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Bulut, Okan; Yildirim-Erbasli, Seyma Nur – International Journal of Assessment Tools in Education, 2022
Reading comprehension is one of the essential skills for students as they make a transition from learning to read to reading to learn. Over the last decade, the increased use of digital learning materials for promoting literacy skills (e.g., oral fluency and reading comprehension) in K-12 classrooms has been a boon for teachers. However, instant…
Descriptors: Reading Comprehension, Natural Language Processing, Artificial Intelligence, Automation
Anson, Chris M. – Composition Studies, 2022
Student plagiarism has challenged educators for decades, with heightened paranoia following the advent of the Internet in the 1980's and ready access to easily copied text. But plagiarism will look like child's play next to new developments in AI-based natural-language processing (NLP) systems that increasingly appear to "write" as…
Descriptors: Plagiarism, Artificial Intelligence, Natural Language Processing, Writing Assignments
Gunasilan, Uma – Higher Education, Skills and Work-based Learning, 2022
Purpose: Debates are well known to encompass a variety of skills we would like higher education candidates to embody when they graduate. Design/methodology/approach: Debates in a classroom with computer science as the main subject has been popular in high schools particularly with emerging issues around the area, however it does not have as an…
Descriptors: Debate, Learning Activities, Teaching Methods, Programming
Bhimdiwala, Ayesha; Neri, Rebecca Colina; Gomez, Louis M. – International Journal of Artificial Intelligence in Education, 2022
With the rapid rise of Artificial Intelligence in Education (AIEd), multiple stakeholders are questioning AI's capability to make fair and trustworthy decisions that improve teaching and learning. We suspect that unfair and unreliable outcomes might stem from lack of systematic collaboration between the developers of AIEd systems and the educators…
Descriptors: Design, Program Implementation, Artificial Intelligence, Technology Uses in Education
McCaffrey, Daniel F.; Casabianca, Jodi M.; Ricker-Pedley, Kathryn L.; Lawless, René R.; Wendler, Cathy – ETS Research Report Series, 2022
This document describes a set of best practices for developing, implementing, and maintaining the critical process of scoring constructed-response tasks. These practices address both the use of human raters and automated scoring systems as part of the scoring process and cover the scoring of written, spoken, performance, or multimodal responses.…
Descriptors: Best Practices, Scoring, Test Format, Computer Assisted Testing
Bialystok, Ellen; Hawrylewicz, Kornelia; Grundy, John G.; Chung-Fat-Yim, Ashley – Developmental Psychology, 2022
Early research that relied on standardized assessments of intelligence reported negative effects of bilingualism for children, but a study by Peal and Lambert (1962) reported better performance by bilingual than monolingual children on verbal and nonverbal intelligence tests. This outcome led to the view that bilingualism was a positive…
Descriptors: Bilingualism, Children, Intelligence Tests, Monolingualism
Shojaeian, Nazila; Li, Zeyun; Kaurav, Rahul Pratap Singh; Salem, Ashraf Atta M. S. – Journal of Autism and Developmental Disorders, 2022
The present study examined the role of IQ and the Theory of Mind understanding in children with an autism spectrum disorder and down syndrome. Sixty-six Swedish children with ASD (n = 26), DS (n = 18), and typically developed group (n = 22) ranged between 6 and 12 years old were compared on ToM tasks consisted of standard ToM and IQ tasks. SPSS 25…
Descriptors: Theory of Mind, Foreign Countries, Children, Autism Spectrum Disorders
Güler, Bahar; Turan, Serhat – Journal of Educational Issues, 2022
The aim of the research is to determine how much peer relationships are explained by emotional intelligence in adolescents. For this purpose, 539 (283 female+256 male) adolescent individuals participated in the study. "Personal Information Form", "Trait Emotional Intelligence-Adolescent Questionnaire Short Form (TEIQue-ASF)"…
Descriptors: Emotional Intelligence, Peer Relationship, Predictor Variables, Adolescents
Machielsen, John A. – Education and Culture, 2022
I argue for taking John Dewey's pluralistic ethics as a starting point, or embedded practice, from and in which technological innovations are conceptualized, critiqued, designed, tested, and eventually implemented. Dewey reconstructs human reason into operational intelligence where all behavior becomes gradually imaginative. I take Dewey's view of…
Descriptors: Educational Theories, Ethics, Technological Advancement, Intelligence
Zhang, Wei; Wang, Yu; Wang, Suyu – Education and Information Technologies, 2022
Educational data mining (DEM) provides valuable educational information by applying data mining tools and techniques to analyze data at educational institutions. In this paper, tree-based machine learning algorithms are used to predict students' overall academic performance in their bachelor's program. The transcript data of the students in the…
Descriptors: Grade Prediction, Academic Achievement, Models, Artificial Intelligence
Kardas, Abdurrahman; Yildirim, Bilal – Educational Process: International Journal, 2022
Background/purpose: In addition to many competencies of school administrators, the level of intellectuality can increase the commitment of educational actors to the organization in schools with sociocultural diversity, which is considered as a wealth of Turkey. Considering the sociocultural developments of the present day, it is important to know…
Descriptors: Intelligence Tests, Administrators, Test Validity, Test Reliability
Baker, Ryan S.; Hawn, Aaron – International Journal of Artificial Intelligence in Education, 2022
In this paper, we review algorithmic bias in education, discussing the causes of that bias and reviewing the empirical literature on the specific ways that algorithmic bias is known to have manifested in education. While other recent work has reviewed mathematical definitions of fairness and expanded algorithmic approaches to reducing bias, our…
Descriptors: Mathematics, Bias, Education, Race
Smeyne, Catelyn N.; Esbensen, Anna J.; Schworer, Emily K.; Belizaire, Shequanna; Hoffman, Emily K.; Beebe, Dean W.; Wiley, Susan – American Journal on Intellectual and Developmental Disabilities, 2022
This study evaluates the psychometric properties of a verbal fluency task for potential use as an outcome measure in future clinical trials involving children with Down syndrome. Eighty-five participants attempted a modified version of the Neuropsychological Assessment of Children, Second Edition Word Generation Task at two time points. In the…
Descriptors: Children, Down Syndrome, Verbal Ability, Language Fluency
Molenaar, Inge – European Journal of Education, 2022
Education is a unique area for application of artificial intelligence (AI). In this article, the augmentation perspective and the concept of hybrid intelligence are introduced to frame our thinking about AI in education. The involvement of quadruple helix stakeholders (i.e., researchers, education professionals, entrepreneurs, and policymakers) is…
Descriptors: Educational Technology, Artificial Intelligence, Technology Uses in Education, Stakeholders
Kaya, Mehmet Melik – International Journal of Progressive Education, 2022
The purpose of this study was to examine the relationship between cultural intelligence and global citizenship. The study group of the research consisted of 336 pre-service teachers, including pedagogical formation students, selected by a random sampling method from a state university in eastern Turkey, where the immigrant population is dense.…
Descriptors: Foreign Countries, Preservice Teachers, Cultural Awareness, Intelligence

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