International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Blog/Latest News Contact Us
10th percentile
Powered by  Scopus
Scopus coverage:
Nov 2018 to May 2020


IJSTR >> Volume 9 - Issue 12, December 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

The Impact Of Smart Classrooms On The Academic Success Of Sri Lankan Government School Students

[Full Text]



Thivanka Mailewa, Piumika Chandrasiri, Dileepa Chandrasena, Sajeevkanth Kirubhakaran, Diluksan Jesudasan, Wasantha Rajapakshe, Akalanka Mailewa



Smart classroom, Comfortability, Availability, Adaptability, Personalization, Distance education, Remote learning



A smart classroom is regarded as one of the essential modes of teaching that can transform an old-fashioned educational system into a more cutting-edge method. Past articles and social opinion has identified that there is a doubt among the Sri Lankan general populace whether Smart classrooms are really useful for school students in this country. This study, therefore, has four objectives. They are to identify the determinants factors of a smart classroom, to evaluate the impact of a smart classroom on a school student’s academic success, to determine the relationship between the variables of the study and to provide practical suggestions to the government to improve the digital educational system. The study used a mixed approach to analyze both primary data and secondary data. A survey questionnaire was created and distributed among the students. Past research articles were used as a secondary data collecting methods for the analysis. The sample size for the study was 200 students from four government schools. The purposive sampling method was used for data collection. 250 questionnaires were distributed among the students and 200 usable responses were gathered. The study analyzed the data using multiple regression and Pearson correlation. The analytical tool was SPSS. Through the analysis, the researchers found that all the objectives were achieved and the hypotheses were supported. The significance of this study is that it is able to provide suggestions and recommendations to the relevant authorities regarding the implementation of Smart classrooms in primary and secondary schools.



(1)ALLEN, D. (1997) The hunger factor in student retention: An analysis of motivation. To The Educational Resources Information Center (ERIC), 9-92
(2) BOLUSTEVE, F. N., OYEYEMI, O. P. andAMALI, I. O. O. (2015) Internet Usage and Academic Performance of Undergraduate Students in University of Ilorin, Nigeria. Internet Usage and Ethiop. J. Educ. & Sc., 11 (1), 39-47
(3) COLLIE, R. J., MARTIN, A. J., PAPWORTH, B. andGINNS, P. (2016) Students’ interpersonal relationships, personal best (PB) goals, and academic engagement. Learning and Individual Differences, 45 65-76
(4) DOMINGO, M. andMARQUÈS, P. (2011) Classroom 2.0 Experiences and Building on the Use of ICT in Teaching. Scientific Journal of Media Literacy, 169-174
(5) GLADIEUX, L. E. andSWAIL, W. S. (1999) The virtual university & educational opportunity. issues of equity and access for the next generation. policy perspectives. Policy Perspectives, 1-36
(6) GUILLERMO, B. andBORGES, F. (2013) Smart Classrooms: Innovation in formal learning spaces to transform learning experiences. Bulletin of the Technical Committee on Learning Technology 1-3
(7) GUNN, C. (2003) Dominant or different? Gender issues in computer supported learning. Jaln, 7 (1), 14-30
(8) GUPTA, M. andSINGH, K. (2017) Effect of Smart Classroom Teaching On Achievement of Students: A Closer Focus on Gender and Intelligence. Imperial Journal of Interdisciplinary Research (IJIR), 3 (1), 1077-1086
(9) JOSHI, F. V. (2017) The effect of smart class on academic achievement. International Journal on Recent and Innovation Trends in Computing and Communication, 5 (7), 416 – 419
(10) MARTIN, A. J., NEJAD, H. G., COLMAR, S. andLIEM, G. A. D. (2013) Adaptability: How students’ responses to uncertainty and novelty predict their academic and non-academic outcomes. Journal of Educational Psychology, 105 (3), 728-746
(11) MARY, C. H. andKATHRYN, K. E. (2010) The Impact of Physical Classroom Environment on Student Satisfaction and Student Evaluation of Teaching in the University Environment Academy of Educational Leadership Journal, 14 (4), 65-79
(12) MORAHAN-MARTIN, J. (2005) Internet abuse addiction? disorder? symptom? alternative explanations? SocialScience Computer Review,, 23 (1), 39-48
(13) NISHANTHA, G. G. D., PISHVA, D. andYUKUO, H. (2008) Smart classrooms: Architectural requirements and deployment issues. IEEE Region 10 Colloquium and the Third ICIIS, Kharagpur, 1-6
(14) SCHACTER, J. andJO, B. (2017) Improving preschoolers’ mathematics achievement with tablets: a randomized controlled trial. Preschoolers’ mathematics achievement with tablets, 1 (1),
(15) TALEBA, Z. andHASSANZADEHB, F. (2014) Toward smart school: a comparison between smart school and traditional school for mathematics learning. Procedia - Social and Behavioral Sciences, 171 (1), 90 – 95
(16) THIYAGARAJAN, V., TAMIZHARASAN, T., SENTHILKUMAR, N. andKARTHIKEYAN, B. (2018) Enhancing human comfort and improving illuminance level in smart class room through optimization approach. Journal of Advanced Engineering Research, 5 (1), 20-30
(17) WATTERS, C. A., KEEFER, K. V., KLOOSTERMAN, P. H., SUMMERFELDT, L. J. andPARKER, J. D. A. (2013) Examining the Structure of the Internet Addiction Test in Adolescents: A Bifactor Approach. Computers in Human Behavior, 29 (6), 2294-2302
(18) YANG, U., PAN, H., ZHOU, W. andHUANG, R. (2018) Evaluation of Smart Classroom From the Perspective of Infusing Technology into Pedagogy. Smart Learning Environments, 5 (20), 2-11
(19) YUE, S., NAOKI, M., TORU, I. andYUANCHUN, S. (2008) Open smart classroom: extensible and scalable smart space using web service technology. Department of Computer Science and Technology, (3), 428-439