SUPPORTING TEAMS IN STUDENT ALLOCATION TO ACCOMPLISH CHALLENGING TASKS IN SPECIAL NEEDS EDUCATION

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SUPPORTING TEAMS IN STUDENT

ALLOCATION TO ACCOMPLISH CHALLENGING

TASKS IN SPECIAL NEEDS EDUCATION

Master’s Thesis 2020 for Technology Operations Management

Author: K. L. van Agteren

First supervisor: Prof. Dr. J. Riezebos Second supervisor Dr. J.A.C. Bokhorst

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The aim of special needs education is to offer students with emotional and behavioural disorders suitable education. Allocating the expertise of teachers effectively to provide the students with suitable education is recognised as a complex task. Multi-team membership (MTM) is a relatively new concept in the educational sector and can fit in the special needs education because is enables the flexibility to allocate students as well as teachers. A side effect is that MTM increases the workload of the team due to an increased amount of communication and allocation decisions. For this reason a decision support system was designed which is applicable in special needs education. It supports the team in making optimal allocation decisions and thereby positively influencing team and education performance of the school. This Design Science Research aims to improve the applicability of team-based education to improve flexibility, contributing to the literature by developing a decision support system for effective allocation of teachers and students on the basis of academic performance and teaching approach. The new decision support system not only helps in providing the necessary expertise for students but also in effective resource management for organisations which face serious allocation problems because the capacity of teachers is limited in the Netherlands.

Keywords: Multi-team membership, Special Needs Education, Team-based education, Cellular

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1 Introduction

The Netherlands is facing a large shortage in the supply of teachers (Rijksoverheid, 2018). The teaching profession must compete in a shrinking pool of young talent at a time when the attractiveness of a career in (secondary) education is declining (Santiago, 2001). This is especially the case for special needs education (SNE), where teaching students with emotional and/or behavioural disorders (EBD) is perceived as a challenge for teachers (Kauffman, 2013). Despite this demanding profession there is no difference in remuneration, compared to regular education, which negatively affects the attractiveness of teaching in special needs education. The shortage of new teachers increases workload, which has been acknowledged by research of Timperley and Robinson (2000). The increased workload among teachers makes a school more vulnerable to the absence of teachers (Ost and Schiman, 2017). Increasing flexibility among teachers is required since absence among teachers causes a reduced student performance (Herrmann and Rockoff, 2012). Exploring concepts to reduce workload and increase flexibility is essential for this sector. Due to this need, the applicability of team-based education could have great potential in offering a solution to this problem. Team-based working has already gained a lot of popularity in other sectors, like healthcare to improve patient care (So, West, and Dawson, 2011). Notably, the studies on team-based structure in the education sector have lagged as a focus of research, compared to research on teamwork in industry, business services and the healthcare sector (van Dartel and Koppens, 2019). A form of team-based working is multi-team membership (MTM), where an employee can be part of multiple teams within the organisation. This form of teamwork is used to leverage resources and share information across teams more effectively. Also, the flexibility among teachers increases through working in teams. The application of multi-team membership in the special needs educational sector could have a significant impact to increase the flexibility of teachers, therefore it is examined in this study.

Recent surveys indicate that 65 to 90 percent of knowledge workers are concurrently members of more than one team (Wageman, Gardner, and Mortensen, 2012). Teams are defined as set groups of individuals that work interdependently towards a shared outcome (Hackman and Hackman, 2002). Multi-team membership (MTM) is defined in this study as ”A situation in which working time is fragmented over multiple teams. Switching between team contexts implies that employees hold a variety of roles” (Pluut, Flestea, and Cur¸seu, 2014). The application of MTM could have the following advantages; increased flexibility, increased professional development of teachers, and increased student performance. These effects will be achieved only when the implementation of MTM is correct and complete, otherwise MTM will lead to negative effects on individual and team performance. Firstly, increasing flexibility in terms of providing the school with more support in response to changing circumstances of availability, imparting knowledge and skills when they need them, and delivering focus areas where it is convenient (Wang, 2012). Secondly, multi-team membership can affect a variety of individual and team outcomes, like workload, individual stress, and social identity. The application of MTM could contribute to special needs education by developing efficiency-enhancing practices in teams, which facilitate team members to become more task-focused to deal with the limited time they can spend together (O’leary, Mortensen, and Woolley, 2011). In a multi-team membership context, teams can share members, which benefits the members by ’cross pollination’ of ideas (O’Leary, Woolley, and Mortensen, 2012). In the context of the educational sector, multi-team membership (MTM) can be applied for the specific educational year teams and to the course-specific teams (Jans, 2020). Enabling teamwork supports an environment of professional growth for teachers, in which they learn together, share knowledge, and expertise (Somech and Drach-Zahavy, 2007). The professional growth of the teachers has a significant effect on student performance (Lomos, Hofman, and Bosker 2011). Thirdly, MTM in special needs education makes it possible to allocate students based on their needs, regardless of their class or year. This is essential for students with emotional behavioural disorders (EBD), as ensuring that students receive suitable academic curriculum and instruction leads not only to improvement in their academic outcomes, but could also be an effective way to handle or prevent behavioural problems (van der Kamp, 2018). This could help in analysing individual students’ strengths and weaknesses providing a student-specific programme of effective instruction (Walker, 2010). This allows teams to group students with similar needs to a suitable teacher within the team. For example, teachers might specialise in a typical behavioural problem that only a small group of students face, while at the same time being responsible for a larger group of students when teaching basic skills or topics.

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composition and a timetable, but concluded that incomplete implementation of MTM is likely to have a negative effect on the individual and team performance. The proposed team composition and timetable for team-based education but did not address the specific allocation decisions of the timetable for the specific teams. MTM enables the flexibility to allocate students, and teachers accordingly, but this increases the workload of the team by having an increased amount of decisions to determine as a team. This was recognised by Gonzalez and Mark (2005) who stated that the effects of poor execution of MTM cause competing demands that imply time pressure and heavy workloads, which requires a high level of effort from employees. Preventing this outcome is essential since the management of the institution and multidisciplinary workforce must contain a stable, secure and predictable learning environment for students of a special needs education school (Bellour, Bartolo, and Kyriazopoulou, 2017). For this reason, the aim of this study is to investigate how multi-team membership could be designed to be more applicable to special needs education. This study explores how a decision support system (class of computer-based information system or knowledge-based system that support-decision making activities) could be designed for special needs education in order to improve the applicability of multi-team membership in special needs education. The aim of the decision support system (DSS) is to support the team in allocation decisions. Prior research about decision making in teams concludes that team structure and workload, significantly influence team performance (Urban, Bowers, Monday, and Morgan Jr, 1993). Other research has shown that effective teams can maintain performance even under conditions of high workload when communication opportunities are reduced (Kleinman and Serfaty, 1989).

In order to be a helpful DSS for SNE, the DSS needs to be developed and designed with the correct values to achieve effective allocation. Effective allocation in terms of providing suitable education to students, while minimised workload variability among the team is ensured. Optimising the allocation of the resources (courses, students, and teacher) could improve team-based education in the decision-making process. The DSS needs to successfully answer the following questions: How can the students be allocated into different groups?; which teacher will teach which group of students?; what is the course (subject) of a specific lesson? How will all these factors be quantified? Is there trade-off between the need of students and teachers? These decisions need to be determined on a daily basis in a limited timespan. Fast decision-making is important when there is a limited amount of time to determine these allocation decisions. By developing a DSS that helps the team in decision-making, this study aims to provide insight in how to relevant factors could be applied in a DSS to support effective allocation in team-based education. The following research question is constructed in this research:

“How could the model-based optimisation of resource allocation support the decision-making in effective student allocation in team-based education in special needs education, in a multi-team membership context?”

Although the positive effects of multi-team membership have been acknowledged, there is a lack of research in the design of MTM in special needs education. The primary goal is to ensure effective allocation for SNE in an MTM context. To ensure the goal of the DSS the following questions need to be addressed. Which decisions are required to be determined by the DSS? What aspects are relevant factors for making these decisions? When does the team need to determine these aspects? Firstly, the team has to determine what course (subject) will be provided for a selection of classes for a certain timeslot. Secondly, the students are not in fixed classes, so how will the students be allocated into groups that suits their needs. Thirdly, the team has to decide which teacher will provide education to which class. The aim is to narrow the gap between scientific knowledge and theory used in common practice (Shadish, Cook, and Leviton, 1991). Providing a DSS that answers to all these questions could potentially improve students’ performance and behaviour, reduce the amount of time in the decision-making process, and increase the flexibility of school staff. By providing DSS to connect course, student and teacher and designing how the DSS can be applied effectively, this study contributes by extending the literature of effective student allocation in team-based education in special needs education.

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8 states the critical aspects of the developed DSS. Sections 9 and 10 contain the discussion and conclusion of the study.

2 Methodology

2.1 Research design

In order to achieve effective student allocation in team-based education in special needs education (SNE) from an multi-team membership perspective, the critical requirements for the application of a decision support system in team-based education are required to be identified. There is a long-standing culture of teacher isolation and individualism, a prevalent conflict-avoidance and non-interfering behaviour of teachers, together with a wish to preserve their individual autonomy, which may avoid a more collaborative culture to grow in education. In SNE, this individualistic approach interferes with the decision-making process, when there is a lack of expertise among the team members to handle students with emotional and behavioural disorders (EBD). To make teachers aware of the value of team-based education, they need to realise that they are not alone and may tackle ideas and projects through collaborative experiences (Walker, 2010). Determining the critical requirements and identifying others is key for developing a effective DSS in team-based education. Research states that the supplementary fit of a DSS can lead to higher group cohesiveness and faster decision processes (Evans and Dion, 1991).

Designing a DSS that fits in the team-based education context is essential to accomplish the indicated benefits. The application of a DSS in SNE, from a MTM perspective, has not been done. Envisaging the applicability of a new system in SNE suggests design science research (DSR) as being the most suitable research method for this research. DSR focuses on improving the present generic knowledge which can be transferred to various contexts within a specific application domain. The core mission of design science is to develop knowledge that can be used by professionals in the research field, in finding design solutions to problems in their field. Understanding the nature and causes of problems is essential in designing solutions. However, a design science approach does not limit itself to understanding but also develops knowledge of the advantages and disadvantages of alternative solutions (Van Aken, 2005). Design science mainly focuses on developing knowledge that can be applied in an instrumental way to implement and design processes, systems, or actions that are used to address problems or promising opportunities. This is in line with the work of van Aken, Chandrasekaran, and Halman (2016) who stated that design science aims at improvements to a system based on a thorough understanding of these problems and opportunities. Design science fits the aim of this research, expanding the knowledge of the decision-making process of allocation in team-based education for SNE from an MTM perspective, and supports the school staff’s logistics problems, since this research strategy helps to develop the knowledge needed in designing systems (van Aken et al., 2016). According to Wieringa (2009), design science for emergent systems consists of four phases: problem investigation, solution design, design validation, and solution implementation. Limited time made the solution implementation not feasible, therefore the four phases of Szirbik (2019) are applied. For a design science for envisaged systems Szirbik (2019) describes four phases for design science, based on those of Wieringa (2009); the four phases of Szirbik (2019) are described as reviewing existing literature, analyse the current systems, designing the architecture and guidelines of the envisaged system, and validation of the design outcomes and identification of new critical aspects of the envisaged system.

2.1.1 Phase 1: The review of existing literature about the envisaged system

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2.1.2 Phase 2: Analysis of the current system

Through semi-structured interviews with the SNE school’s staff, documentation, and observations in the SNE school the needs of the school staff are determined. Therefore, three of the six data sources are used to realise the data triangulation, namely documentation, direct observations, and interviews. Data triangulation increases the validity of research results (Yin,2014). The open nature of the questions of the semi-structured interviews is aimed to encourage vitality and depth and to allow unidentified concepts to emerge. The participants are more encouraged to talk about their experiences through the openness of the questions, and the ordering is determined by the responses of the interviewee (Dearnley, 2005). This is suitable for this research, because offering the interviewee flexible questions could leads to obtaining different perspectives of the interviewee about this envisaged system. The semi-structured interviews aim to provide a solid understanding of the needs of the school staff, which determined the characteristics of the DSS adjustments for the development of the DSS. Knowing all the relevant information concerning the assessment of students and teachers could help to construct clear guidance for effective allocation of teachers and students. The DSS is required to determine the allocation decisions based on the key variables and the input of the users. Identifying what aspects are important in determining the allocation and how these aspects should be measured is essential for an effective result of the DSS. Documentation of the special needs education school contains valuable information for team formation and boundaries for the model of the DSS. To observe the current system an SNE school is visited several times to analyse the day-to-day operations of special needs education, which could only be done in the ealry phase of the research due to the global pandemic COVID-19. Besides the obtainment of information, the current system and the design of Jans (2020) need to be analysed.

2.1.3 Phase 3: Design the architecture and guidelines of the envisaged system

When a solid understanding of the current and envisaged system is established, the design process of the envisaged system can start. First, in section 5, the framework and the boundaries of the system of SNE can be shaped. A DSS is developed with the support of the modelling program AIMMS, where all the required parameters, functions, variables, and constraints can be implemented. Second, the design of the decision support system is addressed in section 6. In this section the obtained critical requirements of sections 3 and 4 are evaluated, and then addressed in the BPMN flow diagram design of the applicability of the DSS. The critical requirements are addressed in the designed BPMN models.

2.1.4 Phase 4: Validation of the design outcomes and identification of new critical aspects of the envisaged system

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Figure 2.1: Coherence of the phases of design science research

2.2 Research Questions

The aim of this study is the develop a DSS that provides benefits to team-based education for special needs education. The main research question “What benefits could a decision support allocation provide to improve team-based education in special needs education, in a multi-team membership context?” aims to identify how a DSS could improve team-based education in special needs education. Prior work of Jans (2020) identified barriers to the applicability of multi-team membership. This DSS aims to improve team-based education by identifying and securing the critical requirements of the envisaged system. The critical requirements can vary from teamwork-related requirements to operational requirements. In section 2.2, the structure of identifying the critical requirements is addressed. The identified critical aspect forms the basis for the research questions. Each of the four phases of Szirbik (2019) answers a different part of the main research from a different perspective. The following sub-research questions have been established to answer the complete context.

Phase 1: The review of existing literature about the envisaged system

“Which critical requirements are identified from the literature?”

Phase 2: Analysis of the current system

“Which critical requirements are identified from practise?”

Phase 3: Design the architecture and guidelines of the envisaged system

“How can the decision support system be designed to improve team-based education, while coping with the identified critical requirements?”

Phase 4: Validation of the design outcomes and identification of new critical aspects

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3 Theoretical Background

3.1 Special Needs Education

The work of van der Kamp (2018) is a great contribution to the understanding of special needs education and the perceived difficulties of the teachers and students. Her work is mentioned and evaluated in this section. Special needs education is defined as education specialised for students who suffer from severe cognitive, emotional, or behavioural problems that negatively affect their well-being in their home environment as well as at school (van der Kamp, 2018). These students, commonly recognised as having special educational needs, require additional support or adaptations in order to benefit from education (van der Kamp, 2018). The number of students identified with serious EBD problems stands out and has become a major concern for teachers (Goei and Kleijnen, 2009). The students have a disadvantage already, compared to students without EBD. The class size is smaller compared to a high school class so that the students can have more specialised attention. This has led to a growing body of literature that emphasises the importance of teaching basic academic skills (like maths and language-related skills) to EBD students (Hagaman, 2012). Since students in SNE score poorly in these core skills (Ledoux, Roeleveld, Langen, and Smeets, 2012), which relates to the outcomes of demonstrating, that more opportunity to respond correlates with better performance and improved on-task-behaviour (Sutherland, Alder, and Gunter, 2003). Research has recognised that students’ problem behaviour, as observed in classrooms, often seems to be the result of a mismatch between the tasks offered to students and their strengths, skills, or preferences’ (van der Kamp, 2018; Lewis, Hudson, Richter, and Johnson, 2004). Providing students with a suitable academic curriculum and instruction is not only important to improve their academic outcomes, but it could be an effective way to handle or prevent problem behaviour (van der Kamp, 2018). Nevertheless, in the current situation, schools and teachers often presume that the academic shortfall can best be addressed once the behavioural problems are under control, their focus primarily concentrated on the students’ unruliness and problematic behaviour, this is often at the expense of academic instruction (Reid, Gonzalez, Nordness, Trout, and Epstein, 2004; van der Kamp, 2018). This is supported by van der Wolf and van Beukering (2011), who states ”Teachers often considered good behaviour and well-being more important, or even a condition for performance and this was underlined in their teaching approach”. Therefore, it can be concluded that finding the balance between a good behavioural ethos and providing academic contribution is hard for teachers. Although, the paper of Sutherland and Wehby (2001) concludes that if students have increased opportunities to respond to academic requests, their task engagement, and academic outcomes increases while inappropriate and disruptive behaviour decreases. Regardless of the origin of the academic and behavioural problems of these students, teachers have to regulate problem behaviour and improve academic results. It is important for special needs education staff to analyse individual students’ strengths and weaknesses to provide a student-specific programme of effective instruction (Walker, 2010). It is the teacher’s responsibility to provide the course, based on students’ personal annual goals and objectives. Ensuring all the students’ goals and progressions are met places a lot of pressure on the teachers and are received as an enormous task (Walker, 2010).

The aim of the DSS should allocate students in a way that suits their individual needs while main-taining the students’ good behaviour. In order to do so, students should be allocated to the most suitable class-based on performance and teaching approach (see section 3.2) while limiting the class size. In regular education, the performance of a student would normally be measured through the grades of the students. However, students who have EBD are known for being easily distracted and having weak attention control, weak inhibition, short attention spans, and problems with their working memories. These typical characteristics erect barriers for students with EBD, which prevent them from demonstrating their knowledge and abilities accurately, leading to poor school outcomes and weak test performance (van der Kamp, 2018;Bolt and Roach, 2009). The results of students may be affected by other factors, including the preferred teaching approach of individual students. Therefore, this study tries to find the most suitable education by taking into teaching approach and performance. The next section addresses the possibilities in distinguishing different teaching approaches.

3.2 Competence

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2001). The management of the school indicated the importance of competence by distinguishing didactic and pedagogical competence (interview 03-04-2020, Appendix A). A didactic approach is more focused on how knowledge, competences, and learning attitude can be taught by teachers to students, whereas pedagogical is more focused on the educative task of the teacher. The didactic approach would normally suit students of lower educational levels, and the pedagogical approach would suit students of higher educational levels.

Competence is defined as the teacher’s ability to act adequately, to respond to situations and stimuli that arise during lessons, and to capitalise on these in order to improve the quality of their students’ education (Tich´a and Hoˇspesov´a, 2013). A teacher with a high pedagogical or didactic competence is described in this study as having a pedagogical or didactic teaching approach. Detecting which approaches suits which student and identifying which teacher prefers teaching with a certain approach would help the students find suitable education. In the study of Jans (2020) the importance of the competence level of the teacher is discussed, but the competence level was addressed as a general level without making the distinction between the different kinds of competences.

To analyse the needs of students, the distinction between didactic and pedagogical competence is essential. Didactic competence consists of a skilled orientation towards the educational meaning of teaching a specific subject and putting this into action in relation to specific students. This competence encompasses mastering the scientific basis of the subject and its teaching (Tichá and Hoˇspesová, 2013). Pedagogical competence consists of creating conditions for the development of students’ requirements by effective organisation of educational influences, by motivating students’ own educational activities and by exploiting the potential of the student, removing mental blocks and barriers, mastering diagnostic operations, getting insight and empathy, and designing procedures for effective pedagogical intervention (Tichá and Hoˇspesová, 2013).

By measuring teachers’ or students’ ability to analyse and interpret the depicted teaching situation, their own teaching competence can be elicited and hence assessed (Kersting, Givvin, Sotelo, and Stigler, 2010). Measuring the competence levels of teachers and the students’ need for a particular teaching approach is hard to quantify. Jeffries and Maeder (2009) state that vignettes with open-ended answer formats are appropriate to provide evidence of problem-solving and critical thinking. A more valid and reliable analysis for teachers’ teaching behaviour is the appplication of the Rasch model (Maulana, Helms-Lorenz, and van de Grift, 2015). In this model six domains of teaching behaviour are analysed; safe and stimulating learning environment, efficient classroom management, clarity of instruction, activating learning, adaptive teaching, and teaching learning strategies. The Rasch model is not applied in this research, but this study provides an indication of which domain suits which teaching approach. A didactic approach tends to be more focused on how to efficiently provide education, such as the domains efficient classroom management, clarity in instruction, teaching learning strategies and adaptive learning. A pedagogical approach tends to be more focused behavioural aspects of learning, such as the domains safe and stimulating learning environment and activating learning.

3.3 Teamwork in Education Sector

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Feigin, 2005).

Nowadays, teamwork is used extensively because teams offer flexible working units that help organisa-tions to maintain and gain a competitive advantage (Delarue, Van Hootegem, Procter, and Burridge, 2008). Although the collaborative process is not the traditional method of staff development for teaching professionals, the process is becoming more common (Lee, 2005). Since the field of teaching has become more complex, specific, sophisticated, and encompassing knowledge from a broad range of disciplines. Therefore, effective teaching requires the synergy of experts from different disciplines (Somech and Drach-Zahavy, 2007). Research also shows that the transition to teamwork enables the team to be more efficient to changes compared with the traditional hierarchical structure, which currently characterises the education system (Porter-O’Grady and Wilson,1998). Teamwork processes occur during two phases of team performance episodes: action and transition (see figure 3.1) (Marks, Mathieu, and Zaccaro, 2001). Team processes are the means by which members work interdependently to utilise various resources, such as equipment, expertise, and money, to yield meaningful outcomes (e.g. student performance/needs, teacher allocation, teacher performance). Action phases are periods of time when teams conduct task work and rely on coordination and monitoring activities that lead directly to goal accomplishment (providing education). In contrast, transition phases are periods of time when teams focus primarily on mission analysis, planning, goal setting, and evaluation activities (Marks et al., 2001).

Figure 3.1: Teamwork processes

Teamwork makes teaching more than a process experienced by professionally isolated individuals in their classrooms. It enables professional growth for teachers, in which they learn together and share knowledge and expertise (Somech and Drach-Zahavy, 2007). Teamwork stimulates the development of teachers, but the review of Lomos et al. (2011) also showed a small but significant aggregated effect on student performance. However, there are a lot of variables that can have an effect on student’s performance and achievement, for example varying from a teacher’s and students’ characteristics, changes in the environment and school courses, and circumstances at the student’s home (Walker, 2010). Nevertheless, prior research (Holland, 2005; Fullan, 1987) found a direct correlation between professional development of teachers and the levels of student achievement. Therefore, improving the professional development of the teacher should have to be considered as one of the key performance indicators for the school to increase the students’ performance and learning. Richardson (1994) suggested that teachers’ professional training should focus on placing the teachers in collaborative groups. Through these groups, teachers realise that they are not alone and may tackle ideas and projects through collaborative experiences (Walker, 2010). This relates to Oliphant’s (1996) suggestion about a sense of a common goal and a growing appreciation for others’ expertise and knowledge, which provides teachers with a sense of community. This is especially relevant for SNE, where many teachers feel a lack of expertise to handle students with EBD and have reported a limited arsenal of approaches, interventions, and management strategies in dealing with them (Jones and Chronis-Tuscano, 2008). In team-based learning, the task is identified as a unifying objective for the team with shared responsibility for its completion, rendering the task independent of the individual (Adair, 2009). Through this approach, control of the learning moves to the team, and the team is addressed to the task. The individual team members enjoy the support of their peers and the comfort of shared responsibility (Lawlor, Marshall, and Tangney, 2016).

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students, or performance evaluation. Some topics are required to be discussed in each meeting, but others will only be addressed when individual members indicate the need for discussing that topic. Creating a safe environment supports individual members to address certain topics openly, such as perceived difficulties. The team could experience improvements in the action phase by using the transition phases effectively. The shared responsibility of teachers improves the professional development of individual teachers, which ultimately affects the students’ performance in a positive way. Reflection leads to improved team performance and helps to improve the result of the DSS by evaluating the input of the DSS. The application of the DSS should fit into the transition phase of teamwork.

3.4 Self-managing Teams

There is a limited amount of research about self-managing teams in the educational sector. This study uses the definition of Hackman (1986) for self-managing workgroups ”Collections of people who take personal responsibility for the outcomes of their work, monitor their own performance, manage their own performance and seek ways to improve it, seek needed resources from the organization, and take the initiative to help others improve”. Key empowerment components for teachers are an increased status, autonomy in decision making, and a highly developed knowledge base (Maeroff, 1988). This self-managing team is responsible of a set of courses, which requires the members to consists of multiple skills. Multiple skills in terms of consisting with the expertise to provide education concerning different courses. Therefore, this self-managing team can be considered a multi-skilled workforce. Multi-skilling is referred in this study as means of removing traditional divisions separating disciplines in work areas and giving responsibility to individuals well-trained for a range of different types of activities (Singh and Shah, 2014). In other sectors, a multi-skilled workforce is typically carried out with the aim of improving efficiency, production, quality and costs reduction (Manyi, Sibanda, and Katrodia, 2018). In the educational sector, improving efficiency and quality are the main desired results of a multi-skilled workforce. Team members share the responsibility and reward for their team’s work and recognise each other as members of the team. Autonomy is defined as the ability of employees to set organisational goals and to structure the organisation to maximise professional concerns (Price,1997). However, working systematically only makes sense if teachers have the opportunity, skills, and autonomy to adapt their approach to the specific needs of students with EBD (van der Kamp 2018). Carsten and Spector’s (1987) a meta-analysis revealed that autonomy is related to lower levels of employee turnover and absenteeism and to higher levels of motivation and job satisfaction. Short (1993) made some interesting points about self-managing teams in the educational sector. The purpose of that study is for the school staff to develop the competence to take charge of the professional growth of individual teachers and resolve their own problems. Self-managing teams create more empowered individuals, who believe they have the knowledge and skills to act in certain situations and improve the outcomes. However, changing the isolated environment of the teacher to a more collaborative environment needs to be communicated and monitored. The positive outcomes of self-managing teams are achieved only when managed correctly. Prior literature supports this by stating that the outcome of self-managing working teams varies considerably in effectiveness (Guzzo and Dickson,1996). At times, such team structures have failed to outperform traditional workgroups (Bailey, 1998) or have undermined work-life quality (Barker, 1993). The autonomy of the members of multi-skilled self-managing team is a factor, which requires attention in the development of the DSS.

3.5 Multi-team Membership

Multi-team membership (MTM) can offer a solution to the shortage of teachers while improving the quality of the provided education. The prior work of Jans (2020) indicates that multi-team membership can be an effective way of applying a team-based education in this sector. O’leary et al. (2011) define multiple team membership as ”a form of work organization in which individuals are concurrently members of two or more teams for a given period of time”. Through the prior research of Jans, the two types of teams are addressed as within-grade level (level teams) and cross-grade level (expert team). The level teams are teams of teachers, who are responsible for a certain education year. The expert teams are teams of teachers, who are responsible for the education of a selection of related expertise courses for all classes, regardless of the educational year of level of a .

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teams that consist of members that switch between contexts are exposed to a greater diversity of knowl-edge, opinions, and views. Multi-team membership implies cross-boundary activities that are likely to drive the development and foster team-level performance and team cognition (Ancona and Caldwell, 1992). Secondly, the development of efficiency-enhancing practices in teams improves because team members become more task-focused to deal with the limited time they can spend together (O’leary et al., 2011). Thirdly, expert teams will be more focused on transmitting knowledge on the specific subjects to students across education levels and/or years. Creating a more safe learning environment depends on their teaching skills, which can be divided into verbal competences, pedagogic competences, didactic competences, and organisational competencies (B¨uttner, Pijl, Bijstra, and Van den Bosch, 2014). This relates to van der Kamp (2018)’s results, who stated that providing students with a suitable academic curriculum and instruction is not only important to improve their academic outcomes but could be an effective way to handle or prevent problem behaviour. MTM enables opportunities in effective student and teacher allocation can contribute by offering a flexible structure, which deviates from the current fixed system.

The monitorisation of team-based education safeguards the effectiveness of the quality of the educa-tion but is complex. Prior research found that teams comprised of members who committed a higher percentage of time to the team demonstrated superior performance, relative to teams comprising members who allocated a smaller percentage of their time to the team (Cummings and Pletcher, 2011). The extent to which team members allocate their time to a given team will influence the attention given to team processes (Tannenbaum, Mathieu, Salas, and Cohen, 2012). The psychological disadvantages of MTM describe this work practice as overly confusing and demanding for individuals (Wageman et al., 2012). The allocation of the time spent and personal complications should be communicated within the team. Teachers, who participate in multiple teams, use their time among the teams more effectively and efficiently since there is a reduced amount of slack (O’Leary et al., 2012).

A DSS is supposed to increase the effectiveness and efficiency of a team by providing decisions for the team, to reduce time and workload. The DSS aims to reduce the negative effects of MTM, such as the increased confusion and demand of the team members by providing support in the decision-making process of effective student and teacher allocation.

3.6 Decision support system

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3.7 Cellular Manufacturing

Having the flexibility to allocate students and teachers across classes should not lead to high workload variability among the team. To allocate the students accordingly, the applicability of the algorithm supporting the manufacturing system ’cellular manufacturing’ is an interesting concept to consider for effective student allocation. Cellular manufacturing (CM) is an application of group technology, where a part of a firm’s manufacturing system has been converted into cells. A manufacturing cell is a cluster of dissimilar machines or processes located in close proximity and dedicated to manufacturers of a family of parts a cell family (Wemmerl¨ov and Hyer, 1989). The objective of cellular manufacturing is to have the flexibility to produce a high variety of medium demand products while maintaining high efficiency of large-scale production by grouping parts and machines according to the similarity between parts. Offering more flexibility while minimising the workload of the staff of the organisation is a goal of cellular manufacturing.

The challenge for the design of cell formation is how to group similar parts and the corresponding machines, which is called the cell formation problem. Since this is an objective with multiple optimisation problems, the solution is complex. There are three different kinds of group technology cell formation models to solve this problem. First, the standard cell formation models often ignore many manufacturing factors and only consider the machine operations of parts, which is presented in binary machine-part incidence. Secondly, the generalised cell formation models are a more comprehensible method, by applying different design objectives and constraints. Thirdly, metaheuristics models are able to solve optimisation problems with the global optimal, or near-global optimal, solution in a reasonable time span (Onwubolu and Songore, 2000). The conversion process of cellular manufacturing and multi-team membership has similar disadvantages when not managed correctly, including declining social interactions, increased incidence of conflict, performance obstacles. Conversion to cellular manufacturing changes the social interactions among employees and their supervisors. These social changes require careful attention because of their potential impact on employee attitudes, motivation, and retention (Irani, 1999). In the process of conversion, it is assumable that an employee loses autonomy of a specific part in the process within the factory; this scenario is equivalent to the teachers losing the autonomy of being responsible for a specific class or course. Klein (1989) states that lost work autonomy leads to a decline in employee motivation. Huber and Brown (1991) found several areas where CM employees experienced more performance obstacles than those who worked in the functional layout. The negative effect of cellular manufacturing is related to the negative effect of team-based working, like communication, resolving conflicts, and losing autonomy. How is this related to MTM? MTM enables the allocation of students among other classes, this flexi-bility may lead to uneven workload among the team since the workload of EBD students can vary highly. Therefore, even class sizes does not mean even workload among the different classes. The goal of applying CM in team-based education is to effectively allocate students to the most suitable class while minimising workload variability among the team. To transform the CM into team-based education, the expert team consists of teachers (machines in CM), who need to provide education to a class (cells in CM) of students (parts in CM). To allocate the student accordingly, the students are required to have individual workload levels. The goal is to allocate the students into a class in such a way that provides a minimised workload variability for the team. Cellular manufacturing achieves this by grouping the parts and machines accord-ing to similarities, in the educational sector this would mean groupaccord-ing students with similar needs in a class.

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which could which could be the allocation of the second table of figure 3.2. Resulting in different class sizes, but a minimised workload variability. This example only reflects the minimised workload in the student allocation, without taking into account finding suitable education for students. In section 5, the application of cellular manufacturing is used to minimise the workload variability between the different classes.

Figure 3.2: An example of the application of cellular manufacturing in team-based education

3.8 Identified critical requirements from the literature

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Critical requirements Sections DSS should support the team in finding suitable education for students 3.1 ; 3.2 DSS should distinguish teaching approaches 3.1 ; 3.2 DSS should be flexible in adjusting input of the model 3.3 ; 3.6 DSS should fit in the transition phase of teamwork 3.3 DSS should not lead to loss of autonomy of teacher 3.4 DSS should take into account minimised workload variability 3.7

Table 3.1: Identified critical requirements

4 Problem investigation

The problem investigation starts with a case description, which leads to a problem analysis. After the problem analysis, the stakeholders of the system are identified and analysed. The envisaged MTM system will cause certain changes in allocating courses, classes, students, and teachers. The problem analysis elaborates on which decision difficulties arise in team-based education and how the DSS could facilitate these emergent problems. Finally, all course of the school are required to be allocated to the expert teams or level teams. Section 4.4 elaborates how all courses are allocated.

4.1 Case description

In the research of Jans (2020) the implementation of multi-team membership in special needs education was examined. Contributing to the literature by presenting a timetable and team composition for a special needs education school, this study extends the work of Jans (2020) by designing a DSS for the same SNE school. This school is part of a regional expertise cooperation (RENN4) in the northern part of the Netherlands, that provides primary and secondary special needs education to up to 2300 students. This institution is specialised in the provision of special needs education for students that have emotional and behavioural disorders (EBD). The difficulties of the students can be extremely diverse, varying in form of learning and behavioural difficulties as a result of physical, intellectual, and communication disorders. Students with EBD are a serious challenge to their teachers (Kauffman, 2013). Together with the parents and youth care sectors, the school tries to maximise the work opportunities of the students by offering a more suitable, individualistic, and adaptive approach. The mission of the cooperation RENN4 (RENN4, 2020) is stated on their website as:

“Every student has got a talent. It is our challenge to make the hidden talent of each student visible. Together with discovering which topic suits them best. This search is not always easy. Especially when there are extra challenges due to behaviour. Where regular education falls short in providing this extra attention, special needs education can offer an environment where each student can find his/her suitable education. Our goal is to give each student the opportunity to discover where the student’s talents lay, in a pleasant environment”

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et al., 2012). This increases flexibility while reducing the chance of cancellation of classes for the students. In the proposed team composition in team-based education, there are two types of teams, namely expert teams and level teams. Where level teams are responsible for a certain educational year, by providing the less-specialised education, this team can create a safe learning environment by having a close relationship with the students and parents. The expert teams are teams of teachers that are specialised in a specific category of courses (for example mathematical-related courses). Courses are described in this study as the provided subjects of this school, a course is either allocated to the level teams or expert teams. This study develops a DSS for the expert teams. Expert teams have to provided to all classes of the school, which enables allocation of student to other classes. To establish a distinction between the normal class composition and the new class composition, the normal class composition is referred as class and the new class composition is referred as group. Effective student and teacher allocation could have a great impact on providing the EBD students with their specific needs, since students, who receive suitable academic curriculum and instruction, improve their academic outcomes and behaviour (van der Kamp, 2018). Several studies have provided evidence that one of the main causes of the deficiency of meeting the students’ specific needs is that teachers of students with EBD often tend to focus more on students’ behaviour rather than on their academic skills (Mooney, Epstein, Reid, and Nelson, 2003;Reid et al., 2004). In the current situation, there are no teams of teachers, and teachers educate students in a quite isolated environment. The schedule consists of fixed classes, courses and teacher, which limits the flexibility of the school staff. The average expert team course (Table 4.2) is provided by only two teachers. The absence of one of these teachers leads to replacement by a teacher that most-likely does not have the required knowledge to educate this course, otherwise, the course would be cancelled (RENN4 main findings of interview with internal mentor 20-03-2020, Appendix A). The cancellation of lessons is not a fitting solution for the school. MTM would increase the flexibility to the school staff, so the staff can effectively respond to absence.

Theory suggests that MTM support effective education, but in practice there seem to be some pitfalls that can be avoided. Although the designed integrated composition and timetabling approach were positively received, Jans (2020) also received concerns about the applicability of MTM during a presentation to the teachers of this SNE school. Jans (2020) concluded that an incomplete implementation of MTM has a high chance of negative effects on the individual team members and team performance. After evaluating the work of Jans (2020) and having spoken to some involved teachers, the potential of MTM was acknowledged by all participants but the current designed form is not yet suitable for implementation in this SNE school. The main concerns of the teachers were about communication and the impact on the students (RENN4 Main findings of the interview with internal mentor 20-03-2020 / observations during a working day 25-02-2020, Appendix A).

Communication is identified as a problem, because in the current system teachers are not interde-pendent to each other. In the current system, teachers learn to work alone, to rely mainly on their personal talents and skills, to cope alone with problems that arise in the classroom, and to develop their professional abilities independently (Somech and Drach-Zahavy, 2007). With an MTM perspective, as a member of a team(s), the members are obliged to communicate with their fellow team members of team(s) and to make decisions as a team. The teachers have to find consensus in their decision-making process as a team, which can be difficult in a relatively short morning meeting of 15 minutes (RENN4 observations during a working day 25-02-2020, Appendix A).

The impact on the student was another concern of the teachers, who emphasise the importance of a solid student-teacher relation was stated. Establishing this relation takes a long time, which seems harder to establish from an MTM perspective. This relation is especially important in the level team since the members of the level team spend more time with an individual class. When relating this concern to the expert team, the impact seems less relevant. Teachers of expert team-related courses see the classes less often than the level team members. Nevertheless, allocating the students too frequent among groups need to be avoided to ensure a limited impact on their behaviour.

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4.2 Problem analysis

This study develops a DSS through a formulated integrated approach for the SNE school. The objective of the DSS aims effectively allocate students by optimising resource allocation. Effective team-based education results in increased staff flexibility, stimulate teachers’ professional development and increases students’ performance and behaviour (Wang, 2012; Somech and Drach-Zahavy, 2007; Lomos et al., 2011). Developing a DSS that stimulates effective student allocation is desired. This complex task needs to take into account a number of problems, limitations, and desires to ensure the optimal result. To effectively allocate students, the staff also has to determine staff and course allocation. The DSS aims to obtain the optimal allocation of resources, which is in this study the allocation of courses, students and teachers for a timeslot. The optimal allocation of students aims to provide students with the most suitable education. The optimal allocation of teachers aims to allocate the teacher which is most suitable to a class, but the value of an equal workload is essential. The optimal course allocation aims to assign the most valuable course for the students. The DSS is required to take into account these different decision to achieve effective student allocation. For effective student allocation, the optimal allocation of resources

is required.

Describing team-based education without a DSS helps identifying how and what are important factors for the desired DSS. The proposed team composition and timetable of Jans (2020) is used as a basis. All courses are allocate either the level team or expert team, how this is determined is addressed in section 4.4. There are four expert courses: Math, Language, Behavioural and Mental Resilience, and Workfield. All teachers are assigned to a level team and/or an expert team, based on competence and knowledge level. The expert team consists of optimal composition of individual team members with the same expertise. Optimal team composition by means of taking into account the following ambitions; available content knowledge, team size, and level of competence and skills, expert (Jans, 2020). The expert teams have fixed schedules, so the team knows what timeslots are allocated to which classes of students, Table B.1 (Appendix B) shows the fixed schedule of the expert team ’Math’. The expert team is responsible for a set of related courses for all classes. MTM enables that several classes, regardless of their educational year or level, could have a course (subject) in the same timeslot. For example, on Monday5 second timeslot Arbeid3 (C9), BB3 (C10), KB3 (C11) and TL3 (C12) have a course of an expert team. The expert team has to make several decisions before the lesson starts. To effectively allocate the student the most valuable course is required to be determined first, since course performance of students may vary.

Firstly, the expert team is responsible for a selection of courses, the team has to determine which course is most relevant for the scheduled classes of a given timeslot. The argument could follow that several courses could be given to the classes, but this dramatically increases the complexity of the allocation, as students can be allocated to the different groups. It is more complex to determine the value of allocating students to another group, since the allocated students miss another course of their class. Therefore, this study assigns one course to a timeslot. In the current system, a course would be provided a fixed number of timeslots per week, since courses are not interdependent. In team-based education, this fixed amount is related to a set of courses. Therefore, the expert team has the flexibility to adjust the frequency of individual courses of the team. This flexibility should be limited since each course must be provided. Adjusting the frequency could have several reasons, such as an upcoming test, poor test results, or preference of the team members. In determining the course for a timeslot, the available knowledge of the team members is also relevant. One could expect that the knowledge level of a different team member could vary for each course since team member could have expertise in a certain course and are relatively new in educating the other courses. All these factors raise several questions; What reason could a team have to adjust the frequency of a course? How would an upcoming test affect this decision? How would be decided which course has a lower frequency? To what extent should the knowledge level of team members affect the course allocation? Determinants such as

performance, urgency, frequency and expertise are identified as the most important in the decision-making process of assigning the most relevant course to a timeslot.

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the students to the group that suits their needs. Effective student allocation is the goal of this study, identifying the relevant factor for this decision is required. An important factor in student allocation is student performance. In the educational sector, the performance of a student is normally quantified by the average grade of a student. The content of the course between the different educational levels of the same educational year is related to each other, nevertheless, a higher educational level is received as more difficult since it goes more in-depth in the subjects of the course. Allocating students of the same educational year would be easier than transferring student of different educational years of the same educational level (RENN4 main findings interview maths teacher 15-04-2020). Another identified factor in the allocating students is the workload of each class. It is desired for the expert team to effectively spread the total workload of the students of the scheduled classes. The workload of EBD students can vary highly, therefore equal group sizes will not solve this problem. Minimised workload variability is desired for the team, but also for the students. Since EBD students are easily distracted, therefore the workload of a class cannot be too high. High workload results in a teacher focusing primarily on the behaviour instead of focusing on academic instruction. Therefore, group with a high workload impacts the students’ performance and behaviour negatively. When demands and resources are balanced, people feel able to manage workloads and experience positive effective outcomes; when demands exceed resources, teachers may feel overwhelmed and consequently experience stress and emotional exhaustion, leading to attrition (Bettini, Cumming, O’Brien, Brunsting, Ragunathan, Sutton, and Chopra, 2020). In section 3.8, the workload variability of the team is discussed. Minimising the workload variability limits the allocation of students to suitable education, nevertheless impacts the students’ performance and behaviour positively. Balancing the interests enhances improvement of the students’ performance and behaviour, while supporting the team with a matching amount of workload. To enhances effective student

allocation, workload and performance are identified as the most important determinants in this decision.

Lastly, the expert team is responsible for several classes instead of an individual teacher for one class for a given timeslot. The team has to determine which teacher is educating which group of students. Each teacher has their own teaching approach, preference, and expertise in the courses. The expertise of a teacher would be the most important factor in a regular school, but to educate students with emotional and behavioural disorders, other factors are also relevant. The expert team consists of a multi-skilled team, who master the courses of the team in some degree. Besides the expertise of the team members, a teachers’ teaching approach is valuable for improving students’ performance. Measuring this is a complex task, especially when students could be allocated on the basis of teaching approach, which enables the team to allocate the most suitable teacher. This is essential for improving the per-formance of students, but also to improve the behaviour of students with emotional and behavioural disorders (EBD). In section 3, retaining the autonomy of the teachers is desired for effectiveness of team-based education. Therefore the team should contain individual preferences. Questions arise like; How will it be identified which teacher educates in a certain teaching approach? How would this be measured and how does a team know which teachers suit which group best? Who will be responsible for making the final decision? The team needs to find consensus in this allocation, but disagreement is a possibility. The team needs to avoid these situations or find a constructive way to solve the dis-agreements. The positive effect of team-based education can be accomplished only when the members of the team share experiences and support each other when required. The team is responsible for the performance of the students and for the selection of their courses. Teaching approach, availability,

expertise and preference are identified as the most important determinants in this decision.

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a moment for school management to address absence and provides teachers the opportunity to discuss adjustments and other relevant points of interest. The long-term meeting is not yet applied in this school, nevertheless it could have great value when considering team-based education. In the current situation, there is no need to reflect, evaluate and/or discuss the performance of the team or student, since there is no team. This long-term meeting is addressed in this study as the evaluation meeting. The evaluation meeting could be a weekly meeting of approximately one hour, where the team can improve by addressing the important factors of transition phase of teamwork, such as goal setting, evaluation, reflection and feedback. The DSS should be able to be applied in both kinds of meeting. In section 6, the design of DSS is discussed in relation to both meetings. This research recommends the application of both

meetings in team-based education in SNE.

The DSS is developed for the expert teams of the school, but who should be responsible for the daily operation of the application of the DSS? Should each team member be responsible for the application of the DSS or should one person be responsible for the application? Each team member should at least be able to apply the DSS, since the availability of team members differs from day to day. This could lead to situations where no available team members know how to apply to DSS, this needs to be avoided. In the implementation phase of the DSS, each teacher should follow training to master a basic set of knowledge of the application of the DSS. During one of the interviews the school management guidance assigning a team leader to each team (RENN4 main findings interview with school management 03-04-2020). The school management stated that assigning a team leader creates responsibility and stability, which is in line with the research of Andersen, Jensen, Lippert, and Østergaard (2010) who stated ”The absence of leadership and explicit task distribution has been described as causing insufficient compliance with resuscitation guidelines”. This study assumes based on the statements of the school management that the school will assign a team leader for each expert team when MTM is implemented. If one person should be responsible for the application of the DSS, this person should be the team leader, especially for the application of the DSS in a weekly meeting. This study recommends that all teachers follow DSS

and assumes that each expert team has a team leader, who bears the main responsibility of the application of the DSS.

The complexity and importance of these decisions significantly increase when there is absence among the team. Every teacher would be allocated to a group of students in the normal circumstances, but if one teacher is absent there are more groups than teachers. Responding to the absence of teachers is received as one of the main problems of the current situation (RENN4 several interviews, Appendix A). The absence of teachers have a negative effect on the students’ performance (Herrmann and Rockoff, 2012). The class size of EBD students is smaller compared to high school, to provide the students with more specialised attention to improve performance and behaviour, but this is not possible anymore. All students need to be allocated into a number of groups that is equal to the number of available teachers of the team, which causes greater group sizes and increases the workload, and is expected to reduce the performance of students. The increased group size, workload and reduced performance is inevitable, but through effectively allocating the students of the scheduled classes into the available classes the effects could be minimised. Effective student allocation is required, especially in this situation due to the inevitable high workload. Besides effective student allocation, the allocation is required to be quick since there is limited time in the morning meeting. What if the absence occurs in the latter phase of the day? How and when will the team respond to the absence of a teacher? Could the application of the DSS be applied during breaks?

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(courses, students, and themselves).

The aim of the proposed DSS is to support teams in effective student allocation in team-based education. To achieve this result the identified determinants are required to be taken into account in the model of the DSS.

4.3 Stakeholders

There are multiple stakeholders, who would benefit from a well-functioning DSS in SNE if MTM would be implemented. The most important stakeholders in this research are the students and teachers, who are directly related to the DSS. In this section, the stakeholders are discussed, as are their particular needs for when a DSS would be implemented.

4.3.1 Teachers

Communication between teachers is of increased importance since the teachers are now part of a team. The management addressed that the morning meeting is not structured and short, which is in accordance with the observation. In order to secure individual and team professional development, communication is essential. It appears that the morning meeting is too short to address all relevant topics, which gives rise to a need to evaluate in a more-structured manner over a longer timespan.

The DSS aims to reduce the workload of the team by offering support in the decision-making process and effectively allocating the students. Since the DSS determines these decisions, the members have more time to discuss other relevant subjects. In order to reduce workload, the application of the DSS needs to be simple and quick. During the observation, it was identified that not all teachers the digital provided services of the school (RENN4 observations during a working day 25-02-2020, Appendix A). Main reason for this aversion of the digital services is the lack of perceived value.With this in mind, the DSS is desired to be simple. By making the team leader responsible the usage of the DSS is a good way to minimise aversion of the DSS.

4.3.2 Students

The DSS directly impacts the students, by assigning the students to a group instead of their class. In section 3, the importance of finding suitable education for individual students was already addressed. The re-allocation of students needs to increase their performance and behaviour, instead of decreasing it. Identifying the needs of individual students is essential in this process. If a certain group does not have the expected effect on a student, the team does not simply re-allocate the student. The reason why this student is under-performing should be the focus of the team, in order to improve the student’s performance and behaviour. Communication between the student, the parents, and the team is important in this process, according to the internal mentor of the school.

4.3.3 Parents of students

The DSS has an indirect impact on the parents of the students. The DSS aims to provide more suitable education for the students, which has a relation with their home situation. EBD students suffer from severe cognitive, emotional, or behavioural problems that already affects their well-being in their home environment negatively, as well as at school (van der Kamp, 2018). Providing students with a suitable academic curriculum and instruction is important to improve their academic outcomes and is an effective way to handle or prevent problem behaviour (van der Kamp, 2018). Therefore, improved outcomes of the students can have a positive impact on the home environment. But studies have also shown that the involvement of parents can have a significant positive effect on the performance of the student (Henderson and Mapp, 2002). Nevertheless, changing the group composition of the students could also have negative effects on the students’ behaviour, in this case the parents should notify the school if this significantly impacts the students’ behaviour.

4.3.4 School administration

SUPPORTING TEAMS IN STUDENT ALLOCATION TO ACCOMPLISH CHALLENGING TASKS IN SPECIAL NEEDS EDUCATION