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Chu, Jinjin; Szlagor, Maciej – International Journal of Web-Based Learning and Teaching Technologies, 2023
Distance education between the student and the teacher through online sessions can make it difficult for a student who does not understand a concept to ask for clarification. Lack of a physical campus or social pressure from peers can demotivate students from completing their assignments. The framework of multi-intelligence English teaching based…
Descriptors: Distance Education, Blended Learning, Educational Technology, Multiple Intelligences
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Deutsch, Joe – Quest, 2021
The National Association for Kinesiology in Higher Education's (NAHKE) efforts to connect professionals to share our strategies and passions for success within kinesiology are more valuable than ever before and developing emotionally intelligent leaders and administrators is very important. For the 30th Delphine Hanna Commemorative Lecture, the…
Descriptors: Emotional Intelligence, Kinesiology, Higher Education
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Ellala, Ziyad K.; Abu Attiyeh, Jamal H.; Ellala, Saeb K.; Kaba, Abdoulaye – Gifted Education International, 2022
The current study aimed to identify the level of emotional intelligence of outstanding students at the College of Education, Al Ain University (AAU), the United Arab Emirates, and their counterparts at Princess Nourah University (PNU), in the Kingdom of Saudi Arabia. A sample of 77 students was selected from both universities, of whom 41 students…
Descriptors: Emotional Intelligence, Academically Gifted, Foreign Countries, Schools of Education
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Figueiredo, Sandra – European Journal of Educational Research, 2022
The main goal of this study is to examine the differences between school-aged children with different chronotypes who are only children or have a sibling in the household, regarding their sleeping habits and performance in intelligence tasks. The main measures used were Chronotype Questionnaire for Children and Raven's Coloured Progressive…
Descriptors: Foreign Countries, Intelligence Tests, Grade 1, Sleep
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Hoq, Muntasir; Brusilovsky, Peter; Akram, Bita – International Educational Data Mining Society, 2023
Prediction of student performance in introductory programming courses can assist struggling students and improve their persistence. On the other hand, it is important for the prediction to be transparent for the instructor and students to effectively utilize the results of this prediction. Explainable Machine Learning models can effectively help…
Descriptors: Academic Achievement, Prediction, Models, Introductory Courses
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Shen, Guohua; Yang, Sien; Huang, Zhiqiu; Yu, Yaoshen; Li, Xin – Education and Information Technologies, 2023
Due to the growing demand for information technology skills, programming education has received increasing attention. Predicting students' programming performance helps teachers realize their teaching effect and students' learning status in time to provide support for students. However, few of the existing researches have taken the code that…
Descriptors: Prediction, Programming, Student Characteristics, Profiles
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Ouyang, Fan; Xu, Weiqi; Cukurova, Mutlu – International Journal of Computer-Supported Collaborative Learning, 2023
Collaborative problem solving (CPS) enables student groups to complete learning tasks, construct knowledge, and solve problems. Previous research has argued the importance of examining the complexity of CPS, including its multimodality, dynamics, and synergy from the complex adaptive systems perspective. However, there is limited empirical…
Descriptors: Artificial Intelligence, Learning Analytics, Cooperative Learning, Problem Solving
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Nguyen, Ngoc Nhu; Nham, Tuan Phong; Takahashi, Yoshi – Policy Futures in Education, 2023
This research investigated the relationship between emotional intelligence of university students and their resilience ability during crisis: the pandemic of COVID-19. A large-scale quantitative approach was applied with a national survey in the midst of the fourth wave of COVID-19 outbreak in Vietnam. The research obtained data from 2252 students…
Descriptors: Emotional Intelligence, Resilience (Psychology), COVID-19, Pandemics
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Goldstein, Yoav; Legewie, Nicolas M.; Shiffer-Sebba, Doron – Sociological Methods & Research, 2023
Video data offer important insights into social processes because they enable direct observation of real-life social interaction. Though such data have become abundant and increasingly accessible, they pose challenges to scalability and measurement. Computer vision (CV), i.e., software-based automated analysis of visual material, can help address…
Descriptors: Artificial Intelligence, Data Analysis, Interpersonal Relationship, Social Science Research
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Jiang, Zhehan; Han, Yuting; Xu, Lingling; Shi, Dexin; Liu, Ren; Ouyang, Jinying; Cai, Fen – Educational and Psychological Measurement, 2023
The part of responses that is absent in the nonequivalent groups with anchor test (NEAT) design can be managed to a planned missing scenario. In the context of small sample sizes, we present a machine learning (ML)-based imputation technique called chaining random forests (CRF) to perform equating tasks within the NEAT design. Specifically, seven…
Descriptors: Test Items, Equated Scores, Sample Size, Artificial Intelligence
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Ranger, Jochen; Schmidt, Nico; Wolgast, Anett – Educational and Psychological Measurement, 2023
Recent approaches to the detection of cheaters in tests employ detectors from the field of machine learning. Detectors based on supervised learning algorithms achieve high accuracy but require labeled data sets with identified cheaters for training. Labeled data sets are usually not available at an early stage of the assessment period. In this…
Descriptors: Identification, Cheating, Information Retrieval, Tests
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Martin, Joshua L.; Wright, Kelly Elizabeth – Applied Linguistics, 2023
Research on bias in artificial intelligence has grown exponentially in recent years, especially around racial bias. Many modern technologies which impact people's lives have been shown to have significant racial biases, including automatic speech recognition (ASR) systems. Emerging studies have found that widely-used ASR systems function much more…
Descriptors: Automation, Speech Communication, Black Dialects, Racism
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Flores-Viva, Jesús-Miguel; García-Peñalvo, Francisco-José – Comunicar: Media Education Research Journal, 2023
This article analyses and reflects on the ethical aspects of using artificial intelligence (AI) systems in educational contexts. On the one hand, the impact of AI in the field of education is addressed from the perspective of the Sustainable Development Goals (specifically, SDG4) of the UNESCO 2030 Agenda, describing the opportunities for its use…
Descriptors: Ethics, Artificial Intelligence, Educational Quality, Technology Uses in Education
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Jung, Rex E.; Hunter, Dan R. – Creativity Research Journal, 2023
Psychologist J. P. Guildford issued a challenge to study creativity nearly 70 years ago. How well have we done and what might the next steps be in our endeavors to understand creativity? The field of creativity research has examined the internal thinking process of creativity, largely through measures of divergent thinking and remote associates.…
Descriptors: Creativity, Creative Thinking, Success, Intelligence
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Rahm, Lina; Rahm-Skågeby, Jörgen – British Journal of Educational Technology, 2023
This paper suggests that artificial intelligence in education (AIEd) can be fruitfully analysed as 'policies frozen in silicon'. This means that they exist as both materialised and proposed problematisations (problem representations with corresponding solutions). As a theoretical and analytical response, this paper puts forward a heuristic lens…
Descriptors: Artificial Intelligence, Technology Uses in Education, Heuristics, Problem Solving
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