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Lief Esbenshade; Jonathan Vitale; Ryan S. Baker – International Educational Data Mining Society, 2024
In a number of settings risk prediction models are being used to predict distal future outcomes for individuals, including high school risk prediction. We propose a new method, non-overlapping-leave-future-out (NOLFO) validation, to be used in settings with long delays between feature and outcome observation and where there are overlapping…
Descriptors: Risk, Prediction, Models, High School Students
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Scott Crossley; Yu Tian; Joon Suh Choi; Langdon Holmes; Wesley Morris – International Educational Data Mining Society, 2024
This study examines the potential to use keystroke logs to examine differences between authentic writing and transcribed essay writing. Transcribed writing produced within writing platforms where copy and paste functions are disabled indicates that students are likely copying texts from the internet or from generative artificial intelligence (AI)…
Descriptors: Plagiarism, Writing (Composition), Essays, Artificial Intelligence
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Gyuhun Jung; Markel Sanz Ausin; Tiffany Barnes; Min Chi – International Educational Data Mining Society, 2024
We presented two empirical studies to assess the efficacy of two Deep Reinforcement Learning (DRL) frameworks on two distinct Intelligent Tutoring Systems (ITSs) to exploring the impact of Worked Example (WE) and Problem Solving (PS) on student learning. The first study was conducted on a probability tutor where we applied a classic DRL to induce…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Artificial Intelligence, Teaching Methods
Reima Al-Jarf – Online Submission, 2024
This study explores Arab university faculty's views on fully AI-generated assignments and research papers submitted by students, what reasons they give for their stance and how they react in this case. Surveys with a sample of 45 Arab instructors revealed that 98% do not accept AI-generated assignments and research papers from students at all.…
Descriptors: Assignments, Research Papers (Students), Foreign Countries, College Faculty
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David A. Joyner; Zoey Anne Beda; Michael Cohen; Melanie Duffin; Amy Garcia Fernandez; Liz Hayes-Golding; Jonathan Hildreth; Alex Houk; Rebecca Johnson; Kayla Matcheck; Ana Santos – International Educational Data Mining Society, 2024
This study examines log data from proctored examinations from two classes offered as part of a large online graduate program in computer science. In these two classes, students are permitted to access any internet content during their exams, which themselves have remained largely unchanged over the last several semesters. As a result, when ChatGPT…
Descriptors: Computer Assisted Testing, Tests, Internet, Graduate Students
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Nhat Tran; Benjamin Pierce; Diane Litman; Richard Correnti; Lindsay Clare Matsumura – International Educational Data Mining Society, 2024
Automatically assessing classroom discussion quality is becoming increasingly feasible with the help of new NLP advancements such as large language models (LLMs). In this work, we examine how the assessment performance of 2 LLMs interacts with 3 factors that may affect performance: task formulation, context length, and few-shot examples. We also…
Descriptors: Artificial Intelligence, Technology Uses in Education, Discussion (Teaching Technique), Language Arts
Chad P. Salyer – Online Submission, 2024
Artificial intelligence was an emergent and powerful new force in education. The public release of ChatGPT 3.0 in 2022 transformed learning for many students. This phenomenological qualitative study sought to record and analyze student's perspectives on the influence of artificial intelligence on their learning routines. This study collected data…
Descriptors: Artificial Intelligence, Student Attitudes, Technology Uses in Education, Undergraduate Students
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Nasri, Nurfaradilla Mohamad; Nasri, Nurfarahin; Nasri, Nur Faraliyana; Talib, Mohamad Asyraf Abd – IEEE Transactions on Learning Technologies, 2023
Intelligent personal assistants (IPAs) carry massive potential in enhancing students' performance through individualized dynamic scaffolding strategy. Despite IPAs being increasingly recognized among educationists, little is known about their application in the development of students' scientific inquiry skills, particularly in physics. This study…
Descriptors: Academic Achievement, Artificial Intelligence, Handheld Devices, Inquiry
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Putnikovic, Marko; Jovanovic, Jelena – IEEE Transactions on Learning Technologies, 2023
Automatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no…
Descriptors: Automation, Computer Assisted Testing, Grading, Natural Language Processing
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Crompton, Helen; Burke, Diane – International Journal of Educational Technology in Higher Education, 2023
This systematic review provides unique findings with an up-to-date examination of artificial intelligence (AI) in higher education (HE) from 2016 to 2022. Using PRISMA principles and protocol, 138 articles were identified for a full examination. Using a priori, and grounded coding, the data from the 138 articles were extracted, analyzed, and…
Descriptors: Artificial Intelligence, Higher Education, Publications, Educational Trends
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Özbey, Muhammed; Kayri, Murat – Education and Information Technologies, 2023
In this study, the factors affecting the transactional distance levels of university students who continue their courses with distance education in the 2020-2021 academic years due to the COVID pandemic process were examined. Factors that affect transactional distance are modeled with Artificial Neural Networks, one of the data mining methods.…
Descriptors: College Students, Distance Education, Electronic Learning, Anxiety
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Jiang, Shiyan; Qian, Yingxiao; Tang, Hengtao; Yalcinkaya, Rabia; Rosé, Carolyn P.; Chao, Jie; Finzer, William – Education and Information Technologies, 2023
As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…
Descriptors: Computation, Thinking Skills, Cognitive Processes, Artificial Intelligence
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Lu, Yu; Wang, Deliang; Chen, Penghe; Meng, Qinggang; Yu, Shengquan – International Journal of Artificial Intelligence in Education, 2023
As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…
Descriptors: Learning Processes, Artificial Intelligence, Intelligent Tutoring Systems, Data Analysis
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Tan, Hongye; Wang, Chong; Duan, Qinglong; Lu, Yu; Zhang, Hu; Li, Ru – Interactive Learning Environments, 2023
Automatic short answer grading (ASAG) is a challenging task that aims to predict a score for a given student response. Previous works on ASAG mainly use nonneural or neural methods. However, the former depends on handcrafted features and is limited by its inflexibility and high cost, and the latter ignores global word cooccurrence in a corpus and…
Descriptors: Automation, Grading, Computer Assisted Testing, Graphs
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Sun, Fuhai; Ye, Ruixing – Science & Education, 2023
One of the ultimate problems of moral philosophy is to determine who or what is worth moral consideration or not. "Morality" is a relative concept, which changes significantly with the environment and time. This means that morality is incredibly inclusive. The emergence of AI technology has a significant impact on the understanding and…
Descriptors: Moral Issues, Ethics, Artificial Intelligence, Definitions
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