Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 8 |
Since 2016 (last 10 years) | 10 |
Since 2006 (last 20 years) | 12 |
Descriptor
Artificial Intelligence | 13 |
Data Collection | 13 |
Decision Making | 13 |
Models | 6 |
Data Analysis | 5 |
Accuracy | 4 |
Automation | 4 |
Classification | 4 |
Information Technology | 4 |
Prediction | 4 |
Academic Achievement | 3 |
More ▼ |
Source
Author
Baker, Ryan S. | 1 |
Barnes, Tiffany | 1 |
Battou, Amal | 1 |
Bousnguar, Hassan | 1 |
Brandon Sepulvado | 1 |
Chen, Haohui | 1 |
Cody Gene Singer | 1 |
Croy, Marvin | 1 |
Evans, David | 1 |
Islam, A. H. M. Saiful | 1 |
Jennifer Hamilton | 1 |
More ▼ |
Publication Type
Journal Articles | 8 |
Reports - Research | 5 |
Reports - Descriptive | 3 |
Dissertations/Theses -… | 2 |
Collected Works - Proceedings | 1 |
Guides - General | 1 |
Reports - Evaluative | 1 |
Education Level
Higher Education | 5 |
Postsecondary Education | 5 |
Elementary Secondary Education | 2 |
Adult Education | 1 |
Audience
Location
Australia | 2 |
Germany | 2 |
Asia | 1 |
Brazil | 1 |
Connecticut | 1 |
Denmark | 1 |
Egypt | 1 |
Estonia | 1 |
Europe | 1 |
European Union | 1 |
Florida | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Educational Data Mining: An Application of a Predictive Model of Online Student Enrollment Decisions
Cody Gene Singer – ProQuest LLC, 2023
College and university enrollment has decreased nationwide every year for more than a decade as educational consumers increasingly question the value of higher education and discover alternatives to the traditional university system. Enrollment professionals seeking growth are tasked to develop and implement innovative solutions to address…
Descriptors: Data Collection, Predictor Variables, Electronic Learning, Enrollment
Bousnguar, Hassan; Najdi, Lotfi; Battou, Amal – Education and Information Technologies, 2022
Forecasting the enrollments of new students in bachelor's systems became an urgent desire in the majority of higher education institutions. It represents an important stage in the process of making strategic decisions for new course's accreditation and optimization of resources. To gain a deep view of the educational forecasting context, the most…
Descriptors: Higher Education, Undergraduate Students, Enrollment Management, Strategic Planning
Woolverton, Genevieve Alice; Pollastri, Alisha R. – Educational Measurement: Issues and Practice, 2021
Within classrooms, psychologists and teachers use direct behavior observation methods, systematic behavior observations (SBOs) and direct behavior ratings (DBRs), to gather information about students' behaviors for the purposes of making decisions related to diagnosis and classroom management or behavioral feedback respectively. Observers use SBOs…
Descriptors: Student Behavior, Classroom Observation Techniques, Behavior Rating Scales, Behavior Patterns
Brandon Sepulvado; Jennifer Hamilton – Society for Research on Educational Effectiveness, 2021
Background: Traditional survey efforts to gather outcome data at scale have significant limitations, including cost, time, and respondent burden. This pilot study explored new and innovative large-scale methods of collecting and validating data from publicly available sources. Taking advantage of emerging data science techniques, we leverage…
Descriptors: Automation, Data Collection, Data Analysis, Validity
William McHenry – Journal of Management Education, 2024
The prevalent paradigm for understanding what constitutes a 'good' data visualization, and what we are likely teaching business students, relates to a conventional wisdom of efficiency, clarity, transparency, and faithful representation of truth. Teaching about the ethics of visualizations seems to be largely absent from business school curricula.…
Descriptors: Ethics, Management Development, Business Administration Education, Visual Aids
Nahar, Khaledun; Shova, Boishakhe Islam; Ria, Tahmina; Rashid, Humayara Binte; Islam, A. H. M. Saiful – Education and Information Technologies, 2021
Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…
Descriptors: Learning Analytics, College Students, Engineering Education, Data Collection
Mason, Claire M.; Chen, Haohui; Evans, David; Walker, Gavin – International Journal of Information and Learning Technology, 2023
Purpose: This paper aims to demonstrate how skills taxonomies can be used in combination with machine learning to integrate diverse online datasets and reveal skills gaps. The purpose of this study is then to show how the skills gaps revealed by the integrated datasets can be used to achieve better labour market alignment, keep educational…
Descriptors: Taxonomy, Artificial Intelligence, Data Collection, Data Analysis
Pouliakas, Konstantinos, Ed. – Cedefop - European Centre for the Development of Vocational Training, 2021
The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate…
Descriptors: Job Skills, Information Technology, Artificial Intelligence, Employment Qualifications
Deep Learning Based Imbalanced Data Classification and Information Retrieval for Multimedia Big Data
Yan, Yilin – ProQuest LLC, 2018
The development in information science has enabled an explosive growth of data, which attracts more and more researchers to engage in the field of big data analytics. Noticeably, in many real-world applications, large amounts of data are imbalanced data since the events of interests occur infrequently. Classification of imbalanced data is an…
Descriptors: Information Science, Information Retrieval, Multimedia Materials, Data
Baker, Ryan S. – International Journal of Artificial Intelligence in Education, 2016
The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Hypothesis Testing, Data Collection
Stamper, John; Barnes, Tiffany; Croy, Marvin – International Journal of Artificial Intelligence in Education, 2011
The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to "seed" the hint generation…
Descriptors: Cues, Prompting, Learning Strategies, Teaching Methods
Streifer, Philip A.; Schumann, Jeffrey A. – Journal of Education for Students Placed at Risk, 2005
The implementation of No Child Left Behind (NCLB) presents important challenges for schools across the nation to identify problems that lead to poor performance. Yet schools must intervene with instructional programs that can make a difference and evaluate the effectiveness of such programs. New advances in artificial intelligence (AI) data-mining…
Descriptors: Federal Legislation, Accountability, Data Collection, Educational Change
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers