MDOI Convergence Chronicles 110.1127/CON.2026.01098
110.1127/CON.2026.01098
Article

Understanding self-directed learning in AI-Assisted writing: A mixed methods study of postsecondary learners

Chaoran Wang, Zixi Li, Curtis Bonk 2024 Convergence Chronicles

Abstract

This study investigates how postsecondary learners employ generative AI, specifically ChatGPT, to support their self-directed learning (SDL) for writing purposes. Following a sequential mixed methods design, we analyzed 384 survey responses and 10 semi-structured interviews with postsecondary writers. Findings suggest that the major learning task that the learners used ChatGPT for writing is brainstorming and seeking inspiration for ideas. While the entering motivation for using ChatGPT varies from curiosity about innovative technologies to fulfilling academic requirements, such entering motivation transformed into task motivation when the learners perceived the potential benefits of ChatGPT for assisting their writing. In terms of self-management, participants mostly demonstrated a high responsibility towards their own learning with ChatGPT and employed various strategies for SDL. Although survey respondents demonstrated a comparatively low level of self-monitoring, most interviewees claimed that they critically reflected on their learning process and validated information provided by ChatGPT. There are mixed opinions regarding whether the writing skills have improved as a result of using ChatGPT. Some participants suggested that the benefits brought by ChatGPT, such as alleviating social pressure and receiving instant feedback at any time, encouraged them to spend more time practicing writing and making revisions. However, some argue that assessing their AI-assisted SDL learning progress in the short term is challenging. This study addresses gaps in the existing literature where there is scarce, large-scale empirical research on self-directed AI usage in writing, shedding light on the emerging phenomenon of utilizing generative AI as a means of SDL in writing.

Identifier Metadata

Identifier 110.1127/CON.2026.01098
Canonical mdoi:110.1127/CON.2026.01098
Resolver URL https://mdoi.org/110.1127/CON.2026.01098
Resource URL Open resource
Document URL Open document
Content Type Article
Authors Chaoran Wang, Zixi Li, Curtis Bonk
Year 2024
Depositor Convergence Chronicles Organisation
Prefix 110.1127
Registered Aug. 17, 2026
Updated Aug. 17, 2026
Status Active
Visibility Public

Cite This Identifier

APA 7th Edition

Click to copy

MLA 9th Edition

Click to copy

Chicago 17th Edition

Click to copy

BibTeX

Click to copy

Persistent Identifier

mdoi:110.1127/CON.2026.01098

Click to copy

About MDOI

MDOI identifiers are permanent and unique identifiers assigned to digital objects to ensure long-term access, tracking, and referencing.

  • MDOI provides a permanent identity for digital objects.
  • Each MDOI is unique and points to one specific resource.
  • The prefix, such as 110.XXXX, identifies the registrant.
  • The suffix identifies the exact digital object.
  • MDOI remains stable even when a website URL changes.
  • It helps prevent broken links in digital publishing.
  • It makes academic and digital resources easier to find and cite.
  • MDOI supports proper tracking and management of digital content.
  • It improves the credibility and visibility of published resources.
  • MDOI ensures digital objects remain accessible, traceable, and reliable over time.
CO
Registered by Convergence Chronicles