Abstract
Education is a Nation’s strength. Association analysis of academic performance and its influential factors has remained research interest for all education researchers all over the world. India being an agriculture dominated country, for its development in agricultural front it requires ahuge numberof efficient technocrats having strong academic background. In this study an attempt has been made to examine the associationship of academic performance of the agriculture graduates, as measured through overall grade point average (OGPA) with the factors supposed to influence the academic performance. Special emphasis has been given to visualize the performance in presence of the influences of nominal factors. Students at masters level were surveyed for their social, economic, demographic and family and educational background through a designed questionnaire and tested accordingly. Statistical tools, starting from frequency, percentage, Chi-square test, test for normality, Cramer’s V test, multiple regression analysis with the inclusion of dummy variables were employed. Dependency of OGPA with gender, caste and expenditure on education is recorded. The dependency of educational expenditure on OGPA is quite obvious. But the dependency of OGPA with those of gender and caste is most probably not a good sign for a healthy higher education system. This study will help the education planners to take group oriented action plan for improving the education standard in higher education institutions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abdullahi HA, Mlozi MRS, Nzalayaimisi GK (2015) Determinants of students’ academic achievement in agricultural sciences: a case study of secondary schools in Katsina state, Nigeria. Afr Educ Res J 3(1):80–88
Bulala T, Ramatlala M, Nenty HJ (2014) Location as a factor in the prediction of performance in Botswana junior school certificate agriculture examinations by continuous assessment scores. Creat Educ 5(1):11–14
Cano J, Porter T (1997) The relationship between learning styles, academic major, and academic performance of agriculture students. In: Proceedings of the 24th annual national agricultural education research meeting, pp 373–380
Choudhury RG, Sinha KR (2015) Relationship between Personality traits, academic achievement and salary: an empirical study in a reputed B-school in Bangalore, India. J Res Method Edu 5(3):37–43
David ML, Martin FJ (1994) The effect of agricultural students’ learning styles on academic achievement and their perceptions of two methods of instruction. J Agric Educ 35(1):58–72
Garton BL, Dyer JE, King BO (2000) The use of leraning styles and admission criteria in predicting academic performance and retention of college fresmen. J Agric Educa 41(2):46–53
NDirika M, Njoku UJ (2012) Home influences on the academic performance of agricultural science students in Ikwuano local government area of Abia state, Nigeria. Res Educ 88(2):156–176
Ogweno PO, Nephat NK, Obara J (2014) Influence of students characteristics on academic performance in secondary agriculture, in Rachuonyo North Sub County, Kenya. Int J Educ Res 2(3):67–89
Olson D, Shi Y (2007) Introduction to business data mining. McGraw-Hill/Irwin, New York
Shi Y (2014) Big data: history, current status, and challenges going forward. Bridge 44(4):6–11
Shi Y, Tian YJ, Kou G, Peng Y, Li JP (2011) Optimization based data mining: theory and applications. Springer, Berlin
Suphamitmongkol W, Nie G, Liu R, Kasemsumranand S, Shi Y (2013) An alternative approach for the classification of orange varieties based on near infrared spectroscopy. Comput Electron Agric 91:87–93
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Singh, H., Das, A., Dey, S. et al. A Study on Academic Attainment of Agriculture Students and its Correlates: A Dummy Regression Approach. Ann. Data. Sci. 10, 129–152 (2023). https://doi.org/10.1007/s40745-020-00275-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40745-020-00275-z