دانلود رایگان مقاله انگلیسی ارزیابی عملکرد دانشجویان مبتنی بر اینترنت اشیا - تیلور و فرانسیس 2018

ABSTRACT

In recent years, solutions based on Internet of Things (IoT) are gaining impetus in educational institutions. It is observed that student performance evaluation system in education institutions is still manual. The performance score of student in traditional evaluation system is confined to its academic achievements while activity-based performance attributes are overlooked. Moreover, the traditional system fails to capitalise information of each student related to different activities in learning environment. In relation to this context, we propose to facilitate automated student performance evaluation system by exploring ubiquitous sensing capabilities of IoT. The system deduces important results about the performance of the students by discovering daily spatial–temporal patterns. These patterns are based on the data collected by the sensory nodes (objects) in the institution learning environment. The information is generated by applying data mining algorithms for each concerned activity. The automated decisions are taken by management authority for each student using game theory. In addition, to effectively manage IoT-based activity data, tensor-based storage mechanism is proposed. The experimental evaluation compares the student performance score generated by the proposed system with the manual student performance evaluation system. The results depict that the proposed system evaluates the performance of the student efficiently.

6. Conclusion

IoT can be used to create more significant learning spaces in education institutes. Based on this concept, we have proposed a system that focuses on student’s interaction with each other and surrounding objects which are virtually associated with an activity. Tensor is defined to store activity recording of each student for a particular day. Processed tensor is generated to compute studentactivity-based performance based on the educational data mining results. In the experiment section, results show evidence that IoT, applied as a tool to support the evaluation process, improves the student overall performance score. Moreover, taking students as a real object and associate them as a learning resource through Internet of Objects facilitates meaningful learning. Using this, one can link specific knowledge to a real context. Lastly, game-based decision making using parameters namely institution reputation score and student performance score enhances the utility of the proposed methodology. The road in front of Internet of Objects and their application in education is just a beginning. In future we can utilise IoT concept for student academic learning process.