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(Dis)placed Contributions: Uncovering Hidden Hurdles to Collaborative Writing Involving Non-Native Speakers, Native Speakers, and AI-Powered Editing Tools

Yimin Xiao, Yuewen Chen, Naomi Yamashita, Yuexi Chen, Zhicheng Liu, Ge Gao

TL;DR

Light is shed on the fair assessment and effective promotion of a co-writer's contributions in language diverse settings and the necessity of disentangling contributions made to the ideational, expressional, and lexical aspects of the joint writing is underscored.

Abstract

Content creation today often takes place via collaborative writing. A longstanding interest of CSCW research lies in understanding and promoting the coordination between co-writers. However, little attention has been paid to individuals who write in their non-native language and to co-writer groups involving them. We present a mixed-method study that fills the above gap. Our participants included 32 co-writer groups, each consisting of one native speaker (NS) of English and one non-native speaker (NNS) with limited proficiency. They performed collaborative writing adopting two different workflows: half of the groups began with NNSs taking the first editing turn and half had NNSs act after NSs. Our data revealed a "late-mover disadvantage" exclusively experienced by NNSs: an NNS's ideational contributions to the joint document were suppressed when their editing turn was placed after an NS's turn, as opposed to ahead of it. Surprisingly, editing help provided by AI-powered tools did not exempt NNSs from being disadvantaged. Instead, it triggered NSs' overestimation of NNSs' English proficiency and agency displayed in the writing, introducing unintended tensions into the collaboration. These findings shed light on the fair assessment and effective promotion of a co-writer's contributions in language diverse settings. In particular, they underscore the necessity of disentangling contributions made to the ideational, expressional, and lexical aspects of the joint writing.

(Dis)placed Contributions: Uncovering Hidden Hurdles to Collaborative Writing Involving Non-Native Speakers, Native Speakers, and AI-Powered Editing Tools

TL;DR

Light is shed on the fair assessment and effective promotion of a co-writer's contributions in language diverse settings and the necessity of disentangling contributions made to the ideational, expressional, and lexical aspects of the joint writing is underscored.

Abstract

Content creation today often takes place via collaborative writing. A longstanding interest of CSCW research lies in understanding and promoting the coordination between co-writers. However, little attention has been paid to individuals who write in their non-native language and to co-writer groups involving them. We present a mixed-method study that fills the above gap. Our participants included 32 co-writer groups, each consisting of one native speaker (NS) of English and one non-native speaker (NNS) with limited proficiency. They performed collaborative writing adopting two different workflows: half of the groups began with NNSs taking the first editing turn and half had NNSs act after NSs. Our data revealed a "late-mover disadvantage" exclusively experienced by NNSs: an NNS's ideational contributions to the joint document were suppressed when their editing turn was placed after an NS's turn, as opposed to ahead of it. Surprisingly, editing help provided by AI-powered tools did not exempt NNSs from being disadvantaged. Instead, it triggered NSs' overestimation of NNSs' English proficiency and agency displayed in the writing, introducing unintended tensions into the collaboration. These findings shed light on the fair assessment and effective promotion of a co-writer's contributions in language diverse settings. In particular, they underscore the necessity of disentangling contributions made to the ideational, expressional, and lexical aspects of the joint writing.
Paper Structure (51 sections, 4 figures, 5 tables)

This paper contains 51 sections, 4 figures, 5 tables.

Table of Contents

  1. INTRODUCTION
  2. RELATED WORK
  3. Native vs. Non-Native Speakers in the Production of Lexical Content
  4. Non-Native Speaker’s Potential from the Lens of Footing
  5. Expressional Edits, Ideational Edits, and the Workflow Connecting Co-Writers
  6. Expression and the Use of AI-Powered Editing Tools
  7. METHOD
  8. Participants
  9. Task Procedure
  10. Task context and writing prompts.
  11. Task procedure and the arrangement of editing turns.
  12. Measurements
  13. Changes in the document’s lexical content between every two adjacent turns.
  14. Edits to the expressional and/or ideational aspects of the written content.
  15. Perceived quality of task coordination.
  16. ...and 36 more sections

Figures (4)

  • Figure 1: Order of Turn-Taking with NNSs or NSs at Turn1
  • Figure 2: Time Curves [2] that indicate changes in the document’s lexical content across turns. On each curve, the spatial proximity between two dots represents the lexical distance between two corresponding document versions. All versions of the same group’s document are connected by one curve, ordered by the sequence of turn-taking. Each solid dot represents one document version by the end of a given co-writer’s editing turn. Each hollow dot with an empty interior represents an intermediate document version generated during the editing turn. The spatial distribution of dots appears highly similar among groups following the same order of turn-taking. Thus, we present the curves for one randomly selected group whose turn-taking began with an NNS at turn1 and another whose turn-taking began with an NS at turn1.
  • Figure 3: Co-writers’ ratings of the perceived task coordination quality by their individual language background and the order of turn-taking followed by their group.
  • Figure 4: Co-writers’ ratings of the perceived value of English (left) or Japanese (right) ability by their individual language background and the order of turn-taking followed by their group.