Predicting Instructors Performance in Higher Education Systems

Journal Title: EAI Endorsed Transactions on Energy Web - Year 2018, Vol 5, Issue 18

Abstract

In recent years, knowledge mining has become one of the effective tools for data analysis and information management systems. Educational sector is the recent research endeavors that make use of data mining algorithms. Prior works carried in data mining algorithms like J48 Decision Tree, Multilayer Perception, Naïve Bayes, and Sequential Minimal Optimization impose issues like the curse of dimensionality, cardinality and imbalance attributes. In this paper, we have proposed FA-Paired t-test method which is a novel knowledge discovery process to predict the performance of the instructors. The aim of the study is to find the factors that associated for the prediction of teaching quality. Thus, the contribution of the factor analysis method helps to find the relevant attributes from a set of attributes. Then, the selected attributes are fed as input to paired t-test model which find the associations between those linked attributes. The selected attributes are experimenting using SPSS modeler. Many attributes test for the performance evaluation. It is strongly found that content arrangement, delivery of speech, effective class hours and completion of the course helps to predict the quality of the teaching. In addition to, the proposed model is compared to prior two classifiers, named, J48DT and Naïve Bayes which shows our proposed method works better than other two classifiers in term of Attribute reduction and evaluation process.

Authors and Affiliations

Dr. K. Kalaiselvi, J. Sowmiya

Keywords

Related Articles

Exploration on Increasing Packet delivery rate in WSN using Cluster Approach

Wireless Sensor Network (WSN) plays a vital role and part of real time communication applications. Location of unknown node is difficult to find in the presence of mobile sensor nodes. Navigator plays an important role i...

Univariate Interpolation-based Modeling of Power and Performance

Performance and power scale non-linearly with device utilization, making characterization and prediction of energy efficiency at a given load level a challenging issue. A common approach to address this problem is the cr...

Simulation Modes Of Relay Protection Devices In Networks With Insulated Neutral

This program was developed as a universal model of typical devices for protecting electrical networks with insulated neutral. Imitation experiments are executed by the design of working operating and emergency modes. It...

Message Admission Control along with Buffer Space Advertisement to Control Congestion in Delay Tolerant Networks (DTNs)

Delay and Disruption Tolerant networks (DTN) are subject to intermittent connection and long delay, thus the internet congestion control mechanisms are not suitable for DTNs. Data Delivery Rate and Delivery Delay are the...

Classification of Vehicle Types in Car Parks using Computer Vision Techniques

The growing population of big cities has led to certain issues, such as overloaded car parks. Ubiquitous systems can help to increase the capacity through an efficient usage of existing parking slots. In this case, cars...

Download PDF file
  • EP ID EP45361
  • DOI http://dx.doi.org/10.4108/eai.12-6-2018.154811
  • Views 231
  • Downloads 0

How To Cite

Dr. K. Kalaiselvi, J. Sowmiya (2018). Predicting Instructors Performance in Higher Education Systems. EAI Endorsed Transactions on Energy Web, 5(18), -. https://europub.co.uk/articles/-A-45361