Assessing students' answers and in particular natural language answers is a crucial challenge in the field of education. Advances in transformer-based models such as Large Language Models (LLMs), have led to significant progress in various natural language tasks. Nevertheless, amidst the growing trend of evaluating LLMs across diverse tasks,…

Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This…

Automated multiple-choice question (MCQ) generation is valuable for scalable assessment and enhanced learning experiences. How-ever, existing MCQ generation methods face challenges in ensuring plausible distractors and maintaining answer consistency. This paper intro-duces a method for MCQ generation that integrates reasoning-based explanations…

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…

We conducted a collective case study investigating two college algebra students' graph reasoning and selection on an online assessment. Students completed the assessment during individual, semi-structured interviews, as part of a broader validation study. The assessment contained six items; students selected Cartesian graphs to represent…

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.…

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,…

The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…

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…

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…

In this article, the beta-binomial model for count data is proposed and demonstrated in terms of its application in the context of oral reading fluency (ORF) assessment, where the number of words read correctly (WRC) is of interest. Existing studies adopted the binomial model for count data in similar assessment scenarios. The beta-binomial model,…

For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…

The COVID-19 pandemic situation spreading around the world had brought dynamic changes in every field of life since 2019, especially in the learning processes. The processes of learning were done by using online platform. In a sudden shift in the learning processes, students were forced to adapt. Consequently, the processes of online learning…

Prior to the COVID-19 pandemic, digital or virtual learning was gaining traction and popularity, but relatively small percentages of K-12 and post-secondary students engaged in virtual learning environments. The pandemic forced emergency remote learning, altering the landscape of education. While the long-term plans of K-12 school districts and…

This research aims to determine the strengths and weaknesses of the online exams, as well as the aspects that can be evaluated as opportunities and threats, by making a SWOT analysis of the online exams that are frequently used in the distance education process. For this purpose, the study was designed with the case study technique, one of the…