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Individualized Learning Experience Framework: Teaching of Data Science to Non-Computer Science Students 个性化学习体验框架:对非计算机专业学生的数据科学教学
Pub Date : 2022-12-16 DOI: 10.33422/6th.rteconf.2022.12.20
Gholamreza Rafiee
Data science is a difficult subject to learn because it requires a wide range of prerequisite skills. This paper describes a data science teaching practice that has been running for over three years for students in two different non-computer science pathways including CIT (computing and information technology) and BIT (business information technology) at the school of Electronics, Electrical Engineering and Computer Science (EEECS) in Queen’s University Belfast (QUB). In this paper, a novel framework is proposed by which student learning experiences are personalized before the module begins in an academic year. By identifying each student’s requirements and skills to focus on using a multilevel assessment approach, individualized content recommendations for each student will be provided in the first week of teaching. This enables each learner to concentrate on essential customized learning content materials and self-directed learning. Some preliminary evidence for the efficacy of this framework in improving student learning experience is discussed.
数据科学是一门很难学习的学科,因为它需要广泛的先决技能。本文描述了在贝尔法斯特女王大学(QUB)电子、电气工程和计算机科学学院(EEECS)为两种不同的非计算机科学途径(包括CIT(计算和信息技术)和BIT(商业信息技术))的学生运行了三年多的数据科学教学实践。在本文中,提出了一个新的框架,通过该框架,学生的学习经验是个性化的,在一个学年的模块开始之前。通过确定每个学生的需求和技能,重点使用多层次评估方法,在教学的第一周为每个学生提供个性化的内容建议。这使每个学习者都能专注于基本的定制学习内容和自我指导学习。讨论了该框架在改善学生学习体验方面的有效性的一些初步证据。
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引用次数: 0
Problems Encountered in the Assessment of Architecture Design Studio 建筑设计工作室考核中遇到的问题
Pub Date : 2022-12-16 DOI: 10.33422/6th.rteconf.2022.12.10
Rahma M. Doheim
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引用次数: 0
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Proceedings of The 6th International Conference on Research in Teaching and Education
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