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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
Francisco Ortin; Alonso Gago; Jose Quiroga; Miguel Garcia – International Educational Data Mining Society, 2025
Online learning has enhanced accessibility in education, but also poses significant challenges in maintaining academic integrity during online exams, particularly when students are prohibited from accessing unauthorized resources through the Internet. Nonetheless, students must remain connected to the Internet in order to take the online exam.…
Descriptors: Electronic Learning, Computer Assisted Testing, Access to Internet, Synchronous Communication
Jeffrey Matayoshi; Eric Cosyn; Christopher Lechuga; Hasan Uzun – International Educational Data Mining Society, 2024
ALEKS is an adaptive learning and assessment system, with courses covering subjects such as math, chemistry, and statistics. In this work, we focus on the ALEKS math courses, which cover a wide range of content starting at second grade math and continuing through college-level precalculus. To help instructors and students navigate this content,…
Descriptors: Student Placement, Evaluation Methods, Elementary Secondary Education, Accuracy
Doewes, Afrizal; Kurdhi, Nughthoh Arfawi; Saxena, Akrati – International Educational Data Mining Society, 2023
Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…
Descriptors: Essays, Writing Evaluation, Evaluators, Accuracy
Langerbein, Janine; Massing, Till; Klenke, Jens; Striewe, Michael; Goedicke, Michael; Hanck, Christoph – International Educational Data Mining Society, 2023
Due to the precautionary measures during the COVID-19 pandemic many universities offered unproctored take-home exams. We propose methods to detect potential collusion between students and apply our approach on event log data from take-home exams during the pandemic. We find groups of students with suspiciously similar exams. In addition, we…
Descriptors: Information Retrieval, Pattern Recognition, Data Analysis, Information Technology
Zur, Amir; Applebaum, Isaac; Nardo, Jocelyn Elizabeth; DeWeese, Dory; Sundrani, Sameer; Salehi, Shima – International Educational Data Mining Society, 2023
Detailed learning objectives foster an effective and equitable learning environment by clarifying what instructors expect students to learn, rather than requiring students to use prior knowledge to infer these expectations. When questions are labeled with relevant learning goals, students understand which skills are tested by those questions.…
Descriptors: Equal Education, Prior Learning, Educational Objectives, Chemistry
Zhang, Mengxue; Heffernan, Neil; Lan, Andrew – International Educational Data Mining Society, 2023
Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…
Descriptors: Scoring, Computer Assisted Testing, Mathematics Instruction, Mathematics Tests
Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2023
In MOOCs for programming, Automated Testing and Feedback (ATF) systems are frequently integrated, providing learners with immediate feedback on code assignments. The analysis of the large amounts of trace data collected by these systems may provide insights into learners' patterns of utilizing the automated feedback, which is crucial for the…
Descriptors: MOOCs, Feedback (Response), Teaching Methods, Learning Strategies
Baral, Sami; Botelho, Anthony; Santhanam, Abhishek; Gurung, Ashish; Cheng, Li; Heffernan, Neil – International Educational Data Mining Society, 2023
Teachers often rely on the use of a range of open-ended problems to assess students' understanding of mathematical concepts. Beyond traditional conceptions of student open-ended work, commonly in the form of textual short-answer or essay responses, the use of figures, tables, number lines, graphs, and pictographs are other examples of open-ended…
Descriptors: Mathematics Instruction, Mathematical Concepts, Problem Solving, Test Format
Doewes, Afrizal; Saxena, Akrati; Pei, Yulong; Pechenizkiy, Mykola – International Educational Data Mining Society, 2022
In Automated Essay Scoring (AES) systems, many previous works have studied group fairness using the demographic features of essay writers. However, individual fairness also plays an important role in fair evaluation and has not been yet explored. Initialized by Dwork et al., the fundamental concept of individual fairness is "similar people…
Descriptors: Scoring, Essays, Writing Evaluation, Comparative Analysis
Matayoshi, Jeffrey; Uzun, Hasan; Cosyn, Eric – International Educational Data Mining Society, 2022
Knowledge space theory (KST) is a mathematical framework for modeling and assessing student knowledge. While KST has successfully served as the foundation of several learning systems, recent advancements in machine learning provide an opportunity to improve on purely KST-based approaches to assessing student knowledge. As such, in this work we…
Descriptors: Knowledge Level, Mathematical Models, Learning Experience, Comparative Analysis
Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating

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