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Yan Jin; Jason Fan – Language Assessment Quarterly, 2023
In language assessment, AI technology has been incorporated in task design, assessment delivery, automated scoring of performance-based tasks, score reporting, and provision of feedback. AI technology is also used for collecting and analyzing performance data in language assessment validation. Research has been conducted to investigate the…
Descriptors: Language Tests, Artificial Intelligence, Computer Assisted Testing, Test Format
Ying Fang; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Student Evaluation, Evaluation Methods
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Jeon, Jaeho; Lee, Seongyong – Education and Information Technologies, 2023
Artificial Intelligence (AI) is developing in a manner that blurs the boundaries between specific areas of application and expands its capability to be used in a wide range of applications. The public release of ChatGPT, a generative AI chatbot powered by a large language model (LLM), represents a significant step forward in this direction.…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Models
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Elbawab, Mohamed; Henriques, Roberto – Education and Information Technologies, 2023
Electronic learning (e-learning) is considered the new norm of learning. One of the significant drawbacks of e-learning in comparison to the traditional classroom is that teachers cannot monitor the students' attentiveness. Previous literature used physical facial features or emotional states in detecting attentiveness. Other studies proposed…
Descriptors: Students, Electronic Learning, Attention Span, Artificial Intelligence
Jennifer Hill; George Perrett; Vincent Dorie – Grantee Submission, 2023
Estimation of causal effects requires making comparisons across groups of observations exposed and not exposed to a a treatment or cause (intervention, program, drug, etc). To interpret differences between groups causally we need to ensure that they have been constructed in such a way that the comparisons are "fair." This can be…
Descriptors: Causal Models, Statistical Inference, Artificial Intelligence, Data Analysis
Sarah Kirkland – ProQuest LLC, 2023
The purpose of this study was to provide recommendations to improve the practice of incorporating emotional intelligence instructional strategies at Marine Corps University (MCU) in Quantico, Virginia. The problem was that emotional intelligence needs to be consistently addressed in the curriculum at MCU since research and strategic guidance…
Descriptors: Armed Forces, Universities, Emotional Intelligence, Educational Strategies
Ariel Rosenfeld; Avshalom Elmalech – Journal of Education for Library and Information Science, 2023
Many Library and Information Science (LIS) training programs are gradually expanding their curricula to include computational data science courses such as supervised and unsupervised machine learning. These programs focus on developing both "classic" information science competencies as well as core data science competencies among their…
Descriptors: Graduate Students, Information Science, Data Science, Competence
Anjali Adukia; Alex Eble; Emileigh Harrison; Hakizumwami Birali Runesha; Teodora Szasz – Grantee Submission, 2023
Books shape how children learn about society and norms, in part through representation of different characters. We use computational tools to characterize representation in children's books widely read in homes, classrooms, and libraries over the last century, and describe economic forces that may contribute to these patterns. We introduce new…
Descriptors: Self Concept, Racism, Gender Bias, Childrens Literature
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Persson, Roland S. – International Journal for Talent Development and Creativity, 2020
While it is easy to include gifted into society individuals representing the social functions of maintenance or entertainment, it is much more challenging to fully include brilliant intellectuals, who can potentially change society and its power structure by their insights. This paper presents the theory and research underpinning various aspects…
Descriptors: Cognitive Ability, Intelligence, Inclusion, Gifted
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Puttaswamy, Ash; Barone, Anjelica; Viezel, Kathleen D.; Willis, John O.; Dumont, Ron – Journal of Psychoeducational Assessment, 2020
An area of particular importance when examining index scores on the Wechsler Intelligence Scale for Children--Fifth Edition (WISC-V) is the utilization and interpretation of critical values and base rates associated with differences between an individual's subtest scaled score and the individual's mean scaled score for an index. For the WISC-V,…
Descriptors: Children, Intelligence Tests, Scores, Differences
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Warne, Russell T.; Burton, Jared Z. – Journal for the Education of the Gifted, 2020
Research in educational psychology consistently finds a relationship between intelligence and academic performance. However, in recent decades, educational fields, including gifted education, have resisted intelligence research, and there are some experts who argue that intelligence tests should not be used in identifying giftedness. Hoping to…
Descriptors: Intelligence, Educational Research, Teacher Attitudes, Attitudes
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Sternberg, Robert J. – Journal of Creative Behavior, 2020
This article describes a "straight-A" model of the creative process. It characterizes the creative process in five overlapping phases, with the variables most affecting those phases characterized as: (1) activators, (2) abilities, (3) amplifiers, (4) appeal to audience, and (5) assessment by audience. The creative process does not…
Descriptors: Intelligence, Creativity, Audiences, Correlation
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Sternberg, Robert J. – Journal of Creative Behavior, 2020
Creativity testing as it is now done is often based on a defective assumption that different kinds of creativity can be compressed into a single unidimensional scale. There is no reason to believe that the different kinds of creativity represent, simply, different amounts of a single unidimensional construct. The article shows how three different…
Descriptors: Creativity Tests, Test Validity, Misconceptions, Models
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King, Ronnel B. – British Journal of Educational Psychology, 2020
Background: Beliefs about the malleability of intelligence (fixed or growth mindsets) are strongly influenced by teachers and parents. However, the social contagion of mindsets among one's classmates has not been given sufficient attention. Aims: This study aimed to examine the social contagion of mindsets among one's peers by investigating the…
Descriptors: Intelligence, Beliefs, Students, Cognitive Structures
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Mendelson, Richard A.; Stabile, Christopher – New Directions for Teaching and Learning, 2019
Emotional intelligence influences educational leaders, educators, and the overall performance of learning institutions.
Descriptors: Emotional Intelligence, Instructional Leadership
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