Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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The applicability of a mobile learning system reflects how it works in an actual situation under diverse conditions. In previous studies, researches for evaluating applicability in learning systems using data mining approaches are challenging to find. The main objective of this study is to evaluate the applicability of the proposed mobile learning framework. This framework consists of seven independent variables and their influencing factors. Initially, 1000 students and teachers were allowed to use the mobile learning system developed based on the proposed mobile learning framework. The authors implemented the system using Moodle mobile learning environment and used its transaction log file for evaluation. Transactional records that were generated due to various user activities with the facilities integrated into the system were extracted. These activities were classified under eight different features, i.e., chat, forum, quiz, assignment, book, video, game, and app usage in thousand transactional rows.
D.D.M. Dolawattha. 2026. \u201cA Novel Frequent Pattern Mining Algorithm for Evaluating Applicability of a Mobile Learning Framework\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 23 (GJCST Volume 23 Issue C2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 102
Country: Sri Lanka
Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering
Authors: D.D.M. Dolawattha, H. K. Salinda Premadasa (PhD/Dr. count: 0)
View Count (all-time): 258
Total Views (Real + Logic): 2074
Total Downloads (simulated): 35
Publish Date: 2026 01, Fri
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Neural Networks and Rules-based Systems used to Find Rational and
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The applicability of a mobile learning system reflects how it works in an actual situation under diverse conditions. In previous studies, researches for evaluating applicability in learning systems using data mining approaches are challenging to find. The main objective of this study is to evaluate the applicability of the proposed mobile learning framework. This framework consists of seven independent variables and their influencing factors. Initially, 1000 students and teachers were allowed to use the mobile learning system developed based on the proposed mobile learning framework. The authors implemented the system using Moodle mobile learning environment and used its transaction log file for evaluation. Transactional records that were generated due to various user activities with the facilities integrated into the system were extracted. These activities were classified under eight different features, i.e., chat, forum, quiz, assignment, book, video, game, and app usage in thousand transactional rows.
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