NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 23 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Lukas Höper; Carsten Schulte – Informatics in Education, 2024
In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life…
Descriptors: Student Empowerment, Data Use, Computer Science Education, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Jiang, Shiyan; Tang, Hengtao; Tatar, Cansu; Rosé, Carolyn P.; Chao, Jie – Learning, Media and Technology, 2023
It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…
Descriptors: Artificial Intelligence, High School Students, Models, Classification
Peer reviewed Peer reviewed
Direct linkDirect link
Bader Muteb Alsulami; Abdullah Baihan; Ahed Abugabah – Cogent Education, 2024
The COVID-19 pandemic precipitated an abrupt transition to online learning, impacting students with disabilities uniquely. This study examines the experiences of 62 such students in the new educational paradigm, employing a mixed-methods approach. Quantitative data were collected through surveys and questionnaires to assess privacy and security…
Descriptors: Students with Disabilities, Inclusion, Artificial Intelligence, Computer Security
Peer reviewed Peer reviewed
Direct linkDirect link
Nadia Ahmad; Hirok Chakraborty; Ratnesh Sinha – Cogent Education, 2024
Background: Artificial Intelligence (AI) has immense potential varying from diagnosing, decision-making in-patient care, and education. To successfully integrate AI into medicine and medical education, it is important to know the outlook and willingness of medical students. This study was done to learn about the medical students opinions about it…
Descriptors: Medical Students, Student Attitudes, Artificial Intelligence, Medical Education
Yim Register – ProQuest LLC, 2024
The field of Data Science has seen rapid growth over the past two decades, with a high demand for people with skills in data analytics, programming, statistics, and ability to visualize, predict from, and otherwise make sense of data. Alongside the rise of various artificial intelligence (AI) and machine learning (ML) applications, we have also…
Descriptors: Artificial Intelligence, Ethics, Algorithms, Data Science
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Yueqiao Jin; Vanessa Echeverria; Lixiang Yan; Linxuan Zhao; Riordan Alfredo; Yi-Shan Tsai; Dragan Gasevic; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across…
Descriptors: Learning Analytics, Accountability, Ethics, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Chanaa, Abdessamad; El Faddouli, Nour-eddine – International Journal of Information and Communication Technology Education, 2022
Massive open online courses (MOOCs) have evolved rapidly in recent years due to their open and massive nature. However, MOOCs suffer from a high dropout rate, since learners struggle to stay cognitively and emotionally engaged. Learner feedback is an excellent way to understand learner behaviour and model early decision making. In the presented…
Descriptors: MOOCs, Student Attitudes, Data Analysis, Electronic Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Azzah Al-Maskari; Thuraya Al Riyami; Sami Ghnimi – Journal of Applied Research in Higher Education, 2024
Purpose: Knowing the students' readiness for the fourth industrial revolution (4IR) is essential to producing competent, knowledgeable and skilled graduates who can contribute to the skilled workforce in the country. This will assist the Higher Education Institutions (HEIs) to ensure that their graduates own skill sets needed to work in the 4IR…
Descriptors: Career Readiness, Technological Literacy, Student Attitudes, Information Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Baragash, Reem Sulaiman; Aldowah, Hanan; Umar, Irfan Naufal – Journal of Information Technology Education: Research, 2022
Aim/Purpose: To gain insight into the opinions and reviews of Malaysian university students regarding e-learning systems, thereby improving the quality and services of these systems and resolving any problems, concerns, and issues that may exist within the institution. Background: This exploratory study examines the students' perceptions of…
Descriptors: College Students, Student Attitudes, Electronic Learning, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Xu Li; Wee Hoe Tan; Yu Bin; Peng Yang; Qiancheng Yang; Taukim Xu – Education and Information Technologies, 2025
Globally, physical education curricula are progressively integrating intelligent physical education systems, a breakthrough in physical technology. These systems utilise advanced data analytic and sensing technologies, significantly enhancing the interactivity and personalisation of physical activity, thus improving students' athletic performance…
Descriptors: Undergraduate Students, Intelligent Tutoring Systems, Physical Education, Curriculum
Peer reviewed Peer reviewed
Direct linkDirect link
Amanda Barany; Andi Danielle Scarola; Alex Acquah; Sayed Mohsin Reza; Michael A. Johnson; Justice Walker – Information and Learning Sciences, 2024
Purpose: There is a need for precollege learning designs that empower youth to be epistemic agents in contexts that intersect burgeoning areas of computing, big data and social media. The purpose of this study is to explore how "sandbox" or open-inquiry data science with social media supports learning. Design/methodology/approach: This…
Descriptors: Student Empowerment, Data Science, Social Media, Open Education
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Osmanoglu, Usame Omer; Atak, Osman Nuri; Caglar, Kerim; Kayhan, Hüseyin; Can, Talat Cemre – Journal of Educational Technology and Online Learning, 2020
Nowadays many companies and institutions are interested in learning what do people think and want. Many studies are conducted to answer these questions. That's why, emotions of people are significant in terms of instructional design. However, processing and analysis of many people's ideas and emotions is a challenging task. That is where the…
Descriptors: Data Analysis, Student Attitudes, Distance Education, Instructional Materials
Peer reviewed Peer reviewed
Direct linkDirect link
Santiago Berrezueta Ed. – Lecture Notes in Educational Technology, 2023
The proceedings of the 18th edition of Latin American Conference on Learning Technologies (LACLO) demonstrates the developments in the research of learning science, learning resources, challenges and solutions. This Proceedings book showcases a collection of quality articles that explores and discusses trending topics in education in the upcoming…
Descriptors: Educational Technology, Active Learning, Design, Telecommunications
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Maruyama, Yukiko – International Association for Development of the Information Society, 2019
This paper presents the results of an attempt to analyze the benefits and risks of information and communication technologies (ICTs) and their applications, as perceived by university students. A survey was conducted using questionnaire with a free descriptive answering format. Responses were analyzed via text mining and correspondence analysis;…
Descriptors: Risk, Computer Software, College Students, Student Attitudes
Peer reviewed Peer reviewed
Direct linkDirect link
Taçgin, Zeynep; Arslan, Ahmet – Education and Information Technologies, 2017
The purpose of this study is to determine perception of postgraduate Computer Education and Instructional Technologies (CEIT) students regarding the concepts of Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), Augmented Virtuality (AV) and Mirror Reality; and to offer a table that includes differences and similarities between…
Descriptors: Graduate Students, Student Attitudes, Computer Science Education, Educational Technology
Previous Page | Next Page »
Pages: 1  |  2