Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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(1) Background: In the era of generative AI (GenAI), assessing AI literacy is essential for understanding how effectively non-expert users can interact with AI. However, existing assessment tools primarily focus on users' understanding of AI principles or rely on self-reported scales, neglecting critical thinking and actual interaction capabilities. To address this gap, this study aims to design and validate evaluation indicators targeting the behavioral process of human-GenAI interactions and analyze the impact of critical thinking. (2) Methods: Grounded in information literacy and critical thinking frameworks, this study operationalized human-AI interaction capabilities into behavioral indicators and rubrics through observation, surveys, and pilot studies. Data were collected from 121 undergraduates completing two real-world tasks with GenAI, and their interaction processes were documented and evaluated. (3) Results: The indicators showed acceptable inter-rater and internal consistency reliability. Exploratory and Confirmatory Factor Analysis confirmed a three-dimensional structure. Further analysis showed that interaction capabilities varied across gender, academic background, AIGC use frequency, critical thinking disposition levels, and question chain logic. (4) Conclusions: The developed evaluation indicators are reliable and valid. Further analysis reveals that a high critical thinking disposition can offset the disadvantage of lower usage frequency. This highlights the significance of critical thinking in enhancing human-GenAI interaction capabilities.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12194078 | PMC |
http://dx.doi.org/10.3390/jintelligence13060062 | DOI Listing |