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Now showing 1 - 4 of 4
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    The Methodology of Using Active Learning Methods in Teaching Mathematical Analysis Courses to Students
    (2022) Abdullah Almas
    Relevance of the work: The demand for specialists in mathematics and natural sciences should be said that is growing all over the world. Many governments and private organizations have modernized STEM education to effectively meet this demand and promote teaching to improve students’ mathematical skills. Recently, a lot of academics and organizations have emphasized that for students to succeed beyond graduation, they must acquire 21st-century skills. According to the study, the most important STEM talents are those that require collaboration, problem-solving, imagination, entrepreneurship, adaptability, critical thinking, initiative, effective community, access to information, analysis, and curiosity.
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    Development of supervisorship system with tracking progress and the use of artificial intelligence
    (SDU University, 2024) Serek Azamat
    The Supervisorship service has been developed with the feature to match students to supervisors based on psychological perceptions through multidimensional analysis of matching algorithms and the feature to track students’ progress. This study explores the utilization of four distinct algorithms for the purpose of student-supervisor matching. A comprehensive evaluation of these algorithms is conducted, encompassing a variety of metrics including preference satisfaction, workload balance, time and space complexities, minimum and maximum workload, and compatibility scores which this work introduced.
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    Advisory system for adapting a single machine problem to a distributed solution
    (SDU University, 2024) Orynbekova Kamila
    General characteristics of the work. The work encompasses developing an advisory system to recommend solutions for single-machine problems adaptable to distributed systems, mainly focusing on implementation within the MapReduce platform. Methodologically, an experiment evaluated learning effectiveness, while extensive data collection informed model development. Predictive models, including Naive Bayes and Logistic Regression, were optimized and integrated into a recommendation system validated through rigorous evaluation. The aim of the research is to develop an advisory system that recommends single-machine problem solutions that adapt to distributed systems and are suitable for implementation on the MapReduce platform.
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    Research and Development of Intelligent Testing System based on Android Platform
    (Suleyman Demirel University, 2014) Bogdanchikov A.V.
    This thesis is devoted to developing advanced methods for intelligent testing system to test students’ knowledge and inspire prudent motivation to study. Set of methods are compared and stressed advantages and drawbacks of each, given different approaches in teaching students’ modern technologies. For some methods provided practical implementation on Android platform.