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arxiv: 2503.02885 · v3 · pith:EBOQIUDUnew · submitted 2025-02-02 · 💻 cs.CY · cs.CL· cs.HC

"Would You Want an AI Tutor?" Understanding Stakeholder Perceptions of LLM-based Systems in the Classroom

Caterina Fuligni , Daniel Dominguez Figaredo , Armanda Lewis , Julia Stoyanovich This is my paper

Pith reviewed 2026-05-23 04:22 UTC · model grok-4.3

classification 💻 cs.CY cs.CLcs.HC
keywords LLM in educationstakeholder perceptionsAI tutorsresponsible AIframework developmentfocus groupseducational technologygovernance
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The pith

Perceptions of LLM tutors in class depend on surfacing specific stakeholder concerns in context rather than measuring broad approval.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces Co-PALE, a framework that ties educational settings, responsible AI principles, and distinct perception categories to guide decisions on LLM tools. It shows that prior studies often overlook how the same technology creates different worries for faculty versus parents in different scenarios. Focus groups with these groups reveal tensions that approval surveys miss, supporting more deliberate choices about where and for whom such tools should be used. This matters because deployment without this approach risks ignoring key voices and leading to mismatched governance.

Core claim

The central claim is that understanding stakeholder perceptions of LLM-based systems in the classroom requires identifying whose concerns are surfaced, in which contexts, and with what implications for responsible design and governance, rather than measuring approval or acceptance. Co-PALE connects educational context, responsible AI principles, and categories of perception to support more systematic reasoning about adoption. It is grounded through analysis of prior work that reveals recurring gaps, contextually distinct scenarios that illustrate differing concerns, and focus groups with university faculty and K-12 parents that surface tensions and uncertainties.

What carries the argument

Co-PALE (Contextualized Perceptions for the Adoption of LLMs in Education), a stakeholder-first framework linking educational contexts, responsible AI principles, and perception categories to enable deliberate deployment decisions.

If this is right

  • Deployment decisions must account for distinct concerns raised by different stakeholders in specific educational settings.
  • The framework enables identification of recurring gaps in how perceptions have been studied previously.
  • Focus-group reflections demonstrate uncertainties that arise when applying the framework to real groups.
  • Context-specific scenarios illustrate that identical LLM tools produce varying implications for different stakeholders.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The approach could be extended to other emerging classroom technologies to check for similar context-dependent concerns.
  • It implies that governance policies should require explicit mapping of stakeholder groups before any LLM rollout.
  • Schools might test the framework by running parallel decision processes with and without it to compare outcomes.
  • This could connect to broader responsible-AI practices by treating perception categories as inputs to risk assessment.

Load-bearing premise

That grounding the framework in prior-work analysis and focus groups with faculty and parents will surface enough tensions and uncertainties to support better reasoning about deployment.

What would settle it

A comparison showing that simple approval surveys produce the same deployment recommendations as Co-PALE across multiple school contexts.

Figures

Figures reproduced from arXiv: 2503.02885 by Armanda Lewis, Caterina Fuligni, Daniel Dominguez Figaredo, Julia Stoyanovich.

Figure 1
Figure 1. Figure 1: Contextualized Perceptions for the Adoption of LLMs in Education (Co-PALE) framework for assessing stakeholder perceptions of LLM-based systems. Co-PALE comprises four components: Stakeholders, Context, Goals, and Perceptions. Starting at the top, one should consider components at each layer before moving to the next layer. The Perceptions component can be used as a checklist to assess the presence of spec… view at source ↗
Figure 2
Figure 2. Figure 2: Breakdown of statistics of the analyzed articles ( [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: [Summary of perceptions of two major stakeholders, students (3a) and teachers (3b), reported in the articles in our [PITH_FULL_IMAGE:figures/full_fig_p015_3.png] view at source ↗
read the original abstract

Large Language Models (LLMs) have gained traction in educational settings, often framed as virtual tutors or teaching assistants. Following early skepticism and bans, many schools and universities have begun integrating these systems into curricula. Yet decisions about whether and how to deploy LLM-based tools are frequently made without systematic engagement with the full range of stakeholders they affect. In this paper, we argue that understanding stakeholder perceptions of LLM-based systems in the classroom is not a matter of measuring approval or acceptance, but of identifying whose concerns are surfaced, in which contexts, and with what implications for responsible design and governance. We introduce Contextualized Perceptions for the Adoption of LLMs in Education (Co-PALE), a stakeholder-first framework that connects educational context, responsible AI principles, and categories of perception to support more deliberate decision-making about the adoption of LLM-based tools. We ground Co-PALE through a targeted analysis of prior work to diagnose recurring gaps in how stakeholder perceptions are studied, and through contextually distinct educational scenarios that illustrate how the same technology raises different concerns for different stakeholders. We further examine how university faculty and K--12 parents make sense of the framework through focus groups, using their reflections to surface tensions and uncertainties. Co-PALE supports more systematic reasoning about whether, where, and for whom LLM-based tools should be deployed in education.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The manuscript claims that understanding stakeholder perceptions of LLM-based systems in education is not primarily about measuring approval or acceptance, but about identifying whose concerns are surfaced, in which contexts, and with what implications for responsible design and governance. It introduces the Co-PALE framework (Contextualized Perceptions for the Adoption of LLMs in Education), which connects educational contexts, responsible AI principles, and perception categories to support more deliberate deployment decisions. The framework is grounded via analysis of prior literature to identify gaps, contextually distinct illustrative scenarios, and focus groups with university faculty and K-12 parents whose reflections surface tensions and uncertainties.

Significance. If the framework holds, it could advance stakeholder-centered approaches to LLM adoption in education by providing a structured way to diagnose gaps in perception research and map context-specific concerns to responsible AI principles, potentially improving governance and reducing risks of unexamined deployment.

major comments (1)
  1. [Abstract] Abstract: The central claim that Co-PALE enables 'more systematic reasoning about whether, where, and for whom LLM-based tools should be deployed' across the full range of stakeholders is load-bearing but under-supported. The empirical grounding uses only focus groups with university faculty and K-12 parents (plus prior-work analysis and scenarios); the absence of students, administrators, and policymakers means distinct tensions from these groups that could alter the context-perception-responsible-AI mappings are not yet incorporated.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive feedback, which highlights an important scope consideration for the Co-PALE framework. We address the comment below and outline targeted revisions.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The central claim that Co-PALE enables 'more systematic reasoning about whether, where, and for whom LLM-based tools should be deployed' across the full range of stakeholders is load-bearing but under-supported. The empirical grounding uses only focus groups with university faculty and K-12 parents (plus prior-work analysis and scenarios); the absence of students, administrators, and policymakers means distinct tensions from these groups that could alter the context-perception-responsible-AI mappings are not yet incorporated.

    Authors: We agree that the empirical component is limited to university faculty and K-12 parents (chosen as accessible, high-influence groups whose perspectives are underrepresented in existing LLM-education literature). The prior-work analysis and scenarios draw from a broader set of sources that reference additional stakeholders, but they do not constitute primary data from students, administrators, or policymakers. The framework itself is presented as a conceptual structure intended to be extensible rather than a fully validated mapping for every stakeholder. To address the concern directly, we will revise the abstract and introduction to (a) explicitly state the current empirical scope, (b) qualify the claim as providing a structured approach that can support reasoning across stakeholders once additional groups are incorporated, and (c) add a dedicated limitations paragraph outlining the need for future focus groups or surveys with students, administrators, and policymakers. This is a partial revision because new primary data collection is outside the scope of the current revision cycle. revision: partial

Circularity Check

0 steps flagged

No circularity: framework constructed from independent analysis and new data

full rationale

The paper derives Co-PALE by analyzing gaps in prior work, presenting contextually distinct scenarios, and incorporating reflections from new focus groups with university faculty and K-12 parents. No equations, fitted parameters, self-definitional loops, or load-bearing self-citations appear in the derivation chain. The central claim—that stakeholder perceptions should be understood via context, responsible AI principles, and perception categories—does not reduce to its inputs by construction; the grounding steps remain external to the framework itself and are not justified solely through overlapping-author citations or renamed empirical patterns.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 1 invented entities

The paper introduces a conceptual framework without quantitative fitting or new physical entities; it relies on standard responsible AI principles as background.

axioms (1)
  • domain assumption Responsible AI principles provide a valid lens for categorizing stakeholder perceptions in education
    Invoked in the abstract when connecting the framework components to support deliberate decision-making.
invented entities (1)
  • Co-PALE framework no independent evidence
    purpose: To connect educational context, responsible AI principles, and perception categories for LLM adoption decisions
    Newly introduced construct; no independent falsifiable evidence provided beyond the paper's own focus groups.

pith-pipeline@v0.9.0 · 5783 in / 1205 out tokens · 23455 ms · 2026-05-23T04:22:37.150704+00:00 · methodology

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Reference graph

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