ERIC Number: EJ1406358
Record Type: Journal
Publication Date: 2024
Pages: 15
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0119-5646
EISSN: EISSN-2243-7908
Multi Objective Evaluation between Learning Behavior and Learning Achievement
Xiaona Xia; Tianjiao Wang
Asia-Pacific Education Researcher, v33 n1 p1-15 2024
The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the learning behavior and learning achievement based on the particle swarm optimization mechanism, which ensures the global optimization of data analysis. Compared with the performance indicators of several approximate algorithms, this algorithm has the advantage of association analysis, which improves the accuracy and robustness; Furthermore, three tested problems are constructed by GeoDa tool, and through data training and analysis, the dynamic multi-objective decision rules are obtained. The whole research can provide theoretical and technical support for other related or similar issues.
Descriptors: Learning, Behavior, Achievement, Learning Analytics, Data Analysis, Performance, Algorithms, Accuracy, Robustness (Statistics), Decision Making, Evaluation, Objectives, Prediction
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://bibliotheek.ehb.be:2123/
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A