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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
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Lucía Torres-Sales; Begoña Vigo-Arrazola – Policy Futures in Education, 2025
This article critically analyzes the representation of standardised assessments in Spanish educational policies, particularly in the current Spanish education law (LOMLOE), in reports on the state of the Spanish educational system (2020-2023), and through the voices of teachers working in schools with special difficulties and their implications…
Descriptors: Foreign Countries, Educational Legislation, Standardized Tests, Educational Policy
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Jonathan Liu; Seth Poulsen; Erica Goodwin; Hongxuan Chen; Grace Williams; Yael Gertner; Diana Franklin – ACM Transactions on Computing Education, 2025
Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present a systematic survey and literature review of CS Education studies. We search for research that is both…
Descriptors: Teaching Methods, Algorithms, Design, Computer Science Education
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Olaf Lund; Rune Raudeberg; Hans Johansen; Mette-Line Myhre; Espen Walderhaug; Amir Poreh; Jens Egeland – Journal of Attention Disorders, 2025
Objective: The Conners Continuous Performance Test-3 (CCPT-3) is a computerized test of attention frequently used in clinical neuropsychology. In the present factor analysis, we seek to assess the factor structure of the CCPT-3 and evaluate the suggested dimensions in the CCPT-3 Manual. Method: Data from a mixed clinical sample of 931 adults…
Descriptors: Factor Structure, Factor Analysis, Attention Span, Measures (Individuals)
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Ilhama Mammadova; Fatime Ismayilli; Elnaz Aliyeva; Narmin Mammadova – Educational Process: International Journal, 2025
Background/purpose: Artificial Intelligence (AI) is increasingly shaping assessment practices in higher education, promising faster feedback and reduced instructor workload while also raising concerns about fairness and transparency. This study examines how AI technologies are transforming assessment processes and the experiences of stakeholders.…
Descriptors: Artificial Intelligence, Student Evaluation, Technology Uses in Education, Undergraduate Students
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Wallace N. Pinto Jr.; Jinnie Shin – Journal of Educational Measurement, 2025
In recent years, the application of explainability techniques to automated essay scoring and automated short-answer grading (ASAG) models, particularly those based on transformer architectures, has gained significant attention. However, the reliability and consistency of these techniques remain underexplored. This study systematically investigates…
Descriptors: Automation, Grading, Computer Assisted Testing, Scoring
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Daniel Lupiya Mpolomoka – Pedagogical Research, 2025
Overview: This systematic review explores the utilization of artificial intelligence (AI) for assessment, grading, and feedback in higher education. The review aims to establish how AI technologies enhance efficiency, scalability, and personalized learning experiences in educational settings, while addressing associated challenges that arise due…
Descriptors: Artificial Intelligence, Higher Education, Evaluation Methods, Literature Reviews
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Sun-Joo Cho; Goodwin Amanda; Jorge Salas; Sophia Mueller – Grantee Submission, 2025
This study incorporates a random forest (RF) approach to probe complex interactions and nonlinearity among predictors into an item response model with the goal of using a hybrid approach to outperform either an RF or explanatory item response model (EIRM) only in explaining item responses. In the specified model, called EIRM-RF, predicted values…
Descriptors: Item Response Theory, Artificial Intelligence, Statistical Analysis, Predictor Variables
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Mncedisi Christian Maphalala; Ntombikayise Nkosi – Open Praxis, 2025
This conceptual study explores and proposes strategies for enhancing security and academic integrity within the Open and Distance e-learning (ODeL) context, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols. As higher education continues to evolve, the reliance on online assessments has become more…
Descriptors: Literature Reviews, Meta Analysis, Supervision, Computer Assisted Testing
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Amie J. Dirks-Naylor – Advances in Physiology Education, 2025
Artificial intelligence (AI) tools like ChatGPT offer new opportunities to enhance student learning through active recall and self-directed inquiry. This study aimed to determine student perceptions of a classroom assignment designed to develop proficiency in using ChatGPT for these strategies. First-semester Doctor of Pharmacy students in a…
Descriptors: Artificial Intelligence, Technology Uses in Education, Recall (Psychology), Inquiry
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Patel, Nirmal; Sharma, Aditya; Shah, Tirth; Lomas, Derek – Journal of Educational Data Mining, 2021
Process Analysis is an emerging approach to discover meaningful knowledge from temporal educational data. The study presented in this paper shows how we used Process Analysis methods on the National Assessment of Educational Progress (NAEP) test data for modeling and predicting student test-taking behavior. Our process-oriented data exploration…
Descriptors: Learning Analytics, National Competency Tests, Evaluation Methods, Prediction
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Steven L. Wise; Megan R. Kuhfeld; Marlit Annalena Lindner – Applied Measurement in Education, 2024
When student achievement is assessed, we seek to elicit a student's maximum performance -- a goal requiring the assumption that the student is fully engaged. Otherwise, to the extent that disengagement occurs, test performance is likely to suffer. Effectively managing test-taking disengagement requires an understanding of the testing conditions…
Descriptors: Testing, Attention Span, Learner Engagement, Time Factors (Learning)
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Patrick Kyllonen; Amit Sevak; Teresa Ober; Ikkyu Choi; Jesse Sparks; Daniel Fishtein – ETS Research Report Series, 2024
Assessment refers to a broad array of approaches for measuring or evaluating a person's (or group of persons') skills, behaviors, dispositions, or other attributes. Assessments range from standardized tests used in admissions, employee selection, licensure examinations, and domestic and international large-scale assessments of cognitive and…
Descriptors: Assessment Literacy, Testing, Test Bias, Test Construction
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Lahza, Hatim; Smith, Tammy G.; Khosravi, Hassan – British Journal of Educational Technology, 2023
Traditional item analyses such as classical test theory (CTT) use exam-taker responses to assessment items to approximate their difficulty and discrimination. The increased adoption by educational institutions of electronic assessment platforms (EAPs) provides new avenues for assessment analytics by capturing detailed logs of an exam-taker's…
Descriptors: Medical Students, Evaluation, Computer Assisted Testing, Time Factors (Learning)
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Buczak, Philip; Huang, He; Forthmann, Boris; Doebler, Philipp – Journal of Creative Behavior, 2023
Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns…
Descriptors: Computer Assisted Testing, Scoring, Automation, Creative Thinking
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