Publications by Type: Conference Paper

FERNANDO MMPM, Jayasinghe JMUTD. Study of Fourier techniques and Wavelets for audio denoising, in SLAAS 76th Annual Session.Vol E1. 76th ed. SLAAS: SLAAS; 2020:71.
Samaraweera BGTN, Gunawardhana T. The Adaptability of Sustainable Construction Practices: An Analysis of Issues Faced by Sri Lankan Construction Industry, in International Conference on Real Estate Management and Valuation (ICREMV):2019.; 2019:140–157.
KCC.Silva, NGSS.Gamage, Weerasinghe DA. Crustal Structure Of Mannar Sub Basin - Sri Lanka Using 2D Gravity Modeling, in 6th International Conference on Multidisciplinary Approaches - 2019 ; ICMA.Vol 6. Sri Lanka: University of Sri Jayewardenepura; 2019:5-6.
Mannatunga KS, Ordóñez LGG, Amador MB, Crespo ML, Cicuttin A, Levorato S, Melo R, Valinoti B. Design for Portability of Reconfigurable Virtual Instrumentation, in 2019 X Southern Conference on Programmable Logic (SPL). IEEE; 2019:45–52.
Wickramaarachchi NC, Ariyawansa RG, WEERAKOON KGPK, Edirisingh J, Perera TGUP, Kaluthanthri PC, Gunawardhana T, Swarnapali SBY. The Impact of Road Rehabilitation Projects on Walkability, Road Safety and Local Business A Case Study in Old Kottawa-Pannipitiya Road of Colombo District, Sri Lanka, in International Conference on Real Estate Management and Valuation (ICREMV):2019.; 2019:175–184.
Bufon J, Altissimo M, Aquilanti G, Bellutti P, Bertuccio G, Billè F, Borghes R, Borghi G, Cautero G, Ciano S, et al. Large solid angle and high detection efficiency multi-element silicon drift detectors (SDD) for synchrotron based x-ray spectroscopy, in AIP Conference Proceedings.Vol 2054. AIP Publishing; 2019:060061.
DGND Jayarathna, GHJ Lanel ZAMSJ. MODELING OF AN OPTIMAL TRANSPORATATION SYSTEM (A CONTEMPORARY REVIEW STUDY ON VEHICLE ROUTING PROBLEMS), in 4th International Conference on Research and Modern Innovations in Engineering & Technology. ICRMIET –2019; 2019:4.
Public education versus private tutoring in Sri Lanka: who is contributing more?, in Peradeniya 7th International Research Symposium.Vol 2019. Department of Economics and Statistics, Faculty of Arts, University of Peradeniya, Sri Lanka; 2019:82-85.Abstract
Introduction Private tutoring which is also known as shadow education is globally expanding phenomenon (Byun et. al. 2018). Sri Lanka is no exception. “In Sri Lanka, supplementary private tutoring has long been a pervasive part of many students’ everyday experiences” (Bray 2003). Even though Sri Lankan government spent a big amount  of money per-student (Rs. 11,804  in 2015 and Rs.11,357 in 2016 on average, Ministry of Education), many Sri Lankan children start attending  private tutoring leading up to grade five scholarship examination (Cole 2017).  Among Sri Lankan students for private tutoring demand was very high since many years ago. In 1990, it was   estimated that 75 percent of students were attending private tuition classes. The proportion is 62 percent among G.C.E (A.L) arts students, 67 percent for G.C.E (A.L) commerce students and 92 percent among G.C.E (A.L) science students in the same year (De Silva 1994). Empirical literature on private tutoring  is growing. However, whether shadow education indeed matters to academic achievement is still unclear and needs further analyses (Byun 2014: 54;  Cole 2017).  On one hand, in Sri Lanka, the government always tries to provide education at its cost. On the other hand, people always claim for free education. In such a situation, private tutoring is escalating. As a result, household expenditure for private tutoring is also increasing. It seems that parents enroll their students in public schools and send them to learn in informal fee-paid out-of-school classes. As a result, parents have to spend much money on private tutoring. On this background, this study firstly assesses individual contribution of public schools and private tutoring classes to student academic performance, secondly ascertains the reasons for the increasing demand for private tutoring  and  finally estimates household expenditure for both public school education and private tutoring.  Objectives  The study assesses some selected aspects of public school education versus private tutoring for school level education. Therefore, the objectives of the study are: to determine the individual contribution of both public schools and private tutoring classes to students’ academic performance, to estimate per student expenditure borne by households for  private tutoring, and to ascertain reasons for demand for  private tutoring.  Methods and analytical tools  To achieve the objectives of the study, data regarding public schools, private tutoring classes, student performance and household are required. Student performance is available in Department of Examinations. However, for an in-depth analysis, the attendance of students and the extent of teaching (the coverage of subject matter) in public schools and private tuition classes, household expenditure borne for  private tutoring need to be gathered.  To gather these data, a sample of 100 students who sat for the G.C.E (O.L) examination in December 2017 and 300 students who completed their G.C.E. (A.L) examination in August 2017 were randomly selected so that sampled G.C.E (A.L) students represent four  subject streams i.e.  arts, science, technology  and  commerce.  All these sampled students were selected from among those who enrolled in public schools in Colombo district which represents the highest student population (23.3%) according to School Census 2016.  In addition, selected public sector officials of the Department of Education, principals of selected schools, the officials of private tuition classes and famous teachers who conduct private tuition classes were interviewed in order to collect preliminary data that were helpful to design the questionnaires.   In the case of input and output data, student performance is not separately available for public schools and private tutoring. It is available as an added variable of both sectors, and student participation can be estimated separately for both sectors. Considering this situation, the following simple linear model was estimated to determine the contribution of both public schools and private tutoring to student performance.  Yi is the ith student’s academic performance, X1i is the time period of the ith student spent in studying in his or her public school, X2i is the time of the ith student spent in studying in his or her tutoring class/classes, βi is the parameters to be estimated and Ui is the residual term. In addition to these models, descriptive statistics were used in estimating household expenditure for education.  Results and discussion  Out of all G.C.E (O.L) subjects studied in private  tuition classes by students, tuition fee is very high for French, Western Music,  English  Literature, Art, Dancing and IT. However, when compulsory subjects for the G.C.E (O.L) are  considered, tuition fee is the highest for mathematics and followed by science. Monthly tuition fee at G.C.E (O.L) for both mathematics and science are respectively greater than monthly  per student expenditure borne by government for students in public schools (Appendix 1). According to estimated values for quantity demanded from students in private tuition classes for each subject at G.C.E (O.L) it was found that both mathematics and sciences subjects are ranked highest. As such, higher class fee and higher demand for mathematics and science are consistent. In the case of G.C.E (A.L)  monthly tuition fee of all the subjects of all streams is greater than Rs. 1000 which is equal to the   monthly per-student expenditure borne by the government at present for public school education. Sampled public school students at both  G.C.E (O/L) and (A.L) were inquired of eleven reasons regarding their learning  in private tuition classes. Out of these reasons three were found as most influencing ones. According to the descending order of preference of students those reasons can be stated as “in the private tuition classes repetition of the subject matter  taught in the public schools and therefore tuition classes support them to understand academic matters easily, distribution of handouts and notes in the private tuition classes and adoption of better teaching methods in fee-paid out-of-school classes”. Based on the proposed model explained above, linear,  log linear and reciprocal regression  models were estimated respectively taking total marks obtained by each student for his/her G.C.E (O.L) subjects studied in his private tuition class and Z-score each student obtained for his/her G.C.E.(A.L) examination as dependent variables. Total number of hours spent studying  all the subjects in both private tuition class/es and  public schools separately included as independent variables. Parameters of tuition time in private classes are highly significant with the positive sign and  private tuition classes could be identified as  a significant contributor in determination  of  student performance at  both G.C.E (O.L) and (A.L) (Appendix 2). Conclusions and policy recommendations  The paper concludes that private tuition classes also contributes  the knowledge of students in public schools in Sri Lanka, parents of school children spend extensively on fee-paid out-of-school classes. Even though free education is still provided in Sri Lanka, parents pay much more money on education of their children. In the case of policy recommendations, in order to produce productive results through the market forces, rapidly escalating  private tutoring industry emphasizes requirement of  monitoring of the same by the government. Students attending private tuition classes understand that teaching quality is better in these classes than that in public schools.  This proposes public schools to look for more attractive teaching methods. Finally,  higher demand for informal fee-paid out-of-school education puts a big question mark in presence of free school education.  Keywords: Academic performance; Public schools; Shadow education.  References   Bray, Mark (2003). “Adverse Effects of Private Supplementary Tutoring: Dimensions, Implications and Government Responses”,  International Institute for Educational Planning, UNESCO. Byun, Soo-yong (2014). “Shadow Education and Academic Success in Republic of Korea”, in H. Park and K.-k. Kim (eds.), Korean Education in Changing Economic and Demographic Contexts, Education in the Asia-Pacific Region: Issues, Concerns and Prospects 23, Springer Science Business Media Dordrecht. Byun, S., Chung, H., & Baker, D. (2018). “Global patterns of the use of shadow education: Student, family, and national influences”, Research in the Sociology of Education, 20, 71-105. Cole, Rachel (2017). “Estimating the impact of private tutoring on academic performance: primary students in Sri Lanka”,  Education Economics, 25:2, 142-157. De Silva, W.A, (1994). “Extra-School Tutoring in the Asian Context: with special reference to Sri Lanka”, Department of Educational Research, National Institute of Education.  *********************************      Appendix 1 Average monthly tuition fee for private tutoring charged for each G.C.E (O/L) subject as explained by public school students who are attending private tuition classes (Rs.) No of Students Subject Average monthly Tuition fee (Rs.) 97 Science 971.65 99 Maths 1147.98 69 English 1049.28 63 Sinhala 915.87 38 History 869.74 45 Commerce 907.61 8 I.T 1262.50 3 Art 1833.33 3 Music 900.00 2 English Lit. 2500.00 3 Dancing 1266.67 1 W.Music 2500.00 1 Drama 600.00 1 French 3000.00 1 Home Sci. 600.00 1 Agriculture 500.00 435 Total No of Students Source: Field survey, 2019   Appendix 2 Regression Results   Dependent Var   Const Independent Variables R2 D.W Stat n Sum of Tuition hoursb Sum of School hoursc G.C.E (O/L) Total Marks (O/L)a 37.00 (1.79) 0.16 (8.62) 0.06 (4.05) 0.638 2.10 107 G.C.E (A/L) Z-score   1.25 (9.2) 0.000085 (1.79) 0.0000276 (1.76) 0.034 0.62 207 a-      Total marks obtained for all  subjects learned in the tuition class. b-      Total number of hours spent in the tuition class to study all subjects included as the dependent variable.. c-      Total number of hours spent in the public school to study subjects studied in the tuition class.              t-statistics with
FERNANDO MMPM, Perera WGK. A study of gravity anomalies over sedimentary basins of sea mounts of South-East and South-West near Sri Lanka, in SLAAS 75th Annual Session.Vol E1. 75th ed. SLAAS: SLAAS; 2019:93.Abstract
[[{"fid":"1420","view_mode":"default","type":"media","attributes":{"height":"781","width":"720","class":"media-element file-default"}}]]
Munasinghe LM, Gunawardhana T, Ariyawansa RG. Green Rating Systems for Built Environment and its Implications for Real Estate Valuation: A Review of Literature, in 2nd International Conference on Real Estate Management and Valuation (ICREMV).; 2018:120–124.
WRD De Silva GHJL. Study and Analysis of work-flow models using graph theory, in Symposium "Uni-In Alliance 2018" of B.Sc. (Honors) Degree in Applied Sciences. University of Sri Jayewardenepura; 2018.
Amarasekera HS. Upgrading wood based industries in Sri Lanka with special reference to Moratuwa furniture cluster, in South Asia Conference on Multidisciplinary Research SMAR 2018. Colombo, Sri Lanka : International Research and Development Institution TIRDI; 2018:2. Publisher's VersionAbstract
Upgrading Wood Based Industries in Sri Lanka with special reference to Moratuwa Furniture Cluster   H S Amarasekera Department of Forestry and Environmental Science, University of Sri Jayewardenepura, Sri Lanka   The wood-based industry is one of the oldest industries in the country that provides livelihood to many people in both rural and urban areas. However, the industry has been in a state of deterioration in terms of quality and competitiveness due to inadequate wood supply in term of quality and quantity, unfavorable business climate, scarcity of trained manpower, lack of market opportunities, research support and finances for investments to improve the industry. There are around 1700 industries in Moratuwa wood based furniture cluster and it has been in existence for many decades. This industry has deteriorated over the years and is currently incapable of producing furniture of high quality for the export market.  However large firms in the cluster use advanced technology and have a totally integrated production process with saw mills, timber seasoning and treatment facilities indicating that it is an organized cluster that can be upgraded to an innovative cluster by implementing a comprehensive development program. There have been several initiatives on development of wood working industry and timber utilization research on timber processing have yielded data towards upscaling and redefining the small timber manufactures in Sri Lanka.  The key options that can be adopted to improve the industry are to improve utilization of available sustainable timber resources to increase the supply of raw materials to the Moratuwa cluster, improve product quality, increase marketability of products and minimize environmental pollution. Selected industries in this cluster can be upgraded into international standards by introduction of new technology and transfer of knowledge, providing systematic training in improving furniture designing, timber preservation, seasoning and machine maintaining capabilities.   Achievement of productive wood products industry will make a significant contribution towards employment generation and increasing the percentage of contribution to GDP by Timber based products. Keywords – wood industry, furniture, forestry, timber, development plan
BMYUA Batugedara, GHJ Lanel BSLHWLCPC. An algorithm to find the distance between any two railway stations allowing modifications to the existing database, in International Conference on Computational Modeling and Simulation.; 2017.
GDDP Jayaweera, GHJ Lanel TS. Application of queuing theory to enhance the quality of the performance of a bank (ICCMS 060), in International Conference on Computational Modeling and Simulation. University of Colombo; 2017:180–184.
GDDP Jayaweera, GHJ Lanel TS. Application of queuing theory to enhance the quality of the performance of a bank, in International Conference on Computational Modeling and Simulation.; 2017.
Gamage MAMN, Dissanayake T CYKS. The association between Z score in advanced level examination and position in common merit list in a selected group of students, in Proceedings of the Scientific Sessions 2017, Faculty of Medical Science, University of Sri Jayewardenepura: p 99.; 2017.
Nayanthika IVK, Jayawardana DT. Development of a Laboratory Scale Filter Using Laterite to Treat Landfill Leachate, in Proceedings of International Forestry and Environment Symposium.Vol 21. USJP; 2017.
Wickrama Arachchi CM, Kuruppuarachchi D. Drivers of Innovation Performance of the Sri Lankan Software Development Industry, in 14th International Conference on Business Management (ICBM 2017).; 2017.
Thilakarathn GMN, I. L., Wanniarachchi WK. English Character Recognition of an Image and Voicing System, in APIIT Business, Law & Technology Conference, 2017. APIIT; 2017:136–140.
Madusanka RMTD, Jayawardana DT, Jayasinghe RMNPK. Fourier Transform Infrared (FTIR) Spectroscopic Analysis of Soil Organic Matter in an Alluvial Type Gem Deposit in Pelmadulla, Sri Lanka, in Proceedings of International Forestry and Environment Symposium.Vol 21. USJP; 2017.