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Tal Waltzer; Celeste Pilegard; Gail D. Heyman – International Journal for Educational Integrity, 2024
The release of ChatGPT in 2022 has generated extensive speculation about how Artificial Intelligence (AI) will impact the capacity of institutions for higher learning to achieve their central missions of promoting learning and certifying knowledge. Our main questions were whether people could identify AI-generated text and whether factors such as…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, College Students
Rakovic, Mladen; Iqbal, Sehrish; Li, Tongguang; Fan, Yizhou; Singh, Shaveen; Surendrannair, Surya; Kilgour, Jonathan; Graaf, Joep; Lim, Lyn; Molenaar, Inge; Bannert, Maria; Moore, Johanna; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: Assignments that involve writing based on several texts are challenging to many learners. Formative feedback supporting learners in these tasks should be informed by the characteristics of evolving written product and by the characteristics of learning processes learners enacted while developing the product. However, formative feedback…
Descriptors: Artificial Intelligence, Essays, High Achievement, Writing Achievement
Wan, Qian; Crossley, Scott; Banawan, Michelle; Balyan, Renu; Tian, Yu; McNamara, Danielle; Allen, Laura – International Educational Data Mining Society, 2021
The current study explores the ability to predict argumentative claims in structurally-annotated student essays to gain insights into the role of argumentation structure in the quality of persuasive writing. Our annotation scheme specified six types of argumentative components based on the well-established Toulmin's model of argumentation. We…
Descriptors: Essays, Persuasive Discourse, Automation, Identification