Karma al hassan education system quality indicators

Education System Quality Indicators Paper Presented to School-based Reform in Arab Countries Project at AUB (TAMAM) Sponsored by Arab Thought Foundation Karma El Hassan, PhD Associate Professor Director Office of Institutional research & Assessment (OIRA) AUB Table of Contents Page I Introduction II Education reform in last two decades III Education quality Definition Conceptual framework a Basic framework b UNESCO framework 4 6 IV Indicators and indicator sets at system level Indicators Indicator sets at system level a OECD b European Commission c UNESCO d World bank 9 10 12 14 15 V Conclusion and future directions 16 References 19 Appendix: Samples of international indicator sets 21 Education System Quality Indicators I Introduction Education systems in the world are vast organizations that are very complex to manage They emerge over time and their formation and maintenance reflect differing historical traditions, cultural values and religious interests as well as divergent views about the role of the state in shaping the life-chances of its future citizens (Hoffman, Hoffman, Gray, & Daly, 2004.) The quest for higher performance through educational reform has been a worldwide phenomenon, especially over the last decade, and accordingly, the world witnessed a trend towards restructuring education systems Most countries experienced a change in relationships between different levels of the system, or changes in the role of the state, or changed methods and models of managing the education system (Wallin, 1995) The following section will outline the major factors that have dominated the education reform movement in the last two decades II Education Reform in Last Two Decades In recent years, political and educational discussions have increasingly raised questions about the quality of education This interest had its origins in a) emergence of a widely held belief that education systems and their relative cross-national performance were a key element in strategies designed to achieve improvement in national economic development in an increasingly globalized and competitive world, and b) public concerns that governmental expenditures were enormous and they needed to be accompanied by higher levels of scrutiny and accountability concerning the quality of education, especially as education budgets are under pressure (Ross & Genevois, 2006) Reforms that have dominated the education scene in the 1980s, 1990s, and into the 2000s and major forums organized by international agencies also turned their attention towards issues related to the quality of education and the need for assessment The 1990 Jomtien World Conference on Education and 2000 Dakar World Education Forum both called for a broader view of education beyond a concentration on increased access These declarations emphasized that in addition to increased participation in education, all nations need to „improve all aspects of the quality of education and ensure excellence so that recognized and measurable leaning outcomes are achieved by all‟ Assessment information may be used to reach a judgment about the adequacy of the performance of an education system or of a part of it Accordingly, there has been increased government interest in monitoring and evaluating the quality of education Governments needed objective data to provide evidence through which student learning achievement may be monitored both nationally and internationally They needed to monitor student performance over time and in a cross national comparative perspective, in order to provide information for assessing how well or how badly education systems are preparing young people for future adult roles as creative, thinking citizens who can sustain themselves and contribute to well being of their societies (Pigazzi, 2006) The availability of objective data, not only for the monitoring and planning of the education system, but also for use in public debates, was seen as a necessity by policy-makers A culture of evaluation was being formed (European Training Foundation, 2003) Towards the end of the 1990s and into the new millennium, the increased levels of national and international dialogue about the importance of the „quality of education‟ resulted in decisions by many countries to implement programs for national assessment of educational progress, and to participate in networks that conducted large-scale cross-national educational research studies (Pelgrum, Voogt, & Plomp, 1995) Educators believed that research on the quality of education required an international focus because variations among countries in terms of educational policies, practices, and traditions provided a natural laboratory for the study of those aspects of educational environment that were likely to have a substantial and consistent impact upon improved student learning They also argued that crossnational studies of the quality of education offered much more than national studies because „custom and law define what is educationally allowable within a nation, whereas the educational systems beyond one‟s national borders suggest what is educationally possible (Foshay et al, 1962, as cited in Ross & Genevois, 2006) The increasing awareness of the usefulness of these monitoring systems has resulted in a need for indicators that can help in tracing shortcomings and improving educational outcomes The need for information on quality of education has led to many different research initiatives; such as, national assessment studies, international comparative studies, national indicator development projects, etc (Pelgrum, et al, 1995) International comparisons of education, despite their problems and costs, have one particular advantage They have become important instruments for education policy makers in responding to an increasing demand for greater accountability in the public sector of education Many countries, for example, have set national and local standards for assessing outcomes Though many of these standards are not internationally comparable, yet they establish important benchmarks Above all, they foster a culture of self-evaluation around outcomes (Bengston, 2004) The following sections will attempt to provide a conceptual framework for quality education, and will present different models emanating from this conceptual framework Then, will attempt to provide an explanation of indicators, their uses and types, and finally will describe some of indicator sets currently in use for measuring education quality at system level III Education Quality Definition The debate and the views of what constitute education quality are as old as education itself and they are constantly evolving It is a debate influenced by values, norms and subjective judgments (Bengston, 2004) It is not meaningful to try to arrive at a tight, single definition of educational quality, given the evolving scope of education, and the great variety of education systems and value-structures There is no single approach and no size fits all, as different contexts, circumstances, systems, and resources mean that there are different entry points (Ross & Genevois, 2006) Simplest way to define education quality is to refer to available international indicator systems and to conclude that education quality is what these indicator systems describe and measure (Scheerens, 2004) A more functional definition views quality as the adequacy or appropriateness of objects or processes for the purposes for which they were intended (Kellaghan & Greaney, 2001) Conventional definitions have focused on inputs and have included literacy, numeracy and life skills, and those have been linked directly to such critical factors as teachers, content, methodologies, curriculum, examination systems, policy, management, and administration The expanded vision of what is education as articulated by the Jomtien Conference, the exponential growth of new knowledge, and the emerging educational needs of the new millennium have rendered the traditional meaning of „quality of education‟ obsolete, and a need arose to re-think the concept more comprehensively Most of education systems are national initiatives and entities that were not built for a rapidly developing global knowledge economy, where the production, mediation and use of knowledge increasingly operate in a borderless world (Bengston, 2004) Moreover, global economic competition has brought to the fore the critical importance of quality of human resources, and the demand for new competencies in today‟s information society The educational system, schools, and individual students were all under increasing pressure to perform (Kellaghan & Greaney, 2001) Accordingly, and with the advent of knowledge society, educational systems needed to focus on what is learned and how it is learned, and they need be transformed into systems of life long learning with new definitions of education and learning quality They need to develop concepts, practices and quality standards for a range of different types of knowledge from know-what to know-how, from explicit to tacit knowledge; a broader range of competencies and skills for the 21st century (Bengston, 2004) Given the diversity of understanding and interpretation of quality evident in the different traditions discussed above, defining quality and developing approaches to monitoring and improving it requires the following:  broad agreement about the aims and objectives of education and this embodies moral, political, and epistemological issues;  a framework for the analysis of quality that enables its various dimensions to be specified;  an approach to measurement that enables the important variables to be identified and assessed;  a framework for improvement that comprehensively covers the interrelated components of the education system and allows opportunities for change and reform to be identified (UNESCO, 2005) C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an The following section will outline conceptual model for quality of education and then will describe various understandings of this model by international organizations Conceptual Framework A Basic Framework Perspectives on education quality can be clarified on basis of a conceptual framework that describes education Most frequently used one is the one that depicts education as a productive system, in which inputs are transferred into outcomes (Kellaghan & Greaney, 2001; Scheerens, 2004; UNESCO, 2005) This basic model, Figure 1, can be elaborated using following steps: a Context dimension that provides inputs, constraints, and is a generator of required outputs to be produced b Outcomes as direct outputs, longer term outcomes and ultimate societal impact; c Conditions and processes with a hierarchical nature (system, schools, and classroom levels) Figure Basic Systems Model of Functioning of Education Context Process Input Output System School Class Levels Within this basic framework, at least six ways in defining quality can be identified by emphasizing certain parts, aspects or relationships from basic framework (Scheerens, 2004) a Productivity view Success of system is depending on attainment of aspired outcomes/outputs; accordingly output/outcome/impact indicators are predominant or only type of quality indicator that needs to be monitored b Instrumental effectiveness view Emphasizes context, input and process indicators as their effectiveness is essential for successful outputs, therefore instrumental potential are of vital importance c Adaptation perspective How to the right things leading to a critical analysis of educational goals d Equity perspective When inputs, processes and outcomes are analyzed in their equal or „fair‟ distribution among participants in education with different characteristics Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an e Efficiency perspective Considers highest possible outcomes at lowest possible costs f The disjointed view Each element of the model is considered „on its own‟ and judges whether it is manifested in an acceptable way or at an acceptable level For ex level of teacher training, class size, etc Based on this basic education model, several indicator sets at system level were developed like ones used in OECD INES project and the „Sixteen Quality Indicators‟ of the European Commission A slightly different conceptualization of quality education was presented by international organizations like UNESCO and UNICEF that will be described in next section B UNESCO Framework In its report Learning: The Treasure Within, Report to UNESCO of the International Commission on Education for the Twenty-first Century, the commission saw education throughout life as based upon four pillars:  Learning to know acknowledges that learners build their own knowledge daily, combining indigenous and „external‟ elements  Learning to focuses on the practical application of what is learned  Learning to live together addresses the critical skills for a life free from discrimination, where all have equal opportunity to develop themselves, their families and their communities  Learning to be emphasizes the skills needed for individuals to develop their full potential This conceptualization of education provided an integrated and comprehensive view of learning and, therefore, of what constitutes education quality (Delors et al., 1996) In addition, UNESCO promotes access to goodquality education as a human right and supports a rights-based approach to all educational activities (Pigozzi, 2004) Within this approach, learning is perceived to be affected at two levels At the level of the learner, education needs to seek out and acknowledge learners‟ prior knowledge, to recognize formal and informal modes, to practice non-discrimination and to provide a safe and supportive learning environment At the level of the learning system, a support structure is needed to implement policies, enact legislation, distribute resources and measure learning outcomes, so as to have the best possible impact on learning for all (UNESCO, 2005) To meet the above vision of education, the main elements of the education systems and the central dimensions influencing core processes of teaching and learning were characterized as follows:  learner characteristics dimension;  contextual dimension;  enabling inputs dimension;  teaching and learning dimension;  outcomes dimension Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an The framework is comprehensive, in that the quality of education is seen as encompassing access, teaching and learning processes and outcomes in ways that are influenced both by context and by the range and quality of inputs available It emphasizes education‟s relevance to the world, and addresses social and other dimensions of learning According to this perspective, quality of education must recognize the past, be relevant to the present, and have a view to the future It should reflect the dynamic nature of culture and languages, and the value of the individual in relation to the larger context (Pigozzi, 2006) The role of the education system is to create and support learning experience Figure lists the various elements of the model UNICEF‟s view of quality is quite similar and it strongly emphasizes what might be called desirable dimensions of quality, as identified in the Dakar Framework Its paper Defining Quality in Education recognizes five dimensions of quality: learners, environments, content, processes and outcomes, founded on „the rights of the whole child, and all children, to survival, protection, development and participation‟ (UNICEF, 2000) Figure UNESCO Framework for Understanding Education Quality Enabling Inputs Teaching and Learning  Learning time  Teaching methods  Assessment, feedback, incentives  Class size Learn Characteristics  Aptitude  Perseverance  School readiness  Prior knowledge  Barriers to learning     Outcomes  Literacy, numeracy and life skills  Creative and emotional skills  Values  Social benefits Teaching and learning materials Physical infrastructure and facilities Human resources, teachers, principals, inspectors, supervisors, administrators School governance Context    Economic and labour market conditions in the community Socio-cultural and religious factors (Aid strategies)     Educational knowledge and support infrastructure Public resources available for education Competitiveness of the teaching profession on the labour market National governance and management strategies Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn     Philosophical standpoint of teacher and learner Peer effects Parental support Time available for schooling and homework     National standards Public expectations Labour market demands Globalization C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an Having identified the aims and objectives of education and specified the dimensions of its quality, attention should be focused on identifying variables that need to be assessed and measured in order to monitor efficiency of the education system The following sections will describe indicator tools used for this purpose and will present an outline of various indicator sets in use at system level IV Indicators and Indicator Sets at System Level Indicators Education indicators are statistics that are useful for planning, management and policy making (OECD, 1991) They may be defined as tools that offer a good description of the education system and provide a sense of its state, in addition to providing the grounds for an analysis of education policy at the national level A system of indicators must function like a control panel, facilitating the identification of problems and measuring their magnitude Accordingly, the role of indicators could be defined as:  describing the present situation,  quantifying the objectives which have been set,  providing continuous updates on progress towards certain objectives or,  providing insights into which factors might have contributed to achieving the results (European Commission, 2002) For an indicator system to function properly and fulfill its role, it requires a good information system and an education policy and plan Most countries have education databases that are updated regularly There is a problem, however, linked to the presentation and dissemination of available data With few exceptions, data are only published in cumbersome statistical yearbooks that contain excessive raw data and a dearth of analysis Decision-makers need an easier document to read and interpret, one that is more analytical and more relevant (ETF, 2003) Accordingly, there was a need for indicator documents that report on the functioning of the education system in all its aspects with a small number of relevant indicators, that are simple, easy to read, accessible, defined at a high level of aggregation putting all data on education into a single, all encompassing set To meet this need, several types of publications containing a range of indicators have recently appeared: UNESCO initiated the first comparative international work, the World Education Report, the OECD has substantially developed this area over the last ten years, Education at a Glance: OECD Indicators, and several publications have also come out on single countries during the same period These have mostly been produced by Ministries of Education The first of these were L’état de l’école in France and Indicateurs de l’éducation in Quebec (ETF, 2003) The following sections will present on some of the indicators sets at the system level Indicator sets at system level Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an A OECD Indicators Education at a Glance is the OECD‟s annual round-up of data and analysis on education Partly based on economic models, it provides a rich, comparable and up-to-date array of indicators on education systems in the OECD‟s 30 member countries and in a number of partner economies Each edition introduces new countries, indicators and new methodologies, the aim being to over excel both quantitatively and methodologically These indicators enable educational policy makers and practitioners alike to see their education systems in the light of other countries‟ performances and, together with OECD‟s country policy reviews, are designed to support and review the efforts that governments are making towards policy reform They aim to build a profile of education on which the „prominent specialists agree‟, and they function as an encyclopedia (description of actual situation) and a dictionary (highlighting trends and developments) (Sedel, 2004) The OECD indicator set is based on basic education model of context-inputprocess-output at the national education system level However, there is increasing recognition that many important features of the development, functioning and impact of education systems can only be assessed through an understanding of learning outcomes and their relationships to inputs and processes at the level of individuals and institutions To account for this, the indicator framework distinguishes between a macro level, two meso-levels and a micro-level of education systems These relate to: • The education system as a whole; • The educational institutions and providers of educational services; • The instructional setting and the learning environment within the institutions; • The individual participants in education and learning The OECD Indicator set provide information on the human and financial resources invested in education, on how education and learning systems operate and evolve, and on the returns to educational investments They are presented within an organizing framework as described in the following matrix (Figure 3) Our main concern in this paper is the education indicators at the system level, i.e level four The various components of the model defined at level of national education system and their respective indicators are presented below: Context indicators refer to characteristics of the society at large and structural characteristics of national education systems Examples are:  Demographics; relative size of school-age population;  Basic financial and economic context; e.g GDP per capita  Educational goals and standards by level of education; equitable distribution of university graduates, high completion rate  Structure of schools in country, as characterized by International Standard Classification of Education (ISCED-97) 10 Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an independent and complementary teaching modules to enhance the autonomy and diversity of students' choices, so that students can conduct personalized learning according to their own interests (2)With the help of the Internet + platform, the interactivity in teaching is enhanced, so that teachers and students can form a good interactive atmosphere, so that students can learn and master knowledge in the “play” (3)Enriching the types of multimedia in the teaching process, through the comprehensive use of pictures, text, sound, images and 3D images, constructing vivid learning situations, attracting students' attention while guiding students to gradually deepen and build a knowledge system References [1] Liu Caiyan, Huang Danni, Hu Xiaoyue, Zhao Xianglei A Survey on the Current Situation of College Students' MU Learning Based on In-depth Interviews[J] University [1] Liu Caiyan, Huang Danni, Hu Xiaoyue, Zhao Xianglei A Survey on the Current Situation of College Students' MU Learning Based on In-depth Interviews[J] University Education,2020(03):36-38 [2] Zhang Xiaoqian,Wang Haoyong,Wang Minghui Research and analysis on the current situation of university students' learning of “catechism” and online courses: the case of Hebei Agricultural University [J] 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Education(Theory and Practice),2017(11):20-21 Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn 359 C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an [12] Cheng Min,Wang Xiaoyun Research on the evaluation of online teaching quality in smart classrooms [J] Fujian Computer,2020,36(02):120-121 [13] Zhifang Wang,Jia Liu A Teaching Quality Evaluation System of Massive Open Online [14] Courses Based on Big Data Analysis[J] International Journal of Emerging Technologies in Learning (iJET),2019,14(14) [15] Li Yanyan,Dong Xiaonan,Li Xin,Zhang Yuan.Construction of STEM education quality evaluation index system[J] Modern distance education research,2020,32(02):48-55+72 [16] [15 Lai Yang,Jiang Shanshan Construction of teaching quality evaluation system of application-oriented talent training mode in local independent institutions [J] Heilongjiang animal husbandry and veterinary medicine,2019(23):140-145 [17] Xu Weiwei, Wu Jiancheng, Jiang Bibiao, Gong Fanghong Research and practice of teaching quality evaluation system for teachers in higher education[J] Higher Education Research,2011,32(01):100-103 [18] Ding Jialing,Ye Jinhua The application of hierarchical analysis and fuzzy comprehensive judgment in the evaluation of teachers' classroom teaching quality[J] Journal of Wuhan University (Social Science Edition),2003(02):241-245 Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn 360 C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an Stream D: Improving Life Quality and Enhancing Employment Possibilities THE METHOD OF CALCULATION THE QUALITY OF LIFE INDEX Stasys Puškorius Mykolas Romeris University, Lithuania spusk@mruni.lt Purpose The goals of this presentation are: to determine the stages of calculation the quality of life index, to identify the quality of life index estimation branches, to distinguish main indicators which depict quality of each work out area, to introduce the corresponding mathematical models of each area, and present the method of calculation the integral quality of life index Design/methodology/approach The paper includes introduction, determination major dimensions, which define the quality of life index, mathematical models of calculation the integer quality of life index and specific indicators suitable for every situation, estimation of ways to measure weigh constituent coefficients, choosing the unit of measurement of any indicator, discussion different ways of receiving necessary information Findings The report states that the assessment of the diverse country’s status, it is necessary to highlight the welfare of human life and quality criteria, which includes the following major dimensions: health situation, economic situation, environment situation, education situation, culture situation, moral-ethical and spiritual situation, security situation, legal situation, social relations situation The proposed mathematical model, in which quality of life index is calculated by summing up of aggregated and weighted up of those mentioned above values of situations’ indicators Extremely difficult problem of measurement of weigh constituent coefficients is analyzed The recommendations, which should be followed, are formulated It is considered that, firstly, it is advisable to use research results of famous psychologist Maslow's, who composed the list of human needs in hierarchical order According to A Maslow, these needs are arranged in a strict hierarchy: the higher level needs an individual are important only when satisfied with the lower-level needs Secondly, it ISBN 978-9955-19-588-7 (online) Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn 102 C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an Stream D: Improving Life Quality and Enhancing Employment Possibilities should be recognized that the representatives of the different groups in society in different areas of performance may significantly vary, so it is necessary to evaluate the structure of the community, the number of members in each group, and find a way to calculate these differences Thirdly, it is necessary to realize that the weighting factors have the changeable character Fourthly, we need to maximize the use of available statistical data, although in many cases the lack of and far from all the important indicators are reflected in the statistics, so it is necessary to invite experts, and use questionnaire for the survey population It is considered that during the examination of the impact of each mentioned situation on the quality of life index, it is necessary to decide, what indicators will be used, to ground the portfolio of these indicators, to determine the values of each indicator under what can take a decision on its qualitative impact, to identify ways how to measure the values of each indicator, to invite experts, capable perfectly recognize the peculiarities of the operation concrete situation and to propose ways to collect the necessary information to determine its relevance and the selection of possible sources of information, and to assess the validity and reliability of that information The mathematical model that allows computing summing up indicators of each situation is presented It is claimed that it is important to choose the unit of measurement of any indicator The proposed unit of measure is the score; it may have three or even five graduations: in the first case, it would be a good, average and bad scores; in the second case it would be very good, good, average, bad and very bad scores The reading point for each indicator can be selected as a corresponding average point of indicator in Europe countries or in the world Its graduation should be expressed in a percentage of the average, for example, 10 percent of the mean range For each indicator it may be chose different percentages and intervals in the sizes of their range These decisions may be made by experts on the basis of each indicator dispersion, interval, and frequency of specific values and their meaning It is claimed that when main indicators are selected and determined their graduations, it is necessary to carry out a survey of the population following the conclusion of such a questionnaire, which reflected the opinions of the population Only when the residents expressed their opinion on the role of each indicator, can be obtained right conclusions It is considered that the system for selection of statistical data is not developed sufficiently both in Lithuania and elsewhere in the world to compute the necessary ISBN 978-9955-19-588-7 (online) Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn 103 C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an Stream D: Improving Life Quality and Enhancing Employment Possibilities evaluations of the quality of life index In addition, the indicators measuring technology is developed insufficiently It is claimed that the measurement system must be created individually for each indicator The composition of such a system, its purpose and functions depends on what you want to measure, what kind of areas are covered by these objectives and the number of other factors and their combinations Hence, it should be picked out the common and specific features of functioning of these systems The implementation phase of the measurement system encompasses many factors, among which should be mentioned following ones: the approbation of the system, i.e the recognize if it could function properly; the introduction necessary data selection procedures; the establishment of the mechanism of the data processing and the approbation it; the implementation rules and procedures for the formulation of conclusions and recommendations; the inclusion of the obtained recommendations of the measuring system in the decision-making procedures Research limitations Research is theoretical one Author is going to make practical steps to use this method during the research participating in Project “Creation of system of measurement indicators and evolution model of quality of life Lithuanian population” Practical implications This theoretical study will be used during the research in mentioned Project Originality/Value This method is modern one, not used before Key words: quality of life index; indicators; mathematical models; integral quality of life index ISBN 978-9955-19-588-7 (online) Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn 104 C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an American Journal of Water Resources, 2019, Vol 7, No 1, 11-15 Available online at http://pubs.sciepub.com/ajwr/7/1/2 Published by Science and Education Publishing DOI:10.12691/ajwr-7-1-2 Application of National Sanitation Foundation and Weighted Arithmetic Water Quality Indices for the Assessment of Kaani and Kpean Rivers in Nigeria Kalagbor I.A.1,*, Johnny V I.2, Ogbolokot I E.2 Research & Development Centre, Kenule Beeson Saro-Wiwa Polytechnic P.M.B 20 Bori Rivers State Department of Science Laboratory Technology, School of Applied Sciences, Kenule Beeson Saro-Wiwa Polytechnic P.M.B 20 Bori Rivers State *Corresponding author: ksinachi@yahoo.com Received December 14, 2018; Revised January 15, 2019; Accepted January 27, 2019 Abstract Rivers present a continuous renewable physical resource for domestic and agricultural purposes Kaani and Kpean rivers in Bori town in Rivers state, Nigeria are the common sources of water to the people The water quality assessment of these rivers is carried out using fifteen physicochemical parameters These parameters were measured for three consecutive months of July, August and September 2017 at three sampling points for each river These months are the months of the rainy season The samples were analysed using the standardized method of the American Public Health Association (APHA) The concentrations of all the analysed parameters were compared to World Health Organization (WHO) guidelines for drinking water National Sanitation Foundation Water Quality Index (NSF WQI) and Weighted Arithmetic Water Quality Index (WA WQI) were used for assessment The NSF WQI values of 59.77 and 63.45 were obtained for Kaani and Kpean respectively The NSF WQI was able to give a good evaluation of the gradual change in the water quality of these two rivers as they flowed through the communities from Kaani to Kpean The results obtained using the WA WQI gave values of 1.68 and 6.04 for Kaani and Kpean respectively indicating that these water bodies have excellent water quality rating and both methods find useful application in the assessment of Kaani and Kpean and rivers This study shows that in the months of the rainy season, these two rivers have good water quality and are fit for use Keywords: assessment, communities, Kaani, Kpean, Water quality rating, WQI Cite This Article: Kalagbor I.A., Johnny V I., and Ogbolokot I E., “Application of National Sanitation Foundation and Weighted Arithmetic Water Quality Indices for the Assessment of Kaani and Kpean Rivers in Nigeria.” American Journal of Water Resources, vol 7, no (2019): 11-15 doi: 10.12691/ajwr-7-1-2 Introduction Rivers are the most important freshwater resources for man Apart from its function as a source of freshwater for drinking, domestic and industrial uses; freshwater resources serve multiple functions most of them being critical to human settlement and survival Adequate supply of safe and sanitized freshwater is an inevitable factor for human and economic development [1] Report by [2] revealed that in African countries, water related diseases had been interfering with basic human development The common sources of water that are available to local communities in Nigeria are fast being severed by a number of anthropogenic factors of which pollution remain the most dominant problem This is because dead vegetation, metal leachates from solid waste dump, leaching of rocks, sewage, industrial wastes and agricultural chemicals return eventually to the river by runoffs [3] Water abstraction for domestic use, agricultural production, mining, industrial production, power generation and forestry practical can lead to deterioration Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn in water quality and quantity that impacts not only the aquatic ecosystem but also the availability of safe water for human consumption [4] Rivers have been used as a sink for wastes from agriculture and industry due to its flow and ecological nature Rivers are able to regenerate themselves to admit staggering amount of tributaries However, all rivers have limited absorptive capacity for sewage and fertilizer from cropland or farmland Pollution of surface water occurs when too much of an undesirable or harmful substance flows into a body of water, exceeding the natural ability of that water body [5] Water quality monitoring indexing is one of the ways by which the quality of a water system could be assessed [6] It is important to regularly monitor the water body since this action helps to reveal how healthy and hygienic the water is for domestic use, industrial and agricultural purposes [7] The quality of water is the most important factor affecting lives in the ecosystem Rivers and lakes being important fresh water sources are often polluted by natural and anthropogenic sources thereby making them unfit for use Several authors have carried out studies on the physicochemical and microbial properties of some rivers C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an 12 American Journal of Water Resources in Nigeria [8-13] Other studies reveal high concentrations of heavy metals in our rivers, the effect of municipal solid waste discharge and the impact of brewery, tannery and industrial waste water [14-19] on the physiochemical properties of these rivers However, these studies report the assessment of rivers and lakes based on the physiochemical, microbial and heavy metals content only The aim of this study is to analyze fourteen physicochemical parameters and the microbial parameter of Kaani and Kpean rivers using standard methods The results obtained will be applied to National Sanitation Foundation (NSF) and Weighted Arithmetic (WA) water quality indices (WQI) to determine the water quality rating of these rivers dissolved solids (TDS) were determined by gravimetric methods as described by [20] Dissolved oxygen (DO) was determined using oxygen analyzer (model JPB – 607) The conductivity measurements were carried out using a conductivity meter (Hanna conductivity meter model EC 215) and the turbidity was measured using a turbidity meter (Xinrui WGZ – IB Shanghai) The other physicochemical parameters were later analyzed in the laboratory using the stipulated methods in [20] These include; biological oxygen demand (BOD), chemical oxygen demand (COD), the anions (Cl-, NO-3 and PO2-4), the cations (Mg2+ and Ca2+) and fecal coliform The chemicals and reagents used in these analyses were of analytical grade from BDH Materials and Method 2.3.2 NSFWQI Calculations 2.1 Study Area These two rivers flow through so many communities in Ogoniland in Rivers State Waters from Gokana and Yeghe empties into the Kaani River The Kpean River has tributaries from Kono and Opobo Both rivers met at a confluence point and then flow into the Imo River which then empties into the Bight of Bonny These rivers are primarily used for fishing, swimming and as potable water Majority of the people close to the river continue to depend on these rivers for their domestic and agricultural needs The Figure below is a map showing the two rivers and the sampling sites Site Site Site Site Site Site Figure Map showing the two rivers and their sampling points This method was developed by [21] to provide a standardized method for comparing the water quality of various bodies of water using nine water quality parameters These are pH, temperature, turbidity, fecal coliform, dissolved oxygen (DO), biochemical oxygen demand (BOD), total phosphates, nitrate and total solids according to [22] Results obtained for each parameter are compared to the weighting chart curve and a numerical value (Q – value) is obtained and used in the mathematical expression below for NSF WQI: n WQI = ∑QiWi (1) i =1 Where Qi = sub-index for ith water quality parameter; Wi = weight associated with ith water quality parameter; n = number of water quality parameters For this NSFWQI method, the ratings of water quality have been defined by using the following Table 1: Table Water Quality Rating for National Sanitation Foundation Water Quality Index (NSFWQI) WQI Value 91 – 100 71 – 90 51 – 70 26 – 50 – 25 Ratings of Water Quality Excellent water quality Good water quality Medium water quality Bad water quality Very bad water quality Source: Shweta et al., 2013 2.2 Water Sample Collection 2.3.3 Weighted Arithmetic WQI, Method and Calculations Water samples were taken from both rivers (Kaani and Kpean) at three different sampling sites as marked in Figure (Site1, Site and Site 3) which correspond to upstream, midstream and downstream respectively in each of the rivers The water samples were collected in duplicates in sterilized 150 ml plastic bottles and sealed with tight stopper and cap to avoid air bubbles These were taken to the laboratory for analyses This method has been widely used by various scientists [23,24,25] using the most commonly measured water quality variables [26] The calculation involves the use of the following mathematical equation: WQI = ∑QnWn ∑Wn (2) Where Qn is the quality rating scale for each parameter for the nth water quality parameter Wn is the unit weight for each water quality parameter 2.3 Methods 2.3.1 Physicochemical Analysis Temperature and pH were measured in-situ using a Hanna instrument (HI 9813-6) Total solids (TS) and total Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn V − V  Qn = 100  n o   Sn − Vo  (3) C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an American Journal of Water Resources Where Vn is observed value (ie estimated concentration of nth parameter in the analyzed water Vo is the ideal value of this parameter in pure water (Vo = (except pH = 7.0 and DO = 14.6 mg/L)) Sn is the recommended standard value of nth parameter by WHO Wn = K Sn (4) where K = The rating of water quality according to this WQI is given in Table Table Water Quality Rating as per Weight Arithmetic Water Quality Index Method WQI Value Rating of Water Quality Grading 0-25 Excellent water quality A 26-50 Good water quality B 51-75 Poor water quality C 76-100 Very poor water quality D Above 100 Unsuitable for drinking purpose E Source: Shweta e al., 2013 Results and Discussion 13 Table Descriptive Statistics for the Parameters in Kaani River Average Values S/N Parameters Mean values July August September pH 7.20 5.83 7.10 6.71 Temp (°C) 26.87 27.03 27.23 27.04 Turbidity (NTU) 0.31 3.96 0.44 1.57 Conductivity (μs/cm) 140.33 153.77 143.67 145.92 DO (mg/L) 22.07 22.63 28.37 24.36 BOD ( mg/L 5.13 11.87 6.57 7.86 COD (mg/L) 10.83 13.13 12.17 12.04 11.17 20.93 16.87 16.32 32.53 43.03 33.13 36.23 - NO3 (mg/L) - Cl (mg/L) 2- 10 PO4 (mg/L) 0.33 0.12 0.15 0.20 11 TS ( mg/L) 0.17 0.20 0.13 0.17 12 TDS (mg/L) 0.13 0.20 0.13 0.16 13 Mg2+ (mg/L) 20.33 21.73 18.70 20.26 2+ 14 Ca (mg/L) 22.53 32.83 27.07 27.48 15 Fecal coliform 10.33 24.67 49.33 28.11 Table Calculation of Water Quality Index for Kpean using the Weighted Arithmetic Method 3.1 Results Presented in Table and Table are the descriptive statistics of the results obtained from the analysis of the parameters in this study for Kpean river and Kaani river respectively while Table to Table are the results of the calculations for Water Quality Indices for Kpean and Kaani using NSF and WA methods Table Descriptive Statistics for the Parameters in Kpean River Parameters pH Observed WHO mean Unit weight (Wn) Quality Rating (qn) Wnqn 7.68 8.5 0.118 45.185 5.316 Temp ( C) 24.46 28 0.036 87.341 3.119 Turbidity (NTU) 1.41 0.200 28.200 5.640 Conductivity (μs/cm) 132.78 250 0.004 53.111 0.212 DO mg/L 22.11 0.167 -87.339 -14.556 BOD mg/L 4.39 10 0.100 43.889 4.389 Average Values Parameters July August September Mean values pH 7.93 6.93 8.17 7.68 Temp (0C) 25.17 23.40 24.80 24.46 COD (mg/L) 33.17 150 0.007 22.111 0.147 Turbidity (NTU) 0.23 3.72 0.28 1.41 NO3- (mg/L) 22.32 50 0.020 44.644 0.893 Cl- (mg/L) 34.93 250 0.004 13.973 0.056 PO42- (mg/L) 0.16 0.200 3.178 0.636 TS mg/L 0.37 500 0.002 0.073 0.000 TDS mg/L 0.20 500 0.002 0.040 0.000 132.78 (DO mg/L 11.57 18.57 36.20 22.11 BOD mg/L 2.23 8.43 2.50 4.39 COD (mg/L) 32.03 27.57 39.90 33.17 NO3- (mg/L) 19.60 21.30 26.07 22.32 Cl- (mg/L) 29.13 32.53 43.13 34.93 Mg2+ (mg/L) 27.46 150 0.007 18.304 0.122 10 PO42- (mg/L) 0.07 0.13 0.28 0.16 Ca2+ (mg/L) 24.79 200 0.005 12.394 0.062 11 Total Solid (TS) mg/L 0.33 0.37 0.40 0.37 12 TDS mg/L 0.20 0.20 0.20 0.20 26.93 25.20 30.17 27.42 14 Ca (mg/L) 23.47 24.63 26.27 24.79 15 Fecal coliform 9.67 58.67 78.67 49.0 2+ Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn = 6.036 13 Mg (mg/L) 𝑊𝑊𝑊𝑊𝑊𝑊 = 2+ � 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊 123.83 � 𝑊𝑊𝑊𝑊 = 0.870 123.77 150.73 ∑ 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊 ∑ 𝑊𝑊𝑊𝑊 6.036 = 0.870 = 6.935 Conductivity (μs/cm) C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an 14 American Journal of Water Resources Table Calculation of Water Quality Index for Kaani using the Weighted Arithmetic Method Parameters Observe d mean WH O Unit weight (Wn) Quality Rating (qn) Wnqn pH 6.71 8.5 0.118 -19.259 -2.266 Temp (°C) 27.04 28 0.036 96.587 3.450 Turbidity (NTU) 1.57 0.200 31.333 6.267 Conductivity (μs/cm) 145.92 250 0.004 58.369 0.233 DO (mg/L) 24.36 0.167 -113.49 -18.95 BOD (mg/L) 7.86 10 0.100 78.556 7.856 COD (mg/L) 12.04 150 0.007 8.030 0.054 NO3- (mg/L) 16.32 50 0.020 32.644 0.653 CL- (mg/L) 36.23 250 0.004 14.493 0.058 PO42- (mg/L) 0.20 0.200 4.044 0.809 TS (mg/L) 0.17 500 0.002 0.033 0.000 TDS (mg/L) 0.16 500 0.002 0.031 0.000 Mg2+ (mg/L) 20.26 150 0.007 13.504 0.090 Ca2+ (mg/L) ∑ 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊 𝑊𝑊𝑊𝑊𝑊𝑊 = ∑ 𝑊𝑊𝑊𝑊 1.68 = 0.870 = 1.93 27.48 200 0.005 13.739 0.069 � 𝑊𝑊𝑊𝑊 � 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊 = 0.870 =1.68 Table Calculation of Water Quality Index using NSFWQI Method for Kpean Observed mean WHO Unit weight (Wi) Q-values WiQi pH 7.68 8.5 0.118 90.000 10.588 Temp (0C) 24.46 28 0.036 16.500 0.589 Turbidity (NTU) 1.41 0.200 90.500 18.100 DO (mg/L) 22.11 0.167 16.500 2.750 BOD (mg/L) 4.39 10 0.100 56.500 5.650 PO42- (mg/L) 0.16 0.200 96.000 19.200 NO3- (mg/L) 22.32 50 0.020 30.500 0.610 TS (mg/L) 0.37 500 0.002 80.000 0.160 Fecal Coliform 49.00 10 0.100 58.000 5.800 Parameters 𝑊𝑊𝑊𝑊𝑊𝑊 = ∑𝑛𝑛𝑖𝑖=1 𝑄𝑄𝑖𝑖 𝑊𝑊𝑖𝑖 = 𝟔𝟔𝟔𝟔 𝟒𝟒𝟒𝟒𝟒𝟒 Table Calculation of Water Quality Index using NSFWQI Method for Kaani Unit Observed WHO weight Q-values mean (Wi) Parameters WiQi pH 6.71 8.5 0.118 72.500 8.529 Temp (0C) 27.04 28 0.036 12.000 0.429 Turbidity (NTU) 1.57 0.200 90.500 18.100 DO (mg/L) 24.36 0.167 16.500 2.750 BOD (mg/L) 7.86 10 0.100 42.000 4.200 PO42- (mg/L) 0.20 0.200 95.000 19.000 NO3- (mg/L) 16.32 50 0.020 40.000 0.800 Total Solid (TS) mg/L 0.17 500 0.002 80.000 0.160 Fecal Coliform 28.11 10 0.100 58.000 5.800 𝑊𝑊𝑊𝑊𝑊𝑊 = ∑𝑛𝑛𝑖𝑖=1 𝑄𝑄𝑖𝑖 𝑊𝑊𝑖𝑖 = 𝟓𝟓𝟓𝟓 𝟕𝟕𝟕𝟕𝟕𝟕 Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn 3.2 Discussion The average pH value for Kpean was 7.68 which are higher than that for Kaani (6.71) The maximum pH value obtained in this study for both rivers was 8.5 and this was in the month of July These values however are within permissible limits of [27] In August, the temperature of Kaani River was 28.3°C while temperatures in July and September were 27.3°C and 27.5°C respectively For Kpean River, the maximum temperatures (25.4°C and 25.2°C) were recorded only in July and September Turbidity in both rivers was higher only in the month of August (4.20 NTU) and low (0.15 – 0.36 NTU) in the months of July and September The average values for Kaani and Kpean were 1.57 NTU and 1.41 NTU respectively and these values were within WHO permissible limits The conductivity values are high for both rivers These values ranges from 130.7 – 160.0 µs/cm for Kaani River while for Kpean River the values ranges from 120.4 – 150.9 µs/cm with maximum values occurring in the month of August for both rivers DO values were higher in the month of September for both rivers; Kaani (28.37 mg/L) and Kpean (36.2 mg/L) The BOD values were very high in August in comparison with the values obtained in July and September for both rivers COD values were found to be high at Site sampling point for Kaani River and at Site sampling point for Kpean River and these high values were recorded in the month of September Temperature, BOD and conductivity values are higher in Kaani River while COD, TS and TDS were found to be higher in Kpean River This could be attributed to the introduction of solid wastes at the downstream The anions (Cl- and PO42-) are higher in Kaani, most probably due to the introduction of wastes and contaminants The quantity of nitrates and fecal coliform decreased at Kaani River which is an indication of less eutrophication and fecal discharge The levels of Mg2+ and Ca2+ in both rivers were constant (20 – 27 mg/L) throughout the period of study Most of the parameters were higher in the month of August which is the peak of rainy season and is expected This is in agreement with the findings of [1] and [28] All the values obtained for the fourteen parameters used for Weighted Arithmetic WQI were within [27] permissible limits except the DO values (24.36 mg/L and 22.11 mg/L) which were above the WHO permissible limits The low WQI values for Kpean and Kaani rivers in Table and Table fell within Grade A rating (Excellent water quality) as shown in the Weighted Arithmetic weighting chart (Table 2) while the WQI values obtained for both rivers in Table and Table using NSF WQI method were 63.45 and 59.77 for Kpean and Kaani respectively These values indicate that the two water bodies are of medium quality as shown in the NSF WQI chart (Table 1) The NSF WQI Method did not adequately represent the quality of both Kaani and Kpean rivers when compared to the WA WQI method This inadequacy may be due to the fewer number of parameters (nine) used for the calculation This was also observed by [22] in their study The values from downstream (Site 3) samples were higher than those from the upstream (Site 1) This could be attributed to the level of anthropogenic activities in those rivers This agrees with the results obtained by [28] and [29] C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an American Journal of Water Resources Conclusion [9] This study has provided a basis for expressing water quality by using just a single value leading to easier interpretation of the state of these rivers The water quality indices obtained shows that in the months of July, August and September, these two rivers have good water quality and are fit for use WA WQI incorporated fourteen out of the fifteen parameters analyzed as required by the method thereby giving a better assessment of the rivers when compared to NSF WQI method However, the NSF WQI was able to give a good evaluation of the gradual change in the water quality of these two rivers as they flowed through the communities from Kaani to Kpean The results obtained from these two measured methods are in agreement with the results of analysis of the individual parameters which were found to be within WHO permissible limits It is recommended that water monitoring should be carried out more frequently and a data base generated in order to keep track of any seasonal changes and convey same to the communities who depend on these rivers for their source of livelihood [10] Acknowledgements [17] The authors are grateful to the fishermen and canoe men who assisted us in this research by taking us to the six sampling points for water sample collection We are also grateful to the indigenes who offered to show us the course for Kpean River which had so many tributaries [11] [12] [13] [14] [15] [16] [18] [19] [20] References [1] [2] [3] [4] [5] [6] [7] [8] Ayobahan S.U., Ezenwa I.M., Orogun E.E., Uriri J.E and Wemimo I.J, “Assessment of Anthropogenic Activities on Water Quality of Benin River” Journal of Applied Sciences Environmental Management, 18(4), 629-636 2014 Food and Agricultural Organisation, “Coping with Water Scarcity”, 2007 World Water Day, 22nd March, 2007 Available at http://www.fao.org/nr/water 2007 Ademola F.A, “Base Line Heavy Metals Concentration in river sediment within Okitipopo South east belt of the Nigeria bituminous sand field” Journal of chemical society of Nigeria, 33(2), 29-34 2008 United Nations Environment Programme, “Water Quality for Ecosystem and Human Health” Published by the United Nations Environment Programme Global Environment Monitoring System (GEMS)/Water Programme, 132 2006 Agbabiake, T O and Oeyiola, G P, “Microbial and physicochemical assessment of Foma River, Itanmo, Ilorin, Nigeria an important source of domestic water in Ilorin metropolis” Intl J plant, animal and environment sciences, 2(1), 209-216 2012 Goher, M.E., Hassan, A.M., Abdel-Moniem, I.A., Fahny, A.H and El-Sayed, S.M “Evaluation of Surface Water Quality and Heavy Metal Indices of Ismaila Canal, Nile River, Egypt” Egyptian J Aquatic Research, 40, 225-233 2014 Poonam, T., Tanushree, B and Sukalyan, C “Water Quality Indices –Important Tools for Water Quality Assessment: A Review” Intl J Adv Chem, 1, 15-28 2013 Emoyan, O.O., Akporhonor, E.E and Akpoborie, I.A “Environmental Risk Assessment of River Ijana, Ekpan, Delta State Nigeria”, Chemical Speciation and Bioavailability, 20(1), 23-32 2008 [21] [22] [23] [24] [25] [26] [27] [28] [29] 15 Chinedu, S.N., Obinna, C.N., Adetayo, Y.O and Eze, V.N., “Assessment of Water Quality in Cannanland, Ota, Southwest Nigeria”, Agric and Biol J North America 2(4) 577-583 2011 Cosmas A.A and Samuel O.O “Comparative Assessment of the Physico-chemical and Microbial Trends in Njaba River, Niger Delta Basin, South eastern Nigeria” J Water Resour and Protect, 3, 686-693 2011 Salawu, K., Owolarafe, T.A., Barau, M.M., Lawal, T.A., Abubakar, M.A., Fadilu, M and Nwachukwu, F.C “Determination of Selected Heavy Metals in Seasonal River in Mariu Town, Zamfara State, Nigeria” J Environ and Earth Science, 4, 11-14 2014 Nwoko, C.I.A., Ukiwe, L.N., Egereonu, U.U and Ukachukwu, S.N “Assessment of Seasonal Physico-chemical Parameters of Oguta Lake, Nigeria” J Adv in Chem, 11(7), 3759-3764 2015 Kalagbor, I A and Tubonemi, T A “Comparative Assessment of the Physicochemical, Microbial property and the levels of some Heavy Metals in Ekerekana Creek in Rivers State” Intl J App and Nat Sciences, 7(4), 9-18 2018 Ubalua, O.A and Ezeronye, O.U “Nutrients and Selected Physico-Chemical Analysis in the ABA Rivers Surface Waters Abia State, Nigeria” Environment and Ecology, 23(1), 141-144 2005 Igbinosa, E.O and Oko, A.I “Impact of Discharge Wastewater Effluents on the Physiscochemical Qualities of a Receiving Watershed in a Typical Rural Community” Intl J Environ Sci & Technol, 6(2), 175-182 2009 Alao, O., Arojojoye, O., Ogunlaja, O and Famuyiwa, A “Impact of Assessment of Brewery Effluent on Water Quality in Majawe, Ibadan, Southwestern Nigeria”, Researcher, 2(5), 21-28 2010 Chinda, A C., Braide, S A and Obunwo, C.C., “Water Quality of Streams receiving Municipal Waste Water in Port Harcourt Niger Delta, Nigeria” Waste Water – Evaluation and Management InTech, Croatia 2011 Obunwo, C.C., Chinda, A.C and Braide, S.A “Assessment of the Physico-chemical Characteristics of Minichida Stream, Port-Harcourt, Nigeria” J Chem Soc Nigeria, 37, 132-136 2012 Jaji, M.O., Bamgbose, O Odukoya, O.O and Arowolo, T.A, “Water Quality Assessment of Ogun River, Southwest Nigeria”, Environ Monitoring Assess 133(3), 447-482 2007 America Public Health Association (APHA) “Standard methods for the examination of water and waste water 20th edition” American Public Health Association, American Water Works Association and Water Environment Federation Washington DC, USA 1998 Brown, R M., McClelland, N I., Deininger, R.A and Tozer, R.G “Water quality index – we dare”? Water Sewage Work, 117(10), 339-343 1970 Kumar, D and Alappat, B “NSF – Water Quality Index: Does it Represent the Experts’ Opinion?” Practice Periodical of Hazardous Toxic and Radioactive Waste Management, 13(1), 75-79 2009 Chauhan, A and Singh, S “Evaluation of Ganga water for drinking purpose by water quality index at Rishikesh, Uttarakhand, India” Report Opinion, 2(9), 53-61 2010 Balan, I.N., Shivakumar, M and Kumar, P.D.M., “An assessment of ground water quality using water quality index in Chennai, Tamil Nadu, India” Chronicles Young Scientist, 3(2), 146-150 2012 Chowdhury, R.M., Muntasir, S.Y and Hossain, M.M “Water quality index of water bodies along Faridpur-Barisal road in Bangladesh” Global Engineers & Technologists Review, 2(3), 1-8 2012 Shweta, T., Bhavtosh, S., Prashant, S and Rajendra, D “Water Quality Assessment in Terms of Water Quality Index” American Journal of Water Resources 1(3), 34-38 2013 World Health Organization, “Guidelines for Drinking Water Quality”, 4th Ed NLM Classification, WA 675, World Health Organization, Geneva, Switzerland, 307-433 2011 Nyodee, G T “Determination of Water Quality Index for Bangha Stream in Bangha Community, Rivers State, Nigeria” Science and Industrial Technology Education Journal, 3(2), 182-189 2016 Khawakara, M.A., Majid, S.N and Hama, N.Y., “Determination of Water Quality Index (WQI) for Qalyasan Stream in Sulaimani City, Kuradistan Region of Iraq”, Intl J Plant, Animal and Environ Sc 2(4), 148-157 2012 © The Author(s) 2019 This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/) Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an School Educational Quality Index: A Few Observations Arun C Mehta* Exclusively based on U-DISE Data, National Institute of Educational Planning and Administration (NIEPA) initiated computing Educational Development Index (EDI) based on a set of 24 parameters in 2005-06 which continued up to the year 2014-15 It was annual practice to compute EDI separately for Primary and Upper Primary levels of education and also a composite index for the entire Elementary level of education A set of 24 indicators were being used in computing EDI which were re-grouped into the four sub-groups, namely Access, Infrastructure, Teachers and Outcome indicators Principal Component Analysis (PCA) was applied to decide the factor loading and weights In the case of a few variables, policy options were explored to identify the best values instead of based on the observed values The EDI in its new avatar, namely School Education Quality Index (SEQI) is computed for the base year 2015-16 The latest document, namely SEQI: The Success of Our Schools was released by NITI Aayog on 30th September 2019 is based on 2016-17 data i.e reference year which was collected mostly as on 30th September 2016 SEQI is an improved version of EDI as it is more comprehensive in nature and is based on more sets of indicators and unlike EDI; is not confined only to U-DISE data; however, U-DISE still remained the main source of data In addition to U-DISE data, SEQI has also extensively used learning outcomes data of the National Achievement Survey’s (NAS) conducted by the NCERT on November 13, 2017, apart from a few other data-sets provided by the States & UTs While the total number of indicators and sectors which have been used in SEQI is comprehensive but a few of the crucial indicators, like retention rate, ratio of primary to upper primary and upper primary to secondary schools/sections and percentage of schools with female teachers, and a few others, such as, average annual drop-out rate at primary level of education has not been considered which has got significant implications for the Country to achieve the goal of universal school education It may also be of high importance to observe that enrollment in school education in India during 2015-16 and 2016-17 has shown a decline of about million enrollment of which 6.8 million (Primary, 5.32 million & Upper Primary, 1.51 million) alone declined in case of elementary level of education i.e Classes to which has got serious implications for the country to achieve the goal of universal elementary level of education but declining enrollment has not been considered as one of the indicators in computing SEQI It was perhaps for the first time that enrolment at the Upper Primary level of education (Classes VI to VIII) had also declined in 2016-17 from its previous level i.e 2015-16 Individually also, Class I, V, VI & VII and Class X, XI & XII all declined in 2016-17 which has got serious implications for enrolment at other higher levels of education to grow in years that follow At least, Net Apparent Entry Rate which is considered crucial for achieving universal enrolment should have been used Needless to mention that even enrolment in Class I had also declined to 25.29 million in 2016-17 from its previous level, i.e 27.17 million in 2015-16 *Former Professor & Head, Department of EMIS, NIEPA, New Delhi Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an As many as 30 indicators have been used in computing 2016-17 SEQI which are classified under two categories, namely Outcomes and Governance Processes Aiding Outcomes Category one Outcome is further divided into four domains, namely Learning, Access, Infrastructure and Equity outcomes which has as many as 16 indicators as against 14 indicators including student and teacher attendance, teacher availability, training, accountability and transparency all which are not part of the regular collection of administrative data but provided by the states and is not available in the public domain and not an easy task to examine the validity of such data sets Limited information has been provided on how such data set as stated by the States & UTs was validated On the other hand, as many as 10 indicators from NAS have been used as compared to indicators from the U-DISE sources The rest of the indicators are either obtained from the GoI portal, namely ShaGun or have been reported by the States & UTs Depending upon the nature of an indicator, a few indicators have been used for all the schools including Private Aided & Unaided managements while a few others have been used only for Government and Government aided schools/management Few indicators used in computing 2016-17 SEQI are worth to describe Over a period of time, it has been observed that percentage of out-of-school children identified and mainstreamed has always been incomplete because of which the same had never been reported in U-DISE publications which is now under SEQI is used but is reported by the States & UTs and is not easy to validate the same This indicator might have avoided as it has already been captured indirectly in the Adjusted-NER at Elementary and Secondary level of education used in computing SEQI Another important indicator used in SEQI is the percentage of children whose unique Id is seeded in SDMIS It is mentioned that “States and UTs are encouraged to track their students through the SDMIS as a way to inform UDISE UDISE is meant to serve as a longitudinal database for tracking the schooling status of students to provide a foundation for evidence-based policy responses” It is heartening to observe SEQI document mentioning “that all States and UTs have successfully migrated from their existing Management Information Systems (MIS) to the SDMIS” However, it is unfortunate that SDMIS in-sync with U-DISE launched during the 2016-17 data collection was discontinued in the following year for unknown reasons through which detailed individual student records on 35 parameters in case of 210 million students were recorded the majority of which also had the Unique Ids Had it been continued, the same would have eventually helped in improving enrolment statistics generated through the U-DISE which would have lead India towards developing a Child-tracking system in view of which the next SEQI, if computed this indicator would have to be dropped Another indicator that was planned but dropped in the final calculation is GER of CWSN Children (agegroup to 18 years) because of unavailability of the published data which at the very first place shouldn’t have been included in the initial list of indicators because of its very definition Where we get the CWSN population of age-group to 18 years in 2016-17 whereas the reliable child population in the school age-groups is even not available? The percentage of average daily attendance of teachers recorded in the electronics attendance system is another indicator that has been used instead of indicators that focuses more on what teachers in the school Instead of 10 RTE facility indicators, the percentage of schools meeting teacher norms as per the RTE Act has only been used Instead of using the percentage of teachers provided with the sanctioned number of days of training/in-service training, emphasis should have been given to indicators that capture whether the training provided meets the teacher’s requirement and is need-based? It is common practice across the Country that DIET Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an receives themes (along with a number of programs to be conducted, program days & number of participants, etc in each program) of the capacity building programs identified by the SCERT which is generally common to all the districts across the state? It is of interest to observe that many states have reported the percentage of schools that have made school development plans a hundred which is contrary to the situation at the grassroots level across the Country Rather percentage of blocks and districts used school development plans in the formulation of district elementary/secondary education plans as envisaged in SSA must have been used One of another interesting indicators used in computing SEQI is average number of days taken by State/UT to release Central/State share to State Societies but it is silent on a number of months delayed by the Central agencies to release the funds to states Rather, in the case of UTs, there is no provision to release the state share A total 20 weight-age points have been assigned to states recruited new teachers through online system, but the SEQI is totally silent on the percentage of para/contractual-teachers to total teachers which has grown many-fold in the recent past which is evident in the percentage of contractual teachers being disseminated through U-DISE In fact, many states have discontinued recruiting regular teachers and instead recruit only para-teachers It has also been observed that indicators not showing large variations across States & UTs, such as percentage of schools with girls’ toilets, would not have been used in computing SEQI as all the states, small medium and large ones have reported this percentage to be 100 Seeding of UIDs in SDMIS in 2016-17 is another such indicator that also didn’t have any variation in addition, to a few other such indicators One of the other important points which have been observed is that SEQI is computed for the entire school education as one entity whereas in 201617, SSA and RMSA were two separate programs as Samagra came into the picture during 201819 in view of which there must have been two separate indices, one for elementary (also for primary and upper primary levels) and another for secondary and higher secondary level of education School Education Quality Index is based on U-DISE 2016-17 data which was collected as on 30th September 2016 has now become almost years old; therefore data used in computing SEQI is termed outdated The process of data entry of SEQI indicators and submission by the States & UTs began in April 2018 and ended on December 2018 during which the unpublished 2017-18 UDISE data was also available with the States & UTs but the most recent data was not used in computing SEQI It is hoped that the next SEQI will be based on the latest data i.e 201920 (30th September 2019 as date of reference) being collected through U-DISE+ which is supposed to be the real-time data but the same is still being collected It is hoped that the next SEQI data will directly be obtained from the U-DISE+ portal and states will not be required to upload the data on ShaGun or other portal as has been the case with the SEQI 2016-17 It may be observed that the Educational Development Index being computed by MHRD and NIEPA during the period 2005-06 to 2014-15 was more scientific as weights to each indicator was assigned based on Principal Component Analysis and as such no human element was involved in assigning the weights whereas in SEQI weights have been assigned manually in consultation with the MHRD, Sector Experts and even stakeholders, namely States and UTs which may change if different set of experts are engaged in assigning the weights which may dramatically change the SEQI index SEQI document mentioned that because of the lack of timeseries information, it was not possible to assign weight-age but EDI which was also based on Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an cross-sectional data used to assign weights which were more scientific than the procedure adopted in computing SEQI One of the important indicators used is Adjusted-NER which describes children's participation of an age group in the corresponding education level which is based on enrolment and age-specific population Though enrolment is available from the UDISE but the same is not true for corresponding child population in the absence of which projected population has been used but the same based on 2011 Census is not available in the absence of which all enrolment based indicators such as Adjusted-NER may be treated as provisional and may change once more recent child projected population is available It is hoped that the NITI Aayog will quickly get the age-specific child population immediately after the 2021 Census is released state and district-specific It has rightly been said that SEQI has been developed to provide insights and data-based feedback on the success of school education in India which shall help India achieving SDG by 2030 which cannot be achieved unless SEQI is computed district and within the district blockwise A state may have high SEQI but all of its districts may not be at par as a few of which may take more years to achieve goals of school education while a few others may be in a position to achieve the same in the near future From the document, it is not clear whether there is any planning to bring out district-wise SEQI and within the district, block specific SEQIs? It may be recalled that many states attempted computing EDI at the state level and identified districts & blocks which need more attention while formulating district education plans But because of the lake of expertise at the state and district level, the same could not be attempted across the Country and sustained District level Planning & MIS Officials must be oriented to ensure that SEQI is computed at the district level, block-wise by the district officers They are also required to be trained to provide inputs in district plans based on the outcome of district-specific SEQI Computing SEQI may not be an issue as every bit of information used in computing SEQI must be available online interactive portal at all the disaggregated levels, such as school, cluster, block, district, state, and national level Rather, the same should have been taken up along with the computation of the State-specific SEQI The index attempts to provide a platform for promoting evidence-based policymaking and highlights possible course-corrections in the education sector It is mentioned in the document that SEQI will be used in formulation of education policy but form the SEQI document one fails to get the information whether the same was shared with the Kasturi Ranjan Committee report of which is now available in the public domain in the form of Draft National Policy of Education 2019 Needless to mention that SEQI is largely based on published data been provided by national institutions such as NCERT (NAS) and NIEPA (U-DISE) but they failed even to get the acknowledgment or even mentioned in the SEQI document From the document, one gets the impression that these institutions did not play any role or were not engaged in the process of computing SEQI except at the initial stage of identification of indicators A close look at the roles and responsibilities reveals that major role is played by the development partner and private parties and the apex national institutions which has got in-house expertise and were engaged in similar exercises in the form of computing EDI which were used to be published by the MHRD through the Elementary Education in India: Flash Statistics were not engaged Data provided by NCERT & NIEPA were validated by a private agency and the World Bank was the lead agency However, limited information is provided as to how the data was validated and what was the Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn C.vT.Bg.Jy.Lj.Tai lieu Luan vT.Bg.Jy.Lj van Luan an.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj Do an.Tai lieu Luan van Luan an Do an.Tai lieu Luan van Luan an Do an Stt.010.Mssv.BKD002ac.email.ninhd.vT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.LjvT.Bg.Jy.Lj.dtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn.Stt.010.Mssv.BKD002ac.email.ninhddtt@edu.gmail.com.vn.bkc19134.hmu.edu.vn