Authentic Assessment and Critical Thinking in University Students in the Age of Generative Artificial Intelligence: an Explanatory Model
Year: 2026
Type: article
Abstract: The advent of Generative Artificial Intelligence (GenAI) is disrupting traditional thinking about assessment in universities, as it is possible that final written products will not be the only indicator of students' independent thinking. This study investigated the relationship between participation in an authentic assessment process and the use of information problem solving with a critical thinking approach in a task carried out in the university by using the GenAI. The publicly available GenAI-Assisted Information Problem Solving dataset was used to extract secondary data for analysis, which included GenAI dialogue, writing-process activity, annotations, student background characteristics and tutor-assigned proposal scores [6]. There were 230 complete cases used in the multivariable regression and moderation analysis. The relationship between authentic-assessment engagement and critical-thinking-oriented GenAI dialogue was positive (β = 0.174, p = 0.004), and the relationship between evaluative GenAI engagement and authentic-assessment engagement was positive, but stronger (β = 0.379, p < 0.001). Authentic-assessment engagement and evaluative GenAI engagement, however, did not have a statistically significant interaction (β = −0.102, p = 0.110). Process indicators also failed to significantly predict final proposal scores, with 3.8% of the variance in the model of proposal performance explained by the process indicators. The results indicate that authentic assessment can help to set the stage for more evaluative and revision-driven interactions with GenAI, and more process-level critical thinking does not necessarily lead to higher assessment scores. The study underscores the need to separate out the amount of AI use from the quality of the AI use and to include process evidence in the design of assessments in the GenAI era.
Source: Acta Innovations
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7223399779