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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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Sundas Azeem; Muhammad Abbas – Education and Information Technologies, 2025
The study examined the association of big five personality traits (i.e., conscientiousness, openness to experience, and neuroticism) with use of Generative Artificial Intelligence (GenAI) among university students. It also examined the moderating role of perceived fairness in grading on the relationships of personality traits with GenAI usage.…
Descriptors: Personality Traits, Artificial Intelligence, Technology Uses in Education, Technology Integration
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Azevedo, Ana, Ed.; Azevedo, José, Ed. – IGI Global, 2019
E-assessments of students profoundly influence their motivation and play a key role in the educational process. Adapting assessment techniques to current technological advancements allows for effective pedagogical practices, learning processes, and student engagement. The "Handbook of Research on E-Assessment in Higher Education"…
Descriptors: Higher Education, Computer Assisted Testing, Multiple Choice Tests, Guides
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Chen, Yao-Hsien; Cheng, Ching-Hsue; Liu, Jing-Wei – Computers & Education, 2010
In order to evaluate student learning achievement, several aspects should be considered, such as exercises, examinations, and observations. Traditionally, such an evaluation calculates a final score using a weighted average method after awarding numerical scores, and then determines a grade according to a set of established crisp criteria.…
Descriptors: Feedback (Response), Academic Achievement, Student Evaluation, Grading
Polikoff, Morgan S. – Center for American Progress, 2014
The Common Core State Standards (CCSS) were created in response to the shortcomings of No Child Left Behind era standards and assessments. Among those failings were the poor quality of content standards and assessments and the variability in content expectations and proficiency targets across states, as well as concerns related to the economic…
Descriptors: Common Core State Standards, Educational Legislation, Federal Legislation, Elementary Secondary Education
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Bjelica, Momcilo; Rankovic, Dragica – Turkish Online Journal of Distance Education, 2010
The development of computer science, statistics and other technological fields, give us more opportunities to improve the process of evaluation of degree of knowledge and achievements in a learning process of our students. More and more we are relying on the computer software to guide us in the grading process. An improved way of grading can help…
Descriptors: Evaluation Methods, Student Evaluation, Distance Education, Academic Achievement
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Chen, Li-Ju; Ho, Rong-Guey; Yen, Yung-Chin – Educational Technology & Society, 2010
This study aimed to explore the effects of marking and metacognition-evaluated feedback (MEF) in computer-based testing (CBT) on student performance and review behavior. Marking is a strategy, in which students place a question mark next to a test item to indicate an uncertain answer. The MEF provided students with feedback on test results…
Descriptors: Feedback (Response), Test Results, Test Items, Testing
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Palocsay, Susan W.; Stevens, Scott P. – Decision Sciences Journal of Innovative Education, 2008
Web-based homework (WBH) Technology can simplify the creation and grading of assignments as well as provide a feasible platform for assessment testing, but its effect on student learning in business statistics is unknown. This is particularly true of the latest software development of Web-based tutoring agents that dynamically evaluate individual…
Descriptors: Internet, Homework, Objective Tests, Comparative Analysis
Marzano, Robert J. – Association for Supervision and Curriculum Development, 2006
If you've ever questioned the logic of reducing a student's entire academic performance to a single test score or a vague letter grade, then here's a book that will revolutionize the way you think about assessment and grading. Drawing from years of in-depth research, Robert J. Marzano provides you with guidelines and steps for designing a…
Descriptors: Feedback (Response), Report Cards, Academic Achievement, Computer Software
Chase, Clinton I. – 1999
This book provides basic skills and knowledge about assessment so that teachers can expand their ability to deal with appraisal problems in their own settings. The first section deals with the basic principles of assessment. The second section concerns creating and applying assessment tools. The third section reviews issues in understanding and…
Descriptors: Academic Achievement, Computer Assisted Testing, Educational Assessment, Elementary Secondary Education
Morgan, Chris; O'Reilly, Meg – 1999
This book is designed to help readers reflect upon their personal approaches to open and distance learning (ODL) assessment and to adapt their techniques to benefit learners. Part A explores issues and themes in ODL assessment. It examines key terms in assessment; the important relationship between assessment and learning; unique issues of…
Descriptors: Academic Achievement, Adult Education, Case Studies, Computer Assisted Testing
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection