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Showing 1 to 15 of 19 results Save | Export
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Baker, Ryan S.; Hawn, Aaron – International Journal of Artificial Intelligence in Education, 2022
In this paper, we review algorithmic bias in education, discussing the causes of that bias and reviewing the empirical literature on the specific ways that algorithmic bias is known to have manifested in education. While other recent work has reviewed mathematical definitions of fairness and expanded algorithmic approaches to reducing bias, our…
Descriptors: Mathematics, Bias, Education, Race
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Ayadi, Mohamed Issam; Maizate, Abderrahim; Ouzzif, Mohammed; Mahmoudi, Charif – International Journal of Web-Based Learning and Teaching Technologies, 2021
In this paper, the authors propose a novel forwarding strategy based on deep learning that can adaptively route interests/data packets through ethernet links without relying on the FIB table. The experiment was conducted as a proof of concept. They developed an approach and an algorithm that leverage existing intelligent forwarding approaches in…
Descriptors: Computer Networks, Artificial Intelligence, Mathematics, Models
Tamara Broderick; Andrew Gelman; Rachael Meager; Anna L. Smith; Tian Zheng – Grantee Submission, 2022
Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…
Descriptors: Taxonomy, Trust (Psychology), Algorithms, Probability
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Liu, Ruitao; Tan, Aixin – Journal of Educational Data Mining, 2020
In this paper, we describe our solution to predict student STEM career choices during the 2017 ASSISTments Datamining Competition. We built a machine learning system that automatically reformats the data set, generates new features and prunes redundant ones, and performs model and feature selection. We designed the system to automatically find a…
Descriptors: Career Choice, Prediction, Automation, Artificial Intelligence
Zhang, Weiwen – Online Submission, 2020
Recently Prof. Howard Gardner, an outstanding psychologist in the worldwide accepted the interview from Dr. Weiwen Zhang, and talked about a wide range of MI theory and relevant fields, which mainly involved in its core ideas, current situation and future development, and also involved its application in some current hot issues, which gave us…
Descriptors: Multiple Intelligences, Learning Theories, Misconceptions, Criticism
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Bogina, Veronika; Hartman, Alan; Kuflik, Tsvi; Shulner-Tal, Avital – International Journal of Artificial Intelligence in Education, 2022
This paper discusses educating stakeholders of algorithmic systems (systems that apply Artificial Intelligence/Machine learning algorithms) in the areas of algorithmic fairness, accountability, transparency and ethics (FATE). We begin by establishing the need for such education and identifying the intended consumers of educational materials on the…
Descriptors: Educational Technology, Computer Software, Artificial Intelligence, Stakeholders
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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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Luckin, Rosemary; Cukurova, Mutlu – British Journal of Educational Technology, 2019
Interdisciplinary research from the learning sciences has helped us understand a great deal about the way that humans learn, and as a result we now have an improved understanding about how best to teach and train people. This same body of research must now be used to better inform the development of Artificial Intelligence (AI) technologies for…
Descriptors: Instructional Design, Educational Technology, Artificial Intelligence, Mathematics
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Biehler, Rolf; Fleischer, Yannik – Teaching Statistics: An International Journal for Teachers, 2021
This paper reports on progress in the development of a teaching module on machine learning with decision trees for secondary-school students, in which students use survey data about media use to predict who plays online games frequently. This context is familiar to students and provides a link between school and everyday experience. In this…
Descriptors: Secondary School Students, Artificial Intelligence, Man Machine Systems, Educational Technology
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Lawrence Angrave; Jiaxi Li; Ninghan Zhong – Grantee Submission, 2022
To efficiently create books and other instructional content from videos and further improve accessibility of our course content we needed to solve the scene detection (SD) problem for engineering educational content. We present the pedagogical applications of extracting video images for the purposes of digital book generation and other shareable…
Descriptors: Instructional Materials, Material Development, Video Technology, Course Content
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Martínez-Ávila, Daniel – Education for Information, 2018
The paper intends to briefly present a view on current trends on our society, highlighting the technical aspects introduced by the big data phenomenon and the machine learning and artificial intelligence algorithms. It covers the threats that privacy and human rights can suffer by the general ignorance about this issues, and calls for a discussion…
Descriptors: Social Change, Trend Analysis, Mathematics, Information Security
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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
Delgado, M.; Fajardo, W.; Molina-Solana, M. – International Association for Development of the Information Society, 2013
In the last decades there have been several attempts to use computers in Music Education. New pedagogical trends encourage incorporating technology tools in the process of learning music. Between them, those systems based on Artificial Intelligence are the most promising ones, as they can derive new information from the inputs and visualize them…
Descriptors: Electronic Learning, Computer Software, Music Education, Music Activities
Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis – International Association for Development of the Information Society, 2013
In this paper, we present a way of teaching AI search algorithms in a web-based adaptive educational system. Teaching is based on interactive examples and exercises. Interactive examples, which use visualized animations to present AI search algorithms in a step-by-step way with explanations, are used to make learning more attractive. Practice…
Descriptors: Artificial Intelligence, Mathematics, Web Based Instruction, Intelligent Tutoring Systems
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Detterman, Douglas K. – Intelligence, 2011
Watson's Jeopardy victory raises the question of the similarity of artificial intelligence and human intelligence. Those of us who study human intelligence issue a challenge to the artificial intelligence community. We will construct a unique battery of tests for any computer that would provide an actual IQ score for the computer. This is the same…
Descriptors: Artificial Intelligence, Intelligence, Human Body, Comparative Analysis
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