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What Works Clearinghouse Rating
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
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
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
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
Mohd Elmagzoub Eltahir; Nagaletchimee Annamalai; Arulselvi Uthayakumaran; Samer H. Zyoud; Antonia Ramírez García; Viktorija Mažeikiene; Bilal Zakarneh; Najeh Rajeh Al Salhi – SAGE Open, 2023
Online assessment is a new introduction in many developing countries during the COVID-19 pandemic, including Malaysia, Lithuania, and Spain. The current study conducted a phenomenology study to probe insights about fairness in online assessment. The interview data were interpreted from the perspective of social psychology theory that emphasizes…
Descriptors: Foreign Countries, COVID-19, Pandemics, Scoring Rubrics
Gerard, Libby; Kidron, Ady; Linn, Marcia C. – International Journal of Computer-Supported Collaborative Learning, 2019
This paper illustrates how the combination of teacher and computer guidance can strengthen collaborative revision and identifies opportunities for teacher guidance in a computer-supported collaborative learning environment. We took advantage of natural language processing tools embedded in an online, collaborative environment to automatically…
Descriptors: Computer Assisted Testing, Student Evaluation, Science Tests, Scoring
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
Celeste Combrinck; Nelé Loubser – Discover Education, 2025
Written assignments for large classes pose a far more significant challenge in the age of the GenAI revolution. Suggestions such as oral exams and formative assessments are not always feasible with many students in a class. Therefore, we conducted a study in South Africa and involved 280 Honors students to explore the usefulness of Turnitin's AI…
Descriptors: Foreign Countries, Artificial Intelligence, Large Group Instruction, Alternative Assessment
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
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
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
Parisa Aqdas Karimi; Seyyed Kazem Banihashem; Harm J. A. Biemans – International Journal of Technology in Education and Science, 2023
The current paper focusses on the teachers' attitude towards and experiences with e-learning tools at two universities in different phases of e-learning implementation. The study population comprises teachers at university level and a simple random sampling method was used. A total of 45 teachers in bachelor programmes from the Faculty of…
Descriptors: College Faculty, Teacher Attitudes, Electronic Learning, Technology Uses in Education
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