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Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
Johri, Aditya – Research in Learning Technology, 2022
There has been a conscious effort in the past decade to produce a more theoretical account of the use of technology for learning. At the same time, advances in artificial intelligence (AI) are being rapidly incorporated into learning technologies, significantly changing their affordances for teaching and learning. In this article I address the…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Affordances
Coenraad, Merijke – Information and Learning Sciences, 2022
Purpose: Computing technology is becoming ubiquitous within modern society and youth use technology regularly for school, entertainment and socializing. Yet, despite societal belief that computing technology is neutral, the technologies of today's society are rife with biases that harm and oppress populations that experience marginalization. While…
Descriptors: Preadolescents, Childrens Attitudes, Bias, Algorithms
Catherine Barbara Acitelli – ProQuest LLC, 2022
The field of Cryptography is rapidly evolving, and the development of quantum computers is on the rise. Lattice-based cryptosystems are promising candidates for quantum resistance, and it is the responsibility of institutions to prepare students for related careers. Undergraduate students in mathematics and mathematics-adjacent fields can -- and…
Descriptors: Undergraduate Study, Curriculum Design, Technology, Coding
Ilja Cornelisz; Chris van Klaveren – npj Science of Learning, 2022
Longitudinal randomized controlled trials generally assign individuals randomly to interventions at baseline and then evaluate how differential average treatment effects evolve over time. This study shows that longitudinal settings could benefit from "Recurrent Individual Treatment Assignment" ("RITA") instead, particularly in…
Descriptors: Longitudinal Studies, Randomized Controlled Trials, Intervention, Assignments
Scott Anthony Gigante – ProQuest LLC, 2021
In recent years, modern technologies have enabled the collection of exponentially larger quantities of data in the biomedical domain and elsewhere. In particular, the advent of single-cell genomics has allowed for the collection of datasets containing hundreds of thousands of cells measured in tens of thousands of dimensions. This rapid expansion…
Descriptors: Visualization, Data, Algorithms, Artificial Intelligence
Diego G. Campos; Tim Fütterer; Thomas Gfrörer; Rosa Lavelle-Hill; Kou Murayama; Lars König; Martin Hecht; Steffen Zitzmann; Ronny Scherer – Educational Psychology Review, 2024
Systematic reviews and meta-analyses are crucial for advancing research, yet they are time-consuming and resource-demanding. Although machine learning and natural language processing algorithms may reduce this time and these resources, their performance has not been tested in education and educational psychology, and there is a lack of clear…
Descriptors: Artificial Intelligence, Algorithms, Computer System Design, Natural Language Processing
Lishan Zhang; Linyu Deng; Sixv Zhang; Ling Chen – IEEE Transactions on Learning Technologies, 2024
With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…
Descriptors: Automation, Classification, Artificial Intelligence, Tutoring
Dyah Worowirastri Ekowati; Toto Nusantara; Makbul Muksar; Dwi Agus Sudjimat – Pegem Journal of Education and Instruction, 2024
In learning mathematics in the 21st century and after the COVID-19 pandemic, a multimodal role in the process of drawing conclusions involving mathematical symbols or signs is very much needed. This process is called multimodal semiotic reasoning. This research aims to study the literature on multimodal semiotic reasoning research articles. Until…
Descriptors: Semiotics, Mathematics Instruction, Mathematics Skills, Databases
Zoltán Kátai; Pálma-Rozália Osztián; David Iclanzan – Education and Information Technologies, 2024
Visual storytelling, particularly through dance choreographies as showcased in previous AlgoRythmics performances, has been effective in communicating relatively straightforward algorithms in an engaging and memorable way. Nevertheless, when addressing complex algorithmic concepts, an approach with greater expressiveness and flexibility becomes…
Descriptors: Algorithms, Story Telling, Methods Courses, Theater Arts
Monika Mladenovic; Žana Žanko; Goran Zaharija – Journal of Educational Computing Research, 2024
The use of a pedagogical approach mediated transfer with the bridging method has been successful in facilitating the transitions from block-based to text-based programming languages. Nevertheless, there is a lack of research addressing the impact of this transfer on programming misconceptions during the transition. The way programming concepts are…
Descriptors: Programming, Misconceptions, Teaching Methods, Computer Science Education
Yinying Wang – Discover Education, 2024
In this perspective article, I explore the implications of artificial intelligence (AI)-enabled algorithmic decisions on education governance. Three main questions are explored: (1) Are algorithmic decisions de facto policy decisions? (2) What distinct features of algorithmic decisions necessitate a re-evaluation of education governance? (3) How…
Descriptors: Algorithms, Decision Making, Artificial Intelligence, Educational Administration
Gulnur Tyulepberdinova; Madina Mansurova; Talshyn Sarsembayeva; Sulu Issabayeva; Darazha Issabayeva – Journal of Computer Assisted Learning, 2024
Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…
Descriptors: Artificial Intelligence, Algorithms, Predictor Variables, Physical Health
Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
Binbin Zhao; Rim Razzouk – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of…
Descriptors: Music Education, Higher Education, Teaching Methods, Matrices