Collaborative Writing for University Student: History
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University students are frequently required to collaborate, often in the form of collaborative writing tasks. The process as well as the outcomes of the collaboration depend on choices made during the group formation phase. 

  • group composition
  • university students
  • group formation
  • collaborative learning
  • collaboration
  • higher education
  • friendship
  • teacher-assigned
  • self-selection
  • student-selection

1. Introduction

Collaborative learning has been extensively documented in the last few decades [1][2] and it is quite common that university teachers assign collaborative tasks in higher education [3]. Collaborative tasks contribute to the development of collaboration and communication skills [4][5]. Moreover, students also acquire domain-specific knowledge [3][6] through several cognitive activities that are taking place during collaboration, such as collecting and sharing information, creating explanations for concepts, negotiating ideas, and building common ground [7].
One specific collaborative task, often implemented at university, is collaboratively writing papers [8][9] Besides the abovementioned general benefits of collaborative learning, collaborative writing aids students in learning to select relevant and reliable information, integrate information from various sources, and to distribute their own ideas to a broader audience [9][10][11]. Collaborative writing is nowadays often computer-supported. For example, students use collaborative writing tools such as Google Docs or Etherpad to collaboratively produce texts [12][13][14], and can use online meetings to interact and provide feedback while working remotely [15][16].
Notwithstanding the consensus in the literature regarding the many benefits of collaborative learning [17][18][19], difficulties and issues are also reported. Common issues include interpersonal conflicts, free-riding [1][20], and the imbalanced skills and knowledge of collaborating students [21]. These issues obviously impact the collaborative process and subsequently the group product. Taking this into account, it can be said that group formation, as a first step in collaborative learning [22], is crucial.
Several approaches can be followed in forming groups. Groups can be assembled by university teachers, deliberately or at random, or by students themselves [23][24]. When not forming groups randomly, university teachers often depart from a cognitive perspective [21][25][26][27]. However, university students’ perspectives on group formation are less clear.

2. Collaborative Writing in Groups

Collaborative writing is a specific type of collaborative learning. While collaborative learning entails “all instructional arrangements that involve two or more students working together on a shared learning goal” (p. 71) [28], collaborative writing can be defined as “the coauthoring of a single text by two or more writers, where the coauthors are involved in all stages of the composing process and have a shared ownership of the text produced” (p. 1) [29]. Collaborative writing tasks are very specific and complex, requiring extensive knowledge on vocabulary, grammar, content, sourcing, information selection, and writing [9][30]. The contribution of individual group members heavily determines the outcome. Well-composed texts can result from unequal participation [31] as each member brings in other competencies and knowledge [32].
A group consists of at least two students collaborating on the same product. The optimal group size may vary according to the goal and the type of the task [33][34][35]. The composition of a group greatly impacts the interactions between the group members and consequently students’ learning or task quality [33]. Group composition has been well-documented during the last few decades [26][33] and refers to the homogeneity or heterogeneity of a group in terms of, for example, gender [36] or competence level [26], or the degree to which group members are familiar with each other [37][38].
The process leading to group composition is called the group formation, which is a critical phase within collaborative learning [22]. When strategically employed, it can improve group performance [39][40].

3. Group Formation

Two main questions can be put forward with regard to the group formation process: (1) who is forming the groups and (2) what is considered when they are formed. Regarding the first question, a distinction can be made between teacher-assigned and student-selected groups. The term student-selected group formation is used interchangeably with self-selected group formation. Prior research is inconclusive regarding which of these two methods is best. Several studies have shown that students who are allowed to select their own collaboration partner(s) indicate that this method leads to a fairer group composition than being assigned to a group [41][42], as students perceive themselves as being more able than their teachers to select appropriate group members [41]. In particular, when teachers do not know their students very well, teacher-assigned group formation might not be the favorable group formation method, according to Lambić et al. [43].
Regarding the impact of student-selected versus teacher-assigned group formation on the collaborative process, students are more positive when collaborating with self-selected group partners as opposed to teacher-assigned group partners. More specifically, several studies have elicited that students experience more enjoyment, supportive behavior, and at-ease communications [23][40][44]. However, in other studies, students in self-selected groups realized that their partner, despite being a good friend, was not a good collaboration partner [41][45]. Meanwhile, whilst some scholars have indicated a greater extent of equal participation and a fairer task division in self-selected groups [23][40], others have established no differences [24], or contradictory findings, i.e., student-selection leading to lower levels of participation and more off-task talk [20][24][42].
Concerning group outcomes, some studies have shown higher quality writing tasks in teacher-assigned dyads in comparison to student-selected dyads [24][46]. In contrast, other researchers have concluded that student-selected groups outperform randomly assigned groups [47][48] and teacher-assigned groups that were based on self-reported ability [48]. Tsoi and Aubrey [44] found no general difference in language learning between teacher-assigned or student-selected group formation. However, when studying perceived performance, student-selected groups report higher scores which do not necessarily correspond to their actual grades [23]. Mitchell et al. [40] suggest that the appropriate group formation method depends on the task and that especially for tasks requiring much collaborative effort, self-selection might be eligible.
In summary, there are contradictory findings regarding the impact of student-selected or teacher-assigned group formation on both the collaborative process and outcomes. Some of these differences may be related to the way teachers or students actually form their groups [49], which brings us to the second question concerning group formation: what is considered when groups are formed?
The literature shows that teachers assign groups either at random [24] or purposefully homogeneously and/or heterogeneously based on student characteristics such as gender [36], ability [25][26], personality [50], and prior knowledge [6][27].
Regarding student-selected group formation, the research literature consistently points to group familiarity, and more in particular friendship, as the main determining motive for self-selecting a partner for collaboration [24][40][41][42][44][48]. Group familiarity is defined as the extent to which students know each other prior to the collaborative task [38]. The more familiar members are with each other, the quicker they can advance to the core of the collaborative task, as they need less time for regulating their collaborative process [23][38]. Furthermore, group familiarity in general is positively related to teamwork satisfaction [23][37]. In addition, choosing someone familiar decreases uncertainty about the course of the collaborative process, and students tend to prioritize certainty and predictability for academic tasks [49].
Given that students collaborate to perform a particular learning task for which specific skills are needed [49], one could expect that they take their peer’s specific ability into consideration when selecting a partner for collaboration. Several studies indicate the benefits of grouping students based on ability [26][43]. Although ability is one of the main characteristics that university teachers take into account in teacher-assigned group formation, limited research focuses on whether students consider a partner’s ability when forming groups. Ideally, students should consider peers with complementary skills [49]. According to Chen and Gong [48], students heavily rely on friendship for group formation, thereby ignoring the specific abilities of their group members. Fischer et al. [47] analyzed the group formation behavior of 672 higher education students and observed that student-selected groups were significantly more homogeneous than randomly assigned groups in terms of ability, gender, and pro-sociality (i.e., voluntary behavior aimed at benefiting others) [51]. In their study, it is unclear, however, whether students deliberately chose a partner of the same ability.
Students tend to rely on someone’s willingness to contribute to the task. In particular, reputational information on a student’s ability, work ethic, or task approach is considered independent of their actual ability [49]. Objective information is most often unavailable; hence, they rely on either their own experience from collaborating with a particular group member or on information from someone else [49].
In general, as people tend to be attracted to others with similar characteristics, attitudes, or beliefs [52], it can be hypothesized that students, whether consciously or not, self-select peers who share the same characteristics, attitudes, or beliefs for academic collaboration. Student-selected group members quickly recognize similarities in their chosen partners and perceive these as positive. Teacher-assigned group members, on the other hand, rather see differences, regardless of being randomly or purposefully heterogeneously assigned [23]. Collaborating with students similar to oneself can result in easier communication and increases the predictability of others’ behavior and values [49]; hence, improving the predictability of the collaborative process. However, choosing similar students for group formation results in low-diversity-groups [49].
In summary, there is ample research on how university teachers form groups and which student characteristics they take into account. However, while there are studies available on the aspects on which students are focusing in view of selecting group members, detailed information on students’ reasoning to actually select a partner is lacking. This is particularly the case for collaborative writing tasks.

This entry is adapted from the peer-reviewed paper 10.3390/educsci14010031


  1. Johnson, D.W.; Johnson, R.T.; Smith, K. The State of Cooperative Learning in Postsecondary and Professional Settings. Educ. Psychol. Rev. 2007, 19, 15–29.
  2. Lu, J.; Chen, X.; Wang, X.; Zhong, R.; Wang, H. Research on the Influence of Socially Regulated Learning on Online Collaborative Knowledge Building in the Post COVID-19 Period. Sustainability 2022, 14, 15345.
  3. Damsa, C.; Muukkonen, H. Conceptualising Pedagogical Designs for Learning through Object-Oriented Collaboration in Higher Education. Res. Pap. Educ. 2019, 35, 82–104.
  4. Kolm, A.; de Nooijer, J.; Vanherle, K.; Werkman, A.; Wewerka-Kreimel, D.; Rachman-Elbaum, S.; van Merriënboer, J.J.G. International Online Collaboration Competencies in Higher Education Students: A Systematic Review. J. Stud. Int. Educ. 2021, 26, 183–201.
  5. Kreijns, K.; Kirschner, P.A.; Vermeulen, M. Social Aspects of CSCL Environments: A Research Framework. Educ. Psychol. 2013, 48, 229–242.
  6. Erkens, M.; Manske, S.; Hoppe, H.U.; Bodemer, D. Awareness of Complementary Knowledge in Cscl: Impact on Learners’ Knowledge Exchange in Small Groups. In Proceedings of the Collaboration Technologies and Social Computing, Kyoto, Japan, 4–6 September 2019; Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer: Cham, Switzerland, 2019; Volume 11677, pp. 3–16.
  7. Damşa, C.I.; Ludvigsen, S. Learning through Interaction and Co-Construction of Knowledge Objects in Teacher Education. Learn. Cult. Soc. Interact. 2016, 11, 1–18.
  8. Nelson, N.; King, J.R. Discourse Synthesis: Textual Transformations in Writing from Sources; Springer: Dordrecht, The Netherlands, 2022; Volume 36, ISBN 0123456789.
  9. van Ockenburg, L.; van Weijen, D.; Rijlaarsdam, G. Learning to Write Synthesis Texts: A Review of Intervention Studies. J. Writ. Res. 2019, 10, 402–4028.
  10. Mateos, M.; Solé, I. Synthesising Information from Various Texts: A Study of Procedures and Products at Different Educational Levels. Eur. J. Psychol. Educ. 2009, 24, 435–451.
  11. Spivey, N.N.; King, J.R. Readers as Writers Composing from Sources. Read. Res. Q. 1989, 24, 7–26.
  12. Han, M.; Li, Y. The Effect of Face-to-Face and Non-Face-to-Face Synchronously Collaborative Writing Environment on Student Engagement and Academic Performance. J. Educ. Innov. Commun. 2019, 1, 65–74.
  13. Zhou, W.; Simpson, E.; Domizi, D.P. Google Docs in an Out-of-Class Collaborative Writing Activity. Int. J. Teach. Learn. High. Educ. 2012, 24, 359–375.
  14. Pymm, B.; Hay, L. Using Etherpads as Platforms for Collaborative Learning in a Distance Education LIS Course. J. Educ. Libr. Inf. Sci. 2014, 55, 133–149.
  15. Ertl, B.; Fischer, F.; Mandl, H. Conceptual and Socio-Cognitive Support for Collaborative Learning in Videoconferencing Environments. Comput. Educ. 2006, 47, 298–315.
  16. Putzeys, K.; De Wever, B. How University Students Collaboratively Write a Synthesis Text. A Case Study Exploring Small Groups of Students’ Overall Approach, Their Interactions and the Group Atmosphere. In Proceedings of the EDULEARN21 Proceedings 13th International Conference on Education and New Learning Technologies, Online, 5–6 July 2021.
  17. Qureshi, M.A.; Khaskheli, A.; Qureshi, J.A.; Raza, S.A.; Yousufi, S.Q. Factors Affecting Students’ Learning Performance through Collaborative Learning and Engagement. Interact. Learn. Environ. 2021, 31, 2371–2391.
  18. Paavola, S.; Hakkarainen, K. Trialogical Learning and Object-Oriented Collaboration. In International Handbook of Computer-Supported Collaborative Learning; Springer: Cham, Switzerland, 2021; Volume 19, pp. 241–259.
  19. Hernández-Sellés, N.; Muñoz-Carril, P.-C.; González-Sanmamed, M. Computer-Supported Collaborative Learning: An Analysis of the Relationship between Interaction, Emotional Support and Online Collaborative Tools. Comput. Educ. 2019, 138, 1–12.
  20. Le, H.; Janssen, J.; Wubbels, T. Collaborative Learning Practices: Teacher and Student Perceived Obstacles to Effective Student Collaboration. Camb. J. Educ. 2018, 48, 103–122.
  21. Erkens, M.; Bodemer, D. Improving Collaborative Learning: Guiding Knowledge Exchange through the Provision of Information about Learning Partners and Learning Contents. Comput. Educ. 2019, 128, 452–472.
  22. Dillenbourg, P. Over-Scripting CSCL: The Risks of Blending Collaborative Learning with Instructional Design. In Three Worlds of CSCL: Can We Support CSCL? Open Universiteit Nederland: Heerlen, The Nederland, 2002; pp. 61–91.
  23. Hilton, S.; Phillips, F. Instructor-Assigned and Student-Selected Groups: A View from Inside. Issues Account. Educ. 2008, 25, 15–33.
  24. Mozaffari, S.H. Comparing Student-Selected and Teacher-Assigned Pairs on Collaborative Writing. Lang. Teach. Res. 2016, 21, 496–516.
  25. Cohen, E.G. Restructuring the Classroom: Conditions for Productive Small Groups. Rev. Educ. Res. 1994, 64, 1–35.
  26. Schuitema, J.; Palha, S.; Van Boxtel, C.; Peetsma, T. Effects of Task Structure and Group Composition on Elaboration and Metacognitive Activities of High-Ability Students during Collaborative Learning. Pedagog. Stud. 2019, 2019, 136–151.
  27. Slof, B.; van Leeuwen, A.; Janssen, J.; Kirschner, P.A. Mine, Ours and Yours, Whose Engagement and Prior Knowledge Affects Individual Achievement from Online Collaborative Learning? J. Comput. Assist. Learn. 2020, 37, 39–50.
  28. Van Leeuwen, A.; Janssen, J. A Systematic Review of Teacher Guidance during Collaborative Learning in Primary and Secondary Education. Educ. Res. Rev. 2019, 27, 71–89.
  29. Storch, N. Collaborative Writing. In The TESOL Encyclopedia of English Language Teaching; Liontas, J.I., DelliCarpini, M., Eds.; John Wiley & Sons: Hoboken, NJ, USA, 2018; pp. 1–6. ISBN 9781118784235.
  30. Wigglesworth, G.; Storch, N. Pair versus Individual Writing: Effects on Fluency, Complexity and Accuracy. Lang. Test. 2009, 26, 445–466.
  31. Fernández Dobao, A. Collaborative Writing Tasks in the L2 Classroom: Comparing Group, Pair, and Individual Work. J. Second Lang. Writ. 2012, 21, 40–58.
  32. Marttunen, M.; Laurinen, L. Participant Profiles during Collaborative Writing. J. Writ. Res. 2012, 4, 53–79.
  33. Yang, T.; Luo, H.; Sun, D. Investigating the Combined Effects of Group Size and Group Composition in Online Discussion. Act. Learn. High. Educ. 2022, 23, 115–128.
  34. Sugai, M.; Horita, T.; Wada, Y. Identifying Optimal Group Size for Collaborative Argumentation Using SNS for Educational Purposes. In Proceedings of the 2018 7th International Congress on Advanced Applied Informatics, IIAI-AAI, Yonago, Japan, 8–13 July 2018; IEEE: Piscataway, NJ, USA, 2018; pp. 226–231.
  35. Abuseileek, A.F. The Effect of Computer-Assisted Cooperative Learning Methods and Group Size on the EFL Learners’ Achievement in Communication Skills. Comput. Educ. 2012, 58, 231–239.
  36. Takeda, S.; Homberg, F. The Effects of Gender on Group Work Process and Achievement: An Analysis through Self- and Peer-Assessment. Br. Educ. Res. J. 2014, 40, 373–396.
  37. Zhang, S.; Che, S.; Nan, D.; Li, Y.; Kim, J.H. I Know My Teammates: The Role of Group Member Familiarity in Computer-Supported and Face-to-Face Collaborative Learning. Educ. Inf. Technol. 2023, 28, 12615–12631.
  38. Janssen, J.; Erkens, G.; Kirschner, P.A.; Kanselaar, G. Influence of Group Member Familiarity on Online Collaborative Learning. Comput. Human. Behav. 2009, 25, 161–170.
  39. Slavin, R.E. When Does Cooperative Learning Increase Student Achievement? Psychol. Bull. 1983, 94, 429.
  40. Fischer, M.; Rilke, R.M.; Yurtoglu, B.B. Two Field Experiments on Self-Selection, Collaboration Intensity, and Team Performance; IZA Discussion Paper No. 13201. Available online: (accessed on 30 August 2023).
  41. Mitchell, S.N.; Reilly, R.; Bramwell, F.G.; Solnosky, A.; Lilly, F. Friendship and Choosing Groupmates: Preferences for Teacher-Selected vs. Student-Selected Groupings in High School Science Classes. J. Instr. Psychol. 2004, 31, 20–32.
  42. Post, M.L.; Barrett, A.; Scharff, L. Impact of Team Formation Method on Student Performance, Attitudes, and Behaviors. J. Scholarsh. Teach. Learn. 2020, 20, 1–21.
  43. Lambić, D.; Lazović, B.; Djenić, A.; Marić, M. A Novel Metaheuristic Approach for Collaborative Learning Group Formation. J. Comput. Assist. Learn. 2018, 34, 907–916.
  44. Tsoi, S.C.; Aubrey, S. Impact of Student-Selected Pairing on Collaborative Task Engagement. ELT J. 2023, 5, 1–12.
  45. Sadeghi, H.; Kardan, A.A. A Novel Justice-Based Linear Model for Optimal Learner Group Formation in Computer-Supported Collaborative Learning Environments. Comput. Hum. Behav. 2015, 48, 436–447.
  46. Hassaskhah, J.; Mozaffari, H. The Impact of Group Formation Method (Student-Selected vs. Teacher-Assigned) on Group Dynamics and Group Outcome in EFL Creative Writing. J. Lang. Teach. Res. 2015, 6, 147.
  47. Fischer, M.; Rilke, R.M.; Yurtoglu, B.B. When, and Why, Do Teams Benefit from Self-Selection? Exp. Econ. 2023, 26, 749–774.
  48. Chen, R.; Gong, J. Can Self Selection Create High-Performing Teams? J. Econ. Behav. Organ. 2018, 148, 20–33.
  49. Hinds, P.J.; Carley, K.M.; Krackhardt, D.; Wholey, D. Choosing Work Group Members: Balancing Similarity, Competence, and Familiarity. Organ. Behav. Hum. Decis. Process 2000, 81, 226–251.
  50. Stadler, M.; Herborn, K.; Mustafić, M.; Greiff, S. Computer-Based Collaborative Problem Solving in PISA 2015 and the Role of Personality. J. Intell. 2019, 7, 15.
  51. Eisenberg, N.; Fabes, R.A.; Spinrad, T.L. Prosocial Development. In Handbook of Child Psychology and Developmental Science; Damon, W., Lerner, R.M., Eisenberg, N., Eds.; Wiley: Hoboken, NJ, USA, 2007.
  52. Lazarsfeld, P.F.; Merton, R.K. Friendship as a Social Process: A Substantive and Methodological Analysis. In Freedom and Control in Modern Society; Berger, M., Abel, T., Page, C.H., Eds.; Van Nostrand: New York, NY, USA, 1954.
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