Assuring Academic Integrity of Supervisor Appointment in Post-Graduate Program with Data-Driven Decision Making Strategy: A Proposal

Aziman Abdullah, Asar A.K.
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Abstract

Research supervision is one of the important aspect in academic quality assurance and the sustainbility of the science itself. However, there is lack of attention based on research literature and evidence of good practice on research supervision from the context of academic integrity in higher education. This study aims to develop a data-driven decision making strategy in supervisor selection for post-graduate program based using research projects data. Apart of that, the researchers reviewed the indicator of academic integrity in research supervisory from program standards in masters and doctoral degree by Malaysia Qualification Agency (MQA), international recommendation by UNESCO and Islamic principles according to the roles of the supervisor, administrator and student in the context of research supervisory. This study adopted data analytics and visualization technique using cloud-based collaborative platform as a research method for data acqusition, processing and analyzing the data. The researchers acquired the research projects profile data registered in the institutional database in Universiti Malaysia Pahang from Department of Research and Innovation as a case study. We categorized and mapped the research profile according to Malaysian Research and Development Classification System (MRDCS) code. The combined data was been analyzed and visualized to specific online dashboard to indicate the research experience in fraction of years as a metric. The researchers evaluate the characteristics of the dashboard based on the academic integrity indicators from MQA, UNESCO and Islamic principles as our measures. The result shows that there is a potential usefulness of the proposed strategy in assuring academic integrity for supervisor selection in post-graduate programmes. This novel approach has a potential impact on academic integrity in higher education which can be adopted at larger scale by higher education institution in Malaysia.
用数据驱动的决策策略确保研究生项目导师任命的学术诚信:一项建议
科研监督是保证学术质量和科学自身可持续性的重要方面之一。然而,从学术诚信的角度出发,缺乏研究文献的关注和良好实践的证据。本研究旨在以研究项目数据为基础,建立一套数据驱动的研究生导师选择决策策略。此外,研究人员根据导师、管理员和学生在研究监督中的角色,从马来西亚资格认证机构(MQA)的硕士和博士学位课程标准、联合国教科文组织的国际建议和伊斯兰原则等方面审查了研究监督中的学术诚信指标。本研究采用基于云协同平台的数据分析和可视化技术作为研究方法,对数据进行采集、处理和分析。研究人员从马来西亚彭亨大学研究与创新系的机构数据库中获取了注册的研究项目概况数据作为案例研究。我们根据马来西亚研究与开发分类系统(MRDCS)代码对研究概况进行分类和绘制。合并后的数据被分析并可视化到特定的在线仪表板上,以指示以年为单位的研究经验作为度量。研究人员基于MQA、UNESCO和伊斯兰教原则的学术诚信指标来评估仪表板的特征。结果表明,所提出的策略在确保研究生课程导师选择的学术诚信方面具有潜在的有用性。这种新颖的方法对高等教育的学术诚信有潜在的影响,可以在马来西亚的高等教育机构更大规模地采用。
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