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AI evidence extraction

ChatGPT y educación. Adopción y usos por parte de estudiantes en la Argentina

Mariano Zukerfeld · Argumentos. · 2025

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

7/10
Relevance
0/4
Quality (LMQS)
E
Evidence
0
Citations
0.00
FWCI

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.62174/arg.2025.10818

Methodology & findings

Study design

National survey of undergraduate and graduate students in Argentina examining perceptions and adoption patterns of ChatGPT for educational uses

Primary method

null (specific statistical methods not described in abstract)

Main result

The study found that "both general and educational uses of ChatGPT are widely perceived, particularly among individuals who work or study" and that "the most common educational uses include supplementing explanations received, completing writing assignments, and preparing for exams." Additionally, "students report significant gains in time efficiency when using the tool and express high levels of satisfaction with the outcomes, with satisfaction being greater in terms of usefulness and relevance than in terms of accuracy and truthfulness."

Reports effect sizes.

Research paradigm

Empirical-positivist with critical theory orientation (digital capitalism framework)

Author conclusions

The authors conclude that "students report significant gains in time efficiency when using the tool and express high levels of satisfaction with the outcomes," and that "a high percentage of respondents report verifying the information provided, especially among those who are less satisfied with the tool and report lower productivity gains." The framework situates these findings within "the platform phase of digital capitalism."

Risk of bias

Selection bias: Survey respondents likely represent ChatGPT users, potentially excluding non-users; Self-report bias: Participants self-reported usage patterns and satisfaction levels; Sampling frame unclear: No indication of how the national sample was constructed or response rates; Gender differences in overall use but minimal in educational use: potential confounding by other variables not controlled; Selection bias: Survey respondents may not be representative of all Argentine students; Self-report bias: Reliance on student perceptions and self-reported usage patterns; Potential non-response bias in survey administration; Self-reported data (survey-based, susceptible to social desirability bias); Potentially non-representative sample (may exclude students without access to technology or internet); Selection bias based on willingness to complete survey about AI tool use

Data: not_statedCode: not_statedExtracted from: pdfAgreement 75%

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