NotesFAQContact Us
Collection
Advanced
Search Tips
Showing 16 to 30 of 3,464 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Ryo, Masahiro; Jeschke, Jonathan M.; Rillig, Matthias C.; Heger, Tina – Research Synthesis Methods, 2020
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel…
Descriptors: Artificial Intelligence, Case Studies, Biology, Research Reports
Padilla, Thomas – OCLC Online Computer Library Center, Inc., 2019
Responsible Operations is intended to help chart library community engagement with data science, machine learning, and artificial intelligence (AI) and was developed in partnership with an advisory group and a landscape group comprised of more than 70 librarians and professionals from universities, libraries, museums, archives, and other…
Descriptors: Data Collection, Data Analysis, Artificial Intelligence, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Qin, Ying – International Journal of Computer-Assisted Language Learning and Teaching, 2019
This study extracts the comments from a large scale of Chinese EFL learners' translation corpus to study the taxonomy of translation errors. Two unsupervised machine learning approaches are used to obtain the computational evidences of translation error taxonomy. After manually revision, ten types of English to Chinese (E2C) and eight types…
Descriptors: Taxonomy, Translation, Computer Assisted Instruction, Second Language Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Kolog, Emmanuel Awuni; Devine, Samuel Nii Odoi; Ansong-Gyimah, Kwame; Agjei, Richard Osei – Education and Information Technologies, 2019
Learners' adaptation to academic trajectory is shaped by several influencing factors that ought to be considered while attempting to design an intervention towards improving academic performance. Emotion is one factor that influences students' academic orientation and performance. Tracking emotions in text by psychologists have long been a subject…
Descriptors: Psychological Patterns, Artificial Intelligence, Identification, Classification
Peer reviewed Peer reviewed
Direct linkDirect link
Ullmann, Thomas Daniel – International Journal of Artificial Intelligence in Education, 2019
Reflective writing is an important educational practice to train reflective thinking. Currently, researchers must manually analyze these writings, limiting practice and research because the analysis is time and resource consuming. This study evaluates whether machine learning can be used to automate this manual analysis. The study investigates…
Descriptors: Reflection, Writing (Composition), Writing Evaluation, Automation
Peer reviewed Peer reviewed
Direct linkDirect link
Sulmont, Elisabeth; Patitsas, Elizabeth; Cooperstock, Jeremy R. – ACM Transactions on Computing Education, 2019
Given its societal impacts and applications to numerous fields, machine learning (ML) is an important topic to understand for many students outside of computer science and statistics. However, machine-learning education research is nascent, and research on this subject for non-majors thus far has only focused on curricula and courseware. We…
Descriptors: Man Machine Systems, Artificial Intelligence, Nonmajors, College Faculty
Peer reviewed Peer reviewed
Direct linkDirect link
Saltz, Jeffrey; Skirpan, Michael; Fiesler, Casey; Gorelick, Micha; Yeh, Tom; Heckman, Robert; Dewar, Neil; Beard, Nathan – ACM Transactions on Computing Education, 2019
This article establishes and addresses opportunities for ethics integration into Machine-learning (ML) courses. Following a survey of the history of computing ethics and the current need for ethical consideration within ML, we consider the current state of ML ethics education via an exploratory analysis of course syllabi in computing programs. The…
Descriptors: Ethics, Interdisciplinary Approach, Course Descriptions, Computer Science Education
Peer reviewed Peer reviewed
Direct linkDirect link
Qazdar, Aimad; Er-Raha, Brahim; Cherkaoui, Chihab; Mammass, Driss – Education and Information Technologies, 2019
The use of machine learning with educational data mining (EDM) to predict learner performance has always been an important research area. Predicting academic results is one of the solutions that aims to monitor the progress of students and anticipates students at risk of failing the academic pathways. In this paper, we present a framework for…
Descriptors: Data Analysis, Academic Achievement, At Risk Students, High School Students
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Fomunyam, Kehdinga George – International Journal of Education and Practice, 2020
Machine learning technology is currently a new frontier for higher education globally, and the African higher education system needs to change in tandem with this technological trend in order to combat challenges faced by the system. These challenges include lack of institutional research to discover new knowledge, unfavorable methods of…
Descriptors: Foreign Countries, Electronic Learning, Higher Education, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Ezz, Mohamed; Elshenawy, Ayman – Education and Information Technologies, 2020
Some of the educational organizations have multi-education paths such as engineering and medicine collages. In such colleges, the behavior of the student in the preparatory year determines which education path the student will join in the future. In this paper, an adaptive recommendation system is proposed for predicting a suitable education…
Descriptors: Educational Technology, Artificial Intelligence, Computation, Mathematics
Peer reviewed Peer reviewed
Direct linkDirect link
Zhai, Xiaoming; Yin, Yue; Pellegrino, James W.; Haudek, Kevin C.; Shi, Lehong – Studies in Science Education, 2020
Machine learning (ML) is an emergent computerised technology that relies on algorithms built by 'learning' from training data rather than 'instruction', which holds great potential to revolutionise science assessment. This study systematically reviewed 49 articles regarding ML-based science assessment through a triangle framework with technical,…
Descriptors: Science Education, Computer Assisted Testing, Science Tests, Scoring
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Moreno-Estevaa, Enrique Garcia; White, Sonia L. J.; Wood, Joanne M.; Black, Alex A. – Frontline Learning Research, 2018
In this research, we aimed to investigate the visual-cognitive behaviours of a sample of 106 children in Year 3 (8.8 ± 0.3 years) while completing a mathematics bar-graph task. Eye movements were recorded while children completed the task and the patterns of eye movements were explored using machine learning approaches. Two different techniques of…
Descriptors: Artificial Intelligence, Man Machine Systems, Mathematics Education, Eye Movements
Peer reviewed Peer reviewed
Direct linkDirect link
Fu, Qiang; Guo, Xin; Land, Kenneth C. – Sociological Methods & Research, 2020
Count responses with grouping and right censoring have long been used in surveys to study a variety of behaviors, status, and attitudes. Yet grouping or right-censoring decisions of count responses still rely on arbitrary choices made by researchers. We develop a new method for evaluating grouping and right-censoring decisions of count responses…
Descriptors: Surveys, Artificial Intelligence, Evaluation Methods, Probability
Peer reviewed Peer reviewed
Direct linkDirect link
Rennie, Joseph P.; Zhang, Mengya; Hawkins, Erin; Bathelt, Joe; Astle, Duncan E. – Developmental Science, 2020
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self-organizing maps (SOMs)--a type of simple artificial neural network--to represent multivariate cognitive training data, and then tested whether the way tasks are…
Descriptors: Short Term Memory, Teaching Methods, Artificial Intelligence, Cognitive Development
Peer reviewed Peer reviewed
Direct linkDirect link
Martínez-Tenor, Ángel; Cruz-Martín, Ana; Fernández-Madrigal, Juan-Antonio – Interactive Learning Environments, 2019
Preparing students for dealing with a world more and more densely populated with physical machines that possess learning capabilities, e.g. intelligent robots, is of the utmost importance in engineering. In this paper, we describe and analyse a design of interactive sessions devoted to the application of some machine learning (ML) methods within a…
Descriptors: Teaching Methods, Robotics, Masters Programs, Reinforcement
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  ...  |  231