three time points when team learning was measured. The Cronbach’s alpha coeffi- cients were .79 for time 1, .78 for time 2, and .80 for time 3.

Social Loafing Tendencies

We assessed social loafing tendencies with a 4-item measure derived from a questionnaire developed by George (1992) and adapted by Schippers (2014). We operationalized social loafing in two ways: self-reported and peer-reported. Because both sources of assessment have advantages and disadvantages, combining them offers a valid alternative to using one source over the other. To our knowledge, only Stark et al. (2007) use both self-ratings and peer ratings to study social loafing, concluding that participants are more willing to admit their own loafing behaviors than recognize the loaf- ing of their teammates. However, they emphasize it is legitimate to expect that social loafing appraisals from different perspectives (e.g., self vs. teammates) will differ. Therefore, to account for dif- fering perspectives on individual behavior in teams, we use the two separate source measures of social loafing behavior.

We summed self-reported responses across items that asked team members about the extent to which they “defer responsibilities they should assume to other team members,” “put forth less effort than other members of their team,” “prefer to let the other team members do the work if possible,” and “put forth less effort on the assign- ment when other team members are around to do the work” (1 = “totally disagree;” 5 = “totally agree”). For this measure, the Cron- bach's alphas were of .85 for time 1, .88 for time 2, and .88 for time 3. With regard to peer-rated social loafing, team members wrote down the names of their teammates and rated them on each of the four items on a 5-point Likert scale using the same labels as the self-report questionnaire. To justify aggregating the peer ratings, we assessed interrater agreement within teams according to rwg values (level of within-group agreement of the peer evaluation score for each referent). Because these estimates produced very good indica- tors of peer evaluation reliability (average rwg = .88), we averaged the peer ratings and used these scores for all analyses in the study. The Cronbach’s alphas were .87 for time 1, .87 for time 2, and .86 for time 3. In the coding, items were reversed, such that higher scores indicated higher levels of social loafing tendencies.

Learning Orientation and Performance Orientation

To assess learning and performance orientations, we used the 8- item scales developed by Button et al. (1996). Sample items for learning orientation (a = .84) included “The opportunity to learn new things is important to me,” and “I prefer to work on tasks that force me to learn new things.” Sample items for performance ori- entation (a = .74) included “I prefer to do things that I can do well rather than things that I do poorly,” and “The opinions others have about how well I can do certain things are important to me.”

Data Aggregation

We evaluated individual-level scores on the team learning scale to justify aggregation to the team level. To assess within-group heterogeneity, we calculated rWG(j) indices (James et al., 1984) for each measurement time of team learning with a cutoff criterion of

722 GABELICA, DE MAEYER, AND SCHIPPERS

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

.70 (George, 1990). Using the uniform null and normal distribu- tions (George & James, 1993), the average rWG(j) scores were appropriate for T1 (rWG[j] = .99, SD = .52), T2 (rWG[j] = .99, SD = .52), and T3 (rWG[j] = 98, SD = .55). We also calculated the intraclass cor- relation coefficient, ICC(1), to identify the proportion of the var- iance in the measures that could be explained by team membership, and the ICC(2) to assess the reliability of the team means for team learning (Bliese, 2000). All ICC(1) scores were greater than 0, and their corresponding one-way analyses of var- iance (ANOVAs) were significant at p , .05. Specifically, the ICC(1) coefficients were .33 (T1), .41 (T2), .and 40 (T3). The ICC (2) coefficients were .60 (T1), .68 (T2), and .66 (T3). The cutoff level of .60 thus was attained for ICC(2) too (Glick, 1985). These analyses provided sufficient support for aggregating our individ- ual-level scores to the team level.

Hypotheses Testing

We conducted linear mixed effects modeling to examine the degrees to which goal orientations affected initial levels and growth of social loafing and the initial levels and growth of team learning affected initial levels and growth of social loafing (Dun- can et al., 2006). With this technique, we can examine average tra- jectories, the pattern of change in individual and team constructs, and variations across individuals and teams, as well as analyzing the instigators of such variations (e.g., intercept or change in team learning; Mathieu & Rapp, 2009). This method models the repeated measures of an observed variable, reflecting the initial status of individuals and the rate of change in the dependent varia- bles across time periods. Moreover, it allows us to account for the complex multilevel structure of the data. Repeated measures (Level 1) were nested within individuals (Level 2) who were nested within teams (Level 3). For these analyses, we used the computing environment R Core Team (R) and the linear mixed- effects models using “Eigen” and S4 package (LME4; Bates et al., 2016). In a first step, we modeled three unconditional-growth models

in which no predictors were included except the effects of time. For both dependent variables (peer-rated and self-rated social loaf- ing), we first estimated a model in which we assumed a linear effect of time. In the second model, we allowed the intercepts and the slope of time to vary from individual to individual. In the third model, we allowed both the intercept and the slope of time to vary from individual to individual and from team to team. We expected between-team differences in both the initial scores and how social loafing tendencies evolved over the three measurement occasions. The Step 2 analyses tested the effects of goal orientations and

team learning (H1, H2, H3) on both dependent variables. We first modeled the effects of learning and performance orientation on the social loafing intercept and change. We compared the fit of this model to the fit of the best unconditional model using a �2 log likelihood test and the Akaike information criterion (AIC; lower AIC values indicate better model fit). Then, we compared the fit of the model with only individual-level factors against a model in which we added team learning as a team-level explanatory factor, to decide which fit the data best. Finally, to test H3, we con- structed two measures of team learning: team learning initial states and team learning growth throughout the trimester.

Results

Self-Rated Social Loafing

Level 1 Analyses: How Does Self-Rated Social Loafing Change Over Time?

In the first step, we modeled an unconditional growth model in which no predictors of social loafing were included, except the effects of time (with the time variable coded such that the initial time point = 0). We contrasted a model in which the slope of time could vary from individual to individual (model 2) with a model in which the effect of time was included only in the fixed part (model 1; see Table 1). Model 2 achieved better fit. Some individuals loafed more over time, some loafed less, and others stagnated. Moreover, the model that added the team-level perspective of social loafing (model 3) attained an even better fit; the slope of time varied from individual to individual and from team to team. Accordingly, this model pre- dicts that social loafing evolves differently in different teams, such that some teams show increased social loafing and other teams show either no evolution or a decrease in social loafing.

Level 2 Analyses: How Do Learning Orientation, Performance Orientation, and Team Learning Affect Self-Rated Social Loafing?

In the second step, we investigated factors that may explain the change trajectories of social loafing. This stage was fundamental to understanding why some individuals loafed more or reduced their loafing behaviors over time. In model 4, we tested only goal orientation effects, whereas in model 5, we added the main effects of team learning initial states at time 0 and team learning growth, as well as the interaction effects between these variables. Finally, in model 6, we added the control variable ‘team size’.

From the comparison of the various models tested, we conclude that the multilevel model combining the three explanatory factors—

Table 1 Model Fit Statistics for the Five Models Fitted on Self-Rated Social Loafing

Model �2LL AIC v2 df p

Model 1 (growth only fixed effect) 1,635.4 1,645.4 Model 2 (M1 þ individual differences in growth) 1,492.7 1,506.7 142.67 2 ,.001 Model 3 (M2 þ team differences in growth) 1,485.9 1,503.9 6.78 2 .033 Model 4 (M3 þ goal orientation effects) 1,405.9 1,431.9 80.04 4 ,.001 Model 5 (M4 þ team learning effects) 1,394.8 1,424.8 11.07 2 .004 Model 6 (M5 þ team size) 1,389.5 1,421.5 5.04 1 .021

Note. �2LL = �2 log-likelihood, AIC = Akaike information criterion, df = degrees of freedom.

TAKING A FREE RIDE 723

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

learning orientation and performance orientations of individual members and team learning (model 5)—showed better fit than the model that accounted for individual-level factors only (model 4), which was better than the unconditional model (model 3). Finally, model 6 controlling for team size showed a better fit than model 5. Table 2 displays the model 6 parameter estimates. Individual-Level Factors. Our results show that only learn-

ing orientation had stable effects over time. There was no signifi- cant interaction with time. That is, though neither learning nor performance orientation explained why some individuals differed in their social loafing tendencies over time, learning orientation did influence their initial states of social loafing. Partially consist- ent with H1, learning orientation relates negatively to self-rated social loafing but there are no time effects. We did not, however, find support for H2. Team-Level Factor. At the team level, the change in team

learning showed a negative effect on the change of social loafing. Individual members who were part of teams that scored higher on team learning throughout the nine weeks of teamwork scored lower on social loafing. Thus, only change in team learning explains variations of social loafing over time, thereby confirming our H3 with regard to self-reported social loafing. Finally, there

was a significant effect of the control variable ‘team size’, showing a higher degree of self-rated social loafing for members in teams of 3 than for members in teams of 4.

Peer-Rated Social Loafing

Level 1 Analyses: How Does Self-Rated Social Loafing Change Over Time?

Following the same procedure for self-rated social loafing, we modeled unconditional growth without any predictors of peer-rated social loafing except the effects of time. On average, we found the same pattern of results. In model 3, in which we allowed the slope of time to vary from individual member to individual member, and from team to team, we found better fit than model 2 (in which we allowed the slope of time to vary from individual member to individual member), which was better than model 1, in which we added only the effect of time to the fixed part (see Table 3). Model 3 predicts that growth trajectories in peer-rated social loafing differ from team to team, such that some indicate increases in peer-rated social loafing, but others show no change or decreases in peer-rated social loafing.

Table 2 Parameter Estimates (Est.), Standard Errors (SE), and p-Values From Model 6 Fitted on Self-Rated Social Loafing

Parameter Est. SE p

Fixed part Intercept * 3.171 0.235 ,.001 Time �0.018 0.014 .182 Team size (= 3) 0.543 0.234 .021 Performance orientation �0.015 0.045 .744 Learning orientation �0.387 0.045 ,.001 Team learning (initial score) �0.459 0.353 .194 Team learning (growth) 0.294 0.703 .676 Team Learning (initial score) 3 Time 0.189 0.187 .315 Team Learning (growth) 3 Time �1.181 0.378 .002

Random part Individual level Variance in intercepts 0.243 Variance in slopes 0.037 Correlation intercept slope �0.16

Team level Variance in intercepts 0.002 Variance in slopes 0.006 Correlation intercept slope �1 Residual variance 0.048

* Reference category: team of size = 4.

Table 3 Model Fit Statistics for the Five Models Fitted on Peer-Rated Social Loafing

Model �2LL AIC v2 df p

Model 1 (growth only fixed effect) 2,632.6 2,642.6 Model 2 (M1 þ individual differences in growth) 2,512.2 2,526.2 120.403 2 ,.001 Model 3 (M2 þ team differences in growth) 2,484.6 2,502.6 27.555 2 ,.001 Model 4 (M3 þ goal orientation effects) 2,477.0 2,503.3 7.621 4 .107 Model 5 (M4 þ team learning effects) 2,452.8 2,482.8 24.216 2 ,.001 Model 6 (M5 þ team size) 2,445.7 2,477.7 7.122 1 ,.008

Note. �2LL = �2 log-likelihood, AIC = Akaike information criterion, df = degrees of freedom.

724 GABELICA, DE MAEYER, AND SCHIPPERS

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

Level 2 Analyses: HowDo Learning Orientation, Performance Orientation, and Team Learning Affect Peer-Rated Social Loafing?

In the second step, we tested whether variations of the direction of change in peer-rated social loafing also can be explained by the explanatory factors of our study. Model 4, in which we added the effects of performance and learning orientations on social loafing and their interaction effects with the time variable, did not have a significantly better fit than the unconditional growth model (model 3); we concluded that both performance and learning orientations have no significant effects on peer-rated social loafing. Accord- ingly, we estimated model 5 in a more parsimonious way, keeping the main effects of goal orientations in the model as control varia- bles but removing the interaction effects with time. Thus, model 5 models the effects of team learning on peer-rated social loafing, af- ter controlling for the main effects of the individual-level factors, learning and performance orientations. It achieves a significantly better fit than model 4. Finally, in model 6, in which we added team size, we found better fit than model 5. Table 4 displays the parameter estimates of this model. Individual-Level Factors. Although we controlled for the

effects of goal orientations, the parameter estimates for the effects of learning orientation were not significantly different from zero. By contrast, performance orientation was found to be negatively related to peer-rated social loafing (H2a) but there was no significant interac- tion with time (H2b). This result differs from the self-rated data. Thus, H1 and H2b are not confirmed for peer-rated social loafing. Team-Level Factor. The initial level of team learning had a

significant negative effect on peer-rated social loafing at the start. Therefore, in teams in which initial learning scores were higher, lower social loafing was reported by peers. Over time, the change of team learning (growth) had a negative interaction effect on social loafing as rated by peers. That is, teams that increased their team learning over time were able to counteract the negative effects of social loafing tendencies perceived by the teammates;

these teams showed a decrease in peer-rated social loafing (H3). There was also a significant effect of the control variable ‘team size’, showing a higher degree of peer-rated social loafing for members in teams of 3 than for members in teams of 4.

Discussion

Research in work and educational settings shows that simply ask- ing individuals to collaborate does not necessarily lead to optimal collaboration (Johnson & Johnson, 2014; Kozlowski & Bell, 2013). Teamwork creates social motivational challenges that teams need to overcome throughout their experiences (Järvelä & Järvenoja, 2011). Typically, motivational challenges in teams tend to lie in individual members’ tendency to exert less effort than their team- mates (i.e., social loafing), leading to process loss. This is highly concerning as social loafing may intensify over time and lead to a downward spiral of motivation and process losses. This article aimed to examine how working on a team task shapes individual members’ tendency to exert their fair share of effort. Our study showed that teams that score high on team learning throughout nine weeks of teamwork experience decreased social loafing.

The primary contribution of this article has been to account for the temporal dynamics of social loafing and identify important individual- and team-level factors that affect its development. In doing so, our study produces three important sets of findings.

First, building on the collective effort model (CEM) and social interdependence theory, we find that loafing tendencies are more dynamic than previously thought. In a sample of temporary teams, social loafing trajectories appear to fluctuate across individuals and teams and even over a three-month period. Literature on teams has implicitly considered social loafing as a static rather than tem- poral variable (Aggarwal & O’Brien, 2008; Hofmann & Jones, 2005). Hence, this finding extends current knowledge about the dynamic nature of social motivation losses in teams (Kozlowski & Bell, 2013). Our finding is also consistent with the conceptualiza- tion that social loafing behaves like effort exertion (as part of

Table 4 Parameter Estimates (Est.), Standard Errors (SE), and P-Values From Model 6 Fitted on Peer-Rated Social Loafing

Parameter Est. SE p

Fixed part Intercept* 2.105 0.283 ,.001 Time 0.016 0.021 .449 Team size (= 3) 0.565 0.210 .007 Performance orientation �0.111 0.055 .045 Learning orientation 0.016 0.054 .770 Team learning (initial score) �1.292 0.505 .012 Team learning (growth) 0.912 1.008 .367 Team Learning (initial score) 3 Time 0.251 0.295 .455 Team Learning (growth) 3 Time �2.406 0.597 ,.001

Random part Individual level Variance in intercepts 0.255 Variance in slopes 0.048 Correlation intercept_slope 0.230

Team level Variance in intercepts 0.061 Variance in slopes 0.025 Correlation intercept_slope �0.670 Residual variance 0.135

* Reference category: team size = 4.

TAKING A FREE RIDE 725

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

behavioral engagement) in individual learning situations, which has been shown to be altered by situational constraints (Malmberg & Martin, 2019). Researchers who investigated participation in social settings more generally have successfully demonstrated that participation can fluctuate over time (Cheung et al., 2008; Hewitt, 2005). Complementary research focused on SSRL in collaborative learning has recently provided evidence that engagement in cogni- tive interactions can vary from moment to moment (e.g., Isohätälä et al., 2020). However, factors triggering fluctuations in participa- tion in student-led team tasks are less well understood (Isohätälä et al., 2020). Extending these lines of research on the temporal aspects of participation into social loafing models allowed us to verify that social loafing was also a fluctuating phenomenon across individuals and teams and to identify factors contributing to those fluctuations. Second, building on previous research on the individual characteris-

tics that determine people’s tendencies to loaf (e.g., Charbonnier et al., 1998; Schippers, 2014), our findings show that the learning orien- tation of individual team members appears to have constant effects for any member across time (H1). However, if we had measured learning orientation repeatedly as well, we might have found some time effects of other observations of learning orientation on social loafing trajectories, in line with the strand of research that supports goal orientation variability (Bernacki et al., 2014). Nevertheless, these results corroborate the findings of recent work applying Achievement Goal theory (AGT) to collaborative settings. In this work, cross-sec- tional data reveal that learning orientation is positively related to col- laborative (as opposed to antisocial) behaviors such as coregulating the team processes and elaborating peers’ content (Greisel et al., 2018; Lee et al., 2010). Note that an unanticipated finding of our study is that self-reported learning orientation does not predict peer- rated social loafing. This inconsistency may be due to differing per- ceptions of attitudes and behaviors by different members of the team. Finally, although the results of this study do not show any significant effects of performance orientation on self-rated social loafing emer- gence or development (H2), performance orientation is found to be negatively related to initial peer-rated social loafing (H2a). This means that individuals scoring high on performance orientation are rated by their peers as low loafers at the first team assignment. This result may be explained by the fact that, because they seek to obtain affirmative judgments about their competencies, members scoring high on per- formance orientation are perceived as behaving collaboratively. Since the effect is not present for self-rated social loafing, these relationships may partly be explained by differing perceptions of own versus other behaviors, an interesting avenue for future research. These conflicting results corroborate previous studies in the collaborative learning litera- ture. In fact, contrary to learning orientation’s main motivative role in collaborative learning, mixed results have been described so far regarding performance orientation (e.g., Lim & Lim, 2020). Such results raise the possibility that holding a performance orientation might have different consequences in team contexts where only team performance is measured, depending on the timing of the collabora- tion (Muis & Edwards, 2009). Additionally, it might be that social loafing is related to the avoidance variant of the achievement goals. Performance-avoidance goals—engaging in a task with the goal of avoiding revealing inabilities—have been shown to be related to dis- engagement in individual learning situations (Urdan & Kaplan, 2020). It can thus be suggested that the relationship between goal orien-

tation and social loafing is mediated by social goals, such as

building caring and committed relationships and belonging to a team, and team orientation (Johnson & Johnson, 2009). Moreover, social goals could increase or decrease the level of endorsement of members’ goals throughout the process of teamwork (Bernacki et al., 2014). For example, a high team orientation might explain how self-interest is expanded to joint interest and how new goals are crafted in collaborative situations, reducing the emergence of social loafing. Reaching a shared clarity and consensus about the team’s purpose and an alignment between individual and team goals could hence help teams prevent dysfunctional inefficiencies such as social loafing and optimize the use of the team capabilities (Johnson & Johnson, 2015; Kayes et al., 2005). If this hypothesis holds true, this will also suggest that social loafing can be changed and com- pensated for by strengthening team members’ identification.

Third, the development of social loafing depends not only on the passage of time but also on the increase of team learning that arises and grows among team members. Importantly, our results show that only team learning —a team-level concept—appears to explain changes in the trajectories of social loafing, over and above individual goal orientations. Consistent with our hypothesis 3, over time, an increase in team learning leads to a decrease in social loafing. This finding is particularly significant in the context of the complex nature of motivation loss and the dearth of research that demonstrates a relationship between the emergence and changes in team learning and social loafing (Bell et al., 2012). It highlights the need to consider temporal aspects of teams, which include not only team development (i.e., changes in the team as a whole) but also team socialization (i.e., changes in the relationship between the team and its members; Levine & Moreland, 1994). Consequently, these results corroborate group socialization theory introduced by Levine and Moreland (1994) who suggested that individuals change as a function of the team that they join. This theory provides a valuable temporal explanation of how individu- als can become team members although, as noted by Kozlowski and Bell (2013), there is a paucity of research focusing on team socialization over time. Surprisingly, it is still widely believed that over time, individuals striving for their own goals naturally develop into team members of an autonomous team capable of adapting itself to meet environmental contingencies (Kayes et al., 2005). Furthermore, the present study extends our understanding of the regulatory approach to team learning (Bell et al., 2012; Chen et al., 2009) by linking the upgrade of shared knowledge to moti- vational processes.

However, in the current study we could only infer that sociocog- nitive interactions had occurred that led to a shift in team’s collec- tive knowledge (Fransen et al., 2013). Prior research has identified several factors that may influence why and how an increase in team knowledge predicts ensuing changes in social loafing, namely: (1) positive interdependence, (2) group processing behav- iors, (3) perception of a team reward, and (4) socioemotional inter- actions. Below, we elaborate on these four factors.

First, it is possible to hypothesize that positive interdependence (i.e., team members’ perception that they can attain their goals only if all other teammates promote each other’s efforts to achieve the goals) is necessary for team learning to have positive effects on social loafing. When individual members perceive positive interdependence, they might realize that their efforts are required for the team to create team knowledge and that they make a unique contribution to their team. Positive interdependence is also posited

726 GABELICA, DE MAEYER, AND SCHIPPERS

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

to create a sense of responsibility and accountability for complet- ing their share of work (Johnson & Johnson, 2015). Second, we can argue that group processing enables team learn-

ing development. Several fields of research provide insights into the nature of group processing. Social interdependence theory states that group processing encompasses analyzing and imple- menting actions to achieve the team’s goals (Johnson & Johnson, 2009). In social psychology, group-level information processing (Hinsz et al., 1997) involves information sharing and use. Simi- larly, in the research on socially shared regulation of learning (SSRL), Volet and colleagues (2009) use the term ‘high-level cog- nitive processing’ depicting behaviors such as elaborating, drawing inferences, asking thought-provoking questions, and negotiating. They are all presumed to contribute to the coconstruction of knowledge, a core behavior that can augment team knowledge (Van den Bossche et al., 2011). Hence, based on the premise that shared regulation leads to increased shared knowledge (Lajoie & Lu, 2011; Saab et al., 2012), and that shared regulation is scarce when at least one member is disengaged (Isohätälä et al., 2017), we could suggest that teams that experienced the steeper team learning shifts in our study self-regulated their motivation and cognition. Finally, these social regulation processes are similar to team learning behaviors described in small group research. They include reflecting on team processes and outcomes, asking ques- tions, sharing and discussing ideas and divergences, and solving them constructively to coconstruct new understandings and reach mutual agreement (see Decuyper et al., 2010; for review). Third, based on behavioral learning theories (Bandura, 1977)

that posit that individuals will work hard on tasks for which they obtain a reward and exert less effort in tasks that yield no reward, we could propose that an increase in team knowledge can be per- ceived as a reward that make loafers work harder toward their team goals. Finally, team learning may affect social loafing through enhanced

concern with the team and its outcomes, higher sense of community and/or higher cohesiveness (Lam, 2015). Both research on collabo- rative learning and work in social psychology and organizational behavior have raised the importance of socioemotional interactions that complement sociocognitive interactions for successful team- work (Isohätälä et al., 2017). To summarize, our study complements past research by demon-

strating the salience of studying the temporal dynamics of group motivational constructs and identifying team factors that eliminate motivation losses in group endeavors (Aggarwal & O’Brien, 2008; Bell et al., 2012). It therefore contributes to address the essential issues of why teams develop differently and how different aspects of interaction are connected at the individual and team levels (Fransen et al., 2013). Examining these relationships over a pro- longed period of time, and over many performance episodes, may be a viable route for further research, which also should seek to specify any boundary conditions for the present effects. Research on other individual differences or contextual variables that might explain different social loafing trajectories also is necessary. For example, positive norms for co-operative work and constructive behaviors (Buchs et al., 2015) could prevent social loafing. Specif- ically, social norms that promote team goals, open lines of com- munication, early resolution, and that expect everyone to work hard will likely increase members’ motivation to contribute to the team efforts. It is expected that the more those norms are shared,

the stronger would be the involvement of members in the team ac- tivity (Levine & Moreland, 2004). Further, research on other team-emergent mechanisms (e.g., trust, psychological safety, team cohesion) that might minimize social loafing also is necessary. Complementary research on regulated learning in social settings has provided insightful evidence that team members need to engage in regulated learning to develop joint knowledge construc- tion (Järvelä et al., 2016; Malmberg et al., 2017). Growth in this research field provides an exciting opportunity for researchers to investigate teamwork by shedding light on metacognitive proc- esses that are essential for overcoming motivational problems in collaborative learning. By examining these phenomena empiri- cally, we could gain a better grasp on the complexities of motiva- tion in team settings. Such insights could assist the design and application of interventions that stimulate behaviors and processes that have been shown to be helpful in reducing the tendency to engage in social loafing. If these results replicate across settings (e.g., in workplaces) and tasks, the use of team exercises, feed- back, incentives, and debriefing interventions arguably could increase the use of effective behaviors and even reduce motivation loss (Gabelica et al., 2014; Pritchard et al., 2008).

Limitations and Future Directions

Although obvious strengths of the current study are that we tested the hypotheses with a large number of teams, over time and in a context where social loafing often occurs, our study is not without limitations. First, it is conceivable that there was a per- cept–percept bias in the first model, that predicted changes in self- rated loafing for testing relationships between variables from the same questionnaire. However, we minimized the impact of this bias by using temporal measurements (Podsakoff et al., 2003). Although the instruments and constructs we use have been shown to be both reliable and valid, self-reported team learning cannot fully cover learning behaviors and strategies in which teams engage. Because we did not systematically observe team learning processes, the challenges for continuing research are to document the processes that occur when individuals collaborate to solve team tasks (Fransen et al., 2013), validate interventions to make teams function as effectively as possible, and investigate the impact of team learning and motivation processes on performance. Closer examination of communication processes may help deter- mine whether and how learning behaviors vary in quality and affect social loafing. To address this issue, researchers could over- lay qualitative analyses to clarify how the quality of specific learn- ing processes (e.g., sharing information and knowledge; mutually refining, building on, or modifying each original offer; reflecting on team processes) increases or decreases over time in dynamic episodes with social loafing tendencies (Goodman & Dabbish, 2011). The focus of these analyses should be on the sociocognitive and socioemotional interactions that occur during teamwork, the conditions under which they occur, what the effects of these inter- actions are, and how they are interrelated (i.e., the interactions par- adigm; Dillenbourg et al., 1996).

Second, our validated model differs slightly across the two sour- ces of ratings of social loafing. We chose to investigate peer ratings and self ratings independently, because prior outcomes are mixed with regard to which source best assesses social loafing (Karau & Williams, 1993; Stark et al., 2007). We find a different pattern

TAKING A FREE RIDE 727

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

(higher peer-rating means) than Stark et al. (2007; higher self-rating means); their study participants were more willing to report their own versus their teammates’ social loafing. However, the question of the “true” score of social loafing remains unanswered. To mea- sure actual social loafing, researchers would need to observe, re- cord, and interpret accurately team members’ efforts (Lord, 1985; Mulvey & Klein, 1998). Although perceptions of social loafing and actual reduced effort may be associated, reduced effort also may occur without the awareness of team members (Mulvey & Klein, 1998). If reduced efforts are not perceived by the team, they may not affect team functioning and motivation. Therefore, perceptions of social loafing require further research. Along these lines, it also is important to note that prior work has provided empirical evidence that peer appraisals are associated with reduced social loafing (e.g., Druskat & Wolff, 1999). In our study, because students’ evalua- tions were completed early in the academic year and at multiple points, social loafing may have been lower than expected in situa- tions of no peer appraisal. As a result, the magnitude of the underly- ing effects may be underestimated. Third, we conducted our study with undergraduate student pro-

ject teams. Although past research on social loafing also has used student samples (Alnuaimi et al., 2010; Gagné & Zuckerman, 1999; Schippers, 2014), we are cautious about the external validity of our findings. Student groups sometimes work less as a team and more as individual participants who complete separate portions of their assigned task independently (Skilton et al., 2008). Moreover, expertise distribution within teams in educational settings may be limited, which may limit the inputs team members have available to complete tasks and increase their dispensability. Researchers should determine if our results generalize to employees who con- stitute project teams outside formal educational settings (Price et al., 2006). Although loafing tendencies usually are demonstrated in laboratory settings (Huguet et al., 1999), team members in our study were not role playing; rather, they were performing mean- ingful tasks designed to be complex enough to demand team efforts, have a team goal and reward (i.e., have positive interde- pendence), and require that a few months be spent together. Our student teams had assignments that required the cooperation and coordination of team efforts across multiple meetings, but unlike teams in a work context, they lacked the same history of common experiences and identity (Karau & Hart, 1998). Finally, the current study focused on just two goals assessed

once at the start of the collaboration. While focusing on learning and performance goals is parsimonious, it fails to account for other goals that are potentially important in achievement situations in teams. Research within the achievement goal framework has pro- liferated over the past years and more complex models have been studied (i.e., trichotomous achievement goal framework and 2 3 2 achievement goal framework; Urdan & Kaplan, 2020). Addition- ally, there has been growing evidence that achievement goals can change across tasks (Bernacki et al., 2014; Fryer & Elliot, 2007). Future research could capture variations in team members’ endorsement of achievement goals over time and relate these fluc- tuations to social loafing trajectories. Researchers could verify if throughout the process of team goal pursuit and regulation, indi- vidual goal switches or intensification are related to increases or drops of social loafing. Despite these limitations, our research contributes to emerging

literature on the development of social loafing. By demonstrating

that the increase of team learning can lower the emergence of social loafing, it provides further empirical support for the power of team learning on individual behaviors (Gabelica et al., 2014; Bell et al., 2012; Decuyper et al., 2010). It also provides an inte- grative theoretical model that combines individual- and team-level predictors of social loafing. It highlights the importance of other team members and their interactive behaviors in determining indi- vidual behavior. We hope this study stimulates further empirical and theoretical research on the temporal dynamics of social loafing.

Practical Implications

Any setting in which people’s efforts are merged into a single output might be conducive to the demotivating effects of working in teams. Teachers and trainers may experience withheld effort that negatively affects not only teams’ but also classes’ perform- ance and dynamics. In school settings, dealing with social loafing and its consequences has become a time-consuming concern for teachers who use team-based learning. An important challenge for research and practice is to implement strategies for maximizing team functioning and team learning, such that the potential of each team’s resources can be fulfilled (Webb et al., 1998).

The outcomes of our study provide substantial insights for designing and supporting teams in ways that reduce opportunistic behavior such as social loafing (Tan & Tan, 2008). Our findings underscore the positive effects of learning orientation on the level of social loafing at the start of team activities. During team forma- tion phases (Tuckman & Jenson, 1977), devoting specific attention to favorable beliefs and appraisals of tasks and teams (high value to the task and team) may reduce tension arising from the uneven motivations that often occur in newly formed teams. Assessing members’ goal orientations may help team managers and teachers anticipate antisocial behaviors and take early action to build the learning tones of their teams (Bunderson & Sutcliffe, 2003; Gagné & Zuckerman, 1999).

When working in increasingly learning-oriented teams, individ- ual members also may move away from individualistic concerns and work harder when everyone’s ideas and contributions are val- ued. This result is encouraging, because it suggests social loafing is a changeable behavior that fluctuates over time. Stimulating knowledge sharing and building, learning from prior mistakes, and constructive team discussions may reduce social loafing tenden- cies. By asking critical questions and introducing competing per- spectives and interpretations, teachers and team facilitators can broaden discussions and promote deeper team concern, commit- ment, and engagement. This approach calls for the implementation and evaluation of the motivational benefits of interventions that facilitate team learning and maintain high learning opportunities and challenges throughout team tasks (Gabelica et al., 2014; Hack- man & Wageman, 2005). For example, emerging research indi- cates that providing teams with feedback on how they have performed, and inducing team reflection on what teams do and how they do it, helps them become more effective, especially if their initial team performance is low (Gurtner et al., 2007). The co-operative learning literature also provides insight in this regard. Buchs et al. (2015), for example, highlight the needs to better pre- pare students for collaboration and use structured methods to en- courage constructive interactions. Social interdependence theory

728 GABELICA, DE MAEYER, AND SCHIPPERS

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

traditionally presumed that team members had the necessary skills to collaborate successfully (Johnson & Johnson, 2015). To achieve team learning and effectiveness, it therefore appears necessary to help teams construct shared understandings of task characteristics and the team’s knowledge in early stages of teamwork (Fransen et al., 2013). From a cognitive perspective, team members with poor communication skills are less likely to benefit from team-based learning, because they may not be able to share their ideas and proposals with others; ask critical questions; reflect on their own and team functioning; provide constructive criticism; or disagree with elaborated argumentation (Kramarski, & Mevarech, 2003; Webb & Farivar, 1994). Therefore, preparing newly formed teams for collaboration by training them in team learning processes (e.g., shared reflection, coconstruction, high-level elaboration, construc- tive disagreements, reaching agreement) that produce high team performance (Webb et al., 1998) is a promising avenue for team development.

References

Aggarwal, P., & O'Brien, C. L. (2008). Social loafing on group projects: Structural antecedents and effect on student satisfaction. Journal of Market- ing Education, 30(3), 255–264. https://doi.org/10.1177/0273475308322283

Alnuaimi, O. A., Robert, L. P., & Maruping, L. M. (2010). Team size, disper- sion, and social loafing in technology-supported teams: A perspective on the theory of moral disengagement. Journal of Management Information Systems, 27(1), 203–230. https://doi.org/10.2753/MIS0742-1222270109

Arrow, H., McGrath, J. E., & Berdahl, J. L. (2000). Small groups as com- plex systems: Formation, coordination, development, and adaptation. Sage.

Bakhtiar, A., Webster, E. A., & Hadwin, A. F. (2017). Regulation and socio-emotional interactions in a positive and a negative group climate. Metacognition and Learning, 13(1), 57–90. https://doi.org/10.1007/ s11409-017-9178-x

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/ 0033-295X.84.2.191

Barclay, J. H., & Harland, L. K. (1995). Peer performance appraisals: The impact of rater competence, rater location, and rating correctability on fairness perceptions. Group & Organization Management, 20(1), 39–60. https://doi.org/10.1177/1059601195201004

Bates, D. M., Maechler, M., Bolker, B., Walker, S., Christensen, R. H. B., Singmann, H., Dai, B., Grothendieck, G., & Green, P. (2016). lme4: Linear mixed-effects models using S4 classes. R package version 1.1–12.

Bell, B. S., Kozlowski, S. W. J., & Blawath, S. (2012). Team learning: A theoretical integration and review. In S. W. J. Kozlowski (Ed.), The Oxford handbook of organizational psychology (pp. 859–909). Oxford University Press.

Bernacki, M. L., Aleven, V., & Nokes-Malach, T. J. (2014). Stability and change in adolescents’ task-specific achievement goals and implications for learning mathematics with intelligent tutors. Computers in Human Behavior, 37, 73–80. https://doi.org/10.1016/j.chb.2014.04.009

Bliese, P. D. (2000). Within-group agreement, non-independence, and reli- ability: Implications for data aggregation and analysis. In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research, and methods in organizations: Foundations, extensions, and new directions (pp. 349–381). Jossey-Bass.

Bolin, A. U., & Neuman, G. A. (2006). Personality, process, and perform- ance in interactive brainstorming groups. Journal of Business and Psy- chology, 20(4), 565–584. https://doi.org/10.1007/s10869-005-9000-7

Boud, D., Cohen, R., & Sampson, J. (2001). Peer Learning in Higher Edu- cation: Learning from and with each other. Kogan.

Brophy, J. (2005). Goal theorists should move on from performance goals. Educational Psychologist, 40(3), 167–176. https://doi.org/10.1207/ s15326985ep4003_3

Buchs, C., Gilles, I., Antonietti, J.-P., & Butera, F. (2015). Why students need to be prepared to cooperate: A co-operative nudge in statistics learning at university. Educational Psychology, 36(5), 956–974. https:// doi.org/10.1080/01443410.2015.1075963

Bunderson, J. S., & Sutcliffe, K. M. (2003). Management team learning orientation and business unit performance. Journal of Applied Psychol- ogy, 88(3), 552–560. https://doi.org/10.1037/0021-9010.88.3.552

Butler, R. (1995). Motivational and informational functions and consequen- ces of children’s attention to peers’ work. Journal of Educational Psy- chology, 87(3), 347–360. https://doi.org/10.1037/0022-0663.87.3.347

Button, S. B., Mathieu, J. E., & Zajac, D. M. (1996). Goal orientation in organizational research: A conceptual and empirical foundation. Organi- zational Behavior and Human Decision Processes, 67(1), 26–48. https:// doi.org/10.1006/obhd.1996.0063

Carver, C. S., & Scheier, M. F. (1998). On the self-regulation of behavior. Cambridge University Press. https://doi.org/10.1017/CBO9781139174794

Cellar, D. F., Stuhlmacher, A. F., Young, S. K., Fisher, D. M., Adair, C. K., Haynes, S., & Riester, D. (2010). Trait goal orientation, self-regu- lation, and performance: A meta-analysis. Journal of Business and Psy- chology, 26, 467–483. https://doi.org/10.1007/s10869-010-9201-6

Charbonnier, E., Huguet, P., Brauer, M., & Monteil, J. M. (1998). Social loafing and self-beliefs: People’s collective effort depends on the extent to which they distinguish themselves as better than others. Social Behav- ior and Personality, 26(4), 329–340. https://doi.org/10.2224/sbp.1998 .26.4.329

Chen, G., Kanfer, R., DeShon, R. P., Mathieu, J. E., & Kozlowski, S. W. J. (2009). The motivating potential of teams: Test and extension of Chen and Kanfer’s (2006) cross-level model of motivation in teams. Organi- zational Behavior and Human Decision Processes, 110(1), 45–55. https://doi.org/10.1016/j.obhdp.2009.06.006

Cheng, W., & Warren, M. (1999). Peer teacher assessment of the oral and written tasks of a group project. Assessment & Evaluation in Higher Education, 24(3), 301–314. https://doi.org/10.1080/0260293990240304

Cheung, W. S., Hew, K. F., & Ng, S. L. C. (2008). Toward an understand- ing of why students contribute in asynchronous online discussions. Jour- nal of Educational Computing Research, 38(1), 29–50. https://doi.org/ 10.2190/EC.38.1.b

Cohen, S. G., & Bailey, D. E. (1997). What makes teams work: Group effec- tiveness research from the shop floor to the executive suite. Journal of Man- agement, 23(3), 239–290. https://doi.org/10.1177/014920639702300303

Comer, D. (1995). A model of social loafing in real work groups? Human Relations, 48(6), 647–667. https://doi.org/10.1177/001872679504800603

Conway, J. M., & Lance, C. E. (2010). What reviewers should expect from authors regarding common method bias in organizational research. Jour- nal of Business and Psychology, 25(3), 325–334. https://doi.org/10 .1007/s10869-010-9181-6

Davison, H. K., Mishra, V., Bing, M. N., & Frink, D. D. (2014). How indi- vidual performance affects the variability of peer evaluations in class- room teams: A distributive justice perspective. Journal of Management Education, 38(1), 43–85. https://doi.org/10.1177/1052562912475286

De Dreu, C. K. W., Nijstad, B. A., & van Knippenberg, D. (2008). Moti- vated information processing in group judgment and decision making. Personality and Social Psychology Review, 12(1), 22–49. https://doi .org/10.1177/1088868307304092

Decuyper, S., Dochy, F., & Van den Bossche, P. (2010). Grasping the dynamic complexity of team learning: An integrative model for effective team learning in organizations. Educational Research Review, 5(2), 111–133. https://doi.org/10.1016/j.edurev.2010.02.002

TAKING A FREE RIDE 729

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

Dillenbourg, P., Baker, M., Blaye, A., & O’Malley, C. (1996). The evolu- tion of research on collaborative learning. In E. Spada & P. Reiman (Eds.), Learning in Humans and Machine: Towards an interdisciplinary learning science (pp. 189–211). Elsevier.

Dochy, F., Gijbels, D., Raes, E., & Kyndt, E. (2014). Team learning in education and professional organisations. In S. Billett, C. Harteis, & H. Gruber (Eds.), International handbook of research in professional and practice-based learning (pp. 987–1020). Springer. https://doi.org/10 .1007/978-94-017-8902-8_36

Druskat, V. U., & Wolff, S. B. (1999). Effects and timing of developmen- tal peer appraisals in self-managing work groups. Journal of Applied Psychology, 84(1), 58–74. https://doi.org/10.1037/0021-9010.84.1.58

Duffy, M. K., & Shaw, J. D. (2000). The Salieri syndrome: Consequences of envy in groups. Small Group Research, 31(1), 3–23. https://doi.org/ 10.1177/104649640003100101

Duncan, T. E., Duncan, S. C., & Strycker, L. A. (2006). An introduction to latent variable growth curve modeling. LEA.

Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41(10), 1040–1048. https://doi.org/10.1037/0003-066X.41 .10.1040

Dweck, C. S. (1999). Self-theories: Their role in motivation, personality, and development. Psychology Press.

Elliot, A. J. (2005). A conceptual history of the achievement goal con- struct. In A. J. Elliot & C. Dweck (Eds.), Handbook of competence and motivation (pp. 52–72). Guilford Press.

Elliot, A. J., & McGregor, H. A. (2001). A 2 X 2 achievement goal frame- work. Journal of Personality and Social Psychology, 80(3), 501–519. https://doi.org/10.1037/0022-3514.80.3.501

Elliot, A. J., & Church, M. A. (1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 72(1), 218–232. https://doi.org/10.1037/0022-3514 .72.1.218

Ellis, A. P., Hollenbeck, J. R., Ilgen, D. R., Porter, C. O., West, B. J., & Moon, H. (2003). Team learning: Collectively connecting the dots. Jour- nal of Applied Psychology, 88(5), 821–835. https://doi.org/10.1037/ 0021-9010.88.5.821

Erez, M., & Somech, A. (1996). Is group productivity loss the rule or the exception? Effects of culture and group-based motivation. Academy of Management Journal, 39(6), 1513–1537. https://doi.org/10.2307/257067

Forgas, J., Williams, K., & Laham, S. (2005). Social motivation: introduc- tion and overview. In K. D. Williams & S. M. Laham (Eds.), Social motivation: Conscious and unconscious processes (pp. 1–15). Cam- bridge University Press.

Fransen, J., Weinberger, A., & Kirschner, P. (2013). Team effectiveness and team development in CSCL. Educational Psychologist, 48(1), 9–24. https://doi.org/10.1080/00461520.2012.747947

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engage- ment: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059

Fryer, J. W., & Elliot, A. J. (2007). Stability and change in achievement goals. Journal of Educational Psychology, 99(4), 700–714. https://doi .org/10.1037/0022-0663.99.4.700

Gabelica, C., Van den Bossche, P., De Maeyer, S., Segers, M., & Gijselaers, W. (2014). The effect of team feedback and guided reflexiv- ity on team performance change. Learning and Instruction, 34, 86–96. https://doi.org/10.1016/j.learninstruc.2014.09.001

Gagné, M., & Zuckerman, M. (1999). Performance and learning goal orien- tations as moderators of social loafing and social facilitation. Small Group Research, 30(5), 524–541. https://doi.org/10.1177/104649649903000502

George, J. M. (1990). Personality, affect, and behavior in groups. Journal of Applied Psychology, 75(2), 107–116. https://doi.org/10.1037/0021 -9010.75.2.107

George, J. M. (1992). Extrinsic and intrinsic origins of perceived social loafing in organizations. Academy of Management Journal, 35(1), 191–202. https://doi.org/10.2307/256478

George, J. M., & James, L. R. (1993). Personality, affect, and behavior in groups revisited: Comment on aggregation, levels of analysis, and a recent application of within and between analysis. Journal of Applied Psychology, 78(5), 798–804. https://doi.org/10.1037/0021-9010.78.5.798

Glick, W. H. (1985). Conceptualizing and Measuring Organizational and Psychological Climate: Pitfalls in Multilevel Research. Academy of Management Review, 10(3), 601–616. https://doi.org/10.5465/amr.1985 .4279045

Goodman, P., & Dabbish, L. (2011). Methodological issues in measuring group learning. Small Group Research, 42(4), 379–404. https://doi.org/ 10.1177/1046496410385471

Greisel, M., Melzner, N., Kollar, I., & Dresel, M. (2018). How groups reg- ulate their learning: The influence of achievement goals on self-, co- and shared regulation strategies. Proceedings of the 13th International Con- ference of the Learning Sciences: Rethinking Learning in the Digital Age. Making the Learning Sciences Count.

Gurtner, A., Tschan, F., Semmer, N. K., & Nagele, C. (2007). Getting groups to develop good strategies: Effects of reflexivity interventions on team process, team performance, and shared mental models. Organiza- tional Behavior and Human Decision Processes, 102(2), 127–142. https://doi.org/10.1016/j.obhdp.2006.05.002

Hackman, J. R., & Wageman, R. (2005). A theory of team coaching. Acad- emy of Management Review, 30, 269–287. https://doi.org/10.5465/amr .2005.16387885

Harkins, S. (1987). Social loafing and social facilitation. Journal of Experi- mental Social Psychology, 23(1), 1–18. https://doi.org/10.1016/0022 -1031(87)90022-9

Hewitt, J. (2005). Toward an understanding of how threads die in asyn- chronous compute conferences. Journal of the Learning Sciences, 14(4), 567–589. https://doi.org/10.1207/s15327809jls1404_4

Hinsz, V. B., Tindale, R. S., & Vollrath, D. A. (1997). The emerging con- ceptualization of groups as information processors. Psychological Bulle- tin, 121(1), 43–64. https://doi.org/10.1037/0033-2909.121.1.43

Hofmann, D. A., & Jones, L. M. (2005). Leadership, collective personality, and performance. Journal of Applied Psychology, 90, 509–522. https:// doi.org/10.1037/0021-9010.90.3.509

Høigaard, R., Safvenbom, R., & Tonnessen, F. E. (2006). The relationship between group cohesion, group norms, and perceived social loafing in soccer teams. Small Group Research, 37(3), 217–232. https://doi.org/10 .1177/1046496406287311

Hommes, J., Van den Bossche, P., de Grave, W., Bos, G., Schuwirth, L., & Scherpbier, A. (2014). Understanding the effects of time on collabora- tive learning processes in problem based learning: A mixed methods study. Advances in Health Sciences Education: Theory and Practice, 19(4), 541–563. https://doi.org/10.1007/s10459-013-9487-z

Huguet, P., Charbonnier, E., & Monteil, J. (1999). Productivity loss in per- formance groups: People who see themselves as average do not engage in social loafing. Group Dynamics, 3(2), 118–131. https://doi.org/10 .1037/1089-2699.3.2.118

Ilgen, D. R., Hollenbeck, J. R., Johnson, M., & Jundt, D. (2005). Teams in organizations: From input-process-output models to IMOI models. An- nual Review of Psychology, 56, 517–543. https://doi.org/10.1146/ annurev.psych.56.091103.070250

Ilgen, D. R., Major, D. A., & Spencer, L. T. (1994). The cognitive revolu- tion in organizational behavior. In J. Greenberg (Ed.), Organizational Behavior: The State of the Science (pp. 1–22). Erlbaum.

Isohätälä, J., Näykki, P., & Järvelä, S. (2020). Cognitive and socio-emo- tional interaction in collaborative learning: Exploring fluctuations in stu- dents’ participation. Scandinavian Journal of Educational Research, 64(6), 831–851. https://doi.org/10.1080/00313831.2019.1623310

730 GABELICA, DE MAEYER, AND SCHIPPERS

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

Isohätälä, J., Näykki, P., Järvelä, S., & Baker, M. J. (2017). Striking a bal- ance: Socio-emotional processes during argumentation in collaborative learning interaction. Learning, Culture and Social Interaction, 16, 1–19. https://doi.org/10.1016/j.lcsi.2017.09.003

James, L. R., Demaree, R. J., & Wolf, G. (1984). Estimating withingroup interrater reliability with and without response bias. Journal of Applied Psychology, 69(1), 85–98. https://doi.org/10.1037/0021-9010.69.1.85

Järvelä, S., & Järvenoja, H. (2011). Socially constructed self-regulated learning and motivation regulation in collaborative learning groups. Teachers College Record, 113(2), 350–374.

Järvelä, S., Järvenoja, H., Malmberg, J., Isohätälä, J., & Sobocinski, M. (2016). How do types of interaction and phases of self-regulated learn- ing set a stage for collaborative engagement? Learning and Instruction, 43, 39–51. https://doi.org/10.1016/j.learninstruc.2016.01.005

Jassawalla, A. R., Malshe, A., & Sashittal, H. (2008). Student perceptions of social loafing in undergraduate business classroom teams. Decision Sciences Journal of Innovative Education, 6(2), 403–406. https://doi .org/10.1111/j.1540-4609.2008.00183.x

Johnson, D. W., & Johnson, R. T. (1999). Making co-operative learning work. Theory into Practice, 38(2), 67–74. https://doi.org/10.1080/ 00405849909543834

Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and co-operative learning. Educa- tional Researcher, 38(5), 365–379. https://doi.org/10.3102/0013189X09 339057

Johnson, D. W., & Johnson, R. T. (2014). co-operative Learning in 21st Century. Anales de Psicología, 30(3), 841–851. https://doi.org/10.6018/ analesps.30.3.201241

Johnson, D. W., & Johnson, R. T. (2015). Theoretical approaches to co-op- erative learning. In R. Gillies (Ed.), Collaborative learning: Develop- ments in research and practice (pp. 17–46). Nova.

Johnson, S. D., Suriya, C., Won Yoon, S., Berrett, J. V., & La Fleur, J. (2002). Team development and group processes of virtual learning teams. Computers & Education, 39(4), 379–393. https://doi.org/10 .1016/S0360-1315(02)00074-X

Kaplan, A., & Maehr, M. L. (2007). The contributions and prospects of goal orientation theory. Educational Psychology Review, 19(2), 141–184. https://doi.org/10.1007/s10648-006-9012-5

Karau, S. J., & Wilhau, A. J. (2020). Social loafing and motivation gains in groups: An integrative review. In S. J. Karau (Ed.), Individual motiva- tion within groups: Social loafing and motivation gains in work, aca- demic, and sports teams (pp. 3–51). Academic Press. https://doi.org/10 .1016/B978-0-12-849867-5.00001-X

Karau, S. J., & Hart, J. R. (1998). Group cohesiveness and social loafing: Effects of a social interaction manipulation on individual motivation within groups. Group Dynamics Theory Research and Practice, 2(3), 185–191. https://doi.org/10.1037/1089-2699.2.3.185

Karau, S. J., & Williams, K. D. (1993). Social loafing: A meta-analytic review and theoretical integration. Journal of Personality and Social Psy- chology, 65(4), 681–706. https://doi.org/10.1037/0022-3514.65.4.681

Karau, S. J., & Williams, K. D. (1997). The effects of group cohesiveness on social loafing and social compensation. Group Dynamics, 1(2), 156–168. https://doi.org/10.1037/1089-2699.1.2.156

Kayes, A. B., Kayes, C., & Kolb, D. A. (2005). Experiential learning in teams. Simulation & Gaming, 36(3), 330–354. https://doi.org/10.1177/ 1046878105279012

Kirschner, P. A. (2009). Epistemology or pedagogy, that is the question. In S. Tobias & T. M. Duffy (Eds.), Constructivist theory applied to instruc- tion: Success or failure? (pp. 144–157). Routledge.

Kozlowski, S. W. J., & Bell, B. S. (2008). Team learning, development, and adaptation. In V. I. Sessa & M. London (Eds.),Work group learning (pp. 15–44). LEA.

Kozlowski, S. W. J., & Bell, B. S. (2013). Work groups and teams in organizations: Review update. In N. Schmitt & S. Highhouse (Eds.),

Handbook of psychology, vol. 12: Industrial and organizational psy- chology (2nd ed., pp. 412–469). Wiley.

Kozlowski, S. W. J., & Ilgen, D. R. (2006). Enhancing the effectiveness of work groups and teams. Psychological Science in the Public Interest, 7(3), 77–124. https://doi.org/10.1111/j.1529-1006.2006.00030.x

Kozlowski, S. W. J., & Klein, K. J. (2000). A multilevel approach to theory and research in organizations: Contextual, temporal, and emer- gent processes. In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research, and methods in organizations: Foundations, exten- sions, and new directions (pp. 3–90). Jossey-Bass.

Kramarski, B., & Mevarech, Z. R. (2003). Enhancing mathematical rea- soning in the classroom: The effects of co-operative learning and meta- cognitive training. American Educational Research Journal, 40(1), 281–310. https://doi.org/10.3102/00028312040001281

Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pit- falls for social interaction in computer-supported collaborative learning environments: A review of the research. Computers in Human Behavior, 19(3), 335–353. https://doi.org/10.1016/S0747-5632(02)00057-2

Lajoie, S. P., & Lu, J. (2011). Supporting collaboration with technology: Does shared cognition lead to coregulation in medicine? Metacognition and Learning, 7(1), 45–62. https://doi.org/10.1007/s11409-011-9077-5

Lam, C. (2015). The role of communication and cohesion in reducing social loafing in group projects. Business and Professional Communication Quarterly, 78(4), 454–475. https://doi.org/10.1177/2329490615596417

Lee, E., Yoon, J., & Kim, M. (2010). Analysing participation types and developing instructional strategies of wiki-based collaborative learning by considering learners’ goal orientation and self-esteem. The Korean Journal of Educational Methodology Studies, 22(4), 43–66.

Levine, J. M., & Moreland, R. L. (1994). Group socialization: Theory and research. European Review of Social Psychology, 5(1), 305–336. https:// doi.org/10.1080/14792779543000093

Levine, J. M., & Moreland, R. L. (2004). Collaboration: The social context of theory development. Personality and Social Psychology Review, 8(2), 164–172. https://doi.org/10.1207/s15327957pspr0802_10

Levine, J. M., Moreland, R. L., & Choi, H.-S. (2001). Group socialization and newcomer innovation. In M. Hogg & R. S. Tindale (Eds.), Black- well handbook of social psychology: Group processes (pp. 86–106). Blackwell.

Liden, R. C., Wayne, S. J., Jaworski, R. A., & Bennett, N. (2004). Social loafing: A field investigation. Journal of Management, 30(2), 285–304. https://doi.org/10.1016/j.jm.2003.02.002

Lim, J. Y., & Lim, K. Y. (2020). Co-regulation in collaborative learning: Grounded in achievement goal theory. International Journal of Educa- tional Research, 103(3), 101621. https://doi.org/10.1016/j.ijer.2020.101621

Locke, E. A., Shaw, K. N., Saari, L. M., & Latham, G. P. (1981). Goal set- ting and task performance: 1969–1980. Psychological Bulletin, 90(1), 125–152. https://doi.org/10.1037/0033-2909.90.1.125

Lord, R. G. (1985). An information processing approach to social percep- tions, leadership, and behavioral measurement in organizations. Research in Organizational Behavior, 7, 87–128.

Loughry, M. L., Ohland, M. W., & Moore, D. D. (2007). Development of a theory-based assessment of team member effectiveness. Educational and Psychological Measurement, 67(3), 505–524. https://doi.org/10 .1177/0013164406292085

Madjar, N., Kaplan, A., & Weinstock, M. (2011). Clarifying mastery-avoid- ance goals in high school: Distinguishing between intrapersonal and task- based standards of competence. Contemporary Educational Psychology, 36(4), 268–279. https://doi.org/10.1016/j.cedpsych.2011.03.003

Malmberg, J., Järvelä, S., & Järvenoja, H. (2017). Capturing temporal and sequential patterns of self, co- and socially shared regulation in the con- text of collaborative learning. Contemporary Educational Psychology, 49(1), 160–174. https://doi.org/10.1016/j.cedpsych.2017.01.009

Malmberg, L. E., & Martin, A. J. (2019). Processes of students’ effort exertion, competence beliefs and motivation: Cyclic and dynamic effects

TAKING A FREE RIDE 731

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

of learning experiences within school days and school subjects. Contem- porary Educational Psychology, 58, 299–309. https://doi.org/10.1016/j .cedpsych.2019.03.013

Mathieu, J. E., & Rapp, T. L. (2009). Laying the foundation for successful team performance trajectories: The roles of team charters and perform- ance strategies. Journal of Applied Psychology, 94(1), 90–103. https:// doi.org/10.1037/a0013257

Mathieu, J. E., Gallagher, P. T., Domingo, M. A., & Klock, E. A. (2019). Embracing complexity: Reviewing the past decade of team effectiveness research. Annual Review of Organizational Psychology and Organiza- tional Behavior, 6(1), 17–46. https://doi.org/10.1146/annurev-orgpsych -012218-015106

Mathieu, J. E., Maynard, M. T., Rapp, T. L., & Gilson, L. L. (2008). Team effectiveness 1997-2007: A review of recent advancements and a glimpse into the future. Journal of Management, 34(3), 410–476. https://doi.org/10.1177/0149206308316061

McCardle, L., & Hadwin, A. F. (2015). Using multiple, contextualized data sources to measure learners’ perceptions of their self-regulated learning. Metacognition and Learning, 10(1), 43–75. https://doi.org/10 .1007/s11409-014-9132-0

Michaelsen, L., Bauman Knight, A., & Fink, L. D. (Eds.). (2004). Team- based learning: A transformative use of small groups in college teach- ing. Stylus.

Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals: Good for what, for whom, under what circumstances, and at what cost? Journal of Educational Psychology, 93(1), 77–86. https://doi.org/ 10.1037/0022-0663.93.1.77

Morgeson, F. P., Reider, M. H., & Campion, M. A. (2005). Selecting indi- viduals in team settings: The importance of social skills, personality characteristics, and teamwork knowledge. Personnel Psychology, 58(3), 583–611. https://doi.org/10.1111/j.1744-6570.2005.655.x

Muis, K. R., & Edwards, O. (2009). Examining the stability of achieve- ment goal orientation. Contemporary Educational Psychology, 34(4), 265–277. https://doi.org/10.1016/j.cedpsych.2009.06.003

Mulvey, P. W., & Klein, H. J. (1998). The impact of perceived loafing and collective efficacy on group goal processes and group performance. Organizational Behavior and Human Decision Processes, 74(1), 62–87. https://doi.org/10.1006/obhd.1998.2753

Newman, R. S., & Schwager, M. T. (1995). Students’ help seeking during problem solving: Effects of grade, goal, and prior achievement. Ameri- can Educational Research Journal, 32(2), 352–376. https://doi.org/10 .3102/00028312032002352

Oliveira, A. W., & Sadler, T. D. (2008). Interactive patterns and conver- gence of meaning during student collaborations in science. Journal of Research in Science Teaching, 45(5), 634–658. https://doi.org/10.1002/ tea.20211

Patrick, H. S., Van Joolingen, W. R., Savelsbergh, E. R., & van Hout- Wolters, B. (2008). Motivation and performance within a collaborative computer-based modelling task: Relations between students’ achieve- ment goal orientation, self-efficacy, cognitive processing, and achieve- ment. Contemporary Educational Psychology, 33(1), 58–77. https://doi .org/10.1016/j.cedpsych.2006.12.004

Payne, S. C., Youngcourt, S. S., & Beaubien, J. M. (2007). A meta-analytic examination of the goal orientation nomological net. Journal of Applied Psychology, 92(1), 128–150. https://doi.org/10.1037/0021-9010.92.1.128

Pearsall, M. J., Ellis, A. P. J., & Bell, B. S. (2010). Building the infrastruc- ture: The effects of role identification behaviors on team cognition de- velopment and performance. Journal of Applied Psychology, 95(1), 192–200. https://doi.org/10.1037/a0017781

Piezon, S., & Ferree, W. (2008). Perceptions of social loafing in online learning groups: A study of public university and U.S. Naval War Col- lege students. International Review of Research in Open and Distance Learning. Advance online publication. https://doi.org/10.19173/irrodl .v9i2.484

Pintrich, R. R. (2000). Multiple goals, multiple pathways: The role of goal orientation in learning and achievement. Journal of Educational Psy- chology, 92(3), 544–555. https://doi.org/10.1037//0022-O663.92.3.544

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Poortvliet, P. M., Janssen, O., Van Yperen, N. W., & Van de Vliert, E. (2009). The joint impact of achievement goals and performance feed- back on information giving. Basic and Applied Social Psychology, 31, 197–209. https://doi.org/10.1080/01973530903058276

Poortvliet, P. M., Anseel, F., Janssen, O., Van Yperen, N. W., & Van de Vliert, E. (2012). Perverse effects of other-referenced performance goals in an information exchange context. Journal of Business Ethics, 106(4), 401–414. https://doi.org/10.1007/s10551-011-1005-8

Poortvliet, P. M., Janssen, O., Van Yperen, N. W., & Van de Vliert, E. (2009). Low ranks make the difference: How achievement goals and ranking information affect cooperation intentions. Journal of Experi- mental Social Psychology, 45(5), 1144–1147. https://doi.org/10.1016/j .jesp.2009.06.013

Poortvliet, P. M., Janssen, O., Van Yperen, N. W., & Van de Vliert, E. (2007). Achievement goals and interpersonal behavior: How mastery and performance goals shape information exchange. Personality and Social Psychology Bulletin, 33(10), 1435–1447. https://doi.org/10.1177/ 0146167207305536

Price, K. H., Harrison, D. A., & Gavin, J. H. (2006). Withholding inputs in team contexts: Member composition, interaction processes, evaluation structure, and social loafing. Journal of Applied Psychology, 91(6), 1375–1384. https://doi.org/10.1037/0021-9010.91.6.1375

Pritchard, R. D., Harrell, M. M., DiazGranados, D., & Guzman, M. J. (2008). The productivity measurement and enhancement system: A meta-analysis. Journal of Applied Psychology, 93(3), 540–567. https:// doi.org/10.1037/0021-9010.93.3.540

Raes, E., Kyndt, E., Decuyper, S., Van den Bossche, P., & Dochy, F. (2015). An exploratory study of group development and team learning. Human Resource Development Quarterly, 26(1), 5–30. https://doi.org/ 10.1002/hrdq.21201

Ramos, A., De Fraine, B., & Verschueren, K. (2021). Learning goal orien- tation in high-ability and average-ability students: Developmental trajec- tories, contextual predictors, and long-term educational outcomes. Journal of Educational Psychology, 113(2), 370–389. https://doi.org/10 .1037/edu0000476

Reeve, J. (2015). Understanding motivation and emotion (6th ed.). Wiley. Rogat, T., & Linnenbrink-García, L. (2011). Socially shared regulation in

collaborative groups: An analysis of the interplay between quality of social regulation and group processes. Cognition and Instruction, 29(4), 375–415. https://doi.org/10.1080/07370008.2011.607930

Rolland, R. G. (2012). Synthesizing the evidence on classroom goal struc- tures in middle and secondary schools: A meta-analysis and narrative review. Review of Educational Research, 82(4), 396–435. https://doi .org/10.3102/0034654312464909

Saab, N., Van Joolingen, W. R., & Van Hout-Wolters, B. (2012). Support of the collaborative inquiry learning process: influence of support on task and team regulation. Metacognition and Learning, 7(1), 7–23. https://doi.org/10.1007/s11409-011-9068

Salas, E., Stagl, K. C., Burke, C. S., & Goodwin, G. F. (2007). Fostering team effectiveness in organizations: Toward an integrative theoretical framework. In B. Shuart, W. Spaulding, & J. Poland (Eds.), Modeling complex systems (pp. 185–243). University of Nebraska Press.

Schippers, M. C. (2014). Social loafing tendencies and team performance: The compensating effect of agreeableness and conscientiousness. Acad- emy of Management Learning & Education, 13(1), 62–81. https://doi .org/10.5465/amle.2012.0191

732 GABELICA, DE MAEYER, AND SCHIPPERS

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.

Schippers, M. C., Homan, A. C., & van Knippenberg, D. L. (2013). To reflect or not to reflect: Prior team performance as a boundary condition of the effects of reflexivity on learning and final team performance. Journal of Organizational Behavior, 34(1), 6–23. https://doi.org/10 .1002/job.1784

Schippers, M. C., & Scheepers, A. W. A. (2020). Individual motivation, team learning and performance in collaborative academic contexts. In S. J. Karau (Ed.), Individual motivation within groups: Social loafing and motivation gains in work, academic, and sports teams (pp. 81–108). Academic Press. https://doi.org/10.1016/B978-0-12-849867-5.00003-3

Simms, A., & Nichols, T. (2014). Social loafing: A review of the literature. Journal of Management Policy and Practice, 15(1), 58.

Skilton, P. F., Forsyth, D., & White, O. J. (2008). Interdependence and integration learning in student project teams: Do team project assign- ments achieve what we want them to? Journal of Marketing Education, 30(1), 57–65. https://doi.org/10.1177/0273475307312198

Skinner, E. A., Kindermann, T. A., Connell, J. P., Wellborn, J. G. (2009). Engagement and disaffection as organizational constructs in the dynam- ics of motivational development. In K. R. Wenzel & A. Wigfield (Eds.), Educational psychology handbook series. Handbook of motivation at school (p. 223–245). Routledge/Taylor & Francis Group.

Slavin, R. E. (2011). Instruction based on co-operative learning. In R. Mayer (Ed.), Handbook of research on learning and instruction (pp. 344–360). Taylor and Francis.

Stark, E. M., Shaw, J. D., & Duffy, M. K. (2007). Preference for group work, winning orientation, and social loafing behavior in groups. Group & Organization Management, 32(6), 699–723. https://doi.org/10.1177/ 1059601106291130

Tan, H. H., & Tan, M. L. (2008). Organizational citizenship behavior and social loafing: The role of personality, motives, and contextual factors. The Journal of Psychology, 142(1), 89–108. https://doi.org/10.3200/ JRLP.142.1.89-112

Tan, H. H., & Tan, M. L. (2008). Cooperation versus competition effects on information sharing and use in group decision-making. Social and Personality Psychology Compass, 142(1), 89–467.

Toma, C., & Butera, F. (2015). Cooperation versus competition effects on information sharing and use in group decision making. Social and Per- sonality Psychology Compass, 9(9), 455–467. https://doi.org/10.1111/ spc3.12191

Tuckman, B. W., & Jensen, M. A. C. (1977). Stages of small-group devel- opment revisited. Group & Organization Studies, 2(4), 419–427. https:// doi.org/10.1177/105960117700200404

Urdan, T., & Kaplan, A. (2020). The origins, evolution and future direc- tions of achievement goal theory. Contemporary Educational Psychol- ogy, 61, 101862https://doi.org/10.1016/j.cedpsych.2020.101862

Van den Bossche, P., Gijselaers, W., Segers, M., Woltjer, G., & Kirschner, P. A. (2011). Team Learning: Building Shared Mental Models. Instruc- tional Science, 39(3), 283–301. https://doi.org/10.1007/s11251-010-9128-3

van Dick, R., Tissington, P. A., & Hertel, G. (2009). Do many hands make light work? How to overcome social loafing and gain motivation in

work teams. European Business Review, 21(3), 233–245. https://doi.org/ 10.1108/09555340910956621

Vangrieken, K., Dochy, F., & Raes, E. (2016). Team learning in teacher teams: Team entitativity as a bridge between teams-in-theory and teams- in-practice. European Journal of Psychology of Education, 31(3), 275–298. https://doi.org/10.1007/s10212-015-0279-0

Veenman, S., Denessen, E., van den Akker, A., & van der Rijt, J. (2005). Effects of co-operative learning program on the elaborations of students during help seeking and help-giving. American Educational Research Journal, 42(1), 115–115. https://doi.org/10.3102/00028312042001115

Volet, S., & Mansfield, C. (2006). Group work at university: Significance of personal goals in the regulation strategies of students with positive and negative appraisals. Higher Education Research & Development, 25(4), 341–356. https://doi.org/10.1080/07294360600947301

Volet, S. E., Summers, M., & Thurman, J. (2009). High-level co-regulation in collaborative learning: How does it emerge and how is it sustained? Learning and Instruction, 19(2), 128–143. https://doi.org/10.1016/j .learninstruc.2008.03.001

Webb, N., & Cullian, L. (1983). Group interaction and achievement in small groups: Stability over time. American Educational Research Jour- nal, 20(3), 411–423. https://doi.org/10.3102/00028312020003411

Webb, N. M., Nemer, K. M., Chizhik, A. W., & Sugrue, B. (1998). Equity issues in collaborative group assessment: Group composition and per- formance. American Educational Research Journal, 35(4), 607–651. https://doi.org/10.3102/00028312035004607

Webb, N., & Farivar, S. (1994). Promoting helping behavior in co-opera- tive small groups in middle school mathematics. American Educa- tional Research Journal, 31(2), 369–396. https://doi.org/10.3102/ 00028312031002369

Weinberger, A., Stegmann, K., & Fischer, F. (2007). Knowledge conver- gence in collaborative learning: Concepts and assessment. Learning and Instruction, 17(4), 416–426. https://doi.org/10.1016/j.learninstruc.2007 .03.007

Wiese, C. W., & Burke, C. S. (2019). Understanding Team Learning Dy- namics Over Time. Frontiers in Psychology, 10, 1417. https://doi.org/10 .3389/fpsyg.2019.01417

Williams, K., Harkins, S., & Latane, B. (1981). Identifiability as a deter- rent to social loafing: Two cheering experiments. Journal of Personality and Social Psychology, 40(2), 303–311. 0022-3514/814002-0303100.

Wilson, J. M., Goodman, P. S., & Cronin, M. (2007). Group learning. Academy of Management Review, 32(4), 1041–1059. https://doi.org/10 .5465/amr.2007.26585724

Zhu, M., Singh, S., & Wang, H. (2019). Perceptions of social loafing dur- ing the process of group development. International Journal of Organi- zation Theory and Behavior, 22(4), 350–368. https://doi.org/10.1108/ IJOTB-04-2018-0049

Received August 19, 2020 Revision received July 10, 2021

Accepted August 17, 2021 n

TAKING A FREE RIDE 733

T hi s do cu m en ti s co py ri gh te d by

th e A m er ic an

Ps yc ho lo gi ca lA

ss oc ia tio

n or

on e of

its al lie d pu bl is he rs .

T hi s ar tic le is in te nd ed

so le ly

fo r th e pe rs on al us e of

th e in di vi du al us er

an d is no tt o be

di ss em

in at ed

br oa dl y.