Oct 2026· Educational Journal of Learning Technology
Artificial Intelligence in Education
Abstract
This study examines how Artificial Intelligence (AI) use affects students' critical thinking skills in learning. The study uses a quantitative, explanatory research design. The study population consisted of students in the Economics Education Study Program who used AI-based applications for learning. The study collected data through a five-point Likert-scale questionnaire from 64 respondents who met the research criteria. The researchers analyzed the data using validity and reliability tests, assumption tests, and simple linear regression in SPSS. The results show that using AI has a positive and significant effect on students' critical thinking skills. The t-test yielded t = 4.670 (p = 0.000), and the regression coefficient was 0.431. The R-square value of 0.260 indicates that AI use explains 26% of the variation in students' critical thinking skills, while other factors account for the remaining 74%. These findings suggest that appropriate AI use can support students' ability to analyze, evaluate, and solve problems.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
An algorithm is proposed which leverages disentangled semantic factors to generate adversarial perturbation by altering controlled semantic attributes to fool the learner towards various "adversarial" targets.
Haonan Qiu, Chaowei Xiao, Lei Yang et al.· arXiv.org· 208 citations· ⚡17
This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
