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Chen, Fu; Lu, Chang; Cui, Ying; Gao, Yizhu – IEEE Transactions on Learning Technologies, 2023
Learning outcome modeling is a technical underpinning for the successful evaluation of learners' learning outcomes through computer-based assessments. In recent years, collaborative filtering approaches have gained popularity as a technique to model learners' item responses. However, how to model the temporal dependencies between item responses…
Descriptors: Outcomes of Education, Models, Computer Assisted Testing, Cooperation
Tan, Hongye; Wang, Chong; Duan, Qinglong; Lu, Yu; Zhang, Hu; Li, Ru – Interactive Learning Environments, 2023
Automatic short answer grading (ASAG) is a challenging task that aims to predict a score for a given student response. Previous works on ASAG mainly use nonneural or neural methods. However, the former depends on handcrafted features and is limited by its inflexibility and high cost, and the latter ignores global word cooccurrence in a corpus and…
Descriptors: Automation, Grading, Computer Assisted Testing, Graphs
Aditya Shah; Ajay Devmane; Mehul Ranka; Prathamesh Churi – Education and Information Technologies, 2024
Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…
Descriptors: Computer Assisted Testing, Difficulty Level, Grading, Test Construction
Doewes, Afrizal; Kurdhi, Nughthoh Arfawi; Saxena, Akrati – International Educational Data Mining Society, 2023
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…
Descriptors: Essays, Writing Evaluation, Evaluators, Accuracy
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
Missaoui, Siwar; Maalel, Ahmed – Education and Information Technologies, 2021
A student's profile defines the best way a student chooses to learn. It comprises information on student's characteristics such as background knowledge, learning style preference, goals, personality etc. The foremost challenge that the students experience in learning system is that they are unable to bring back relevant information based on their…
Descriptors: Profiles, Models, Computer Games, Cognitive Style
Capacho, Jose – Turkish Online Journal of Distance Education, 2017
This paper aims at showing a new methodology to assess student learning in virtual spaces supported by Information and Communications Technology-ICT. The methodology is based on the Conceptual Pedagogy Theory, and is supported both on knowledge instruments (KI) and intelectual operations (IO). KI are made up of teaching materials embedded in the…
Descriptors: Student Evaluation, Computer Assisted Testing, Difficulty Level, Thinking Skills
Mark Wilson; Kathleen Scalise; Perman Gochyyev – Educational Psychology, 2019
In this article, we describe a software system for assessment development in online learning environments in contexts where there are robust links to cognitive modelling including domain and student modelling. BEAR Assessment System Software (BASS) establishes both a theoretical basis for the domain modelling logic, and offers tools for delivery,…
Descriptors: Computer Software, Electronic Learning, Test Construction, Intelligent Tutoring Systems
Finkelstein, Idit; Soffer-Vital, Shira; Shraga-Roitman, Yael; Cohen-Liverant, Revital; Grebelsky-Lichtman, Tsfira – International Journal of Higher Education, 2022
Due to COVID-19, the world has encountered new challenges regarding pedagogy, learning, assessment, and evaluation. In meeting these challenges, there have been rapid changes in learning, and the gap between pedagogy and evaluation has grown. The purpose of this paper is to develop a new evaluative model suitable for the technologically enhanced,…
Descriptors: Student Evaluation, Evaluation Methods, Models, Culturally Relevant Education
Russell, Michael – Journal of Applied Testing Technology, 2016
Interest in and use of technology-enhanced items has increased over the past decade. Given the additional time required to administer many technology-enhanced items and the increased expense required to develop them, it is important for testing programs to consider the utility of technology-enhanced items. The Technology-Enhanced Item Utility…
Descriptors: Test Items, Computer Assisted Testing, Models, Fidelity
Abass, Olalere A.; Olajide, Samuel A.; Samuel, Babafemi O. – Turkish Online Journal of Distance Education, 2017
The traditional method of assessment (examination) is often characterized by examination questions leakages, human errors during marking of scripts and recording of scores. The technological advancement in the field of computer science has necessitated the need for computer usage in majorly all areas of human life and endeavors, education sector…
Descriptors: Computer Assisted Testing, Computer System Design, Test Format, Design Requirements
Wolf, Mikyung Kim; Guzman-Orth, Danielle; Lopez, Alexis; Castellano, Katherine; Himelfarb, Igor; Tsutagawa, Fred S. – Educational Assessment, 2016
This article investigates ways to improve the assessment of English learner students' English language proficiency given the current movement of creating next-generation English language proficiency assessments in the Common Core era. In particular, this article discusses the integration of scaffolding strategies, which are prevalently utilized as…
Descriptors: English Language Learners, Scaffolding (Teaching Technique), Language Tests, Language Proficiency
Boyd, Aimee M.; Dodd, Barbara; Fitzpatrick, Steven – Applied Measurement in Education, 2013
This study compared several exposure control procedures for CAT systems based on the three-parameter logistic testlet response theory model (Wang, Bradlow, & Wainer, 2002) and Masters' (1982) partial credit model when applied to a pool consisting entirely of testlets. The exposure control procedures studied were the modified within 0.10 logits…
Descriptors: Computer Assisted Testing, Item Response Theory, Test Construction, Models
Santos, Patricia; Cook, John; Hernández-Leo, Davinia – Educational Technology & Society, 2015
Authentic assessment is important in formal and informal learning. Technology has the potential to be used to support the assessment of higher order skills particularly with respect to real life tasks. In particular, the use of mobile devices allows the learner to increase her interactions with physical objects, various environments (indoors and…
Descriptors: Performance Based Assessment, Scaffolding (Teaching Technique), Interaction, Models
Li, Feiming; Cohen, Allan; Shen, Linjun – Journal of Educational Measurement, 2012
Computer-based tests (CBTs) often use random ordering of items in order to minimize item exposure and reduce the potential for answer copying. Little research has been done, however, to examine item position effects for these tests. In this study, different versions of a Rasch model and different response time models were examined and applied to…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Models