https://scipg.com/index.php/101/issue/feed International Journal of Educational Technology and Learning 2021-04-09T05:36:09+00:00 Open Journal Systems <p>The International Journal of Educational Technology and Learning (IJETL) is a peer-reviewed academic journal published by Scientific Publishing Institute.</p> https://scipg.com/index.php/101/article/view/396 ICT: Didactic Strategy using Online Simulators for the Teaching Learning of the Law of Conservation of Matter and its Relationship to Chemical Reactions in Higher Middle Education 2021-03-25T05:46:17+00:00 Yvonne Rodriguez Barocio obaya@unam.mx Adolfo Eduardo Obaya Valdivia obaya@unam.mx Yolanda M. Vargas-Rodriguez obaya@unam.mx <p>It is imperative that a profound transformation be carried out in the traditional way in which we teach science subjects, so it is necessary that the role of student change from being a mere recipient of information to being the main player in the construction of his knowledge. One of the strategies to achieve this is to make use of ICT, within which are educational simulators, as a support resource to facilitate the teaching-learning processes taught in the classroom. The didactic strategy developed in this work was carried out with the PhET (https://phet.colorado.edu) simulator was used to improve the learning teaching of the law of conservation of the subject matter and its relationship with chemical reactions. To evaluate the learnings acquired by students, the Hake factor was determined. In terms of the implementation of this didactic strategy, students demonstrated greater recognition, understanding and appropriation of the knowledge gained about the importance of this law in chemical reactions. This teaching strategy is useful for higher middle-level schools that do not have a school science lab.</p> 2021-03-25T00:00:00+00:00 ##submission.copyrightStatement## https://scipg.com/index.php/101/article/view/400 Development of Personalized Learning Resources Recommendation System Based on Knowledge Graph 2021-04-09T05:36:09+00:00 XU Xiaoli 158656163@qq.com HUANG Hui 158656163@qq.com WU Mengmeng 158656163@qq.com LIAO Yu 158656163@qq.com YUAN Ziheng 158656163@qq.com WNAG Yingfeng 158656163@qq.com <p>This study focuses on how to efficiently and accurately recommend personalized learning resources for users when they are in the face of massive learning resources. A recommendation system is developed with software engineering methods. Knowledge graph technology is integrated in the system; curriculum knowledge graphs are constructed to solve the problems of semi-structured data storage and knowledge fragmentation. Two kinds of recommendation methods are adopted to achieve the goal of learners' personalized learning, one is Euclidean distance recommendation algorithm based on user behavior graph library, the other is learning mode recommendation algorithm and sequential mode recommendation algorithm based on user session library. The recommendation system maintains the interpret-ability and the accuracy of recommendation based on user historical behavior data; and realizes recommendation based on user session library in the context of lacking users’ historical data.</p> 2021-04-09T00:00:00+00:00 ##submission.copyrightStatement##