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Reham Salhab – Online Learning, 2024
Artificial Intelligence (AI) is increasingly prevalent, permeating various aspects of and spreading across education. However, a comprehensive understanding of AI applications and how to define AI literacy is under-investigated. On this note, teaching and evaluating AI literacy necessitates educators to integrate it into course content. The…
Descriptors: Artificial Intelligence, Multiple Literacies, College Faculty, Higher Education
Kaiwen Man – Educational and Psychological Measurement, 2024
In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…
Descriptors: Prior Learning, Testing, Behavior, Artificial Intelligence
Viezel, Kathleen D.; Freer, Benjamin; Morgan, Chelsea D. – Focus on Autism and Other Developmental Disabilities, 2022
As an increasing number of individuals with autism spectrum disorder (ASD) matriculate on college campuses, all stakeholders should be prepared to meet their needs. Despite a body of literature describing adaptive behavior deficits of individuals with ASD, there is a paucity of research examining these skills among those who are college-ready. The…
Descriptors: Autism, Pervasive Developmental Disorders, Student Adjustment, College Freshmen
Joseph, Dana L.; Zemen, Betsir; McCord, Mallory A.; Fado, Stephanie – New Directions for Teaching and Learning, 2019
This chapter reviews the existing literature on emotional intelligence training in higher education and the emotional intelligence courses offered at top ranking national universities.
Descriptors: Emotional Intelligence, Training, Higher Education, Courses
Phusee-orn, Songsak; Ruannakarn, Prasert; Seehamongkon, Yannapat; Piyakul, Araya; Yurayat, Phamornpun; Suk-erb, Winpanee; Tuklang, Supachai; Sirisittanapak, Sudares; Khoungsimma, Pornweenus; Sakulthong, Lucksana – Journal of Education and Training Studies, 2019
This research focuses on intelligence quotient (IQ) of the primary school students in Mahasarakham Province. There are 5,053 subjects from 64 schools under the Mahasarakham Primary Education Office. Stratified Random Sampling is applied in selecting the subjects. The subjects are divided according to their districts and school sizes (Small,…
Descriptors: Intelligence Quotient, Elementary School Students, Foreign Countries
Gillespie-Lynch, Kristen; Hotez, Emily; Zajic, Matthew; Riccio, Ariana; DeNigris, Danielle; Kofner, Bella; Bublitz, Dennis; Gaggi, Naomi; Luca, Kavi – Autism: The International Journal of Research and Practice, 2020
The writing skills of autistic university students have received very little empirical attention. Previous research has suggested that autistic people may struggle with writing, in part, due to challenges with Theory of Mind. However, other research indicates that Theory of Mind difficulties are far from universal in autism, varying across…
Descriptors: Writing Skills, Autism, Pervasive Developmental Disorders, College Students
Gillespie-Lynch, Kristen; Hotez, Emily; Zajic, Matthew; Riccio, Ariana; DeNigris, Danielle; Kofner, Bella; Bublitz, Dennis; Gaggi, Naomi; Luca, Kavi – Grantee Submission, 2020
The writing skills of autistic university students have received very little empirical attention. Previous research has suggested that autistic people may struggle with writing, in part, due to challenges with Theory of Mind. However, other research indicates that Theory of Mind difficulties are far from universal in autism, varying across…
Descriptors: Writing Skills, Autism, Pervasive Developmental Disorders, College Students
Erbeli, Florina; He, Kai; Cheek, Connor; Rice, Marianne; Qian, Xiaoning – Scientific Studies of Reading, 2023
Purpose: Researchers have developed a constellation model of decodingrelated reading disabilities (RD) to improve the RD risk determination. The model's hallmark is its inclusion of various RD indicators to determine RD risk. Classification methods such as logistic regression (LR) might be one way to determine RD risk within the constellation…
Descriptors: At Risk Students, Reading Difficulties, Classification, Comparative Analysis
Hao, Jianjiang; Guo, Jiong; Wang, Charles Xiaoxue – TechTrends: Linking Research and Practice to Improve Learning, 2021
The 24th Global Chinese Conference on Computers in Education (GCCCE) was held September 12-16, 2020 at Northwest Normal University, Lanzhou, China. The GCCCE adopted a hybrid conference format for the first time, combining traditional face-to-face sessions and online live streaming to reduce the impact from the Covid-19 pandemic. The GCCCE hosted…
Descriptors: Educational Innovation, Computer Uses in Education, Educational Change, Artificial Intelligence
Butakor, Paul K.; Guo, Qi; Adebanji, Atinuke O. – Psychology in the Schools, 2021
The purpose of the study was to examine the causal relationship between teachers' emotional intelligence, job satisfaction, professional identity, and work engagement. And to achieve this purpose, a questionnaire consisting of four scales was administered to 260 teachers selected from the Adentan Municipal in the Greater Accra Region. Exploratory…
Descriptors: Structural Equation Models, Foreign Countries, Emotional Intelligence, Job Satisfaction
Lo, Siaw Ling; Tan, Kar Way; Ouh, Eng Lieh – Research and Practice in Technology Enhanced Learning, 2021
Do my students understand? The question that lingers in every instructor's mind after each lesson. With the focus on learner-centered pedagogy, is it feasible to provide timely and relevant guidance to individual learners according to their levels of understanding? One of the options available is to collect reflections from learners after each…
Descriptors: Automation, Artificial Intelligence, Identification, Reflection
Khan, Ijaz; Ahmad, Abdul Rahim; Jabeur, Nafaa; Mahdi, Mohammed Najah – Smart Learning Environments, 2021
A major problem an instructor experiences is the systematic monitoring of students' academic progress in a course. The moment the students, with unsatisfactory academic progress, are identified the instructor can take measures to offer additional support to the struggling students. The fact is that the modern-day educational institutes tend to…
Descriptors: Artificial Intelligence, Academic Achievement, Progress Monitoring, Data Collection
Tian, Xuetao; Liu, Feng – IEEE Transactions on Learning Technologies, 2021
Massive open online courses (MOOCs) have been an important learning tool in education. In order to reduce the high dropout rate and improve learners' satisfactions, it is urgent for MOOCs platform to provide course recommendation and tutoring service. To achieve it, it is necessary to determine and trace learners' learning state. Cognitive…
Descriptors: Online Courses, Item Response Theory, Course Selection (Students), Artificial Intelligence
Keskin, Bülent; Özay Köse, Esra; Güloglu, Fadime – International Journal of Contemporary Educational Research, 2021
This study which used survey model aims to examine the relationship between the multiple intelligence and learning styles of the Social Sciences High School and Science High School students. Multiple Intelligence Inventory and Learning Styles Inventory were used as data collection tools, which was conducted on 761 students from Social Sciences…
Descriptors: Social Sciences, High School Students, Multiple Intelligences, Correlation
Meier, Michaela A.; Burgstaller, Julia A.; Benedek, Mathias; Vogel, Stephan E.; Grabner, Roland H. – Journal of Intelligence, 2021
Mathematical creativity is perceived as an increasingly important aspect of everyday life and, consequently, research has increased over the past decade. However, mathematical creativity has mainly been investigated in children and adolescents so far. Therefore, the first goal of the current study was to develop a mathematical creativity measure…
Descriptors: Adults, Mathematics, Creativity, Intelligence

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