Publication Date
In 2025 | 3 |
Since 2024 | 94 |
Since 2021 (last 5 years) | 272 |
Since 2016 (last 10 years) | 357 |
Since 2006 (last 20 years) | 378 |
Descriptor
Artificial Intelligence | 388 |
Prediction | 388 |
Models | 147 |
Foreign Countries | 99 |
Accuracy | 80 |
Academic Achievement | 74 |
Classification | 74 |
Algorithms | 67 |
Data Analysis | 64 |
College Students | 53 |
Learning Analytics | 53 |
More ▼ |
Source
Author
Danielle S. McNamara | 6 |
Mihai Dascalu | 6 |
Baker, Ryan S. | 5 |
Xing, Wanli | 5 |
Gal, Kobi | 4 |
Li, Chenglu | 4 |
McNamara, Danielle S. | 4 |
Stefan Ruseti | 4 |
Barnes, Tiffany, Ed. | 3 |
Chen, Fu | 3 |
Cui, Ying | 3 |
More ▼ |
Publication Type
Education Level
Location
Turkey | 15 |
Australia | 10 |
Germany | 8 |
China | 7 |
South Korea | 7 |
Pakistan | 5 |
Brazil | 4 |
Canada | 4 |
Europe | 4 |
European Union | 4 |
India | 4 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kotlyar, Igor; Sharifi, Tina; Fiksenbaum, Lisa – International Journal of Artificial Intelligence in Education, 2023
Teamwork skills are commonly evaluated by human assessors, which can be logistically challenging and resource intensive. Technological advancements provide an opportunity for a new assessment method -- virtual behavioural simulations with self-scoring algorithms. This study explores whether a rule-based algorithm can match human assessors at…
Descriptors: Algorithms, Undergraduate Students, Computer Simulation, Evaluation
Wang, Yu-Yin; Wang, Yi-Shun – Interactive Learning Environments, 2022
While increasing productivity and economic growth, the application of artificial intelligence (AI) may ultimately require millions of people around the world to change careers or improve their skills. These disruptive effects contribute to the general public anxiety toward AI development. Despite the rising levels of AI anxiety (AIA) in recent…
Descriptors: Test Construction, Test Validity, Artificial Intelligence, Anxiety
Dragos-Georgian Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…
Descriptors: Computer Software, Artificial Intelligence, Learning Analytics, Natural Language Processing
Yoonjae Noh; YoonIl Yoon; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
The default risk, one of the main risk factors for bonds, should be measured and reflected in the bond yield. Particularly, in the case of financial companies that treat bonds as a major product, failure to properly identify and filter customers' workout status adversely affects returns. This study proposes a two-stage classification algorithm for…
Descriptors: Prediction, Classification, Accuracy, Risk
Houssam El Aouifi; Mohamed El Hajji; Youssef Es-Saady – Education and Information Technologies, 2024
Dropout refers to the phenomenon of students leaving school before completing their degree or program of study. Dropout is a major concern for educational institutions, as it affects not only the students themselves but also the institutions' reputation and funding. Dropout can occur for a variety of reasons, including academic, financial,…
Descriptors: At Risk Students, Potential Dropouts, Identification, Influences
Nesrine Mansouri; Mourad Abed; Makram Soui – Education and Information Technologies, 2024
Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…
Descriptors: Undergraduate Students, Decision Making, Majors (Students), Specialization
Sezer Kanbul; Idris Adamu; Yakubu Bala Mohammed – SAGE Open, 2024
This article presents a research investigation focusing on the effects of ChatGPT utilization on sustainable education and development. The study employed five machine learning (XGBoost, RF, SVM, GBDT, and ANN) models for predicting the impacts of ChatGPT usage in education, aiming at identifying the potential benefits of ChatGPT usage on…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Sustainable Development
Balqis Albreiki; Tetiana Habuza; Nishi Palakkal; Nazar Zaki – Education and Information Technologies, 2024
The nature of education has been transformed by technological advances and online learning platforms, providing educational institutions with more options than ever to thrive in a complex and competitive environment. However, they still face challenges such as academic underachievement, graduation delays, and student dropouts. Fortunately, by…
Descriptors: Multivariate Analysis, Graphs, Identification, At Risk Students
Hyemin Yoon; HyunJin Kim; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…
Descriptors: Classification, Artificial Intelligence, Prediction, Decision Making
Thomas Mgonja; Francisco Robles – Journal of College Student Retention: Research, Theory & Practice, 2024
Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…
Descriptors: Predictor Variables, Remedial Mathematics, Mathematics Achievement, Graduation Rate
Lincke, Alisa; Jansen, Marc; Milrad, Marcelo; Berge, Elias – Research and Practice in Technology Enhanced Learning, 2021
Web-based learning systems with adaptive capabilities to personalize content are becoming nowadays a trend in order to offer interactive learning materials to cope with a wide diversity of students attending online education. Learners' interaction and study practice (quizzing, reading, exams) can be analyzed in order to get some insights into the…
Descriptors: Artificial Intelligence, Prediction, Electronic Learning, Repetition
Kovalkov, Anastasia; Paaßen, Benjamin; Segal, Avi; Pinkwart, Niels; Gal, Kobi – IEEE Transactions on Learning Technologies, 2021
Promoting creativity is considered an important goal of education, but creativity is notoriously hard to measure. In this article, we make the journey from defining a formal measure of creativity, that is, efficiently computable to applying the measure in a practical domain. The measure is general and relies on core theoretical concepts in…
Descriptors: Creativity, Programming, Measurement Techniques, Models
Lwande, Charles; Oboko, Robert; Muchemi, Lawrence – Education and Information Technologies, 2021
Learning Management Systems (LMS) lack automated intelligent components that analyze data and classify learners in terms of their respective characteristics. Manual methods involving administering questionnaires related to a specific learning style model and cognitive psychometric tests have been used to identify such behavior. The problem with…
Descriptors: Integrated Learning Systems, Student Behavior, Prediction, Artificial Intelligence
Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
Imhof, Christof; Comsa, Ioan-Sorin; Hlosta, Martin; Parsaeifard, Behnam; Moser, Ivan; Bergamin, Per – IEEE Transactions on Learning Technologies, 2023
Procrastination, the irrational delay of tasks, is a common occurrence in online learning. Potential negative consequences include a higher risk of drop-outs, increased stress, and reduced mood. Due to the rise of learning management systems (LMS) and learning analytics (LA), indicators of such behavior can be detected, enabling predictions of…
Descriptors: Prediction, Time Management, Electronic Learning, Artificial Intelligence