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Outline

Title
Abstract
Figures
Introduction
Related Work
Data Corpus
Analysis of Documents
Results
Basic Data
Control Methods
New Findings Outside of Previous Taxonomies
Summary and Discussion
Summary of Empirical Findings
Design Implications
Limitations and Future Work
References
FAQs
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Computer Science
Information Systems

How People Write Together Now

Profile image of Gary OlsonGary Olson

2017, ACM Transactions on Computer-Human Interaction

https://doi.org/10.1145/3038919
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description

40 pages

Abstract

Today's commercially available word processors allow people to write collaboratively in the cloud, both in the familiar asynchronous mode and now in synchronous mode as well. This opens up new ways of working together. We examined the data traces of collaborative writing behavior in student teams' use of Google Docs to discover how they are writing together now. We found that student teams write both synchronously and asynchronously, take fluid roles in the writing and editing of the documents, and show a variety of styles of collaborative writing, including writing from scratch, beginning with an outline, pasting in a related example as a template to organize their own writing, and three more. We also found that the document serves as a place where they share a number of things not included in the final document, including links or references to related materials, the assignment requirements from the instructor, and informal discussions to coordinate the collaboration or to structure the document. We computed a number of measures to depict a group's collaboration behavior and asked external graders to score these documents for quality. We found that the documents that included balanced participation and/or exhibited leadership were judged higher in quality, as were those that were longer. We then suggested system design implications and behavioral guidelines to support people writing together better, and concluded the paper with future research directions.

Figures (27)
Table |. A Shortened Version of Posner and Baecker’s [1992] Taxonomy of Styles of Collaborative Writing with Modifications from Lowry et al. [2004] 2. RELATED WORK
Table |. A Shortened Version of Posner and Baecker’s [1992] Taxonomy of Styles of Collaborative Writing with Modifications from Lowry et al. [2004] 2. RELATED WORK
Table II. The Number of Documents in the Corpus for Each type of Assignment for Each Year —combined scope statement and work breakdown structure in one document; and —combination of cost, risk, and quality analyses in one document.
Table II. The Number of Documents in the Corpus for Each type of Assignment for Each Year —combined scope statement and work breakdown structure in one document; and —combination of cost, risk, and quality analyses in one document.
Fig.2. (a) and (b) Views of participation in co-authoring a document, illustrating the amount of contributior each person made and when they made it.
Fig.2. (a) and (b) Views of participation in co-authoring a document, illustrating the amount of contributior each person made and when they made it.
Table III. Summary of the Independent and Dependent Variables, Organized by the Categories in Posner and Baecker’s Framework similarly was 1,531 words, 2 5 pages long. The Cost, Risk and Quality document was on average 967 words or 1.6 pages. Knowing this, we controlled for assignment type in do- ing the regressions on quality and in doing so found that longer documents (controlled for type) often score higher in quality (Beta = .00096*, p < .05). Since points were lost for missing aspects of the assignment, this is likely a reflection of completeness. Having co-authors will make it less likely that portions will be overlooked.
Table III. Summary of the Independent and Dependent Variables, Organized by the Categories in Posner and Baecker’s Framework similarly was 1,531 words, 2 5 pages long. The Cost, Risk and Quality document was on average 967 words or 1.6 pages. Knowing this, we controlled for assignment type in do- ing the regressions on quality and in doing so found that longer documents (controlled for type) often score higher in quality (Beta = .00096*, p < .05). Since points were lost for missing aspects of the assignment, this is likely a reflection of completeness. Having co-authors will make it less likely that portions will be overlooked.
Fig. 3. (a) and (b) The activity spread out on a timeline from when the assignment began (talked about in class) to when it was due.
Fig. 3. (a) and (b) The activity spread out on a timeline from when the assignment began (talked about in class) to when it was due.
Fig.4. Figure 4(a) illustrates an uneven participation where the blue author contributed most of the content in the final draft, 4(b) illustrates a more even participation where the blue, orange, and green authors eack contribute about the same amount of text in the final draft.
Fig.4. Figure 4(a) illustrates an uneven participation where the blue author contributed most of the content in the final draft, 4(b) illustrates a more even participation where the blue, orange, and green authors eack contribute about the same amount of text in the final draft.
Fig. 5. Explicit project management and discussion at the top of the document then deleted at the last session before turning in the final version.
Fig. 5. Explicit project management and discussion at the top of the document then deleted at the last session before turning in the final version.
Fig. 6. Explicit project management in the document. The names were in parentheses next to the section they were to write. We blanked them out for privacy.
Fig. 6. Explicit project management in the document. The names were in parentheses next to the section they were to write. We blanked them out for privacy.
Fig. 8. An example of using the informal in-text commenting, with highlighting added by the participants to call attention to the new material.
Fig. 8. An example of using the informal in-text commenting, with highlighting added by the participants to call attention to the new material.
ACM Transactions on Computer-Human Interaction, Vol. 24, No. 1, Article 4, Publication date: March 2017.
ACM Transactions on Computer-Human Interaction, Vol. 24, No. 1, Article 4, Publication date: March 2017.
Fig. 11. The assignment style. ACM Transactions on Computer-Human Interaction, Vol. 24, No. 1, Article 4, Publication date: March 2017.
Fig. 11. The assignment style. ACM Transactions on Computer-Human Interaction, Vol. 24, No. 1, Article 4, Publication date: March 2017.
How People Write Together Now: Beginning the Investigation with Advanced Undergraduates 4:21 the example, paste it in and then modify it to fulfill their own case and the requirements of the class. That is why in this figure we can see the very long starting document, which then gets smaller with sections replaced with their own text. This style has not been discussed in previous literature, and is opposite to the first two styles, in which the document was almost continuously increasing.
How People Write Together Now: Beginning the Investigation with Advanced Undergraduates 4:21 the example, paste it in and then modify it to fulfill their own case and the requirements of the class. That is why in this figure we can see the very long starting document, which then gets smaller with sections replaced with their own text. This style has not been discussed in previous literature, and is opposite to the first two styles, in which the document was almost continuously increasing.
inserting the text of the assignment, assigning people to sections, adding informal discussion, and in one case pasting in an example as well. It is logical that pasting in an example does not accompany writing from scratch, as both create large amounts of beginning text.
inserting the text of the assignment, assigning people to sections, adding informal discussion, and in one case pasting in an example as well. It is logical that pasting in an example does not accompany writing from scratch, as both create large amounts of beginning text.
Fig. 14. The brainstorm and select the best out of all style. Table V. Distribution of Styles, Where a Document Can Exhibit More Than one Style
Fig. 14. The brainstorm and select the best out of all style. Table V. Distribution of Styles, Where a Document Can Exhibit More Than one Style
Table VI. Distribution of Styles for Each of the Assignments The complicated last assignment, which included discussion of cost, risk, and quality, was more likely to have the exact wording of the assignment pasted to help them be sure they had completed everything. 5.2.5. Work Modes. Lowry et al. list Degree of Proximity and Degree of Synchronicity as two Work Modes. We do not know how many of the sessions were face-to-face versus remote, although many students commented that it was easier to work face-to-face and will do so in the future. Here, we show Degree of Synchronicity as how much of the work is simultaneous.
Table VI. Distribution of Styles for Each of the Assignments The complicated last assignment, which included discussion of cost, risk, and quality, was more likely to have the exact wording of the assignment pasted to help them be sure they had completed everything. 5.2.5. Work Modes. Lowry et al. list Degree of Proximity and Degree of Synchronicity as two Work Modes. We do not know how many of the sessions were face-to-face versus remote, although many students commented that it was easier to work face-to-face and will do so in the future. Here, we show Degree of Synchronicity as how much of the work is simultaneous.
Fig. 15. An example of the team members working in close proximity to each other while working simultaneously. 5.3. New Findings Outside of Previous Taxonomies 5.3.1. Quality. Of major interest in this work is the relationship between many of these measures that depict the writing collaboration and the resultant quality. The HLM showed that one control variable, the assignment type, had a significant effect on quality (p < .01). Later more detailed analyses showed that the Risk, Cost, and Quality assignment was on average lower in quality than the others. This might be because the assignment combined three standard reports in Project Management, and there were no clear examples to follow. Indeed, in all the documents where an example was pasted in to begin their work, only one of them was in the Risk, Cost, and Quality assignment. Most of those began by pasting in the assignment description, which was quite detailed.
Fig. 15. An example of the team members working in close proximity to each other while working simultaneously. 5.3. New Findings Outside of Previous Taxonomies 5.3.1. Quality. Of major interest in this work is the relationship between many of these measures that depict the writing collaboration and the resultant quality. The HLM showed that one control variable, the assignment type, had a significant effect on quality (p < .01). Later more detailed analyses showed that the Risk, Cost, and Quality assignment was on average lower in quality than the others. This might be because the assignment combined three standard reports in Project Management, and there were no clear examples to follow. Indeed, in all the documents where an example was pasted in to begin their work, only one of them was in the Risk, Cost, and Quality assignment. Most of those began by pasting in the assignment description, which was quite detailed.
Fig. 17. The combined relationships between aspects of collaborative work and quality, elapsed time, and proximity to the due date.
Fig. 17. The combined relationships between aspects of collaborative work and quality, elapsed time, and proximity to the due date.
Fig. 18. The conversation (a) at the beginning of the document, and the DocuViz depiction of the larg deletion before “cleaning up” for the final version (b).
Fig. 18. The conversation (a) at the beginning of the document, and the DocuViz depiction of the larg deletion before “cleaning up” for the final version (b).
Fig. 19. The assignment details and project management notes inserted inside a document as a place to keep things needed for the project. One team used the early document as a place by inserting schedules and actua images of their class schedule so they could find a regular time to meet. Anothe inserted a number of links to other examples of documents like the one they were t produce. In Figure 19, we show the notes from what the assignment was to contair from one document that was used as a place. In one document, the first of the assignments, one teammate took the opportunity;
Fig. 19. The assignment details and project management notes inserted inside a document as a place to keep things needed for the project. One team used the early document as a place by inserting schedules and actua images of their class schedule so they could find a regular time to meet. Anothe inserted a number of links to other examples of documents like the one they were t produce. In Figure 19, we show the notes from what the assignment was to contair from one document that was used as a place. In one document, the first of the assignments, one teammate took the opportunity;
Fig. 21. The presumably-motivating or amusing image inserted then quickly deleted.at the end of their simultaneous session. J. S. Olson et al.
Fig. 21. The presumably-motivating or amusing image inserted then quickly deleted.at the end of their simultaneous session. J. S. Olson et al.
Table B.I. Three Models with Document Length, Balance Participation, and Existence of Leadership as Independent Variables, Respectively. Dependent Variable is Quality Table B.II. Ultimate Model Predicting Quality, with Balance Participation and Existence of Leadership as Two Independent Variables, Controlling for Year, Assignment Types, and Team
Table B.I. Three Models with Document Length, Balance Participation, and Existence of Leadership as Independent Variables, Respectively. Dependent Variable is Quality Table B.II. Ultimate Model Predicting Quality, with Balance Participation and Existence of Leadership as Two Independent Variables, Controlling for Year, Assignment Types, and Team
For example, in order to compute t he ultimate model predicting dependent variable Quality, we selected the best-fit model (based on lowest AIC score) at stage three from the three models (with Document Length, Balance Participation, and Existence of Lead- ership as independent variables, res pective y) presented in Table B.I. Then, we used the model with Leadership and all the control variables as the basic model, added one of the other independent variables in pare the xZ,ange between the basic mod el and to the model at stage four. Afterward, we can com- the new model. If the change is bigger than the critical values for the chi-square statistic with 1 degree of freedom, 3.84 (p < .05) and 6.63 (p < .01), this change is highly significant and the model is significantly improved. Therefore, we get the model with Leadership and Balance Participation as independent variables and Qual Table B.II. ity as the dependent variable, as presented in
For example, in order to compute t he ultimate model predicting dependent variable Quality, we selected the best-fit model (based on lowest AIC score) at stage three from the three models (with Document Length, Balance Participation, and Existence of Lead- ership as independent variables, res pective y) presented in Table B.I. Then, we used the model with Leadership and all the control variables as the basic model, added one of the other independent variables in pare the xZ,ange between the basic mod el and to the model at stage four. Afterward, we can com- the new model. If the change is bigger than the critical values for the chi-square statistic with 1 degree of freedom, 3.84 (p < .05) and 6.63 (p < .01), this change is highly significant and the model is significantly improved. Therefore, we get the model with Leadership and Balance Participation as independent variables and Qual Table B.II. ity as the dependent variable, as presented in
Table B.III. Eight Models, Each Model Has One Individual Independent Variable. The Dependent Variable is Earlier Finish Table B.IV. Three Models, Each Has One Independent Variable. The Dependent Variable is Elapsed Time
Table B.III. Eight Models, Each Model Has One Individual Independent Variable. The Dependent Variable is Earlier Finish Table B.IV. Three Models, Each Has One Independent Variable. The Dependent Variable is Elapsed Time
C. CODEBOOK FOR CODING LEADERSHIP AND STYLES
C. CODEBOOK FOR CODING LEADERSHIP AND STYLES
over a section in DocuViz visualizations, or by displaying each slice of the document one by one in Google Docs’s revision history function. Work Styles. Start with visualizing the document’s history with DocuViz.
over a section in DocuViz visualizations, or by displaying each slice of the document one by one in Google Docs’s revision history function. Work Styles. Start with visualizing the document’s history with DocuViz.

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FAQs

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AI

What collaborative writing styles emerged from the study of Google Docs usage?add

The study identified six styles of collaborative writing, including informal discussions and pasting templates, highlighting innovative approaches students used to leverage Google Docs.

How does participation balance affect the quality of collaborative documents?add

Balanced participation was significantly linked to higher document quality, with a beta coefficient of 50.35, suggesting equitable contributions enhance final outputs.

What role does leadership play in the collaborative writing process?add

The presence of a leader in document collaborations correlated with higher quality, indicated by a beta of 9.87, emphasizing the importance of structured guidance.

What are the impacts of simultaneous editing in collaborative writing sessions?add

Simultaneous editing was common, occurring in 95% of documents, and was associated with reduced stress and earlier submission of assignments.

What metrics were used to assess document quality in student collaborations?add

Quality was gauged using a rubric assessing completeness, clarity, and format, validated by a high inter-coder reliability score of 0.87.

About the author
Gary Olson
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Related papers

How Students Collaboratively Write using Google Docs
Gary Olson

2015

Writing collaboratively is increasing in many professions, including among college students. Students are writing many assignments collaboratively, learning as they go. Writing collaboratively, however, takes coordination and awareness of who has done what. We offer a new tool, DocuViz, which displays the entire revision history of Google Docs, showing more than the one-step-at-a-time kind of snapshot currently available in Docs and Word. Using DocuViz, we analyzed 99 students’ reports from a Project Management class and found it to reveal interesting patterns of collaborative writing. We believe this tool would be useful not just for researchers, but also for the authors themselves and instructors.

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Writing Pedagogy Project: Collaborative Composing in Google Docs and Google Drive
Daniel Hocutt

Pedagogy project and conference paper submitted for a class titled Online Writing Instruction at Old Dominion University. Abstract: Collaborative composing is a staple of the workplace. Whether writing a technical manual, a policy statement, a press release, web copy, or an internal newsletter, you’ll seldom write on your own and you’ll always write for an audience. This unit addresses rationale, methods, practices, and strategies for collaborative composing in academic writing, but reflects principles and procedures that easily transfer to workplace settings.

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Studies of Computer Supported Collaborative Writing. Implications for System Design
henrry henrry

2002

This paper analyses transformations in collaborative activities that a computersupported collaborative writing system introduces into co-authors' practices, and, discusses implications for the design of collaborative tools for writing. The analysis is grounded in user studies of four different groups of co-authors writing an academic report during two different collaborative situations. Two groups collaborate face-to-face using a word processor and the other two groups collaborate at a distance using a synchronous collaborative writing system. The study analyses differences between the activities of the groups and focuses on transformations that the CSCW system introduces into the organization of the co-authors' collaboration. The results show that the use of a CSCW system presents constraints in the collaborative activity; in particular we observed a cleavage that makes co-authors write different parts of a common document independently, i.e. without collaborating. This result opens up important issues related to the design of writing technologies for collaboration: how collaborative can collaborative writing be when it is supported by CSCW systems? How can the design of collaborative tools support organized and integrative collaborative activities such as writing? We discuss these issues and some of the alternatives that collaborative tools should offer for writing.

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Challenges Encountered During Synchronous Online Collaborative Writing via Google Docs
Mufeeda Irshad

International Journal of Web-Based Learning and Teaching Technologies, 2022

This study investigated (1) the challenges encountered by a heterogeneous group of first year undergraduates during a synchronous on-line collaborative writing activity conducted through Google Classroom using Google Docs and (2) their perceptions of the pedagogical approach. Five sub-groups of undergraduates participated in the study, and their written transcripts were analysed for patterns of interaction in terms of equality and mutuality based on the Taxonomy of Writing Change Functions and Scaffolding Strategies (Li and Zhu, 2017). Data on learner perceptions were analysed for underlying themes. The findings, which were interpreted from the perspective of the Complex Dynamic Systems Theory, revealed that synchronous on-line collaboration is complex and challenging due to the dynamic patterns of interaction. This study concludes that Google Docs is a useful pedagogical tool and could be used for second language writing development despite the challenges. However, in transferring ...

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Empirical study on collaborative writing: What do co-authors do, use, and like?
meysam dehgahi

Computer Supported Cooperative Work, 2004

How do people work when they are collaborating to write a document? What kind of tools do they use and, in particular, do they resort to groupware for this task? Forty-one people filled out a questionnaire placed on the World Wide Web. In spite of the existence of specialized collaborative writing tools, most respondents reported using individual word processors and email as their main tools for writing joint documents. Respondents noted the importance of functions such as change tracking, version control, and synchronous work for collaborative writing tools. This study also confirmed the great variability that exists between collaborative writing projects, whether it be group membership, management, writing strategy, or scheduling issues.

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    Gaurav Dass

    Proceedings of the 25th International Conference on Intelligent User Interfaces, 2020

    We explore trust in a relatively new area of data science: Automated Machine Learning (AutoML). In AutoML, AI methods are used to generate and optimize machine learning models by automatically engineering features, selecting models, and optimizing hyperparameters. In this paper, we seek to understand what kinds of information influence data scientists' trust in the models produced by AutoML? We operationalize trust as a willingness to deploy a model produced using automated methods. We report results from three studies-qualitative interviews, a controlled experiment, and a card-sorting task-to understand the information needs of data scientists for establishing trust in AutoML systems. We find that including transparency features in an AutoML tool increased user trust and understandability in the tool; and out of all proposed features, model performance metrics and visualizations are the most important information to data scientists when establishing their trust with an AutoML tool. CCS CONCEPTS • Human-centered computing → User studies; Empirical studies in HCI ; • Computing methodologies → Artificial intelligence.

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    Characterizing Stage-aware Writing Assistance for Collaborative Document Authoring
    Bahareh Sarrafzadeh

    Proceedings of the ACM on Human-Computer Interaction, 2020

    Writing is a complex non-linear process that begins with a mental model of intent, and progresses through an outline of ideas, to words on paper (and their subsequent refinement). Despite past research in understanding writing, Web-scale consumer and enterprise collaborative digital writing environments are yet to greatly benefit from intelligent systems that understand the stages of document evolution, providing opportune assistance based on authors&#39; situated actions and context. In this paper, we present three studies that explore temporal stages of document authoring. We first survey information workers at a large technology company about their writing habits and preferences, concluding that writers do in fact conceptually progress through several distinct phases while authoring documents. We also explore, qualitatively, how writing stages are linked to document lifespan. We supplement these qualitative findings with an analysis of the longitudinal user interaction logs of a ...

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    Thesis Writer: Digitale Anleitung zum wissenschaftlichen Arbeiten, Schreiben und Denken
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    Seamless Learning

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    Time-Position Characterization of Conflicts: A Case Study of Collaborative Editing
    Claudia-lavinia Ignat

    Collaboration Technologies and Social Computing, 2020

    Collaborative editing (CE) became increasingly common, often compulsory in academia and industry where people work in teams and are distributed across space and time. We aim to study collaborative editing behavior in terms of collaboration patterns users adopt and in terms of a characterisation of conflicts, i.e. edits from different users that occur close in time and position in the document. The process of a CE can be split into several editing 'sessions' which are performed by a single author ('single-authored session') or several authors ('co-authored session'). This fragmentation process requires a pre-defined 'maximum time gap' between sessions which is not yet well defined in previous studies. In this study, we analysed CE logs of 108 collaboratively edited documents. We show how to establish a suitable 'maximum time gap' to split CE activities into sessions by evaluating the distribution of the time distance between two adjacent sessions. We studied editing activities inside each 'co-author session' in order to define potential conflicts in terms of time and position dimensions before they occur in the document. We also analysed how many of these potential conflicts become real conflicts. Findings show that potential conflicting cases are few. However, they are more likely to become real conflicts.

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    Now that we can write simultaneously , how do we use that to our advantage?
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    Communications of the ACM, 2017

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