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Oscar Karnalim; Hapnes Toba; Meliana Christianti Johan – Education and Information Technologies, 2024
Artificial Intelligence (AI) can foster education but can also be misused to breach academic integrity. Large language models like ChatGPT are able to generate solutions for individual assessments that are expected to be completed independently. There are a number of automated detectors for AI assisted work. However, most of them are not dedicated…
Descriptors: Artificial Intelligence, Academic Achievement, Integrity, Introductory Courses
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Mark Johnson; Rafiq Saleh – Interactive Learning Environments, 2024
Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…
Descriptors: Artificial Intelligence, Evaluation Methods, Technology Uses in Education, Man Machine Systems
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Urtasun, Ainhoa – Industry and Higher Education, 2023
This report describes a teaching experience with undergraduates to approach, in a simple and practical way, artificial intelligence (AI) and machine learning (ML) -- general-purpose technologies that are highly demanded in any industry today. The article shows how business undergraduates with no prior experience in coding can use AI and ML to…
Descriptors: Undergraduate Students, Student Empowerment, Artificial Intelligence, Business Education
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Anita Pásztor-Kovács; Attila Pásztor; Gyöngyvér Molnár – Interactive Learning Environments, 2023
In this paper, we present an agenda for the research directions we recommend in addressing the issues of realizing and evaluating communication in CPS instruments. We outline our ideas on potential ways to improve: (1) generalizability in Human-Human assessment tools and ecological validity in Human-Agent ones; (2) flexible and convenient use of…
Descriptors: Cooperation, Problem Solving, Evaluation Methods, Teamwork
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Martinez, Aleix M. – Developmental Psychology, 2019
Computer vision algorithms have made tremendous advances in recent years. We now have algorithms that can detect and recognize objects, faces, and even facial actions in still images and video sequences. This is wonderful news for researchers that need to code facial articulations in large data sets of images and videos, because this task is time…
Descriptors: Automation, Coding, Nonverbal Communication, Children
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Nina Spada – Language Learning & Language Teaching, 2024
This volume presents the second edition of the "Communicative Orientation of Language Teaching (COLT) Observation Scheme." Since the book's original publication, COLT has become well established as a research instrument in L2 teaching and learning. This new edition brings COLT into the 21st century by introducing digital versions of the…
Descriptors: Second Language Learning, Second Language Instruction, Web Based Instruction, Teaching Methods
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Renzulli, Joseph S. – International Journal for Talent Development and Creativity, 2020
In this article, I describe a series of Five Core Competencies that gifted education specialists should consider integrating into their teaching to respond to the many changes that are taking place in technology, work, and career preparation. Although the focus of this theory is on high- level jobs usually pursued by college graduates and advanced…
Descriptors: Academically Gifted, Gifted Education, Job Skills, Theories
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Tsai, Jinn-Tsong; Chou, Ping-Yi; Fang, Jia-Cen – IEEE Transactions on Education, 2012
An intelligent genetic algorithm (IGA) is proposed to solve Japanese nonograms and is used as a method in a university course to learn evolutionary algorithms. The IGA combines the global exploration capabilities of a canonical genetic algorithm (CGA) with effective condensed encoding, improved fitness function, and modified crossover and…
Descriptors: Puzzles, Artificial Intelligence, Mathematics, Computer Science Education
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Tierney, Patrick J. – International Review of Research in Open and Distance Learning, 2012
This paper introduces a method of extending natural language-based processing of qualitative data analysis with the use of a very quantitative tool--graph theory. It is not an attempt to convert qualitative research to a positivist approach with a mathematical black box, nor is it a "graphical solution". Rather, it is a method to help qualitative…
Descriptors: Natural Language Processing, Qualitative Research, Data Analysis, Graphs