Publication Date
In 2025 | 0 |
Since 2024 | 3 |
Since 2021 (last 5 years) | 11 |
Since 2016 (last 10 years) | 11 |
Since 2006 (last 20 years) | 11 |
Descriptor
Algorithms | 12 |
Comparative Analysis | 12 |
Prediction | 12 |
Models | 7 |
Learning Analytics | 6 |
Artificial Intelligence | 5 |
Classification | 4 |
Computer Software | 4 |
Correlation | 4 |
Learning Processes | 4 |
Scores | 4 |
More ▼ |
Source
Grantee Submission | 3 |
Interactive Learning… | 3 |
ProQuest LLC | 2 |
Education and Information… | 1 |
Information Processing and… | 1 |
Measurement:… | 1 |
Society for Research on… | 1 |
Author
Amisha Jindal | 3 |
Ashish Gurung | 3 |
Erin Ottmar | 3 |
Ji-Eun Lee | 3 |
Reilly Norum | 3 |
Sanika Nitin Patki | 3 |
Al Kurdi, Barween | 1 |
Al-Emran, Mostafa | 1 |
Alshurideh, Muhammad | 1 |
Arpaci, Ibrahim | 1 |
Ben-Michael, Eli | 1 |
More ▼ |
Publication Type
Reports - Research | 9 |
Journal Articles | 6 |
Dissertations/Theses -… | 2 |
Reports - Evaluative | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Higher Education | 3 |
Junior High Schools | 3 |
Middle Schools | 3 |
Postsecondary Education | 3 |
Secondary Education | 3 |
Early Childhood Education | 1 |
Elementary Education | 1 |
Grade 3 | 1 |
Primary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kye, Anna – ProQuest LLC, 2023
Every year, the national high school graduation rate is declining and impacting the number of students applying to colleges. Moreover, the majority of students are applying to more than one college. This makes a lot of colleges to be highly competitive in student recruitment for enrollment and thus, the necessity for institutions to anticipate…
Descriptors: Comparative Analysis, Classification, College Enrollment, Prediction
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
Ben-Michael, Eli; Feller, Avi; Rothstein, Jesse – Grantee Submission, 2021
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit in panel data settings. The "synthetic control" is a weighted average of control units that balances the treated unit's pre-treatment outcomes and other covariates as closely as possible. A critical feature of the original…
Descriptors: Evaluation Methods, Comparative Analysis, Regression (Statistics), Computation
Xia, Xiaona – Interactive Learning Environments, 2023
The interactive learning is a continuous process, which is full of a large number of learning interaction activities. The data generated between learners and learning interaction activities can reflect the online learning behaviors. Through the correlation analysis among learning interaction activities, this paper discusses the potential…
Descriptors: Behavior Patterns, Learning Analytics, Decision Making, Correlation
Alshurideh, Muhammad; Al Kurdi, Barween; Salloum, Said A.; Arpaci, Ibrahim; Al-Emran, Mostafa – Interactive Learning Environments, 2023
Despite the plethora of m-learning acceptance studies, few have tackled the importance of examining the actual use of m-learning systems from the lenses of social influence, expectation-confirmation, and satisfaction. Additionally, most of the prior technology adoption literature tends to use the structural equation modeling (SEM) technique in…
Descriptors: Electronic Learning, Prediction, Least Squares Statistics, Structural Equation Models
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Parhizkar, Amirmohammad; Tejeddin, Golnaz; Khatibi, Toktam – Education and Information Technologies, 2023
Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…
Descriptors: Algorithms, Grade Point Average, Interdisciplinary Approach, Prediction
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Tiffany Wu; Christina Weiland – Society for Research on Educational Effectiveness, 2024
Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…
Descriptors: Attendance, Early Childhood Education, Intervention, Artificial Intelligence
Jennifer Hu – ProQuest LLC, 2023
Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…
Descriptors: Linguistic Theory, Computational Linguistics, Models, Language Research
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games

Raita, Timo; Teuhola, Jukka – Information Processing and Management, 1989
Presents three text compression methods of increasing power and evaluates each based on the trade-off between compression gain and processing time. The advantages of using hash coding for speed and optimal arithmetic coding to successor information for compression gain are discussed. (26 references) (Author/CLB)
Descriptors: Algorithms, Comparative Analysis, Data Processing, Efficiency