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首页> 外文会议>International Technology, Education and Development Conference >(650) ON PERSONALISED LEARNING SCENARIOS EVALUATION MODEL
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(650) ON PERSONALISED LEARNING SCENARIOS EVALUATION MODEL

机译：（650）关于个性化学习场景评估模型

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The main aim of the paper is to present a model (i.e. a system of quality criteria) for evaluation of quality of personalised learning scenarios / units. Learning scenarios / units are referred here as methodological sequences of learning components (learning objects, activities, methods, technologies and tools). High-quality learning scenarios should consist of the learning components optimised to particular students according to their personal needs, e.g. learning styles. In the paper, optimised learning scenarios mean learning scenarios composed of the components having the highest probabilistic suitability indexes to particular students according to Felder-Silverman learning styles model. Personalised learning scenarios evaluation model presented in the paper is based on (1) wellknown principles of Multiple Criteria Decision Analysis (MCDA) for identifying the quality criteria: value relevance, understandability, measurability, non-redundancy, judgmental independence, balancing completeness and conciseness, operationality, simplicity versus complexity, and (2) Unified Theory on Acceptance and Use of Technology (UTAUT) model consisting of performance expectancy, effort expectancy, social influence, facilitating conditions, behavioural intention, and use behaviour constructs. Both MCDM principles and UTAUT constructs are presented in the paper in more detail. In the paper, presentation of the model for evaluating the quality of personalised learning scenarios is followed by discussion on applying different optimisation methods to evaluate the quality of personalised learning scenarios. The methodology of creating personalised learning scenarios evaluation model presented in the paper is absolutely new in scientific literature. This methodology is (1) applicable in the real life situations when teachers have to help their students to create and apply learning scenarios / units that are most suitable for their needs and thus to improve education quality and efficiency, (2) could significantly improve the quality of the expert evaluation of learning scenarios / units by noticeably reducing the expert evaluation subjectivity level.
机译：本文的主要目的是提供一种模型（即质量标准系统），用于评估个性化学习情景/单位的质量。学习场景/单位在此称为学习组件的方法序列（学习对象，活动，方法，技术和工具）。高质量的学习场景应根据他们的个人需求优化对特定学生的学习组件组成。学习方法。本文在根据Felder-Silverman学习风格模型的特定学生对特定学生具有最高的概率适用性指标的组件组成的优化学习情景。本文提出的个性化学习场景评估模型基于（1）多标准决策分析（MCDA）的众所周知的原则，用于识别质量标准：价值相关性，可辨，可衡量，非冗余，判断性独立性，平衡完整性和简洁，操作性，简单性与复杂性，（2）统一理论的接受和使用技术（UTAUT）模型组成的性能预期，努力期望，社会影响，促进条件，行为意图和使用行为构建。 MCDM原理和UTAUT构建体都更详细地介绍。在论文中，评估了用于评估个性化学习场景质量的模型的介绍是关于应用不同的优化方法来评估个性化学习场景的质量。创建论文中的个性化学习情景评估模型的方法论在科学文献中绝对是新的。这种方法是（1）适用于现实生活中，当教师帮助学生创建和应用最适合他们需求的学习情景/单位，从而提高教育质量和效率，（2）可以显着改善通过明显减少专家评估主观性水平，专家评估学习情景/单位的质量。

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