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Kovalkov, Anastasia; Paaßen, Benjamin; Segal, Avi; Pinkwart, Niels; Gal, Kobi – IEEE Transactions on Learning Technologies, 2021
Promoting creativity is considered an important goal of education, but creativity is notoriously hard to measure. In this article, we make the journey from defining a formal measure of creativity, that is, efficiently computable to applying the measure in a practical domain. The measure is general and relies on core theoretical concepts in…
Descriptors: Creativity, Programming, Measurement Techniques, Models
Webb, Mary E.; Fluck, Andrew; Magenheim, Johannes; Malyn-Smith, Joyce; Waters, Juliet; Deschênes, Michelle; Zagami, Jason – Educational Technology Research and Development, 2021
Machine learning systems are infiltrating our lives and are beginning to become important in our education systems. This article, developed from a synthesis and analysis of previous research, examines the implications of recent developments in machine learning for human learners and learning. In this article we first compare deep learning in…
Descriptors: Artificial Intelligence, Learning, Adjustment (to Environment), Accountability
Lwande, Charles; Oboko, Robert; Muchemi, Lawrence – Education and Information Technologies, 2021
Learning Management Systems (LMS) lack automated intelligent components that analyze data and classify learners in terms of their respective characteristics. Manual methods involving administering questionnaires related to a specific learning style model and cognitive psychometric tests have been used to identify such behavior. The problem with…
Descriptors: Integrated Learning Systems, Student Behavior, Prediction, Artificial Intelligence
Hamal, Oussama; El Faddouli, Nour-Eddine; Harouni, Moulay Hachem Alaoui – World Journal on Educational Technology: Current Issues, 2021
Nowadays, AI is a real springboard for finding solutions to optimize and improve learning and teaching processes. This issue has been a focus of humanity for millennia, and very significant advances have been made in this quest. This article aims to address the issue of optimizing and improving learning and teaching processes through AI…
Descriptors: Artificial Intelligence, Learning Analytics, Computer Uses in Education, Classification
Maia, Ana C. – New Directions for Student Leadership, 2021
Many college leadership educators use inventories as part of co-curricular programs, outside the traditional classroom. This article will describe and critique the use of four instruments (Myers-Briggs Type Indicator, CliftonStrengths, Emotionally Intelligent Leadership Inventory, and Earthquake[TM] Simulation) to support student development…
Descriptors: Leadership, Measures (Individuals), Personality Measures, Emotional Intelligence
Shi, Yang; Mao, Ye; Barnes, Tiffany; Chi, Min; Price, Thomas W. – International Educational Data Mining Society, 2021
Automatically detecting bugs in student program code is critical to enable formative feedback to help students pinpoint errors and resolve them. Deep learning models especially code2vec and ASTNN have shown great success for "large-scale" code classification. It is not clear, however, whether they can be effectively used for bug…
Descriptors: Artificial Intelligence, Program Effectiveness, Coding, Computer Science Education
Carlos R. Sepulveda-Torres – ProQuest LLC, 2021
In this study, it was investigated the intention of students to stay enrolled and student retention in undergraduate business management programs. The intention of students to stay enrolled and student retention are concerns for academic institutions. There is the need to direct resources to attract students and provide students with tools to…
Descriptors: Business Administration Education, Undergraduate Students, Emotional Intelligence, Intention
Paul Embleton – ProQuest LLC, 2021
The processes used in identifying/diagnosing specific learning disabilities (SLDs) vary across settings and classification systems. Moreover, the theoretically and mathematically derived identification models (i.e., discrepancy model) have thus far not demonstrated adequate reliability and validity. The present study explores the utility of…
Descriptors: Artificial Intelligence, Disability Identification, Clinical Diagnosis, Learning Disabilities
Jacquelyn Whiting – Knowledge Quest, 2021
When it comes to the spread of disinformation, society has lived through the perfect storm. The isolation of the pandemic and the depression induced by that isolation gave rise to a raw need for camaraderie and connection. Forced into digital spaces to work, teach, and learn, meant spending increasing amounts of time in those spaces hoping to be…
Descriptors: Information Literacy, Social Emotional Learning, Media Literacy, Interpersonal Competence
European University Association, 2023
Following the widespread concern and debate provoked by the arrival of ChatGPT and similar artificial intelligence (AI) tools, the European University Association's Learning and Teaching Steering Committee shares key considerations for European universities. Noting the current shortcomings and potential benefits of these technologies, this…
Descriptors: Educational Technology, Artificial Intelligence, Higher Education, Technology Integration
Echeverria, Vanessa; Yang, Kexin; Lawrence, LuEttaMae; Rummel, Nikol; Aleven, Vincent – IEEE Transactions on Learning Technologies, 2023
Combining individual and collaborative learning is common, but dynamic combinations (which happen as-the-need arises, rather than in preplanned ways, and may happen on an individual basis) are rare. This work reports findings from a technology probe study exploring alternative designs for classroom co-orchestration support for dynamically…
Descriptors: Man Machine Systems, Artificial Intelligence, Cooperative Learning, Educational Technology
Mohammadi Orangi, Behzad; Lenoir, Matthieu; Yaali, Rasoul; Ghorbanzadeh, Behrouz; O'Brien-Smith, Jade; Galle, Julie; De Meester, An – European Journal of Developmental Psychology, 2023
This study's purpose was to explore the relationship between emotional intelligence (EI) and motor competence (MC) in 540 children, adolescents, and young adults. Using the Schutte Self-Report Emotional Intelligence Scale (SSEIT), participants were divided in three groups of high, average, and low EI. The short form of Bruininks-Oseretsky Test for…
Descriptors: Emotional Intelligence, Psychomotor Skills, Children, Adolescents
Boutilier, Justin J.; Chan, Timothy C. Y. – INFORMS Transactions on Education, 2023
Artificial intelligence (AI) and operations research (OR) have long been intertwined because of their synergistic relationship. Given the increasing popularity of AI and machine learning in particular, we face growing demand for educational offerings in this area from our students. This paper describes two courses that introduce machine learning…
Descriptors: Artificial Intelligence, Operations Research, Undergraduate Students, Engineering Education
Emotional Intelligence Capabilities That Can Improve the Non-Technical Skills of Accounting Students
de Bruyn, M. – Accounting Education, 2023
The International Federation of Accountants (IFAC) requires its member professional accounting organisations and their authorised educators to adopt the overarching guidelines that are provided in the International Education Standards (IES). Despite these requirements, which include that accounting students develop several non-technical skills…
Descriptors: Emotional Intelligence, Capacity Building, Soft Skills, Accounting
Cox, Andrew; Cameron, David; Checco, Alessandro; Herrick, Tim; Mawson, Maria; Steadman-Jones, Richard – Higher Education Research and Development, 2023
AI and robots have the potential to transform Higher Education (HE) but pose many ethical and implementation challenges. To ensure the widest debate about our choices for the future of HE with these technologies, engaging ways to present the issues are needed and this article is part of an exploration of the potential of fictional narratives to do…
Descriptors: Artificial Intelligence, Robotics, Higher Education, Educational Research

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