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Andersen, Øistein E.; Yuan, Zheng; Watson, Rebecca; Cheung, Kevin Yet Fong – International Educational Data Mining Society, 2021
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…
Descriptors: Evaluation Methods, Scoring, Essays, Computer Assisted Testing
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Pearson, Christopher; Penna, Nigel – Assessment & Evaluation in Higher Education, 2023
E-assessments are becoming increasingly common and progressively more complex. Consequently, how these longer, more complex questions are designed and marked is imperative. This article uses the NUMBAS e-assessment tool to investigate the best practice for creating longer questions and their mark schemes on surveying modules taken by engineering…
Descriptors: Automation, Scoring, Engineering Education, Foreign Countries
Das, Bidyut; Majumder, Mukta; Phadikar, Santanu; Sekh, Arif Ahmed – Research and Practice in Technology Enhanced Learning, 2021
Learning through the internet becomes popular that facilitates learners to learn anything, anytime, anywhere from the web resources. Assessment is most important in any learning system. An assessment system can find the self-learning gaps of learners and improve the progress of learning. The manual question generation takes much time and labor.…
Descriptors: Automation, Test Items, Test Construction, Computer Assisted Testing
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Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
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…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
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Rafner, Janet; Biskjaer, Michael Mose; Zana, Blanka; Langsford, Steven; Bergenholtz, Carsten; Rahimi, Seyedahmad; Carugati, Andrea; Noy, Lior; Sherson, Jacob – Creativity Research Journal, 2022
Creativity assessments should be valid, reliable, and scalable to support various stakeholders (e.g., policy-makers, educators, corporations, and the general public) in their decision-making processes. Established initiatives toward scalable creativity assessments have relied on well-studied standardized tests. Although robust in many ways, most…
Descriptors: Creativity, Evaluation Methods, Video Games, Computer Assisted Testing
Bradley J. Ungurait – ProQuest LLC, 2021
Advancements in technology and computer-based testing has allowed for greater flexibility in assessing examinee knowledge on large-scale, high-stakes assessments. Through computer-based delivery, cognitive ability and skills can be effectively assessed cost-efficiently and measure domains that are difficult or even impossible to measure with…
Descriptors: Computer Assisted Testing, Evaluation Methods, Scoring, Student Evaluation
Binglin Chen – ProQuest LLC, 2022
Assessment is a key component of education. Routine grading of students' work, however, is time consuming. Automating the grading process allows instructors to spend more of their time helping their students learn and engaging their students with more open-ended, creative activities. One way to automate grading is through computer-based…
Descriptors: College Students, STEM Education, Student Evaluation, Grading
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Brandon J. Yik; David G. Schreurs; Jeffrey R. Raker – Journal of Chemical Education, 2023
Acid-base chemistry, and in particular the Lewis acid-base model, is foundational to understanding mechanistic ideas. This is due to the similarity in language chemists use to describe Lewis acid-base reactions and nucleophile-electrophile interactions. The development of artificial intelligence and machine learning technologies has led to the…
Descriptors: Educational Technology, Formative Evaluation, Molecular Structure, Models
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Zhai, Xiaoming; Yin, Yue; Pellegrino, James W.; Haudek, Kevin C.; Shi, Lehong – Studies in Science Education, 2020
Machine learning (ML) is an emergent computerised technology that relies on algorithms built by 'learning' from training data rather than 'instruction', which holds great potential to revolutionise science assessment. This study systematically reviewed 49 articles regarding ML-based science assessment through a triangle framework with technical,…
Descriptors: Science Education, Computer Assisted Testing, Science Tests, Scoring
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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
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Lu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
Wood, Scott; Yao, Erin; Haisfield, Lisa; Lottridge, Susan – ACT, Inc., 2021
For assessment professionals who are also automated scoring (AS) professionals, there is no single set of standards of best practice. This paper reviews the assessment and AS literature to identify key standards of best practice and ethical behavior for AS professionals and codifies those standards in a single resource. Having a unified set of AS…
Descriptors: Standards, Best Practices, Computer Assisted Testing, Scoring
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Yerushalmy, Michal; Olsher, Shai – ZDM: The International Journal on Mathematics Education, 2020
We argue that examples can do more than serve the purpose of illustrating the truth of an existential statement or disconfirming the truth of a universal statement. Our argument is relevant to the use of technology in classroom assessment. A central challenge of computer-assisted assessment is to develop ways of collecting rich and complex data…
Descriptors: Computer Assisted Testing, Student Evaluation, Problem Solving, Thinking Skills
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DiCerbo, Kristen – Educational Measurement: Issues and Practice, 2020
We have the ability to capture data from students' interactions with digital environments as they engage in learning activity. This provides the potential for a reimagining of assessment to one in which assessment become part of our natural education activity and can be used to support learning. These new data allow us to more closely examine the…
Descriptors: Student Diversity, Information Technology, Learning Activities, Learning Processes
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Madsen, Adrian; McKagan, Sarah B.; Sayre, Eleanor C. – Physics Teacher, 2020
Physics faculty care about their students learning physics content. In addition, they usually hope that their students will learn some deeper lessons about thinking critically and scientifically. They hope that as a result of taking a physics class, students will come to appreciate physics as a coherent and logical method of understanding the…
Descriptors: Science Instruction, Physics, Student Surveys, Student Attitudes
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