Cited by 51Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive LearningDiscourse Analysis in Language Studies

Learner experience in artificial intelligence-scaffolded argumentation

Kim, Min Kyu, Kim, Nam Ju, Heidari, Ali·2022·Assessment & Evaluation in Higher Education

Abstract

Writing academic arguments is a complex and demanding task, even for proficient tertiary students. At the same time, providing prompt support for individual students working on discipline-specific arguments is often challenging for instructors. Artificial Intelligence (AI) techniques enable automated and adaptive educational scaffolding. In this study, we leveraged Natural Language Processing (NLP) AI techniques in an AI-Supported Scaffolding (AISS) system to evaluate written arguments and present alternative writing examples that human experts might write. To evaluate a pilot version of AISS, we gathered mixed-method data from 14 students enrolled in two sections of the same graduate-level online course (6 students in Cohort 1 and 8 students in Cohort 2). We used the Tool for the Automatic Analysis of Cohesion (TAACO) to track revisions in written arguments. TAACO indices demonstrated that the students used AI-generated scaffolding to build stronger claims with more elaborate and cohesive ideas. In written reflections, students revealed the perceived value of AISS, and visual inspection of their writing indicates that students used AISS feedback to improve their arguments. The findings demonstrate the potential of AI to provide personalised scaffolding for academic argument composition.

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Crossref · 10.1080/02602938.2022.2042792

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This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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  • Kim et al. found that iterative feedback loops between AI and students helped build more complex storylines and sustained engagement throughout the writing process.

    “The study found that iterative feedback loops between AI and students helped build more complex storylines and sustained engagement throughout the writing process.”
  • AI suggestions acted as creative catalysts rather than directive templates, allowing students to maintain their creative agency and decision-making power during composition.

    “Importantly, AI suggestions acted as creative catalysts rather than directive templates, allowing students to maintain their creative agency and decision-making power during composition.”
  • Woo et al. [36] and Kim et al. [10] emphasize the importance of designing writing tasks that require students to engage critically with AI-generated suggestions rather than accepting them passively.

    “Woo et al. [36] and Kim et al. [10] emphasize the importance of designing writing tasks that require students to engage critically with AI-generated suggestions rather than accepting them passively.”

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References 40 · Cited by 51

Authors
Kim, M. K., Kim, N. J., & Heidari, A.
Affiliations
  • Georgia State University (US)
  • University of Miami (US)
Corresponding author
Kim, Min Kyu
Venue
Assessment & Evaluation in Higher Education
Published
2022-02-23
Volume
47
Issue
8
Pages
1301-1316
ISSN
  • 0260-2938 (ISSN-L)
  • 1469-297X
OpenAlex
W4213449894
Cited by
51
References
40
Citations by year
2026: 19 · 2025: 19 · 2024: 9 · 2023: 4
FWCI
7.92
Type
journal article
Language
en
Open access
closed
Locations
Assessment & Evaluation in Higher Education (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Arts and Humanities › Literature and Literary Theory › Discourse Analysis in Language Studies
Keywords
academic argumentation, argumentative writing, natural language processing, automated feedback, student experience, online learning, graduate students

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