Chytas Konstantinos, Tsolakidis Anastasios, Triperina Evangelia, Karanikolas Nikitas N, Skourlas Christos
University of West Attica, Agiou Spiridonos 28, Egaleo 122 43, Greece.
Data Brief. 2023 Jul 2;49:109357. doi: 10.1016/j.dib.2023.109357. eCollection 2023 Aug.
The article describes the academic data, which derived from a University E-government analytic platform, which supports the facilitation of blended learning in a Greek University during and after the COVID19 outbreak [1,2]. University e-government services refer to a set of information systems that facilitate the functionalities of the University and enable the management of the underlying information [3,4]. These educational, research and managerial services, also called U-EGOV, follow the four stages of e-government (Presence, Interaction, Transaction, Transformation) [5]. In the presented approach, the data was aggregated from the university services with an automated process and includes all the individual U-EGOV services, that is the synchronous and asynchronous educational platforms, the teleconferencing tool, etc. The dataset created contains information about the courses, the assignments, the grades, the examinations, as well as other significant academic elements of the synchronous and the asynchronous education that takes place in the University. The analysis spans from the spring semester of the academic year 2019-2020, the winter semester of the academic year 2020-2021 to the spring semester of 2020-2021 (three semesters in total). The sample consists of 4800 records and after the preprocessing 4765 records (statistics of courses attended by students) which include 1661 unique students within the university in twenty (20) courses. We have followed an educational data mining approach on the collected data by utilizing an automated data aggregation mechanism to gather data for the selected courses, in order to enhance the learning process and the quality of services. The dataset can be reused: i) as a reference point to measure the quality of the academic outputs and its progress through the years and ii) as a basis for similar analysis in other Higher Educational Institutions (HEIs).
本文描述了源自某大学电子政务分析平台的学术数据，该平台在新冠疫情爆发期间及之后助力希腊一所大学开展混合式学习[1,2]。大学电子政务服务是指一组信息系统，可促进大学的各项功能并实现对基础信息的管理[3,4]。这些教育、研究和管理服务，也称为U-EGOV，遵循电子政务的四个阶段（存在、交互、交易、转型）[5]。在本文所介绍的方法中，数据通过自动化流程从大学服务中汇总而来，涵盖了所有单独的U-EGOV服务，即同步和异步教育平台、电话会议工具等。所创建的数据集包含有关课程、作业、成绩、考试以及大学中同步和异步教育的其他重要学术元素的信息。分析范围从2019 - 2020学年春季学期、2020 - 2021学年冬季学期到2020 - 2021学年春季学期（总共三个学期）。样本包含4800条记录，经过预处理后有4765条记录（学生参加课程的统计信息），其中包括该大学20门课程中的1661名不同学生。我们对收集到的数据采用了教育数据挖掘方法，利用自动化数据汇总机制收集所选课程的数据，以提升学习过程和服务质量。该数据集可重复使用：i）作为衡量多年来学术产出质量及其进展的参考点；ii）作为其他高等教育机构（HEIs）进行类似分析的基础。
