A Novel Frequent Pattern Mining Algorithm for Evaluating Applicability of a Mobile Learning Framework

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D.D.M. Dolawattha
D.D.M. Dolawattha
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H. K. Salinda Premadasa
H. K. Salinda Premadasa

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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.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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Not applicable for this article.

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): .

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Efficient mining pattern algorithm for evaluating mobile learning frameworks. Research on academic impact.
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-C Classification: (ACM): H.2.8, H.3.3
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v1.2

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October 28, 2023

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English

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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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A Novel Frequent Pattern Mining Algorithm for Evaluating Applicability of a Mobile Learning Framework

D.D.M. Dolawattha
D.D.M. Dolawattha
H. K. Salinda Premadasa
H. K. Salinda Premadasa

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