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,…

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.,…

Learning experience designers consistently balance the trade-off between open and close-ended activities. The growth and scalability of Computer Based Learning Platforms (CBLPs) have only magnified the importance of these design trade-offs. CBLPs often utilize close-ended activities (i.e. Multiple-Choice Questions [MCQs]) due to feasibility…

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…

Automated essay scoring (AES), where natural language processing is applied to score written text, can underpin educational resources in blended and distance learning. AES performance has typically been reported in terms of correlation coefficients or agreement statistics calculated between a system and an expert human examiner. We describe the…

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.…

The "Standards for Educational and Psychological Testing" have served as a cornerstone for best practices in assessment. As the field evolves, so must these standards, with regular revisions ensuring they reflect current knowledge and practice. The National Council on Measurement in Education (NCME) conducted a survey to gather feedback…

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…

Sequencing items in adaptive learning systems typically relies on a large pool of interactive question items that are analyzed into a hierarchy of skills, also known as Knowledge Components (KCs). Educational data mining techniques can be used to analyze students response data in order to optimize the mapping of items to KCs, with similarity-based…

Sustainability of education has become of paramount importance during the COVID-19 pandemic at all educational levels worldwide. In this process, the assessment process, which is one of the most important steps of education and teaching activities, started to be applied as online exams. In addition to being compulsory during epidemic periods, the…

The use of technology for teaching and learning has created a paradigm shifting in learning environments and learning process, and also the paradigm shifting has also affected the assessment processes. In addition to these, online environments provide more opportunities to assess of the learners. In this study, the Adaptive Mastery Testing (AMT)…