Taking teamwork seriously towards a new concept for student research projects

(1)

Vol.:(0123456789) TEACHING AND LEARNING: SYMPOSIUM

Taking teamwork seriously towards a new concept for student research projects

Sandra Brunsbach¹ · Ralph Kattenbach² · Ines Weber¹

Published online: 30 July 2020

Abstract

In order to develop and improve a course concept in political science, the Design- Based Research approach is employed. The approach involves three phases that form an iterative evolving cycle of course development. In the first analysis/orientation phase, we identify three major student challenges: an inadequate methodological competence, a prevalent and mostly unfounded methodological dogmatism, and a frequently insufficient ability to work in a team. With the second design development phase, we present the course concept to face these challenges and to evaluate the impact of our measures. We opted for a student research project, which is widely regarded as a suitable tool to enhance the students’ methodological competencies.

We also included professional coaching to build up team capacities. The third evaluation phase is based on multiple methods and sources. Other than standard course evaluations in higher education, it is not the participants’ overall satisfaction that is of interest, but the impact of our measures to meet the defined challenges. In the remainder of the article, the findings of the course evaluation are presented and discussed. The article concludes with recommendations for similar student projects and their evaluation.

Keywords Student research project · Student teams · Team work

* Sandra Brunsbach

sbrunsbach@politik.uni-kiel.de Ralph Kattenbach

ralph.kattenbach@ism.de Ines Weber

iweber@politik.uni-kiel.de

1 Institute for Social Science – Political Science, Kiel University, Westring 400, 24118 Kiel, Germany

2 ISM International School of Management, Brooktorkai 22, 20457 Hamburg, Germany

(2)

Introduction

Designing, evaluating and improving an innovative course concept

When designing a course concept, we consider two aspects to be important. First, the concept should be based on didactic experience and subject-specific knowledge of the lecturers and it should take the strengths and weaknesses of the students into account. Second, theoretical models and empirical findings from didactic research should be applied in order to reflect one’s own impressions and to draw conclusions for further improvements.

Design Based Research (DBR)¹ enables an integration of evaluation and research perspective into the process of developing and improving a wide variety of teaching and learning arrangements. By its very definition DBR is the “systematic study of designing, developing and evaluating educational interventions” (Plomp 2013: 11) such as programs, teaching–learning strategies and materials. DBR involves three main phases: an analysis/orientation phase, design development phase and an evaluation/retrospective phase (McKenney and Reeves 2014). First, a problem is recog- nized and then analysed with recourse to scientific literature. Based on this analysis, in the next phase, the design development phase, an intervention (e.g. course material, course concept) is designed and carried out as a prototype. A rigorous evaluation forms the third phase and allows a retrospective analysis of the effectiveness of the chosen design. Where revision is necessary to achieve the desired results, the design will be adjusted before a new version of the class is held. Thereby the phases form into an iterative cycle (Plomp 2013: 17). This evolutionary principle allows for adjustments not only from semester to semester, but also during the course.

The peculiarity of this approach is that it is not the aim to make comparisons between different courses as it is with commonly used course evaluations in higher education or with experimental settings. DBR is a dynamic approach intending to design innovative learning environments by developing and adapting solutions for complex problems in the teaching and learning process. A course concept is not fixed; it can be adjusted continuously and allows experimental testing of different tools and didactics. DBR is a holistic approach to gain insights in how and why something works. Therefore, it puts emphasis on internal validity in form of data triangulation, thick description, crosschecking and the search for counterexamples.

External validity is gained by “framing issues as instances of something more gen- eral” (Bakker and van Eerde 2015: 25) and by transferability. If results in one study are successfully applied in a different context it can be assumed some kind of gener- alization exists (Bakker and van Eerde 2015).

1 DBR is discussed under diverse names. These include development research, design experiments or educational design research. For an overview see Bakker and van Eerde (2015: 11–12).

(3)

Using DBR for a course concept in higher education

We have adopted a DBR approach to identify existing difficulties in teaching and learning, to develop an innovative course concept, to improve teaching provision, and most importantly to analyse and further improve the entire process.

The identification of three interrelated challenges—analysis and orientation Many years of practical teaching experience and a review of the literature on political science teaching, revealed three interconnected deficits that hinder the development and progress of many students of political science. These deficits are: (1) the inadequate methodological competence of students; (2) a prevalent and mostly unfounded methodological dogmatism and; (3) a frequently insufficient ability to work in a team.

(1) Methodological competence is widely regarded as a central requirement for political science students. Methodological training enables them “to discern, evaluate, and construct knowledge claims, evidence-based arguments and meth- odologically sound work” (Howard 2010: 393) and it is beneficial for a student’s future career (Andersen and Harsell 2005). However, despite numerous lectures on research methods and complementary lab sessions, many undergraduate students and even a lot of students who start a master programme regard methods as unimportant or alien and lack adequate methodological skills (Schnapp et al.

2004: 161; Ryan et al. 2014: 88). Some are even scared, especially when it comes to quantitative approaches (Adriaensen et al. 2014; Bernstein and Allen 2013).

(2) Students tend to succumb to methodological dogmatism (Johnson and Onwuegbuzie 2004: 14). At first glance, it may come as a surprise that limited methodological competence does not hinder students from holding strong believes about ‘correct‘ and ‘wrong’ methods. We believe that lack of proficiency leads to the activation of prevalent research stereotypes. This uninformed methodological dogmatism is characterised by polarisation between quantitative and qualitative approaches and an overemphasis on single characteristics and quality criteria (e.g. sample size). Evidently, this dogmatism prevents students from choosing an adequate empirical approach for their research projects. What is needed is a pragmatic and well-reflected usage of methods (Onwuegbuzie and Leech 2005).

(3) Teamwork capacity is of growing importance for subsequent professional activities of students and a prerequisite for successful joint (research) projects.

Reflections on team processes, consensus-finding and coordinated team behav- iour are required for effective teamwork. However, being young adults, the students’ ability to work in teams is not very developed and therefore not yet pro- nounced (Oakley et al. 2004: 9). Many student teams struggle with social and organisational issues while conducting a project (Hansen 2006: 12). Many students are frustrated with their team experiences (Bolton 1999; Pauli et al. 2008) and quite a few student teams fail to complete their assignments because of team issues (Schmedding 2011).

(4)

Development and a first implementation

To address all three deficits, we designed a course concept for first year master students in political science. This concept is based on three related principles that are accompanied by a stringent evaluation of the course impact, which constitutes a fourth element of our concept.

(1) Regarding the lack of methodological knowledge, we opted for one of the most established and successful approaches (Winn 1995) by having students con- duct their own small-scale research project. A student research project enables students to experience science by completing the whole research process accompanied by skilled lecturers. This form of experiential learning enables them to apply methods in order to really understand them (Parker et al. 2008: 33; Adri- aensen et al. 2015). To keep the student workload manageable, our course concept entails fixed research topics and prescribed research methods to use. For all other decisions, full decision-making responsibility was given to the student teams.

In a first implementation the students dealt with the field of ‘Politics and Gen- der’. The fourteen participants came from various BA degree programmes at other universities and had divergent methodological knowledge. However, all of them had already taken methodological courses. The students were assigned to three different teams. Team A was asked to use a quantitative content analysis of gender policies in party manifestos. Team B implemented a qualitative content analysis of mass media coverage regarding the presentation of female politicians working in highly gendered policies. Team C conducted in-depth interviews on career paths with high- ranking female and male politicians.

The course consisted of an introductory meeting, three obligatory weekend seminars and participant-organised work phases. The obligatory weekend seminars were used to impart knowledge on scientific work and research methods. Additionally, the lecturers offered consultation hours at the team level to provide guidance on scientific challenges. The students were asked to accomplish three tasks: (a) a poster presentation on their research in progress, due at the second weekend seminar, (b) a conference paper with presentation of preliminary results and discussion of another team’s paper (due at the third weekend seminar) as well as (c) a final project report (due at the end of the semester).

(2) To counteract a generalised and poorly founded assessment of diverging research traditions, great importance has been attached to the equal treatment of qualitative and quantitative research approaches. Additionally, we opted for tandem- teaching. One lecturer shall provide knowledge of quantitative methods, whereas the other lecturer was responsible for teaching qualitative research approaches. Of course, both lecturers needed to be open to each other’s research practices in order to serve as role models for a pragmatic approach to methods.

The student teams shall approach related research topics using different qualitative and quantitative methodological approaches. By ascribing the empirical methods to the teams, personal preferences and prejudices in the choice of methods were eliminated. Plenary discussions and peer-exchange were set to uncover the merits and limits of qualitative and quantitative methods as well as their mutual completion.

(5)

(3) As a well-functioning team is crucial for team performance and student research projects. This issue got the most attention in our course concept. We thus designed a number of intervening measures. Since instructors’ attitudes towards teamwork significantly influence the students’ attitude (Chapman and van Auken 2001), we made clear from the very beginning the importance of teamwork. Even before the course started, we mentioned explicitly teamwork capacities as an objec- tive in the course description in order to emphasise its importance. In addition, a chapter on teamwork experiences was an integral part of the final research report of the student teams.

Students were randomly assigned to the groups to avoid team-forming through friendship, sympathy or preferences (e.g. for a methodological approach). The random group formation ensured that all participants had to go through a comparable process of teambuilding to get into a smooth and coordinated action. It also prevented students from grouping according to their level of achievement (Oakley et al.

2004: 11). Besides, our random group formation simulated real-life situations as people do not often get to pick whom to work with, and it prevented the perception that course instructors treat students differently (Crowe and Hill 2006: 33). This teambuilding by lot resulted in one gender-balanced group, one female-dominated group and one male-dominated group.

In order to support the teambuilding process and to train teamwork capacities, we opted to integrate coaching support for the students. Coaching is “the art of facili- tating the performance, learning and development” (Downey 2003: 21). Other than mentors, tutors or consultants, coaches do not provide content-related expertise and guidance. They aim to help the ‘coachees’ find their own answers and solutions to self-defined problems. Coaching is a powerful instrument with a positive impact on various outcome variables like performance (Ellinger 2003), task satisfaction (Kim 2014) and commitment (Parker et al. 2008). Coaching elements in the university context are increasingly found (Hebecker et al. 2016). Coaching is used in the realm of student career service or in faculty development (Iser and Thedorff 2016). Szc- zyrba (2011: 30) speaks of a coaching boom at German universities. Yet, the usage of coaching elements to enhance the learning process within student projects is far from common.

As we dealt with student teams, we opted for team coaching, which incorporated all elements of individual coaching, but focused on a team as a collective unit. For teams, coaching can help to improve coordination within the team, resulting in better performance and project completion within the deadlines (Dimas et al. 2016).

The team coaching shall help the student teams reflect on their team processes to improve coordination and team climate and to enhance social and organisational skills and thus teamwork capacities. Particularly for comprehensive team assignments in a student research project, coaching should reduce the risk of failing due to team conflicts.

Although some articles promote something akin to a teacher-coach (Bolton 1999), we do not deem a coaching role for lecturers practicable. The lecturer’s role represents quite the opposite of a coaching relationship with the students. They provide expertise and guidance to students during the course and in consultation hours;

they proofread, judge and grade the students’ performance. Although a supportive

(6)

trust-relationship between students and lecturer is very much appreciated and personal, mentoring or tutoring of students is common in some national higher education systems, it is still a hierarchical relationship. We therefore included two external professional coaches to complement the teaching activities.² They were required to coach the teams and train them in the use of coaching techniques for team moderation (e.g. retrospectives on team processes). The first examples of the integration of such aspects in course concepts show that they can have a positive influence on the cooperation of student teams (Tammeorg et al. 2019). More specifically, individual team-coaching sessions were planned as an integral part of all weekend seminars. It was the coaches’ mission to provide supervision for moderated team sessions and peer coaching. During the first weekend seminar, initial training on moderation and facilitation techniques was aimed at enabling students to organise and coach them- selves in autonomous working groups. Teambuilding exercises were used, as they can support a positive team atmosphere (Ekimova and Kokurin 2015). For the second weekend, the coaching session focused on the current state of the students’ project work and group dynamics. Students were asked beforehand to describe existing team conflicts and obstacles in order to confidentially discuss constructive ways to handle such conflicts. All teams were scheduled to go through various steps of reflection; they practised how to criticise respectfully, and how to deal with individual requests and needs in a constructive manner without losing track of the scientific goal. At the third weekend, a team-based reflection on workload distribution, decision-making and lessons learned were intended to form the core aspect of the coaching session.

(4) Course evaluation plays a special role in the DBR as it forms the basis for the iterative adjustment process. We consider the evaluation measures a configur- able element of the course concept. Accordingly, we used numerous feedback chan- nels and multiple methods in an experimental way to evolve an optimal evaluation concept.

To understand the impact of teaching and coaching on learning and team progress, qualitative evaluation tools were employed. These included feedback rounds on the team progress at the beginning, and feedback rounds on the course elements at the end of every workshop day. Moreover, regular consultations between lecturers and students, and reflections with the coaches took place. Minutes were taken from all meetings. Finally, the written team-reflections integrated in the research report are a valuable source for evaluation. The qualitative material has been coded and analysed by means of a summarising qualitative content analysis.

These measures were accompanied by evaluation forms, distributed after the completion of one third and two thirds of the project time (at the end of the second and third weekend seminar), which included closed and open-ended questions.

For confidentiality and anonymity, no personal or socio-demographic data were obtained. However, students generated a personal identifier in order to track the

2 Even with little or no budget, there are opportunities to use coaching in higher education. For example, it is not unusual for coaching providers to offer their services pro bono and benefit from the reputation of the university.

(7)

learning progress of each student. The large number of different data sources ena- bled data triangulation, which we used to increase internal validity.

Course evaluation

In a first round of introductions, half of the students say they have little or no prior knowledge of social science methods, while the other half indicates knowledge in either qualitative or quantitative methods. The first evaluation form at the end of the second weekend seminar reveals the same finding using an open retrospective question.³ During the semester, students perceive a huge increase in their methodological competencies and their research expertise. This relates in particular to their skills in performing literature and information searches, the profound assessment of scientific articles, and most importantly, the use of research methods. Improvements are measured at two points in time using the first and the second evaluation form (Fig. 1).

As mentioned above, undergraduate students pass an introduction lecture on social science methods. One can expect that the senior students in our class have at least basic knowledge on methods. The students’ self-perception at the beginning of the course underlines this assumption. Yet, five out of thirteen students raised severe dogmatic statements at the beginning of the course, such as ‘I ridicule qualitative research as unrepresentative’ or ‘quantity does not say a thing’.

With one exception, these students initially believed that they had profound methodological knowledge. Open responses in the second form as well as in

Fig. 1 Self-perception of the learning progress

3 Open question in the first questionnaire: “What understanding of qualitative and quantitative methods existed before the start of the course?”.

(8)

the team reflections in the project report show that all students developed a better understanding of the merits and limits of different qualitative and quantitative approaches. At the end of the course, none of the students raised dogmatic believes anymore. Some still favour one group of research methods, but they do so in a well-informed and reflective manner, without discrediting the other methods. The teaching concept proves to be successful with regard to building knowledge and eliminating dogmatism as this finding consistently returns in all evaluations and observations.

Regarding the development of team competencies and the impact of coaching, the picture is more complex. Firstly, we observe clear team differences in teamwork capacities depending on the gender composition. The gender-balanced team shows a good cooperation style, while the male-dominated team underperforms and fails to accomplish the team assignment.

In the female-dominated team, the sole male student behaves passively. Appar- ently, this result is not random as the observations perfectly match the findings from Takeda and Homberg (2014). They report a superior cooperation style, less social loafing and more equitable contributions in gender-balanced groups.

Moreover, they conclude that a female-dominated team can lead to male members withdrawing and female team members in male-dominated student teams are not being heard on an equal footing. The sole female student in this instance quickly adapts to the prevalent male team culture.

A second finding is that the students’ self-confidence and self-evaluation regarding their teamwork capacities, as expressed in feedback rounds at the first weekend seminar, are much more optimistic than the external assessment by teachers and coaches. This is in line with other findings that students compared to faculty feel much more positive among others about team effectiveness, learning processes, and conflict resolution abilities (Chapman et al. 2010: 44).

Accordingly, the discussion of team processes and the integration of coaching elements initially meet with many reservations. However, lecturers and coaches were able to increase acceptance as interim evaluations and final reflection show.

In the course, students’ requests for team coaching increased and the coaching demand significantly exceeded the supply.

Only the male-dominated team did not rethink their attitude during the semester. They held a strong overconfidence of their own expertise and teamwork experience (‘we are the big ones now [compared to BA-students]’); they denied the benefits of coaching. Consequently, they regard reflections on team processes and coaching support unnecessary until realising that they would not be able to complete their project due to a non-functional team. The students who rejected support were the ones who had the greatest need for it. During the seminar lecturers and coaches agreed that due to the rigid students’ attitudes there was no chance for further external intervention in order to change the masculine team culture.

We assume that this extreme attitude was fostered by male dominance. Only after the end of the course did they come to the realisation that the failure was due to overconfidence and lack of team cooperation, something also expressed by sev- eral team members.

(9)

Lessons learned—designing an improved course concept and evaluation

The results of the evaluations make a compelling argument for a conceptual revision of three issues in order to increase the effectiveness of the teaching–learning process even further.

Firstly, coaching should be more strongly tailored to the needs within each team.

This holds true for the team-specific challenges and solution approaches as well as the timing of coaching sessions. It was not possible to deal with all team-specific dynamics and problems in a target-oriented way at the three coaching sessions scheduled in advance. Therefore, at least some appointments should be arranged individually and at short notice. A voucher system, from which each team can redeem a certain number of coaching sessions, would be possible.

Secondly, the random formation of teams could be done better with a well thought-out predefinition by the lecturers. In this context the gender balance in teams is of special importance (Takeda and Homberg 2014). However, other avail- able information, e.g. on working style, could be used as well.

Thirdly, in particular male students overestimated their own skills. Students’ self- assessments seem not to be a reliable indicator for their level of knowledge, team competence and individual performance. Students should be offered an opportunity for comparison and alignment of self-assessment and actual capacities. Lecturers could provide timely performance feedback on milestones and work packages during the semester and coaches could offer their impressions on the students’ teamwork capacities.

The DBR was applied not only in terms of content to the course concept, but also to the evaluation concept itself. We gathered data in multiple ways to cross-validate the findings but also to find out how well evaluation measures work. We admit that

Fig. 2 Revised evaluation concept

(10)

our findings are based on quantitatively limited data and the extent to which these findings are transferable to other settings must be interpreted with caution. However, the triangulation of quantitative and qualitative evaluation of the students, the lecturers and coaches proved to complement each other well and served as a cross-valida- tion. Based on this experience, we further developed and structured the course evaluation towards a roadmap that could be adapted for similar course concepts (Fig. 2).

Quantitative measures

In order to trace individual learning and developments, we intend to expand the lon- gitudinal character of the evaluations. All quantitative measures will be linked by using personal identifiers.

An initial questionnaire can be used for strategic team formation based on gender and other individual characteristics (e.g. working style) as well as to collect existing experiences and needs.

The periodic evaluation during the semester turned out to provide valuable information on how the students perceive the course content and how well the team process works out. The measurement times approximately after one and two thirds of the course of the seminar give opportunity to make corrections with respect to content during the course and to account for fundamental differences in perceptions between students and lecturers.

Standardising and linking the individual questionnaires provides for a small quantitative diary after each course session to evaluate self-assessed work engage- ment, perceptions of the course elements as well as of the team process. The diary could also be extended to team coaching to track how coaching works. As coaching is based on a trusting relationship, coaching sessions are confidential and cannot be used for evaluation without the student’s explicit permission. Yet, it would be possible to implement a discrete evaluation where the students can indicate quantitatively whether they have made new agreements and whether they have implemented new behavioural patterns.

Qualitative measures

The idea to keep written records on one’s own (non-confidential) observations turned out to be inspiring for awareness and mutual exchange between lecturers and coaches. Implemented as a shared electronic logbook throughout the semester, these records helped to align course content to needs.

Additionally, minutes from oral feedback should be taken at the weekend seminars. Ideally, the feedback is obtained during the course of the day to evaluate single elements.

We fully recommend the team-reflection as an integral part of the final team report. For one thing, this elaborated reflection of the team development provides in-depth explanations for quantitative evaluations and second, as per the examination part, reflections on team processes and students’ awareness gain in importance.

(11)

Finally, from the student reflection reports as well as from our observations, we deem it important to let students practice regular moderated retrospective meetings. Such team-reflection improves team capacities, increases awareness of team processes and implements an ongoing evaluation of team processes for each team.

Although this does not contribute to course evaluation directly, it will most likely increase the quality of the reflection part in the final report.

References

Adriaensen, J., E. Coremans, and B. Kerremans. 2014. Overcoming statistics anxiety. Towards the incor- poration of quantitative methods in non-methodological courses. European Political Science 13(3):

251–265.

Adriaensen, J., B. Kerremans, and K. Slootmaeckers. 2015. ‘Editors’ Introduction to the thematic issue Mad about methods? Teaching research methods in political science. Journal of Political Science Education 11(1): 1–10.

Andersen, K., and D.M. Harsell. 2005. Assessing the impact of a quantitative skills course for undergradu- ates. Journal of Political Science Education 1(1): 17–27.

Bakker, A., and D. van Eerde. 2015. An introduction to design-based research with an example from statistics education. In Approaches to qualitative research in mathematics education. Examples of methodology and methods, ed. A. Bikner-Ahsbahs, C. Knipping, and N. Presmeg, 429–466. Heidelberg: Springer.

Bernstein, J.L., and B.T. Allen. 2013. Overcoming methods anxiety Qualitative first, quantitative next, fre- quent feedback along the way. Journal of Political Science Education 9(1): 1–15.

Bolton, M.K. 1999. ‘The role of coaching in student teams A “just-in-time” approach to learning. Journal of Management Education 23(3): 233–250.

Chapman, K.J., M.L. Meuter, D. Toy, and L.K. Wright. 2010. ‘Are student groups dysfunctional?‘. Journal of Marketing Education 32(1): 39–49.

Chapman, K.J., and S. van Auken. 2001. ‘Creating positive group project experiences. An examination of the role of the instructor on students’ perceptions of group projects. Journal of Marketing Education 23(2):

117–127.

Crowe, M., and C. Hill. 2006. Setting the stage for good group dynamics in semester-long projects in the sciences. Journal of College Science Teaching 35(4): 32–35.

Dimas, I.D., T. Rebelo, and P.R. Lourenço. 2016. Team coaching One more clue for fostering team effectiveness. Revue Européenne de Psychologie Appliquée/European Review of Applied Psychology 66(5):

233–242.

Downey, M. 2003. Effective coaching. Lessons from the Coaches’ Coach. New York: Texere/Thomson.

Ekimova, V., and A. Kokurin. 2015. ‘Students’ attitudes towards different team building methods. Procedia - Social and Behavioral Sciences 186: 847–855.

Ellinger, A.D. 2003. Antecedents and consequences of coaching behavior. Performance Improvement Quar- terly 16(1): 5–28.

Hansen, R.S. 2006. Benefits and problems with student teams. Suggestions for improving team projects.

Journal of Education for Business 82(1): 11–19.

Hebecker, E., B. Szczyrba, and B. Wildt (eds.). 2016. Beratung im Feld der Hochschule. Formate—

Konzepte—Strategien—Standards. Wiesbaden: Springer.

Howard, P. 2010. Triangulating debates within the field teaching international relations research methodology. International Studies Perspectives 11(4): 393–408.

Iser, A., and P. Thedorff. 2016. Peer-coaching als Beratungsformat von Studierenden für Studierende. In Beratung im Feld der Hochschule. Formate—Konzepte—Strategien—Standards, ed. E. Hebecker, B.

Szczyrba, and B. Wildt, 181–192. Wiesbaden: Springer.

Johnson, R.B., and A.J. Onwuegbuzie. 2004. Mixed methods research. A research paradigm whose time has come. Educational Researcher 33(7): 14–26.

Kim, S. 2014. Assessing the influence of managerial coaching on employee outcomes. Human Resource Development Quarterly 25(1): 59–85.

McKenney, S., and T.C. Reeves. 2014. Educational design research. In Handbook of research on educational communications and technology, ed. J.M. Spector, M.D. Merrill, J. Elen, and M.J. Bishop, 131–140.

Dordrecht: Springer.

Oakley, B., R.M. Felder, R. Brent, and I. Elhajj. 2004. Turning student groups into effective teams. Journal of Student Centered Learning 2(1): 9–34.

(12)

Onwuegbuzie, A.J., and N.L. Leech. 2005. On becoming a pragmatic researcher. The importance of com- bining quantitative and qualitative research methodologies. International Journal of Social Research Methodology 8(5): 375–387.

Parker, J., A. Dobson, S. Scott, M. Wyman, and A. Sjöstedt Landén. 2008. International bench-marking review of best practice in the provision of undergraduate teaching in quantitative methods in the social sciences. Keele: Keele University.

Pauli, R., C. Mohiyeddini, D. Bray, F. Michie, and B. Street. 2008. Individual differences in negative group work experiences in collaborative student learning. Educational Psychology 28(1): 47–58.

Plomp, T. 2013. Educational design research. An introduction. In Educational design research. Part A: An introduction, ed. T. Plomp and Nieveen Nienke, 10–51. Enschede: Netherlands Institute for Curriculum Development.

Ryan, M., C. Saunders, E. Rainsford, and E. Thompson. 2014. Improving research methods teaching and learning in politics and international relations. A ‘reality show’ approach. Politics 34(1): 85–97.

Schmedding, D. 2011. Teamentwicklung in studentischen Projekten. In Software engineering im Unterricht der Hochschulen. Tagungsband 12. Workshop SEUH, ed. J. Ludewig and A. Böttcher, 16–20.

Schnapp, K.-U., N. Behnke, and J. Behnke. 2004. ‘Methodenausbildung in der Politikwissenschaft. Oder:

Wie aus dem Aschenputtel eine Prinzessin werden kann‘. Rundbrief der Deutschen Vereinigung für Politikwissenschaft 131: 158–167.

Szczyrba, B. 2011. Beratung und Coaching im Feld der Hochschule. Das Netzwerk Wissenschaftscoaching.

Journal für Hochschuldidaktik 22(2): 30–31.

Takeda, S., and F. Homberg. 2014. ‘The effects of gender on group work process and achievement. An analysis through self- and peer-assessment‘. British Educational Research Journal 40(2): 373–396.

Tammeorg, P., A. Mykkänen, T. Rantamäki, M. Lakkala, and H. Muukkonen. 2019. Improving group work practices in teaching life sciences. Trialogical learning. Research in Science Education 49(3): 809–828.

Winn, S. 1995. Learning by doing. Teaching research methods through student participation in a commis- sioned research project. Studies in Higher Education 20(2): 203–214.

Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Sandra Brunsbach is a scientific research assistant at Kiel University. She holds a diploma degree in political science from Potsdam University and a Ph.D. degree from the Heinrich Heine University Düs- seldorf. Sandra is a fellow at the Institute of German and International Party Law and Party Research, Düsseldorf. Political parties and the political representation of women are fields of her work. She has many years of experience in teaching political science. In 2017, her efforts to innovate and improve teaching were honoured by the CAU Kiel with an award for “outstanding teaching” that she won together with her colleague Ines Weber.

Ralph Kattenbach teaches at the International School of Management, Hamburg. Ralph holds a Mas- ter’s degree in Organizational Psychology from Utrecht University, The Netherlands. He earned his Ph.D.

degree at the Centre for Personnel Research at Hamburg University. He is a member of the AgileVen- tureLab, a global think tank focused on researching and applying agile principles to management and leadership and helping companies and individuals to cope better with ambiguity and unpredictability.

The impact of professional coaching in the organizational and educational context is a recurring topic in his research. As scientific advisory board member, he is currently supporting the cross-national Coaching Benchmark Survey in Asia.

Ines Weber is a scientific research assistant at Kiel University. She holds a Master’s degree in political science, communication science and psychology from Greifswald University and a Ph.D. degree from Kiel University. Ines’ research focuses on political theory, especially socialist and feminist thought are fields of her work. Since 2017, she has been working in the EU-funded project “Baltic Gender” that deals with gender equality structures in the marine sciences. Ines has many years of experience in teaching political science.