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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
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
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
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
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
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
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
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
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
Kim, Keunjae; Kwon, Kyungbin; Ottenbreit-Leftwich, Anne; Bae, Haesol; Glazewski, Krista – Education and Information Technologies, 2023
This study aims to explore the middle schoolers' common naive conceptions of AI and the evolution of these conceptions during an AI summer camp. Data were collected from 14 middle school students (12 boys and 2 girls) from video observations and learning artifacts. The findings revealed 6 naive conceptions about AI concepts: (1) AI was the same as…
Descriptors: Middle School Students, Misconceptions, Artificial Intelligence, Summer Programs
Blaik-Hourani, Rida; Litz, David; Ali, Nagla; Azaza, Mohamed; Parkman, Scott – Educational Research for Policy and Practice, 2023
Emotional intelligence (EI) has been widely researched, but it has not been studied within the context of school leadership in Abu Dhabi. The present study aimed to explore EI in the praxis of school leaders and managers by applying Goleman's five EI dimensions--self-awareness, empathy, managing emotions, motivating oneself and others, and social…
Descriptors: Foreign Countries, Emotional Intelligence, Educational Improvement, Barriers
Buckingham Shum, Simon; Lim, Lisa-Angelique; Boud, David; Bearman, Margaret; Dawson, Phillip – International Journal of Educational Technology in Higher Education, 2023
Effective learning depends on effective feedback, which in turn requires a set of skills, dispositions and practices on the part of both students and teachers which have been termed "feedback literacy." A previously published teacher "feedback literacy competency framework" has identified what is needed by teachers to implement…
Descriptors: Automation, Feedback (Response), Learning Analytics, Artificial Intelligence
Hall, Michelle; Lees, Melinda; Serich, Cameron; Hunt, Richard – National Centre for Vocational Education Research (NCVER), 2023
This paper summarises exploratory analysis undertaken to evaluate the effectiveness of using machine learning approaches to calculate projected completion rates for vocational education and training (VET) programs, and compares this with the current approach used at the National Centre for Vocational Education Research (NCVER) -- Markov chains…
Descriptors: Vocational Education, Graduation Rate, Artificial Intelligence, Prediction
Butler, Brenda C. – ProQuest LLC, 2023
A large percentage of teachers in U. S. public schools are White. In contrast, most students in U. S. public schools are students of color. The racial imbalance results in a cultural mismatch creating a cultural gap between teachers and the students of color they are assigned to teach. Although teacher preparation programs produce teachers with…
Descriptors: Multicultural Education, Cultural Awareness, Intervention, Preservice Teachers
Nuangchalerm, Prasart; Prachagool, Veena – Online Submission, 2023
In recent years, the integration approach of Artificial Intelligence (AI) is called for many disciplines, it also STEM education has paved the way for transformative advancements. This paper provides an example of AI-driven learning analytics within the context of STEM education. It provides a thorough analysis of the AI-driven STEM curriculum and…
Descriptors: Artificial Intelligence, Learning Analytics, STEM Education, Technology Uses in Education

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