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Xuefan Li; Marco Zappatore; Tingsong Li; Weiwei Zhang; Sining Tao; Xiaoqing Wei; Xiaoxu Zhou; Naiqing Guan; Anny Chan – IEEE Transactions on Learning Technologies, 2025
The integration of generative artificial intelligence (GAI) into educational settings offers unprecedented opportunities to enhance the efficiency of teaching and the effectiveness of learning, particularly within online platforms. This study evaluates the development and application of a customized GAI-powered teaching assistant, trained…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation, Academic Achievement
Abdessamad Chanaa; Nour-eddine El Faddouli – Journal of Education and Learning (EduLearn), 2024
Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning…
Descriptors: Electronic Learning, Evaluation Methods, Artificial Intelligence, Taxonomy
Rizki Zakwandi; Edi Istiyono; Wipsar Sunu Brams Dwandaru – Education and Information Technologies, 2024
Computational Thinking (CT) skill was a part of the global framework of reference on Digital Literacy for Indicator 4.4.2, widely developed in mathematics and science learning. This study aimed to promote an assessment tool using a two-tier Computerized Adaptive Test (CAT). The study used the Design and Development Research (DDR) method with four…
Descriptors: Computer Assisted Testing, Adaptive Testing, Student Evaluation, Computation
Somers, Rick; Cunningham-Nelson, Samuel; Boles, Wageeh – Australasian Journal of Educational Technology, 2021
In this study, we applied natural language processing (NLP) techniques, within an educational environment, to evaluate their usefulness for automated assessment of students' conceptual understanding from their short answer responses. Assessing understanding provides insight into and feedback on students' conceptual understanding, which is often…
Descriptors: Natural Language Processing, Student Evaluation, Automation, Feedback (Response)
Malik, Ali; Wu, Mike; Vasavada, Vrinda; Song, Jinpeng; Coots, Madison; Mitchell, John; Goodman, Noah; Piech, Chris – International Educational Data Mining Society, 2021
Access to high-quality education at scale is limited by the difficulty of providing student feedback on open-ended assignments in structured domains like programming, graphics, and short response questions. This problem has proven to be exceptionally difficult: for humans, it requires large amounts of manual work, and for computers, until…
Descriptors: Grading, Accuracy, Computer Assisted Testing, Automation
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
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
Resing, Wilma C. M.; Vogelaar, Bart; Elliott, Julian G. – Educational Psychology, 2020
The present study investigated the usefulness of a pre-programmed, teleoperated, socially assistive peer robot in dynamic testing of complex problem solving utilising the Tower of Hanoi. The robot, in a 'Wizard of Oz' setting, provided instructions and prompts during dynamic testing to children when they had to solve 3 D Tower of Hanoi puzzles.…
Descriptors: Problem Solving, Robotics, Puzzles, Grade 2
Yasuda, Jun-ichiro; Mae, Naohiro; Hull, Michael M.; Taniguchi, Masa-aki – Physical Review Physics Education Research, 2021
As a method to shorten the test time of the Force Concept Inventory (FCI), we suggest the use of computerized adaptive testing (CAT). CAT is the process of administering a test on a computer, with items (i.e., questions) selected based upon the responses of the examinee to prior items. In so doing, the test length can be significantly shortened.…
Descriptors: Foreign Countries, College Students, Student Evaluation, Computer Assisted Testing
Werlen, Egon; Bergamin, Per – International Association for Development of the Information Society, 2018
The continuous measurement of learning behavior or learning outcome by appropriate sensors is fundamental for the implementation of technology-based adaptive learning courses. An adaptive system needs such learning data to adapt the instruction to the needs of students. Depending on the learning objective, the sensors use information generated…
Descriptors: Self Evaluation (Individuals), Measures (Individuals), Computer Assisted Instruction, Computer Assisted Testing
Jayashankar, Shailaja; Sridaran, R. – Education and Information Technologies, 2017
Teachers are thrown open to abundance of free text answers which are very daunting to read and evaluate. Automatic assessments of open ended answers have been attempted in the past but none guarantees 100% accuracy. In order to deal with the overload involved in this manual evaluation, a new tool becomes necessary. The unique superlative model…
Descriptors: Word Frequency, Models, Electronic Learning, Student Evaluation
Molnar, Gyongyver; Hodi, Agnes; Magyar, Andrea – AERA Online Paper Repository, 2016
Vocabulary knowledge assessment methods and instruments have gone through a significant evolution. Computer-based tests offer more opportunities than their paper-and-pencil counterparts, however, most digital vocabulary assessments are linear and adaptive solutions in this domain are scarce. The aims of this study were to compare the effectiveness…
Descriptors: Adaptive Testing, Vocabulary Skills, Computer Assisted Testing, Student Evaluation
Dindar, M.; Kabakçi Yurdakul, I.; Inan Dönmez, F. – Journal of Computer Assisted Learning, 2015
The majority of multimedia learning studies focus on the use of graphics in learning process but very few of them examine the role of graphics in testing students' knowledge. This study investigates the use of static graphics versus animated graphics in a computer-based English achievement test from a cognitive load theory perspective. Three…
Descriptors: Difficulty Level, Cognitive Processes, Animation, Visual Aids
Golovachyova, Viktoriya N.; Menlibekova, Gulbakhyt Zh.; Abayeva, Nella F.; Ten, Tatyana L.; Kogaya, Galina D. – International Journal of Environmental and Science Education, 2016
Using computer-based monitoring systems that rely on tests could be the most effective way of knowledge evaluation. The problem of objective knowledge assessment by means of testing takes on a new dimension in the context of new paradigms in education. The analysis of the existing test methods enabled us to conclude that tests with selected…
Descriptors: Expertise, Computer Assisted Testing, Student Evaluation, Knowledge Level
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