Utilizing artificial intelligence to assess academic exam anxiety, perceived stress, and achievement motivation among college students

Bibliographic Data

ID15528584
AuthorsZ Hamd (Princess Nourah bint Abdulrahman University, corresponding author), Zuhal Y Hamd (0000-0003-2895-2284, Princess Nourah bint Abdulrahman University), Zamzam A Mohmed (Princess Nourah bint Abdulrahman University), Nouf Alroqaiba (Princess Nourah bint Abdulrahman University), Sherine Mohamed Elzagawy (Princess Nourah bint Abdulrahman University), Hala Abd Ellatif Elsayed (Princess Nourah bint Abdulrahman University), Maha Mahmoud Lashin (Princess Nourah bint Abdulrahman University), Maha Aldera (0000-0002-5445-1240, Princess Nourah bint Abdulrahman University), Amal I Alorainy (0000-0002-9434-4335, Princess Nourah bint Abdulrahman University)
Year2026
Volume17
Pages1686106-1686106
Publication date2026-03-09
Open AccessYes
TypeARTICLE
VenueFrontiers in Psychiatry (JOURNAL)
Journal identifiersISSN: 1664-0640 • E-ISSN: 1664-0640
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2026.1686106
PMID41877887
OpenAlexW7134270872
LanguageEN
References cited32

Achievement motivation moderates the relationship between perceived stress and exam anxiety only in the pre-examination period, highlighting the temporal nature of this interaction. The alignment between SPSS and FLS outcomes suggests that artificial intelligence, particularly fuzzy logic systems, can efficiently evaluate students' academic exam anxiety. These findings support the potential use of AI-based tools for psychological state assessment in educational settings, especially for early identification of students at risk of heightened exam anxiety

Academic achievement · Anxiety · Association (psychology · Construct (python library · Need for achievement · Stress (linguistics · Test anxiety · Education, Achievement, and Giftedness · Emotional Intelligence and Performance · Psychometric Methodologies and Testing

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