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Sedigheh Karimpour; Ehsan Namaziandost; Hossein Kargar Behbahani – Journal of Educational Computing Research, 2025
As an integral part of dynamic assessment, computerized dynamic assessment (CDA) offers learners computer-assisted automated mediation. Accordingly, the possible efficacy of corrective feedback seems to be enhanced with new technologies, such as artificial intelligence tools, that offer automatic corrective feedback. Using technology-enhanced…
Descriptors: Computer Assisted Testing, Feedback (Response), Language Acquisition, Electronic Learning
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Dai, Jing; Gu, Xiaoqing; Zhu, Jiawen – Journal of Educational Computing Research, 2023
Personalized recommendation plays an important role on content selection during the adaptive learning process. It is always a challenge on how to recommend effective items to improve learning performance. The aim of this study was to examine the feasibility of applying adaptive testing technology for personalized recommendation. We proposed the…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Evaluation Methods, Tests
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Urrutia, Felipe; Araya, Roberto – Journal of Educational Computing Research, 2024
Written answers to open-ended questions can have a higher long-term effect on learning than multiple-choice questions. However, it is critical that teachers immediately review the answers, and ask to redo those that are incoherent. This can be a difficult task and can be time-consuming for teachers. A possible solution is to automate the detection…
Descriptors: Elementary School Students, Grade 4, Elementary School Mathematics, Mathematics Tests
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Li, Xu; Ouyang, Fan; Liu, Jianwen; Wei, Chengkun; Chen, Wenzhi – Journal of Educational Computing Research, 2023
The computer-supported writing assessment (CSWA) has been widely used to reduce instructor workload and provide real-time feedback. Interpretability of CSWA draws extensive attention because it can benefit the validity, transparency, and knowledge-aware feedback of academic writing assessments. This study proposes a novel assessment tool,…
Descriptors: Computer Assisted Testing, Writing Evaluation, Feedback (Response), Natural Language Processing
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Pejic, Marko; Savic, Goran; Segedinac, Milan – Journal of Educational Computing Research, 2021
This study proposes a software system for determining gaze patterns in on-screen testing. The system applies machine learning techniques to eye-movement data obtained from an eye-tracking device to categorize students according to their gaze behavior pattern while solving an on-screen test. These patterns are determined by converting eye movement…
Descriptors: Eye Movements, Computer Assisted Testing, Computer Software, Evaluation Methods
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Song, Yi; Zhu, Mengxiao; Sparks, Jesse R. – Journal of Educational Computing Research, 2023
In this research, we use a process data analysis approach to gather additional evidence about students' argumentation skills beyond their performance scores in a computer-based assessment. This game-enhanced scenario-based assessment (named Seaball) included five activities that require students to demonstrate their argumentation skills within a…
Descriptors: Data Analysis, Academic Achievement, Interaction, Performance
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Ponce, Héctor R.; Mayer, Richard E.; Loyola, María Soledad – Journal of Educational Computing Research, 2021
One of the most common technology-enhanced items used in large-scale K-12 testing programs is the drag-and-drop response interaction. The main research questions in this study are: (a) Does adding a drag-and-drop interface to an online test affect the accuracy of student performance? (b) Does adding a drag-and-drop interface to an online test…
Descriptors: Computer Assisted Testing, Test Construction, Standardized Tests, Elementary School Students
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Wang, Zhen; Cao, Yang; Gong, Shaoying – Journal of Educational Computing Research, 2023
Although learner characteristics have been identified as important moderator variables for feedback effectiveness, the question of why learners benefit differently from feedback has only received limited attention. In this study, we investigated: (1) whether learners' dominant goal orientation moderated the effects of computer-based elaborated…
Descriptors: Goal Orientation, Feedback (Response), Cues, Student Characteristics