Fostering innovative learning and satisfaction in virtual teamwork: Shedding light on apprentices

Hiller, Frank; Zarnow, Stefanie Article Fostering innovative learning and satisfaction in virtual teamwork: Shedding light on apprentices International Journal for Research in Vocational Education and Training (IJRVET) Provided in Cooperation with: European Research Network in Vocational Education and Training (VETNET), European Educational Research Association Suggested Citation: Hiller, Frank; Zarnow, Stefanie (2024) : Fostering innovative learning and satisfaction in virtual teamwork: Shedding light on apprentices, International Journal for Research in Vocational Education and Training (IJRVET), ISSN 2197-8646, European Research Network in Vocational Education and Training (VETNET), European Educational Research Association, Bremen, Vol. 11, Iss. 2, pp. 171-199, https://doi.org/10.13152/IJRVET.11.2.2 This Version is available at: https://hdl.handle.net/10419/296185 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-sa/4.0/ International Journal for Research in Vocational Education and Training (IJRVET) 2024, Vol. 11, Issue 2, 171–199 https://doi.org/10.13152/IJRVET.11.2.2 ISSN: 2197-8646 https://www.ijrvet.net Fostering Innovative Learning and Satisfaction in Virtual Teamwork: Shedding Light on Apprentices Frank Hiller*, Stefanie Zarnow Institute for Human Resource Education and Management, LMU Munich School of Management, LMU Munich, Munich, Germany Received: 22 June 2023, Accepted 27 December 2023, Published: 02 April 2024 Abstract Purpose: The digital transformation and the increased use of technologies have changed the world of work severely. With it, collaboration and cooperation methods among employees. Therefore, new ways of working together must be applied to work in an international and digital working environment. For Vocational Education and Training (VET), developing new (transversal) competencies to engage in virtual teamwork is necessary to adequately prepare young professionals for the present and future labor market. However, there is little research on the current situation in VET regarding virtual teamwork. Approach: We deployed a cross-sectional design and collected data from N = 181 commercial apprentices in Germany regarding virtual teamwork. We analyze our data using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the interrelationships between input, process, and outcome variables to foster satisfaction and innovative learning in virtual teams as desired targets of VET. To assess these results regarding virtuality, the complexity of tasks, gender of the apprentices, and the size of the training firms, we derived a multigroup analysis (MGA) of our model. Findings: The results indicate that organizational factors have the most significant influence concerning the relationship between input and process factors. Surprisingly, the technical affinity of individuals has only a minor effect. Regarding the relationship between process *Corresponding author: hi[email protected] 172 Fostering Innovative Learning and Satisfaction in Virtual Teamwork and outcome factors, motivation and responsibility have the highest impact on innovative learning, whilst communication culture severely affects the perceived satisfaction in virtual teamwork. Conclusion: The findings lead to valuable insights on factors influencing virtual teamwork in VET and can help to design learning programs to prepare young professionals to smoothly transition to and successfully master their future working environments by using new ways of collaboration and cooperation. This is particularly relevant for VET, as prior research has focused primarily on primary and secondary education. Lastly, we identify potential scales and items that help capture some of the inherent constructs of virtual teamwork. Keywords: Team Work, Workplace Learning, Collaboration, New Work, Outcomes of Education and Training, Vocational Education and Training, VET 1 Introduction The digital transformation and the increased use of information and communication technologies have changed our daily life in many spheres. Major changes become apparent particularly in the world of work. The rapid transformation of the economy and work processes severely affect how work is performed in organizations (Dobricki et al., 2020; Paeßens et al., 2023). One important change regards the ways of working together: Collaboration in (global) teams in a technology-enhanced working environment is becoming increasingly important (Noble & Billet, 2017; Schlicht, 2019). In addition, the megatrend of globalization growingly requires international, cross-border coordinated behavior. With that, a new mindset to master these challenges is required (Schilirò, 2021) and a new set of (transversal) competencies to collaborate in virtual teams (VT) must be developed. However, virtually working together in teams is a demanding task for both employees and young professionals (Darban, 2022). This puts pressure on Vocational Education and Training (VET): The overarching goal of VET is to prepare young professionals to both smoothly transition in and successfully master their future profession (European Commission, 2013). An increased engagement in virtual teams and the development of corresponding VT-competencies during the apprenticeship has therefore become necessary (Harteis, 2018; Schwendimann et al., 2018). VET acts as a crucial factor to foster this by vocational training either in a school-based way or by training in the firm (Busemeyer & Trampusch, 2012). While substantial research has been undertaken to look at how digital technologies are used in the context of learning and how respective learning outcomes can be fostered, this has predominantly been done in the context of primary and secondary education or higher education. However, the immanent factors that shape VET need to be taken into account to allow for a meaningful and contextual interpretation. Yet, only a very limited number of 173 Frank Hiller, Stefanie Zarnow research analysing the use of digital technologies in VET in a collaborative way can be found (Schwendimann et al., 2018). Therefore, we shed light on how apprentices currently work together in VTs and on the factors which help or hinder cognitive, affective, motivational, and behavioral processes to foster meaningful outcomes for both apprentices and training firms: Satisfaction (SAT) and innovative learning (IL). We focus on these two individual outcomes as these can be best depicted and evaluated by apprentices in a sensitive and meaningful way. We derive three research questions (RQs) to shed light on this phenomenon: RQ1: To what extent has virtual teamwork (VTW) been integrated into VET? RQ2: Which relationships can be identified within the input, process, and outcome factors of VTW in VET? RQ3: How does the model differ in the multigroup analysis regarding gender, virtuality, task complexity (TC), and firm size in VTW? 2 TheoreticalFoundation In order to establish the theoretical basis, the following chapter defines relevant concepts regarding virtuality and virtual teamwork and presents the underlying model to examine the interrelationships of input, process, and outcome factors of VTW to foster satisfaction and innovative learning in virtual teams. 2.1 VirtualityandVirtualTeamwork Defining the concept of a VT is not an easy task, as no uniform definition of the term exists. In the literature, terms such as distributed, computer-mediated, transnational or remote teams are also used to describe VTs (Jacques et al., 2020; Jarrett et al., 2016; Lagerström & Andersson, 2003; Silva & Merino, 2017). When it comes to VTs, scholars often refer to aspects of dispersion and the use of digital media (Dulebohn & Hoch, 2017; Gibson & Gibbs, 2006; O'Leary & Cummings, 2007). The phrase dispersion refers to a geographical, temporal, and structural spreading (O'Leary & Cummings, 2007). Concerning the use of digital media in a VT, Kirkman and Mathieu (2005) identified three dimensions: The extent of the use of virtual tools, the informational value, and the synchronicity. The extent of the use of virtual tools pertains to how much team members depend on digital tools to interact with each other. The informational value specifies the extent to which virtual tools transfer data that are useful for VT effectiveness. Synchronicity encompasses the exchange in a team, which can occur in real time (synchronous), or with a time difference between the interactions 174 Fostering Innovative Learning and Satisfaction in Virtual Teamwork (asynchronous) (Goel et al., 2003). Additionally, the dimensions of diversity, transnationality, and heterogeneity indicate a VT (Earley & Mosakowski, 2000; Zander et al., 2012). However, none of these factors is a prerequisite for a VT status. The transition from a face-to-face team to a VT occurs without a clear boundary. Most teams are located somewhere on the spectrum between the two extremes of a face-to-face team or a solely VT (Griffith et al., 2003; Kirkman & Mathieu, 2004). For this paper, we follow the definition of Hertel et al. (2005, p. 71), who describe a VT as following: "VT consist of (a) two or more persons who (b) collaborate interactively to achieve common goals, while (c) at least one of the team members works at a different location, organization, or at a different time so that (d) communication and coordination is predominantly based on electronic communication media (…)". 2.2 TheInput-Process-OutcomeModelofVirtualTeams The input-process-outcome (IPO) model provides a theoretically based framework for decomposing VTW into its essential components (Dulebohn & Hoch, 2017). The basic framework of the model is derived from the empirically tested model of McGrath (1964). Following this, some modifications exist, such as the approaches taken by Martins et al. (2004), Cohen and Gibson (2003), or Maznevski and Chudoba (2000), who explicitly focus on the collaboration of a VT. Ilgen et al. (2005) adapted the model with regard to the allocation of the process level by assigning concrete subcategories (Ilgen et al., 2005; Marks et al., 2001). Furthermore, feedback loops, which can counteract the static character through their cyclical viewpoint, have been integrated (Hackman & Morris, 1975; Ilgen et al., 2005; Salas et al., 2009). In 2017, Dulebohn and Hoch modified the original model by integrating eight independent, empirical study results that adopt different perspectives regarding the effectiveness of VT. In addition, they incorporated a feedback loop into the model based on Ilgen et al. (2005), as a complex system like a VT can have more than a single cycle (Dulebohn & Hoch, 2017). The intention of the IPO model is to provide a theoretical framework that can be used to identify and categorize selected success factors of VTW and to systematically represent their interconnections and relations (Dulebohn & Hoch, 2017). The model has been employed in the international research context multiple times. References can be found, i.e., for investigating leadership in virtual teams (Bartsch et al., 2020; Wong & Berntzen, 2019), to analyze virtual collaboration during the COVID-19 pandemic (Shockley et al., 2021), or to identify factors affecting team performance (Berber et al., 2020; Kim et al., 2020). 175 Frank Hiller, Stefanie Zarnow Figure 1: Input-Process-Outcome Model of Virtual Teams (own illustration based on virtual teams in organizations from Dulebohn & Hoch, 2017) As visualized in Figure 1, the model is composed of four parts: Input factors, team processes or emergent states, moderators, and outcome factors. The input factors are divided into three categories: The organizational factors (OF), team leadership, and team composition. The OF refer to the organizational design and the objectives of the VT, the working environment, and the structural support (Bell & Kozlowski, 2002; Dulebohn & Hoch, 2017). The team leadership subsumes skills and behavior to compensate for the absence of face-to-face contact to lead a VT successfully. A team leader can apply different leadership concepts, such as transformational leadership or leader member exchange (Hoch & Kozlowski, 2014). The team composition refers to surface-level diversity, such as culture, ethnicity, or language, and to the deep-level diversity, such as the personality traits of VT member and their values. Moreover, the knowledge, skills, and attitudes of a team member constitute the team composition factors (Dulebohn & Hoch, 2017). The team processes and emergent states are dynamic processes that occur when interacting in a VT, whereas the states are team properties, affected by the inputs, processes, moderators, and outcomes (Dulebohn & Hoch, 2017; Marks et al., 2001). Individuals of a team come together, interact with each other, and form a social system – a team that is more than the sum of its parts (Steiner, 1972). The process within the team determines the performance or effectiveness of the team and its individuals (Hackman, 1987; Steiner, 1972). In the model, 176 Fostering Innovative Learning and Satisfaction in Virtual Teamwork team processes and emergent states are divided into cognitive, affective, motivational, and behavioral processes. The moderators influence the strength and direction between the input and the team processes/emergent states as well as between the team processes/emergent states and the outcomes. According to Dulebohn and Hoch (2017, p. 572), the key moderator in the model is virtuality as a "multi-dimensional concept and phenomenon". Furthermore, task independence, TC, and the team context – as the external environment in which a VT performs – are included as moderators in the model. Two levels of outcomes are distinguished in the model: The team level and the individual level. Each refers to performance and effectiveness as a team and as an individual VT member, respectively. Furthermore, individual SAT and IL, which constitute the main focus of our paper, are integrated into the model (Dulebohn & Hoch, 2017). 2.3 DerivationofHypotheses The hypotheses to be tested are derived based on the links between the input and process (H1–H4), as well as between the process and outcome factors (H5–H8). The hypotheses are visualized in Figure 2. Figure 2: Input-Process-Outcome Factors of Virtual Teamwork – Latent Variables and Hypotheses (own illustration based on virtual teams in organizations from Dulebohn & Hoch, 2017) 177 Frank Hiller, Stefanie Zarnow The construct of OF in our study includes the team organization as well as organizational support. Team organization represents the organizing of a teamwork, task planning, and the distribution of tasks, as well as how decision-making is supported (Wiedemann et al., 2013). The organizational support focuses on reasonable communication among the team as well as on building trust through fostering equity and understanding (Gibson & Manuel, 2003). Promoting a supportive climate in a team encourages, amongst other aspects, effective conflict management, a shared understanding concerning the goals of the VTW, and the freedom of expression in a VT (Gibson & Manuel, 2003; Hinds & Weisband, 2003). It is important that the organizational goals are congruent with the motivation of individual team members and the team as a whole (Kozlowski & Bell, 2003). In the context of VET, the influence of the organization on team-level processes is expected to be higher than in regular work contexts, as training and supervising by instructors or teachers plays a significant role in apprenticeships (Organisation for Economic Co-operation and Development [OECD], 2021). We therefore derive the following hypotheses: H1a/b/c/d: The dimensions of OF are positively related to goal setting (GO) / cohesion (COH) / motivation and responsibility (MoR) and communication culture (CC). Members of a VT have inherent characteristic personality traits like thoughts or behaviors (Dulebohn & Hoch, 2017). One of these traits is the commitment (CMT) to act as a member of a VT. Being proud of and committed to the team, and contributing to the tasks of the team, are key drivers for building trust and for the COH of a (virtual) team (Derven, 2016; Gonzalez & Melo, 2021). Behaviors in a (virtual) team to foster a commonly shared CMT raise, among others, the level of trust and go along with higher degrees of COH as well as of CC (Derven, 2016; Hackman, 1987). The feeling of belonging to a (virtual) team is also described for apprentices (Price & Lusznat, 2018). We therefore derive the following hypotheses: H2a/b/c: The CMT of a VT member is positively related to COH / MoR / CC. In general, heterogeneous teams struggle with a lower degree of COH, emphasizing the importance of intercultural competence (IC) (Staples & Zhao, 2006). Au and Marks (2012) found that culture and nationality have an impact on the identification with the VT, whereas missing identification with the VT can lead to stereotypical thinking or a lack of CMT and COH. Gibson and Manuel (2003) discovered evidence that trust among team members, is negatively impacted by cultural differences. In addition, communication among culturally different team members is expected to be more difficult (Gibson & Manuel, 2003). Therefore, a sufficient degree of IC is especially relevant to overcome cultural, temporal, or organizational hurdles (O'Hara-Devereaux & Johansen, 1994), especially as apprentices have different cultural backgrounds and cooperation in an international context becomes more relevant during and after VET (Stamm, 2013). On these grounds, we derive the following hypotheses: H3a/b/c: The IC of a VT member is positively related to COH / MoR / CC. 178 Fostering Innovative Learning and Satisfaction in Virtual Teamwork Franke et al. (2019, p. 456) defined the affinity for technology interaction as a "key personal resource for technology interaction". In VTs, team members with a higher technical affinity (TA) are expected to be more able to cope with complex (technical) requirements (Franke et al., 2019). They are more engaged in the team, face complex situations with a higher motivation, take responsibility, and facilitate easier (virtual) communication. Apprentices, many of them belonging to "Generation Z" and, thus, used to socializing online, are expected to have a certain TA (Schwieger & Ladwig, 2018; Serinikli, 2019). Thus, we derive the following hypotheses: H4a/b: The TA of a VT member is positively related to MoR / CC. Clear and explicit formulated (learning) goals (Edmondson & Roloff, 2009) are an important factor for learning. Researchers have found a significant relationship between GO and the outcome level, on SAT and learning orientation, amongst others (Lloyd & Härtel, 2010; Sarin & McDermott, 2003). As apprentices lack extensive experience concerning VTW and goal setting in VTs, the specification of an explicit goal and assistance concerning ways to achieve this goal are important. Based on this derivation, we derive the following hypotheses between GO and the outcome level: H5a/b: The GO is positively related to IL / SAT. The feeling of belonging to a team and identifying with a common goal positively influences the performance of the team as well as team learning (Edmondson & Roloff, 2009). The climate of safety in a team also affects the outcome level (Hofmann & Stetzer, 1996). Studies (Brahm & Kunze, 2012; DeOrtentiis et al., 2013) have shown that for adolescents and young adults, COH in a (virtual) team is relevant for effective teamwork, resulting in the desired team performance. We therefore derive the following hypotheses concerning the relationship between COH and the outcome level: H6a/b: The COH is positively related to IL / SAT. Research has shown that MoR – at an individual as well as at a team level – are critical factors for team performance (Hackman, 1987; Yang & Ok Choi, 2009). Motivation and engagement to reach the goals of the team can lead to better change management, commitment to the organization and its goals, as well as motivated employees with low levels of turnover ( McBain, 2007). Individual and team-level motivation should go hand in hand as far as possible (Kozlowski & Bell, 2003). In VET, taking on MoR must be promoted as they are needed in both VTW and later in working life. Following this, we derive the hypotheses concerning the relationship between MoR and the outcome level: H7a/b: The MoR are positively related to IL / SAT. 185 Frank Hiller, Stefanie Zarnow Figure 3: Duration of Virtual Teamwork in VET (N=181. Own illustration) When assessing the frequency or average duration of a VTW, the use of digital tools becomes also important. It is of high relevance to look at specific tools that are used when virtually working together. We therefore asked about the frequency of usage regarding some of the most prominent hardware (such as PC / laptop, tablets, smartphones), ways of communication (via e-mail, videoconferencing tools, instant messaging), and collaboration tools (such as sharing or learning platforms) when virtually working together in VET. When comparing the frequency of the tools used in VTW in respective learning sites, we find meaningful differences (Figures 4 and 5). Figure 4: Frequency of Tools Used in Virtual Teamwork in Vocational Schools (N=181. Own illustration) 186 Fostering Innovative Learning and Satisfaction in Virtual Teamwork Figure 5: Frequency of Tools Used in Virtual Teamwork in Training Firms (N=181. Own illustration) In training firms, the use of PCs/laptops seems to be much more common than in vocational schools (mTF = 4.80/mVS = 3.29), while tablets are more frequently used in vocational schools (mTF = 2.42/mVS = 2.94). A meaningful difference can be seen with regard to how often videoconferencing tools are used (mTF = 4.20/mVS = 2.51). While in training firms, n = 149 VET-students stated they (very) frequently use such tools, only n = 40 individuals use them very frequently when working in VT in vocational schools. RQ2: Which relationships can be identified within the input, process, and outcome factors of VTW in VET? Concerning RQ2, a correlation matrix depicting the bivariate correlations between our constructs was examined3. Before interpreting our structural model, we briefly touch on the relevant assessment criteria in accordance with Hair et al. (2022). First, collinearity issues cannot be found in the data. Second, the explanatory power of our model is discussed using R² as well as f2 (Cohen, 1988; Hair et al., 2022). The model explains the proportion of variance in the dependent variables according to Cohen (1988) as substantial (≥.26) with the following values: GO: R² = .402, COH: R² = .368, MoR: R² = .318, CC: R² = .348, IL: R² = .446 and SAT: R² = .444. Third, we turn to the model's predictive power to produce meaningful out-of-sample statements. For that, we assess Stone-Geisser's Q2 as well as the mean absolute error (MAE) and the root mean square error (RMSE) (Hair et al., 2022). As most indicators 3 The detailed correlation matrix can be requested from the corresponding author. 187 Frank Hiller, Stefanie Zarnow in the two key target constructs (IL/SAT) uphold the relevant statistical comparison (PLSSEM values < linear regression model (LM) values), we can deduce that our model has a medium predictive power4. To answer the hypotheses, the results of the path analysis between input, process, and outcome factors are illustrated in Figure 6. All the relationships suggest a positive connection between the factors, except the path from GO to IL with a (non-significant) β = -.013. Figure 6: Final PLS-SEM Path Model With β Coefficient and P-Values Note. Path coefficients are presented as standardized β, while p-values are indicated with asterisks: *p < .1, **p < .05, ***p < .01 For the relationships between the input and the process factors, OF are positively associated with all process factors, with each relationship being highly significant (p < .01). When assessing the effect sizes according to Cohen (1988) (≥.02 small effect, ≥.15 medium effect, ≥.35 large effect) a large effect is indicated from OF to GO (H1a: β = .634, p = .000) and from OF to CC (H1d: β = .520. p = .000), and a medium effect from OF to COH (H1b: β = .486, p = .000), and from OF to MoR (H1c: β = .374, p = .000). Concerning CMT, a highly significant, small positive effect is found from CMT to COH (H2a: β = .233, p = .003) as well as from CMT to MoR (H2b: β = .260, p = .000). The influence of IC on MoR (H3b: β = .141, p = .039) and CC 4 Other than in CB-SEM, no GoF measures like RMSEA or CFI are reported. This is due to striving for another goal in PLSSEM: Making an in-and-out-of-model prediction. To assess the predictive power of a PLS-SEM model, several statistical analyses need to be carried out (Hair et al., 2022; details can be requested from the corresponding author). 188 Fostering Innovative Learning and Satisfaction in Virtual Teamwork (H3c: β = .161, p = .012) is significant at p < .05 with a small effect. Surprisingly, TA shows no significant influence and no noteworthy effect on MoR or CC. The relationships between the process factors and IL, MoR (H7a: β = .443, p = .000) and CC (H8a: β = .313, p = .001) show a highly significant association with a medium effect for MoR to IL and a small effect for CC to IL. The association with SAT is highly significant for GO (H5b: β = .211, p = .004), MoR (H7b: β = .253, p = .000) and CC (H8b: β = .335, p = .000) with a small effect, respectively. RQ3: How does the model differ in the MGA regarding gender, virtuality, task complexity, and firm size in VTW? By analyzing the results of the MICOM procedure (Henseler et al., 2016; details can be requested from the corresponding author), we can confirm configural invariance (Step 1) as the setup of our model is equal across all groups. Compositional invariance (Step 2) is approved for TC, VirtVS, and firm size. We therefore refrain from conducting MGA for VirtTF and gender. As the means and variances of TC, VirtVS, and firm size are not equal (Step 3), we can assume partial measurement invariance and can compare the path coefficients for the respective two groups. After MGA for TC, VirtVS, and firm size, we find no significant difference regarding VirtVS, which cannot be adduced as moderator for explaining the differences in path coefficients between group 0 (low virtuality) and 1 (high virtuality). Regarding TC, comparing group 0 (high TC) and group 1 (low TC) indicates a significant difference of path coefficients only for the relationship between MoR and IL (p = .023). A comparison of the path coefficient for group 0 = .684 and for group 1 = .303 reveals a difference in path coefficients of .380. Concerning firm size, group 0 (smallest, small, medium sized firms) and group 1 (large firms) differ regarding the relationship between GO and IL (p = .025). The path coefficients for the relationship between GO and IL are -.374 for group 0 and .061 for group 1, resulting in a difference of -.434. 5 DiscussionandImplications The numbers displayed in RQ1 present the manifold challenges that a VT holds: Employees and apprentices in particular need to be prepared to have the ability to work together in VT in a short-, medium-, and long-term fashion. Moreover, the frequency of VTW indicates the relevance of virtually working together. Regarding RQ2, hypotheses H1a–H1d can be supported and reveal the importance of the organizational influence on processes in VT. Support and guidance, including apprentices receiving all relevant information and having clear goals set, seem to be crucial factors in introducing and encouraging apprentices in VTW in VET. This requires support during the 189 Frank Hiller, Stefanie Zarnow preparation and scheduling (e.g., task planning and the definition of goals), implementation (e.g., supporting communication) and evaluation (e.g., feedback, reflection, and the identification of room for improvement). Following van Merriënboer and Kirschner (2018), support and guidance should be gradually diminished and reduced over time, until the task can be performed without assistance. We encourage organizations to keep this principle in mind when supervising VTW to foster learning in and about VTs. In the case of VET, this could be incorporated by decreasing support for learners during the progress of their apprenticeship and by encouraging apprentices to take more responsibility from the planning to the evaluation of VTW (Ryan & Deci, 2018). Motivation is important for apprentices during VET as well as for their future working lives. The importance of CMT, i.e., feeling committed toward a VT to fulfil a certain task, is especially relevant for COH and MoR. CMT and IC are factors referring to intrinsic motivation as well as being open-minded and help apprentices to carry out VTW following their own free will and with interest and enthusiasm, in accordance with the cognitive evaluation theory of Ryan and Deci (2018). Following our assumptions, CMT also positively influences COH in a VT. A higher degree of IC leads to a better CC, which makes sense, especially for working virtually in culturally diverse teams. Surprisingly, being open to learning new technical systems or enjoying working with them (TA) has no significant influence on MoR or CC. Therefore, our hypotheses H4a and H4b cannot be confirmed. The idea that a basic TA helps apprentices during VTW is therefore questionable. This can be viewed as a chance for apprentices who do not have a high degree of TA to catch up and not be disadvantaged when it comes to VTW in VET. It also suggests that the technical requirements can be learned without prior knowledge and without a penchant for technical ability. The perception of Franke et al. (2019, p. 456) to view TA "as a key personal resource for technology interaction" cannot be confirmed for VTW in VET. Alternatively, the tools frequently used in VTW (see figures 4 and 5) may also be user friendly and commonly employed (i.e., PC / laptop, videoconferencing tools, e-mail), making it easy for individuals to engage in VTW without a higher degree of TA. The individual outcome factor IL involves the perceived feelings of individuals in regard to learning from VTW personally and professionally, as well as bringing in new ideas on how to improve tasks. IL is most strongly influenced by MoR. This is consistent with Ryan and Deci (2018), who identify intrinsic motivation as pivotal for successful learning. As we incorporate the innovative character of learning in VT, our findings underline the importance of motivational aspects. The importance of effectively communicating in a supportive climate to foster IL is also shown. Therefore, we can confirm the relevance of MoR and CC for apprentices to profit privately and professionally from VTW. Furthermore, innovative work methods are discovered during VTW in VET, exploring possibilities and requirements for the "new normal" in current and future work life. The SAT of apprentices depends on a clear and commonly shared goal for VTW. A realistic agreement on objectives ensures the reachability 190 Fostering Innovative Learning and Satisfaction in Virtual Teamwork of ideally commonly set goals and ensures that apprentices become satisfied through achieving them. The motivation of apprentices is in line with these findings due to their willingness to contribute to the VT outcome and by taking responsibility for the VT, resulting in the SAT of apprentices in VTW. The relationship between CC and SAT supports our hypotheses (H8a–H8b), identifying, among other aspects, conflict management and communication as important drivers for SAT in VTW (Lloyd & Härtel, 2010; Malik, 2013). The comparison of groups suggests that there is no significant difference concerning the perceived virtuality in vocational schools, indicating no difference between a low and a high virtuality for input, process, and outcome relationships. VTW in this learning location seems to be independent from the degree of virtuality perceived by the apprentices in a VT. The comparison of groups regarding the perceived complexity of tasks demonstrates no differences between low or high values of TC apart from the relationship between MoR and IL. For more difficult tasks in a VTW, MoR seems to have a stronger influence on IL than for less complex or routine tasks. This indicates that a higher motivation is needed for difficult tasks, as well as the importance of taking responsibility for a team to promote its progress and development. Regarding firm size, in smallest, small or medium sized firms, a higher GO leads to a lower degree of IL. Too narrowly defined goals could cause a limited scope for innovation and learning. In large companies, however, GO has a slightly positive effect on IL. This, in turn, could suggest that despite narrowly defined goals, a stimulating environment of learning and innovation exists in large companies. In addition, it is conceivable that the structures in large companies are already so complex that clear targets within VTW seem to be useful. Theoretical Implications In the problem outline, it was made clear that specific research in the context of VET is necessary in order to be able to map collaborative learning with the aid of digital technologies in a context-specific and content-rich manner (e.g., Schwendimann et al., 2018). Reference has also been made to the fact that the VET sector is still underrepresented in this particular research area. Our research aims to address exactly these points: With our study, we want to provide (first and exploratory) insights about the diverse process flows and important influence factors of VT in the specific context of VET. To this end, we identified an internationally well-known theoretical model of VT (Dulebohn & Hoch, 2017) and potential scales / items to best represent some of the inherent constructs, which could fit into research in VET. The instruments were meaningfully adapted to the needs of the target group of apprentices and tested in EFA / CFA. Results showed that both factor analysis and within PLS-SEM, our instruments and model seem to explain a significant share of variance (with R2 between .318 and .446). As our aim was also to make out-of-sample predictions, we were able to assess a medium predictive power for our model. 191 Frank Hiller, Stefanie Zarnow Practical Implications VET is supposed to prepare young adults for the requirements of their current and future workplaces. However, the digital transformation has changed the way we work and how humans interact in an unprecedented way (European Commission, 2013; Paeßens et al., 2023). Particularly the area of collaboration seems to be impacted rigorously (Schwendimann et al., 2018). With our study, we want to contribute to this line of research by offering first and explorative result for context of VET that have implications for a variety of practical areas: Firstly, it might help organizations in providing them with information on certain conditions which are conducive to learning. In many countries such as Germany, firm-based training provided by in-company trainers plays a pivotal role in preparing apprentices for their working life (Baum et al., 2022). At the same time, in-company trainers perceive an increasing demand on them triggered by a changing working environment. In particular, pedagogical and didactic competencies are becoming increasingly important for in-company trainers in a progressively digital world (Nicklich et al., 2022). In offering a more detailed vision on the manifold factors that shape VTW, firms and in-company trainers could be supported to provide meaningful opportunities for training that are tailored to the needs of apprentices. What is more, for the development of young adults, it appears that the design of successful learning opportunities needs to meet the contextualized affordances of VET. By elaborating on what factors help or hinder a desirable outcome in the context of VTW, we might be able to help practitioners to reach this goal. 6 LimitationsandOutlook As in every study, some limitations must be addressed. Our purposeful sampling procedure was aimed at reaching as many apprentices as possible via the criterion sampling method. While we deem this appropriate for answering our RQs, one could nevertheless argue that a more random sampling would be a reasonable alternative to avoid an overrepresentation of certain groups. With the argument that accessing apprentices' networks is difficult, future research could control for that by applying other modes of data gathering. Moreover, our sample consists of individuals who are undergoing VET in Germany. According to Busemeyer & Trampusch (2012), VET in Germany can be depicted in the collective skill formation regime - with both school-based and in-company training components. Accordingly, some organizational and content-related differences compared to other skill formation regimes may occur. Nevertheless, all skill regimes are characterized by a large variety of (learning) situations in which VT must be applied – regardless of the learning location. Since VET in an overarching sense pursues the training of all relevant knowledge, skills, and attitudes that are needed for collaboration in modern workplaces, it can be assumed that our results are also relevant for other VET contexts than the collective ones. Another limitation involves missing 192 Fostering Innovative Learning and Satisfaction in Virtual Teamwork data: From an initial round of 387 apprentices, 181 matched our specified criteria, eventually. We examined this issue carefully by considering sophisticated imputation methods, such as multiple imputations (Allison, 2009). In the end, we opted for the removal of all those from the sample who did not provide sufficient data on an individual level (e.g., current occupation). Lastly, we need to consider a possible selection bias in our sample. We promoted our survey via online channels rather than "paper and pencil". This could attract those with a higher digital affinity and, therefore, bias our results5. Future research could account for this bias by collecting other forms of data such as qualitative interviews to triangulate the results from the quantitative study with those from a qualitative approach. In our research, we have focused on those factors for which we were able to identify the strongest hypotheses based on an extensive literature review. Yet, the concept of VT also entails other constructs as well, especially trust, affiliation, leadership, perceived feeling of team membership, and human interaction. Future research should, therefore, endeavor an even more extensive use of accompanying instruments to comprehensively paint a holistic picture of VT and to triangulate the present findings. This could also entail an experimental design study that might allow a more content-centered approach by stimulating specific work activities across a wider setting of groups, or by extending the analysis on social factors in a VT. Future research would be also beneficial regarding a differentiation between labor-related learning in explicit learning settings and labor-integrated learning as a part of the working progress (Weber, 2013). With a "new normal" in place, VTW is becoming increasingly important. This poses manifold challenges for firms and employees alike as well as bringing new affordances. 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