JIMS8M: The Journal of Indian Management & Strategy
Web of Science
  • Year: 2013
  • Volume: 18
  • Issue: 1

Empirical analysis of teachers’ research involvement on quality of education and student motivation

  • Author:
  • Neelam Saraswat, Gaurav Bhargava
  • Total Page Count: 8
  • Page Number: 21 to 28

*Assistant Professor, IPEM, Ghaziabad, India

**Assistant Manager, Syndicate Bank, Ghaziabad, India

Online published on 19 March, 2013.

Abstract

Educational institutions have the responsibility to ensure that students who are passing undergraduate and postgraduate courses are highly skilled as per the job requirement of industry. Skill set of students are largely affected by activities of the teachers. To ensure that right inputs are given to students for their overall development, role of teacher cannot be undermined. Research activity is one of the important criterion which gives input for students development. Research based learning and participative learning is replacing the traditional mode of learning because of the increasing demand of high skill set. So it becomes imperative to understand the impact of research on student's motivation and quality learning. Purpose of this research paper is to identify the impact of teachers’ research involvement on student's motivation, learning and perception towards the quality of education imparted. This paper also aims at development of policy framework related to teacher's research involvement in educational institutions. This is an Exploratory Research which is based upon Primary Data Analysis. Total 350 students studying in under graduate and post graduate courses in different streams (science, arts, management, and commerce) from various Indian universities/colleges/institutions formed the sample elements. Students of 14 colleges, universities and institutions participated in the pilot testing of questionnaire. The questionnaire was reviewed by 20 teachers and policy makers before its distribution to the students. Data has been analyzed with the use of different statistical techniques/tools such as power and sample size analysis, Models for Binary and Categorical Outcomes to study Descriptive, Bivariate and Multivariate Statistics and Prediction for identifying groups using SPSS.