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Abstract

Schools worldwide are implementing team structures as means to cope with ever increasing and changing demands, such as more diverse student population and calls for digitalization. For teams to be effective, team learning is needed. However, research shows that this requires a dramatical change in teachers’ attitude and behaviour. The current study examines to what degree and how Team-based Human Resources Management (THRM)—referring to HR practices targeted at enhancing teachers’ abilities, their motivation and opportunities to engage in team learning—can stimulate team learning within teams, specifically teachers’ engagement in information processing and boundary crossing. Analyses of three waves of survey data, among over 600 teachers working in Dutch institutions for vocational education and training, show that THRM indeed contributes to team learning. Not all but specific THRM practices – e.g., acknowledging individuals’ contribution to team achievements - were positively related to the initial levels of team learning and both forms of team learning appeared to reinforce change in the other. THRM practices thus indirectly affected change in team learning by activating the initial levels of each learning activity. The findings conclude with theoretical implications and formulate practical recommendations for school leaders.

Keywords

Team learning information processing boundary crossing team-based human resources management (THRM)longitudinal survey study

Schools all over the world are faced with ever-changing demands, including a more complex and diverse student population, increasing pressure regarding academic achievement and equal chances for every student, and calls for greater digitalization (e.g., Lochmiller and Mancinelli, 2019; Skaalvik and Skaalvik, 2011). Meanwhile, team structures have been adopted in many schools (e.g., Haapaniemi et al., 2021;Watzek and Mulder, 2019), as distributed leadership allow greater organizational adaptability than centralised leadership (Harris, 2009). Adapting to these changes requires teachers to continually engage in learning activities (Hargreaves, 2019; Sun et al., 2017). As a result, there is a renewed focus on how to facilitate learning within teacher teams (Author, 2014; DeCuyper et al., 2010; Somech and Naamneh, 2019).

Team learning refers to team members’ collective engagement in activities that contribute to building and maintaining mutually shared cognitions, which supports team performance (cf. van den Bossche et al., 2011). Team learning occurs during intensive collaboration (DeCuyper et al., 2010). It includes both intentional learning activities (e.g., team evaluations and feedback) and incidental learning that occurs as a by-product of working together (Tynjälä, 2008). Opportunities for team learning are important, as they have been linked with outcomes such as teacher well-being, job satisfaction and student engagement (Shoshani & Eldor, 2016) and teacher team performance (author, 2019a). In this paper, we focus on the specific learning activities of information processing and boundary crossing, as these two activities reflect learning that occurs both within and between teams.

While its importance is widely acknowledged, stimulating team learning is a challenging task for several reasons (e.g., Somech and Drach-Zahavy, 2007; Vangrieken et al., 2015). First, teachers have traditionally worked in relative isolation and have focused on their own teaching responsibilities, some teachers are unaccustomed to collaboration and team learning (Vangrieken et al., 2015). Second, some teachers are less focused on team goals and less aware of the benefits of team learning for their classroom practice (Beverborg et al., 2015). Third, as team learning sometimes involves a critical evaluation of performance, teachers may be discouraged from it if it exposes them to criticism, disagreement or even conflict (Vangrieken et al., 2015). Fourth, teachers increasingly experience an overload of additional, mostly administrative, tasks (e.g., Ingersoll et al. 2016). Due to the increased time pressure and workload, teachers often find it difficult to reserve time for their professional development, including team learning (Vangrieken et al., 2015). Finally, the increased diversity in teacher teams, both in terms of functional as well as demographical characteristics, may engender various types of conflict thereby hindering collaboration (Mintrop and Charles, 2017).

Given these challenges, facilitating team learning among teachers has emerged as a significant research topic in the fields of teacher education (e.g., Tołwińska, 2019) and educational leadership literature as well. Concerning the latter, attention is for instance paid to the roles team leaders play in fostering an organizational culture wherein team members are encouraged to engage in team learning (Polega et al., 2019), to school leaders adopting a transformational leadership style fostering the feelings of collective responsibility in teacher teams as prerequisite for collective learning (Vanblaere and Devos, 2016) and to leadership roles taken on by team members (Ranta et al., 2023). Less attention though is paid to ‘HR roles’ of team leaders, with team leaders referring to people holding personnel responsibility of teams, such as the principals or school leaders and who are the main executors of the personnel policies implemented in schools (author, 2019b). With teacher quality being the key factor in achieving all school goals, human resources management and development is at the heart of all leadership practices (Davis and Fowler, 2020) and thus deserves more attention in research (Tuytens et al., 2023). Hence, in this paper, we address the topic of team learning among teachers from a Human Resource Management (HRM) perspective and explore how team-based HRM (THRM) practices can facilitate team learning. In doing so, we expect to provide new theoretical insights into team leaders’ roles in stimulating team learning and to provide practical recommendations with regard to leadership practice.

Research question

The central question addressed by this paper is: to what extent can team learning be facilitated among teaching teams? In this study, we focus on the role of THRM practices, referring to a set of HRM practices intended to support team functioning and enhance team performance (Chuang et al., 2016). Drawing on the Ability, Motivation and Opportunities theory (AMO; Appelbaum et al., 2001; Jiang et al., 2012), we propose that THRM practices intended to enhance teachers’ abilities, their motivation and opportunity to engage in team learning (author, 2019a) will facilitate team learning, in particular information processing and boundary crossing.

Contribution

While positive effects of HRM have been researched extensively with respect to HRM practices at the employee level, there has been relatively little emphasis on team-based HRM practices and learning (Ren et al., 2021) with some notable exceptions, such as the work by Chi et al. (2009) and Flinchbaugh et al. (2016). Likewise, although HRM is increasingly being studied in the educational literature as well (e.g., Knies & Leisink, 2018; Vekeman et al., 2019), only few studies have examined the effects of team-based HRM practices. Among the few exceptions focusing on team-based HRM practices (e.g., author, 2019a), most, if not all, studies have employed a cross-sectional research design to investigate the effects of team-based HRM practices on employee outcomes. The cross-sectional design does not provide strong evidence of causality, and cannot answer the question of whether any observed effects are short-lived or enduring. Our study builds on previous research by examining the effects of team-based HRM on team learning via a longitudinal research design. Using a three-wave dataset, we examine the differential effects of each component of team-based HRM on two team learning activities—information processing and boundary crossing—and explore the reciprocal relationships between these two team learning activities to establish their temporal precedence over time.

Theory and hypotheses

HR scholars often draw on human capital theory (Becker, 1975) to explain the positive effects of HRM practices. It states that an organisations’ competitive advantage is largely determined by the knowledge, skills and other talents of the employees (i.e., ‘human capital’) (Boon et al., 2018). Thus, HR practices sustain competitive advantage by helping organisations to attract and retain talented employees (Becker and Huselid, 2006). Translated to our study goal, human capital theory suggests that team learning may be facilitated by enhancing abilities (e.g., by recruitment procedures for selecting employees who are effective collaborators, as well as training and development opportunities for the team), strengthening motivations (e.g, enhancing team members’ commitment to achieving team goals by including evaluations of team performance and individual contributions towards team goals) and enriching opportunities (e.g., by designing shared work tasks to facilitate collaboration within teams and creating forums for greater communication and knowledge exchange between teams) (cf. author, 2018; Gardner 2012). Additionally, THRM practices signal the organisation's expectations and values (such as team learning), thereby guiding employees towards activities (such as teachers’ engagement in information processing or boundary crossing) that support the organisation's goals (e.g., author, 2022; Ostroff and Bowen, 2016).

We expect that all three types of THRM practices can in some way support teachers’ engagement in team learning activities. For example, we expect that with the ability-enhancing practices of selective hiring and team-training and -development a message is sent about the value that is attached to teamwork which will in turn stimulate teachers to engage in it. Furthermore, motivation enhancing practices of individual and team reward are expected to provide the inducement for teachers to direct their efforts toward their teams’ goals and therefore stimulate team learning. Finally, opportunity enhancing practices are expected to empower teachers to actually engage in team learning (cf Ogbonnaya and Messersmith, 2019). Although literature increasingly shows differential effects of the various practices on outcome variables, we do not further formulate specific hypotheses about the relative impact of each subset of THRM practices on the two forms of team learning we focus on (i.e., information processing and boundary crossing). Doing so would result in six times two hypotheses which are difficult to underpin with theory. That is, there is not much theory available on the effects of THRM practices on team learning, let alone the two specific forms of team learning we study in the educational context. So instead, we examine the differential effects of each type of THRM practice on an exploratory basis and will elaborate on possible differences in the discussion section. Aligning ourselves to the ‘process model’ of HRM (Nishii and Paluch, 2018)—which suggests that the way teachers perceive policies and practices, such as THRM, determines how they will respond to them in terms of their willingness and capability to engage in team learning—we propose the following general hypothesis:
Hypothesis 1: Team members’ perceptions of team-based HRM practices will positively affect their engagement in (a) information processing and (b) boundary crossing over time.

According to DeCuyper et al. (2010), information processing is concerned with problem solving, reflection and knowledge sharing among team members. For example, information processing could involve teachers working together to develop new pedagogical learning formats or exchange feedback and advice. Boundary crossing involves the exchange of information and ideas with people external to the team. For example, boundary crossing could involve teachers asking stakeholders (e.g., experts, colleagues from other teams) for information, advice or feedback (author, 2018).

Although information processing and boundary crossing are identified as two different activities, it is to be expected that they may reinforce each other over time. For example, if team members have acquired new knowledge from outside of their group, they may share it with their team members (Somech and Naamneh, 2019). On the other hand, team members may seek independent feedback from people outside of their team on ideas or materials they have developed together with other colleagues within their team (e.g., Kayes et al., 2005; Timperley et al., 2017). For these reasons, we propose that these two activities are connected to and reinforce each other over time.
Hypothesis 2: Two types of team learning activities, information processing and boundary crossing will reinforce each other over time.

Method

Research context

Data were collected among teacher teams in vocational education and training (VET) in the Netherlands. This context was chosen for this study because in VET teacher teams are regarded as the basic organisational unit that is responsible for the quality of education (VET Council, 2009). Teacher teams have the authority to make decisions about their educational process, didactics, and pedagogy, if they adhere to legal requirements and the VET college's policy framework. Because these VET teacher teams are multidisciplinary in nature, teachers need to combine their expertise and collaborate with each other to achieve high quality education (Author, 2018). The government and school boards have been active implementing Human Resources Management (HRM) practices to facilitate teachers’ engagement in professional development activities (Author, 2013) and they recently started to develop and implement team based HRM practices as well (Author, 2018).

Procedure

Data were collected through an online survey as part of a larger study on teachers’ team learning in vocational education and training (VET) in the Netherlands. For the current study samples of three waves of data were used, gathered in three consecutive years namely 2014, 2015 and 2016. To obtain these samples, team leaders at every VET college in the Netherlands were contacted and asked to participate with their teams in our research. After agreement, teachers of their teams were sent an email with a personal invitation to participate in the research and were informed on how data would be processed and stored anonymously. By participating teachers gave informed consent.

Participants

A total of 994 teachers participated in wave 1 (response rate: 60.24%), 763 in wave 2 (response rate: 76.76%), and 601 in wave 3 (response rate: 60.46%). There were 531 participants who participated in both waves 1 and 2, 390 participants in waves 2 and 3, and 372 in waves from 1 to 3. The sample sizes vary over the years because of teacher and team dropouts due to staff turnover, heavy workload or because some teams were disbanded. At wave 1, the sample consisted of 52.8% women; the average age was 47.1 years (SD = 11.4); the average years of tenure was 10.9 (SD = 9.6). The most typical level of education reported was higher professional education (HBO; 71.0%), followed by middle-level applied education (MBO; 11.2%), scientific education (WO; 10.3%), and other (7.4%).

Measures

All measurements were assessed using five-point Likert scales (1 = never to 5 = always). Although all concepts focus on team-level processes, they are measured at the individual level through individual teacher's perceptions of these team-level processes. Each measure was found to be reliable (Cronbach's alpha ≥ 0.70). Reliability coefficients are presented in Table 1, and a full list of items is presented in Supplement 1.

Table 1.
Means, standard deviations and correlations Among variables.

1 2 3 4 5 6 7 8 9 10 11 12

Wave 1 (n = 994)

1. Recruitment (0.95) 0.43* 0.53* 0.54* 0.33* 0.38* 0.42* 0.00 0.34* 0.01 0.38* 0.01

2. Developmental Opportunity 0.41* (0.94) 0.48* 0.55* 0.58* 0.62* 0.43* 0.08 0.35* 0.04 0.33* 0.08

3. Individual Performance Evaluation 0.52* 0.51* (0.95) 0.69* 0.38* 0.42* 0.47* 0.15* 0.41* 0.10* 0.38*** 0.13*

4. Team Performance Evaluation 0.52* 0.58* 0.66* (0.95) 0.42* 0.49* 0.41* 0.05 0.38* 0.04 0.34* 0.00

5. Collaboration Between Teams 0.33* 0.59* 0.38* 0.42* (0.92) 0.51* 0.35* 0.16* 0.32* 0.11* 0.28*** 0.12*

6. Collaboration Within Team 0.36* 0.59* 0.40* 0.47* 0.51* (0.92) 0.49* 0.03 0.44* 0.06 0.41* 0.06

7. Information Processing 0.40* 0.40* 0.44* 0.38* 0.34* 0.46* (0.89) 0.23* 0.73* 0.20* 0.66* 0.21***

8. Boundary Crossing 0.02 0.07* 0.14* 0.05 0.13* 0.03 0.21* (0.79) 0.18* 0.70* 0.20* 0.69*

Wave 2 (n = 763)

9. Information Processing 0.33* 0.34* 0.39* 0.36* 0.31* 0.42* 0.66* 0.16* (0.89) 0.25* 0.79* 0.22*

10. Boundary Crossing 0.04 0.04 0.10* 0.05 0.11* 0.07 0.19* 0.58* 0.25* (0.79) 0.24* 0.69*

Wave 3 (n = 601)

11. Information Processing 0.36* 0.33* 0.36* 0.33* 0.30* 0.38* 0.60* 0.20* 0.71* 0.22* (0.89) 0.30*

12. Boundary Crossing 0.03 0.08 0.11* 0.00 0.13* 0.05 0.19* 0.57* 0.20* 0.59* 0.28*** (0.82)

Mean (below diagonal) 3.09 2.74 3.05 3.01 2.88 2.85 2.97 2.42 3.02 2.43 3.08 2.42

SD (above diagonal) 0.97 0.76 0.89 0.88 0.60 0.70 0.61 0.60 0.62 0.58 0.60 0.60

SD (below diagonal) 1.02 0.82 0.92 0.95 0.80 0.79 0.67 0.70 0.68 0.69 0.65 0.70

Note. Total n = 1365. * p < 0.05, p < 0.01, * p < 0.001. Cronbach's alpha reliability coefficient is presented in the diagonal. Observed variable correlations are presented below the diagonal; latent variable correlations from the confirmatory factor analysis (the scalar invariance model) are presented above.

Boundary crossing (four items) was measured using the translated scale of Wong (2004). A referent shift from ‘our team’ to ‘I’ was used on all items, because boundary crossing is regarded as an individual team member activity and not as an activity undertaken by the team as a collective. This has to do with the specific context of this study where VET teachers all fulfill different roles in their teams and thus meet different outsiders in their professional networks. As a result, they may ask different outsiders for advice (Author, 2018). An example item is, ‘I seek feedback about the team's work from people external to the team’.

Information processing was measured using an adaptation of nine items of the team learning instrument of Van Offenbeek (2001), which was validated in previous research (Author, 2018; Wijnia et al., 2016). Information processing was measured as a collective team activity in line with its definition. An example item of information processing is, ‘In my team we challenge each other to look at our work in new ways’.

Team-based THRM practices were measured with the instrument developed by Author, 2018). This instrument measured all THRM practices from three aspects: ability- motivation- and opportunity-enhancing THRM practices. Each aspect consists of two sub-scales and each subscale consists of five items. These THRM practices are similar to those measured in other studies (e.g., Chuang et al., 2016) except that we focused on team-based instead of individual employee-based HR practices. Regarding the Ability-enhancing THRM practices, the survey included scales of team-based recruitment (example item: “ When recruiting new members for my team [from within or outside the organisation], the following is taken into account:….their ability to work in a team”) and team-based development opportunities (example item: “The organisation offers my team development opportunities [inside or outside our organisation], aimed at:…. the learning needs of my team”). Regarding Motivation-enhancing THRM practices, it included scales of team-based performance evaluation for individuals (example item: “During my evaluation, the following is taken into account:…my contribution to team achievements”) and teams (example item: “During the evaluation of my team, the following is taken into account:…the performance of my team”). Finally, regarding the Opportunity-enhancing practices, scales of collaboration inside teams (example item: “This organisation makes it possible for my team to: … work together on our team tasks”) and collaboration between teams (example item: “The organisation makes it possible for my team to: … . share experiences with colleagues outside of the team”) were used.

The items of all scales used in the study as well as the factor loadings of items can be found in the supplementary materials.

Results

Descriptive analyses

All analyses were performed in Mplus 8.7 (Muthén & Muthén, 2017) using the Maximum Likelihood Robust (MLR) estimator. Descriptive statistics, including means, standard deviations and correlations among the variables, are presented in Table 1. All of the HR practices were positively and significantly correlated with information processing. Only recruitment and collaboration between teams were correlated with boundary crossing. Over time, both information processing and boundary crossing remained relatively but not perfectly stable, with autocorrelations (i.e., the correlation between each measure at different waves) ranging from .58 to .71 (all significant).

To verify the measurement structure of the scales, we performed a series of confirmatory factor analyses, which are presented in Supplement 1.

Tests of hypotheses

We tested our hypotheses using a parallel process growth curve model (PPCM), which is depicted in Figure 1. In a PPCM, growth trajectories between two or more variables are modelled over time. In our PPCM, we investigated the trajectories of information processing and boundary crossing over the three waves.

Figure 1.
Hypothesized model linking team-based HRM to two forms of team learning (information sharing and boundary crossing).

Each trajectory is represented with two latent variables, including a latent intercept, which represents each participant's initial levels of each variable at the first wave, and a latent slope, which represents each person's degree of subsequent change in the variable as a function of time. The latent intercepts of each variable are used to predict the latent slopes of the other variables. Thus, in our PPCM, we used the initial levels of information processing (intercept) to predict the degree of change in boundary crossing (slope), and the initial levels of boundary crossing (intercept) to predict the degree of change in information processing (slope). The PPCM provides strong evidence of causation between variables, as the study design examines intraindividual changes across time, and the initial levels of each variable and levels of change are separated in time. The results of this model are presented in Table 2.

Table 2.
Predictors of information processing and boundary crossing.

Information Processing (Within Teams) Boundary Crossing (Between Teams)

Intercept Slope Intercept Slope

Constant
Ability-Enhancing Practices 0.00 (0.00) 0.05* (0.01) 0.00 (0.00) 0.00 (0.01)

Recruitment 0.09* (0.03) 0.00 (0.02) −0.06 (0.03) 0.00 (0.02)

Development Opportunities
Motivation-Enhancing Practices 0.04 (0.04) −0.03 (0.03) −0.02 (0.05) 0.00 (0.03)

Performance Evaluation (Individual) 0.17* (0.04) −0.04 (0.03) 0.16* (0.04) −0.02 (0.03)

Performance Evaluation (Team)
Opportunity-Enhancing Practices −0.02 (0.04) 0.02 (0.03) −0.07 (0.04) −0.02 (0.03)

Collaboration Within Teams 0.25*** (0.04) −0.01 (0.03) −0.04 (0.05) 0.01 (0.03)

Collaboration Between Teams
Reciprocal Relationships 0.05 (0.04) −0.02 (0.03) 0.18 (0.05) −0.05 (0.04)

Information Processing (Intercept) – 0.09 (0.03) – –

Boundary Crossing (Intercept) – – – 0.12** (0.04)

Note. Unstandardized regression coefficients are presented. The model yielded the following fit statistics: model chi-square (χ² = 3874.244) with degrees of freedom (df = 1708; p < 0.000), the comparative fit index (CFI = 0.935), root mean square error of approximation (RMSEA = 0.030) and standardised root mean square residual (SRMR = 0.052). Close model fit is indicated by a non-significant chi-square, CFI > 0.95, RMSEA < 0.06 and SRMR < 0.08 (West, Taylor & Wu, 2012).

Hypothesis 1 proposed that perceptions of team-based HRM practices would positively influence information processing and boundary crossing over time. This hypothesis was partially supported. Three types of THRM practices—recruitment, individual performance evaluation and facilitation of collaboration between teams—are positively related to initial levels of information processing inside teams. Similarly, two types of THRM practices—individual performance evaluation and collaboration between teams—are positively related to boundary crossing. Although the effects of THRM practices on change in information processing and boundary crossing were non-significant, these results indicate that the initial benefits of THRM were sustained over time and remained stable.

Consistent with Hypothesis 2, which proposed that the two types of team learning activities would mutually reinforce each other, we found that the initial levels of each team learning activity predicted change in the other variable. Specifically, we found that the intercept of information processing was positively related to the slope of boundary crossing. Conversely, the intercept of boundary crossing was positively related to the slope of information processing. Collectively, these results indicate a reciprocal, positive relationship between information processing and boundary crossing. These effects are illustrated in Figure 2.

Figure 2.
Reciprocal effects of information processing and boundary crossing over time. Panel A: Effects of Information Processing on Boundary Crossing. Panel B: Effects of Boundary Crossing on Information Processing. Note: The first figure shows the level of boundary crossing over the three waves of data collection at low (−1 standard deviation) and high (+1 standard deviation) initial levels of information processing. The second figure shows the level of information processing at low (−1 standard deviation) and high (+1 standard deviation) initial levels of boundary crossing.

We also conducted additional post-hoc indirect effects analyses to investigate whether initial levels of information processing and boundary crossing mediated the relationship between THRM and change in these outcomes. To perform these analyses, we re-tested the model using 1000 bootstrap samples (Preacher & Hayes, 2008). Significant effects are indicated if the 95% confidence intervals (CI) of the indirect effect size do not include zero. We found that individual performance evaluation (CI: [0.01, 0.28]) and collaboration outside of teams (CI: [0.01, 0.04]) influenced change in information processing via their effects on initial levels of boundary crossing. Similarly, we found that recruitment (CI: [0.003, 0.03]), individual performance evaluation (CI: [0.01, 0.04]), and collaboration inside teams (CI: [0.01, 0.06]) influenced change in boundary crossing via their effects on initial levels of information processing.

Discussion

The aim of our study was to examine if teachers’ team learning—in terms of information processing and boundary crossing—can be facilitated by team-based HRM practices. We conclude that THRM indeed contributes to team learning, but that the relationship among the two is not straightforward. That is, not every THRM practice appeared to have a positive impact on one or both forms of team learning. Moreover, THRM practices were positively related to the initial levels of team learning and none of the HR practices predicted change in team learning. Instead, both forms of team learning appeared to reinforce change in the other. In other words, while THRM did not appear to directly influence change in the two forms of team learning, THRM indirectly affected change by activating the initial levels of each activity.

Theoretical implications

Our study adopted the AMO theory in studying the effects of team-based HRM practices on team learning and found that the separate THRM practices showed differential effects on both forms of team learning. This finding aligns to other empirical studies (e.g., Bello-Pintado, 2015) and HR scholars increasingly try to uncover the underlying mechanisms (e.g., Ogbonnaya and Messersmith, 2019). Explanations for differential effects are, for example, related to different HR practices having different (managerial) goals and as such being perceived differently by employees leading to different attitudinal responses.

Related to our study, an explanation for the differential effects could be found in their impact on the daily practise of teachers. Related to the ability-enhancing practices: while the HR practice of recruitment directly impacts on the composition of teams and as such on the collaboration among team members, the HR practice of team development opportunities, which take place on particular points in time, may have less impact on the daily affairs of teachers. As such, the ‘signalling’ function (Ostroff and Bowen, 2016) of that practice might be less than that of recruitment. Moreover, former studies have shown that professional development of teachers often shows a weak link with their daily practices and learning needs (e.g., van Veen et al., 2012). Another explanation of the fact that team development opportunities appeared not to be related to team learning could be found in the way these opportunities are designed. This suggestion calls for more qualitative research on how HR practices are designed and implemented.

Another explanation of the differential effects of the separate HR practices could be related to the relative relevance of HR practices for teachers. Related to the motivation-enhancing practices: although both forms of performance evaluation (individually-based and team-based) included in the study were team-based (i.e., related to individual's contribution to the team and, respectively, to team performance as a whole) the individual-based performance evaluation may have more impact on teachers since this form may have consequences regarding one's contract or pay. Moreover, studies on performance evaluation in the Netherlands show that individual-based performance evaluation often has a more formal nature than team-based evaluation has (Author, 2018). Therefore, individual-based performance evaluation may be more motivating for teachers to engage in aligned behaviours, such as team learning, than team-based performance evaluation. This finding calls for more research on a possible hierarchy of the sub-elements of HR systems.

Finally, regarding the opportunity-enhancing practices, the differential effects seem more straightforward in the sense that the practices are specifically and directly targeted at enabling the desired behaviour. When teachers perceive more opportunities to engage in information processing, the initial level of information processing which takes place in their teams is also higher. The same applies for initial levels of boundary crossing, which are higher the more teachers perceive opportunities for that activity. This finding suggests that THRM practices can be of a different nature and therefore impact behaviours differently; either directly or via attitudinal responses.

The finding that THRM practices showed differential effects on both forms of team learning, may also be linked to the different nature of the two learning activities. Information processing is seen by several authors (e.g., Burke et al., 2007; Wilson et al., 2007) as a basic team process, or—in other words—as a requirement for improvement or innovation and in itself not per se directed towards a certain change or learning goal. Boundary crossing however is often said to be done with a certain purpose in mind (e.g., Ancona & Caldwell, 1992; Burke et al., 2007). It may be that THRM practices are therefore more influential when it comes to information processing—because it is a certain behaviour which is stimulated—than when it comes to boundary crossing – because this requires a specific goal as well. Moreover, while information processing takes place within the team, boundary crossing forms a bridge among learning that takes place within the team and learning in other teams or the wider organisational or environmental context (DeCuyper et al., 2010). Boundary crossing is therefore potentially more subject to mechanisms or processes that occur on the higher organizational level (such as the overall organisational learning culture) or the level of the wider environment (such as the availability of external experts) than information processing is. Future studies are recommended to include hindering and fostering factors on the supra-team levels playing a role in team learning as well. Moreover, while information processing is inherent a collective activity, boundary crossing is often done by individual team members to bring new insights into the team. Hence, the focus in THRM practices – namely on the individual role within the team or the collective activities – may lead to different messages sent about which type of learning is seen as important (see author, 2017 for more information on the signaling effect of THRM).

Our findings show that THRM practices fuel initial levels of team learning and that, in turn, one form of team learning stimulates change in the other. The reciprocal influence of information processing and boundary crossing makes sense from a practical point of view. For example, the exchange of information or feedback (i.e., information processing) may lead to team members feeling the need to collect additional information or feedback from people outside the team (i.e., boundary crossing). Vice versa, when team members learn new things from colleagues outside the team, it is logical to share new insights within the team. From a theoretical point of view, the finding of the two team learning activities strengthening each other over time, may suggest the existence of ‘gain spirals’, as described by Hobfoll (2002) in the ‘conservation of resources theory’ (COR). COR—often applied by researchers focusing on the effects of (mis)balance among job demands and job resources on the one hand and job outcomes such as work engagement on the other (e.g., Xanthopoulou et al., 2009)—states that human motivation is to obtain, retain and protect resources which help people to reduce demands and to achieve goals and to promote personal growth. Once facilitated by THRM practices, resources such as a particular form of team learning, may lead to certain personal outcomes such as team members’ self-efficacy (e.g., author, 2019a), that in turn motivate people to engage in other forms of team learning as well. Since or study didn’t include personal outcomes, it is hard to tell which outcomes might have played a role, hence we recommend future studies to dig into these motivational processes further.

Finally, another explanation for the finding that TRHM accounts only for the initial stages of both forms of team learning and not for changes in them, we may consider the perpetual effect of learning (e.g., Schein, 1992) meaning that once team learning is initiated, it tends to develop autonomously. External factors (such as TRHM) therefore have a diminished effect. Hence it is crucial to stimulate learning at the outset. Once learning begins, it becomes an internal motivation for the team, making it less influenced by further HRM implementation.

Study limitations

In addition to the study findings, we would like to point out the limitations of this study. First, we relied solely on teachers’ perceptions. Although it is their individual perception of THRM practices which will determine the way they will respond (Nishii and Paluch, 2018), the measurement of their actual response could have been strengthened if other data sources, such as their team leaders’ perceptions, would have been included. That is, the differential effects of THRM practices may be found in the way they are actually designed and executed. Our study focused on teachers’ perceptions of the availability of THRM practices (for example in terms of the degrees to which the ‘organisation offers the team development opportunities … aimed at the learning needs of the team’ or the degree to which ‘during evaluation … the contribution to team achievements is taken into account’) and not so much on their appreciation of how these were designed or offered. Since the congruence among intended, implemented and perceived THRM practices determine their effects, future studies are recommended to include data from the various actors involved in THRM: people who design practices (e.g., HRM practitioners), people who execute them (e.g., team leaders) and, respectively, those who receive them (e.g., teachers).

Secondly, over time, many teachers dropped out of the study for reasons we were not able to investigate. Did those who finished the survey three times a row have a higher interest in team learning than those who dropped out? Or did they have more time than others? To what degree and in what way this unknown fact may have affected the results is unclear. Thirdly, we gathered our data in Dutch VET colleges. Although the context resembles that of most other western countries where schools are increasingly being held accountable for student outcomes and where enhancing teacher quality is at the core of educational policy (OECD, 2023), specific national or sector wide policies may to some extent have had an influence on teachers’ team learning behavior. For example, as explained in the methods section, the Dutch VET colleges implemented team structures whereby teams have gained autonomy when it comes to designing and executing their education. This congruence among HRM policy and organization structure may have strengthened the effects of THRM practices on team learning (cf Boselie et al., 2021). Our results are therefore not generalizable to other educational and national contexts, but show THRM's potential making it worthwhile to experiment with this type of HRM policy in other contexts as well.

Practical implications

The results provide practical implications by showing which THRM elements are especially helpful in stimulating team learning. More specifically, for school leaders to stimulate information processing in teams, it is helpful to recruit new teachers who are willing and able to collaborate with the other team members and who commit themselves to team goals. This can be done for example by stressing the importance of team learning in vacancy texts, by asking candidates about their experiences with team learning and by including team learning skills in assessment procedures. Moreover, school leaders are advised to create opportunities for teams to collaborate within their team, as this fuels information processing in teams. This can be done by offering teachers a place or a room where they can meet or by devoting a fixed time in their schedule to discussion and collaboration with each other. School leaders are also advised to create opportunities to connect to people outside the team, as this fosters boundary crossing. Examples of opportunities are: connecting teachers to experts who are part of the school leaders’ professional network or by inviting experts to the school. Finally, during performance evaluation interviews with team members, it is helpful to explicitly acknowledge their individual contribution to their teams’ performances – for example by expressing appreciation of individual team members’ contribution during the yearly performance interview and by including this topic structurally in evaluation procedures—as this will facilitate both information processing and boundary crossing. Once these forms of learning are activated, they will likely reinforce one another. Finally, in line of the ‘process model’ of HRM (Nishii and Paluch, 2018) referred to earlier, a final recommendation is to involve all relevant actors in the process of designing THRM practices. For example, by holding focus group interviews with team leaders and teachers one can explore their wishes and preferences when it comes to THRM practices and include these in the design.

Supplemental Material

sj-docx-1-ema-10.1177_17411432241313102 - Supplemental material for Promoting team learning in schools: considering the role of team-based HRM practices (THRM)

Supplemental material, sj-docx-1-ema-10.1177_17411432241313102 for Promoting team learning in schools: considering the role of team-based HRM practices (THRM) by Piety Runhaar, Timothy Bednall, Machiel Bouwmans and Huadong Yang in Educational Management Administration & Leadership

	1	2	3	4	5	6	7	8	9	10	11	12
Wave 1 (n = 994)
1. Recruitment	(0.95)	0.43***	0.53***	0.54***	0.33***	0.38***	0.42***	0.00	0.34***	0.01	0.38***	0.01
2. Developmental Opportunity	0.41***	(0.94)	0.48***	0.55***	0.58***	0.62***	0.43***	0.08	0.35***	0.04	0.33***	0.08
3. Individual Performance Evaluation	0.52***	0.51***	(0.95)	0.69***	0.38***	0.42***	0.47***	0.15***	0.41***	0.10*	0.38***	0.13*
4. Team Performance Evaluation	0.52***	0.58***	0.66***	(0.95)	0.42***	0.49***	0.41***	0.05	0.38***	0.04	0.34***	0.00
5. Collaboration Between Teams	0.33***	0.59***	0.38***	0.42***	(0.92)	0.51***	0.35***	0.16***	0.32***	0.11*	0.28***	0.12*
6. Collaboration Within Team	0.36***	0.59***	0.40***	0.47***	0.51***	(0.92)	0.49***	0.03	0.44***	0.06	0.41***	0.06
7. Information Processing	0.40***	0.40***	0.44***	0.38***	0.34***	0.46***	(0.89)	0.23***	0.73***	0.20***	0.66***	0.21***
8. Boundary Crossing	0.02	0.07*	0.14***	0.05	0.13***	0.03	0.21***	(0.79)	0.18***	0.70***	0.20***	0.69***
Wave 2 (n = 763)
9. Information Processing	0.33***	0.34***	0.39***	0.36***	0.31***	0.42***	0.66***	0.16***	(0.89)	0.25***	0.79***	0.22***
10. Boundary Crossing	0.04	0.04	0.10*	0.05	0.11*	0.07	0.19***	0.58***	0.25***	(0.79)	0.24***	0.69***
Wave 3 (n = 601)
11. Information Processing	0.36***	0.33***	0.36***	0.33***	0.30***	0.38***	0.60***	0.20***	0.71***	0.22***	(0.89)	0.30***
12. Boundary Crossing	0.03	0.08	0.11*	0.00	0.13*	0.05	0.19***	0.57***	0.20***	0.59***	0.28***	(0.82)
Mean (below diagonal)	3.09	2.74	3.05	3.01	2.88	2.85	2.97	2.42	3.02	2.43	3.08	2.42
SD (above diagonal)	0.97	0.76	0.89	0.88	0.60	0.70	0.61	0.60	0.62	0.58	0.60	0.60
SD (below diagonal)	1.02	0.82	0.92	0.95	0.80	0.79	0.67	0.70	0.68	0.69	0.65	0.70

	Information Processing (Within Teams)	Boundary Crossing (Between Teams)
Constant Ability-Enhancing Practices	0.00 (0.00)	0.05*** (0.01)	0.00 (0.00)	0.00 (0.01)
Recruitment	0.09*** (0.03)	0.00 (0.02)	−0.06 (0.03)	0.00 (0.02)
Development Opportunities Motivation-Enhancing Practices	0.04 (0.04)	−0.03 (0.03)	−0.02 (0.05)	0.00 (0.03)
Performance Evaluation (Individual)	0.17*** (0.04)	−0.04 (0.03)	0.16*** (0.04)	−0.02 (0.03)
Performance Evaluation (Team) Opportunity-Enhancing Practices	−0.02 (0.04)	0.02 (0.03)	−0.07 (0.04)	−0.02 (0.03)
Collaboration Within Teams	0.25*** (0.04)	−0.01 (0.03)	−0.04 (0.05)	0.01 (0.03)
Collaboration Between Teams Reciprocal Relationships	0.05 (0.04)	−0.02 (0.03)	0.18** (0.05)	−0.05 (0.04)
Information Processing (Intercept)	–	0.09** (0.03)	–	–
Boundary Crossing (Intercept)	–	–	–	0.12** (0.04)

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was funded by NWO-NRO [Dutch Research Council - Netherlands Initiative for Education Research]. File number: 405-17-714/3961; Nationaal Regieorgaan Onderwijsonderzoek, (grant number 411-12-070).

ORCID iDs

Piety Runhaar

Timothy Bednall

Supplemental material

Supplemental material for this article is available online.

Author biographies

Dr. Piety Runhaar works as associate professor at the chair group of Education and Learning Sciences at Wageningen University. Her research focuses on the effects of human resources management and leadership practices on teachers' professional development and wellbeing.

Dr. Timothy Bednall is an Associate Professor of Management at Swinburne University of Technology. Dr Bednall's research focuses on how human resource management practices can be used to promote employee learning, well-being, and learning.

Dr. Machiel Bouwmans works as an assistant professor at the research group Organizations in Digital Transition at the HU University of Applied Sciences Utrecht. His research focuses on interdisciplinary teamwork, and on the impact of disruptive digital technologies on organizations and professionals.

Dr. Huadong Yang is a Reader at the management school of University Liverpool in the UK. His research area is on HR processes including HRM strength and employee HR attributions, employee workplace learning and conflict management.

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	Information Processing (Within Teams)		Boundary Crossing (Between Teams)
	Intercept	Slope	Intercept	Slope
Constant Ability-Enhancing Practices	0.00 (0.00)	0.05*** (0.01)	0.00 (0.00)	0.00 (0.01)
Recruitment	0.09*** (0.03)	0.00 (0.02)	−0.06 (0.03)	0.00 (0.02)
Development Opportunities Motivation-Enhancing Practices	0.04 (0.04)	−0.03 (0.03)	−0.02 (0.05)	0.00 (0.03)
Performance Evaluation (Individual)	0.17*** (0.04)	−0.04 (0.03)	0.16*** (0.04)	−0.02 (0.03)
Performance Evaluation (Team) Opportunity-Enhancing Practices	−0.02 (0.04)	0.02 (0.03)	−0.07 (0.04)	−0.02 (0.03)
Collaboration Within Teams	0.25*** (0.04)	−0.01 (0.03)	−0.04 (0.05)	0.01 (0.03)
Collaboration Between Teams Reciprocal Relationships	0.05 (0.04)	−0.02 (0.03)	0.18** (0.05)	−0.05 (0.04)
Information Processing (Intercept)	–	0.09** (0.03)	–	–
Boundary Crossing (Intercept)	–	–	–	0.12** (0.04)