Relevant bibliographies by topics / Education indicators

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Education indicators'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Education indicators"

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Blank, Rolf K. "Developing a System of Education Indicators: Selecting, Implementing, and Reporting Indicators." Educational Evaluation and Policy Analysis 15, no. 1 (March 1993): 65–80. http://dx.doi.org/10.3102/01623737015001065.

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National and state-level reports on education indicators have been produced since the mid-1980s. However, the debate continues over which education indicators to select and report. This paper outlines the lessons gained by a national organization in building an education indicators system through cooperation with federal and state education agencies. Three issues in the indicator development process are emphasized: (a) the role of a consensus process among educators, researchers, and policymakers in selecting and defining indicators, (b) how education indicators can be produced through a cooperative data system with states, and (c) methods for reporting indicators that increase their usefulness for policymakers and educators.
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Maheu, Robert. "Education Indicators in Quebec." Canadian Journal of Education / Revue canadienne de l'éducation 20, no. 1 (1995): 56. http://dx.doi.org/10.2307/1495052.

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Hattie, John. "Performance Indicators in Education." Australian Journal of Education 34, no. 3 (November 1990): 249–76. http://dx.doi.org/10.1177/000494419003400304.

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Banta, Trudy W. "Editor's notes: Education indicators." Assessment Update 2, no. 3 (1990): 3. http://dx.doi.org/10.1002/au.3650020303.

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Bottani, Norberto. "OECD international education indicators." International Journal of Educational Research 25, no. 3 (1996): 279–88. http://dx.doi.org/10.1016/0883-0355(96)82857-6.

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Sukarsa, I. K. G., and G. K. Gandhiadi. "Mapping of Regencies/City in Bali Province Based on Education Indicators." Jurnal Matematika 8, no. 2 (February 6, 2019): 88. http://dx.doi.org/10.24843/jmat.2018.v08.i02.p100.

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Education Development is one of the important elements of Human Resource Development (HR). In order for education development to be carried out properly, one of the important things is to know how to map the development of education in an area (for example the regencies in this study) based on predetermined education indicators. Based on the map, it can be seen that the education indicator is dominant in an area. With this information, the direction of education development in each region can be designed according to regional conditions by increasing indicators that are relatively lacking and maintaining a good indicator. This study aims to produce information in the form of education development maps in regencies/city in Bali Province based on education indicators so that they can be used as a reference for education development policies in each regencies. The resulting map will provide information on the condition of education indicators in a regencies. To get an overview of the map, Biplot Analysis is carried out on education indicator data. This analysis will provide a graph of the position of objects (regencies / city) and the relationships between variables (education indicators) simultaneously. The results of the analysis in graphical form with biplot shows that Gianyar Regency and Tabanan Regency are regencies that generally have close characteristics. This means that based on education indicators, the two regencies have similar indicators. The same thing is also seen in Karangasem and Bangli . While 5 (five) other regencies / city appear to have different indicator characteristics, the position of each regencies or city is far apart.
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Wang, Wen-Sheng, and Gregory S. Ching. "Developing Sustainability Indicators for Higher Education Institutions in Taiwan." International Journal of Information and Education Technology 5, no. 12 (2015): 905–9. http://dx.doi.org/10.7763/ijiet.2015.v5.635.

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Murnane, Richard J. "Improving Education Indicators and Economic Indicators: The Same Problems?" Educational Evaluation and Policy Analysis 9, no. 2 (June 1987): 101–16. http://dx.doi.org/10.3102/01623737009002101.

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Bottani, Norberto. "The OECD International Education Indicators." Assessment in Education: Principles, Policy & Practice 1, no. 3 (January 1994): 333–50. http://dx.doi.org/10.1080/0969594940010308.

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Ball, Robert, and Jalil Halwachi. "Performance indicators in higher education." Higher Education 16, no. 4 (1987): 393–405. http://dx.doi.org/10.1007/bf00129112.

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Dissertations / Theses on the topic "Education indicators"

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Norton, Susan K. "Indicators of Success in the Blended Doctoral Cohort Model." Thesis, Concordia University Irvine, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10840659.

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For decades, the cohort model has been utilized to bring graduate degrees to working adults who cannot put their family lives and careers on hold to attend a university in the more traditional way. With the growing access to reliable digital tools, some cohorts have taken advantage of the ability to meet online with live-streaming applications such as Skype, GoToMeeting, and Adobe Connect. The blending of online instruction and face-to-face interaction has given birth to blended learning, a hybrid of synchronous and asynchronous learning. With this evolution of curriculum and instruction delivery, questions arise regarding the quality of graduate programs. Are the students who are investing time and money into these graduate degrees receiving the high-level of quality that they would expect if they were attending the university in a traditional way? How are they interacting with their peers in a scholarly fashion? How are the professors engaging the students in meaningful and scholarly ways? How do students and institutions know what is working for the success of the student and what needs to be improved? This study sought to uncover answers to some of these questions as it researched 16 doctoral students in one blended cohort in central California. With primarily qualitative methods, the study attempted to describe the phenomenon that is the blended doctoral cohort, specifically researching the participants’ perspective of themselves and the blended cohort model at the beginning of their program and, again, at the end of their program.

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Paige, R. Michael. "Internationalization of Higher Education : Performance Assessment and Indicators." 名古屋大学高等研究教育センター, 2005. http://hdl.handle.net/2237/16615.

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Downes, Paul, Erna Nairz-Wirth, and Viktorija Rusinaite. "Structural indicators for inclusive systems in and around schools. Analytical Report." Publications Office of the European Union, 2017. http://epub.wu.ac.at/5400/1/Structural%2DIndicators%2D.pdf.

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International evidence indicates that school systems need to change in order to tackle early school leaving and improve social inclusion in education and society. Policy-makers and school actors require practical tools to assist them in this process, made all the more urgent by the EU2020 headline target to reduce early school leaving. This report develops such practical tools; it is designed to inform strategic policy and practice by offering an innovative framework of structural indicators for early school leaving prevention and inclusion in school. It draws upon key European Council and Commission policy documents on early school leaving prevention, and also on the Paris Declaration 2015 on promoting common values of freedom, tolerance and non-discrimination through education, which includes a focus on social marginalization.
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Al-Hosni, Mohammed. "Ministry of Education of Oman : examinations marks and their relationships with educational indicators." Thesis, University of Salford, 2011. http://usir.salford.ac.uk/26520/.

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This study aims to provide a comprehensive view of the national educational system, and then to determine the values of some internationally-used indicators within Oman's schools, and their effects upon student performance in the 12 th grade examinations. From this analysis, the relationships between each variable and the optimal values for overall improvements in the total examination marks of students in the 12 th grade are derived. In pursuing this aim, the research conducts the first statistical analysis of ten educational indicators using data gathered by the Omani Ministry of Education. A logistic regression method is adopted to study repetition, drop-out, and promotion rates, using data pertaining to the school years 2006/2007-2007/2008. The analysis in this respect includes all governmental schools' students in grades 1-12. A linear mixed model is then used to explore data for the school years 2005/2006-2007/2008, relating to class size, school size, student/teacher ratio, teacher/class ratio, student age, student gender, and school gender mix. For these indicators, the analysis includes all the 12th grade students. The results reveal that girls are more likely to promote to the following grades than are boys, since they have low drop-out and repetition rates. This phenomenon causes the average student age of 12th grade girls to be less than that of boys. Grade 12 emerges as having the highest dropout rate, and grade 5 has the highest repetition rate. The distribution of the total marks of the 12 th grade students displays a long left tail, reflecting the fact that many students have low total marks. School size and class size are identified as having a negative effect upon the total examination mark. As the school size increases, so too do classes, but they are not allowed to become too large. The student age has the greatest significant effect on student performance among all the variables, student gender coming second in this ranking. Students who are young for their academic year are performing better than those who are older for the year, and girls perform better than boys. The research concludes that the basic education system in the Sultanate of Oman is in good health but that room for development and improvement does exist.
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Fung, Tak-chuen Daniel. "Using indicators in evaluating the implementation of educational aims : a case study /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B17597328.

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Kirby, Helen. "Stress Indicators of Kentucky Elementary Principals." TopSCHOLAR®, 1990. http://digitalcommons.wku.edu/theses/1774.

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Stress has become a problem to which people of all walks of life may relate, affecting the actions of the individual on both professional and personal levels. In the field of education, administrators often report a high level of stress, sometimes referred to as burnout. Much has been written about teacher stress, but very little research has been done on stress encountered by elementary principals. Research was conducted on stress as perceived by elementary principals in the Commonwealth of Kentucky for this study. The questionnaire used was compiled by the researcher using Koff, Laffey, Olson and Cichon’s table of Stress Ratings on Administrative Events as a source for the situations included. Demographic information that might influence stress was also incorporated in the questionnaire. The Kentucky Elementary Principal’s Questionnaire on Stress Indicators was administered to a random sample of 200 elementary principals. Of 200 questionnaires mailed, 115 were returned for a 57.5 percent response. The mean age of the respondents was 47 years of age, with 67.8 percent of the respondents being male and the majority married (84.3 percent). Respondents indicated that 64.3 percent plan to retire in the next 5 years. Of the 24 stressful situations, forcing the resignation or dismissal of a teacher had the highest rating – 4.26 – on a scale from 1 to 5. Dealing with unsatisfactory performance of professional staff was second with the rating of 3.96. The third highest stressful situation was legal action against the principal or the school with a rating of 3.90. Fourth, rated at 3.74, was involuntary transfer to another principalship. The lowest stress rating – 1.83 – was working with school district central administration. The data indicated that the significant correlations between demographic data and stressful situations were limited. Only two situations, namely forcing the resignation or dismissal of a teacher and dealing with unsatisfactory performance of professional staff, significantly correlated with the variables of male gender, age, and number of years as a principal.
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Myers, Donna J. "Assessing Quality Indicators in Asynchronous Undergraduate Distance Education Courses." NSUWorks, 2008. http://nsuworks.nova.edu/gscis_etd/743.

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The purpose of this study was to determine quality indicators within asynchronous distance education undergraduate courses at an accredited institution. The definition of quality is in and of itself obscure. Therefore, the identification of indicators or characteristics of quality in courses was a primary focus. The identification of such characteristics was based on input from the primary stakeholders in distance education, namely, the students, the administrators, and the instructors. Collecting data from each stakeholder group allowed for a comparison of those characteristics of quality deemed most important by each group. Initially an expert panel meeting was conducted to help categorize topic areas of importance as gleaned from the literature. Those topics were the basis for survey items that were submitted to a body of students, instructors, and administrators involved in distance education undergraduate courses. The survey was emailed to 2,360 participants that included 60 administrators, 300 instructors, and 2,000 students. The response rate was 60% from the administrator group, 61 % from the instructors, and 22.8% from the students for a total of 675 responses or a 28.6% return rate. The responses to the survey were analyzed using descriptive and inferential statistics. A comparison of the responses from the three stakeholder groups was performed. The data analyses indicated that each group agreed that technical issues, course design, class procedures and expectations, interaction, and content delivery are factors that identify quality in distance education courses. A consensus among all stakeholders as to what constitutes quality could be the catalyst for possible improvements to distance education courses in the future. Distance education is still forging new ground and input from the stakeholders should be advantageous for advancing and improving the quality of courses.
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Gittoes, Mark John. "Statistical analysis of performance indicators in UK Higher Education." Thesis, University of Bath, 2001. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.392036.

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Peasley, Donald D. "Ratings of quality indicators for secondary vocational education programs by education policy makers." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu1243604095.

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Boyd, Barbara A. "Early-Warning Indicators of High School Dropout." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1457276247.

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Books on the topic "Education indicators"

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Council, Canada Statistics Canada Canadian Education Statistics. Education indicators in Canada: Pan-Canadian Education Indicators Program. Ottawa: Canadian Education Statistics Council, 1996.

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Council, Canadian Education Statistics, ed. Education indicators in Canada. Toronto: Canadian Education Statistics Council, 1996.

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Guthrie, John T. Indicators of reading education. New Brunswick, N.J: Center for Policy Research in Education, 1987.

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Program, Pan-Canadian Education Indicators. Education indicators in Canada: Report of the Pan-Canadian Education Indicators Program, 2003. Ottawa: Statistics Canada, 2003.

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Canada, Statistics, and Council of Ministers of Education (Canada), eds. Education indicators in Canada: Report of the Pan-Canadian Education Indicators Program, 1999. Toronto, Ont: Statistics Canada, 2000.

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Canada. Statistics Canada. Canadian Education Statistics Council. Education indicators in Canada: Report of the Pan-Canadian Education Indicators Program, 1999. Ottawa: Statistics Canada, 2000.

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Program, Pan-Canadian Education Indicators. Education indicators in Canada: Report of the Pan-Canadian Education indicators program, 2005. Ottawa: Statistics Canada : Council of Ministers of Education, Canada, 2006.

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Phelps, Richard P. State indicators in education 1997. Washington, DC: U.S. Dept. of Education, Office of Educational Research and Improvement, National Center for Education Statistics, 1997.

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Foster, Pablo. Performance indicators and adult education. Bristol: The Staff College, 1991.

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United States. Department of Education. Forum guide to education indicators. Washington, D.C: National Center for Education Statistics, U.S. Dept. of Education, 2005.

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Book chapters on the topic "Education indicators"

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Egeln, Jürgen, and Christoph Heine. "Higher Education Indicators." In National Systems of Innovation in Comparison, 227–43. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/1-4020-4949-1_13.

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Johnes, Geraint. "Performance Indicators." In The Economics of Education, 161–83. London: Macmillan Education UK, 1993. http://dx.doi.org/10.1007/978-1-349-23008-2_9.

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Federkeil, Gero, Ben Jongbloed, Frans Kaiser, and Don F. Westerheijden. "Dimensions and Indicators." In Higher Education Dynamics, 97–124. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3005-2_7.

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Hoshino Neta, Carolina Shizue, and Sônia Regina da Cal Seixas. "Sustainability Indicators." In Encyclopedia of Sustainability in Higher Education, 1–5. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-63951-2_527-1.

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Hoshino Neta, Carolina Shizue, and Sônia Regina da Cal Seixas. "Sustainability Indicators." In Encyclopedia of Sustainability in Higher Education, 1676–80. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11352-0_527.

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Saha, Lawrence J., and Albert Tuijnman. "Comparative Indicators in Education." In International Handbook of Educational Research in the Asia-Pacific Region, 1123–36. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-3368-7_77.

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Jowett, Paul, and Margaret Rothwell. "Higher Education." In Performance Indicators in the Public Sector, 49–82. London: Palgrave Macmillan UK, 1988. http://dx.doi.org/10.1007/978-1-349-08987-1_5.

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Turner, David Andrew. "Performance Indicators and Benchmarking." In Quality in Higher Education, 29–39. Rotterdam: SensePublishers, 2011. http://dx.doi.org/10.1007/978-94-6091-684-7_4.

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Sarrico, Cláudia S. "Performance Indicators in Higher Education." In The International Encyclopedia of Higher Education Systems and Institutions, 2219–22. Dordrecht: Springer Netherlands, 2020. http://dx.doi.org/10.1007/978-94-017-8905-9_88.

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Sarrico, Cláudia S. "Performance Indicators in Higher Education." In Encyclopedia of International Higher Education Systems and Institutions, 1–5. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-017-9553-1_88-1.

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Conference papers on the topic "Education indicators"

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Wagenhals, Sabine, and Katja Kuhn. "Effectiveness Of Sustainability Indicators." In Contemporary Issues in Business, Management and Education ‘2012. Vilnius, Lithuania: Vilnius Gediminas Technical University Publishing House Technika, 2012. http://dx.doi.org/10.3846/cibme.2012.38.

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Pérez-Peñalver, María José, Frances Watts, Juan A. Marín-García, Lorena Atarés-Huerta, Begoña Montero-Fleta, Lourdes E. Aznar-Mas, Mª Ángeles Andreu-Andrés, Fernando González-Ladrón-de-Guevara, and Amparo García-Carbonell. "BEHAVIORAL INDICATORS OF INNOVATION COMPETENCE." In International Technology, Education and Development Conference. IATED, 2016. http://dx.doi.org/10.21125/inted.2016.0998.

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Bolgova, Elena V., and Marina V. Kournikova. "TERRITORIAL ACCOMMODATION INDICATORS." In Treshnikov readings – 2021 Modern geographical global picture and technology of geographic education. Ulyanovsk State Pedagogical University named after I. N. Ulyanov, 2021. http://dx.doi.org/10.33065/978-5-907216-08-2-2021-169-170.

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The article explores the conditions for the territorial distribution of the university network, substantiates the need for assessment, suggests indicators, gives recommendations for their use in strategic planning documents of the constituent entities of the Russian Federation.
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Dumitrescu, Laura. "SUSTAINABILITY INDICATORS FOR EDUCATION BUILDINGS CASE STUDY." In 13th SGEM GeoConference NANO, BIO AND GREEN � TECHNOLOGIES FOR A SUSTAINABLE FUTURE. Stef92 Technology, 2013. http://dx.doi.org/10.5593/sgem2013/bf6/s26.015.

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Suryadi, Kadarsah. "Key Performance Indicators in Higher Education Institution." In The International Symposium on the Analytic Hierarchy Process. Creative Decisions Foundation, 2007. http://dx.doi.org/10.13033/isahp.y2007.030.

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Yaman, Fatih, Onur Dönmez, and Işıl Kabakçı Yurdakul. "DIGITAL PARENTING: COMPETENCES AND INDICATORS." In International Conference on Education and New Learning Technologies. IATED, 2017. http://dx.doi.org/10.21125/edulearn.2017.0539.

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Tahzib, Baryalai. "SIGNIFICANCE OF THE ENVIRONMENTAL INDICATORS." In 14th SGEM GeoConference on ECOLOGY, ECONOMICS, EDUCATION AND LEGISLATION. Stef92 Technology, 2014. http://dx.doi.org/10.5593/sgem2014/b51/s20.081.

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Kobal Grum, Darja. "Psychological Indicators of Successful Inclusive Education: Systematic Review." In 1. mednarodna znanstvena konferenca Vloga inkluzivnega pedagoga v vzgoji in izobraževanju. Unviersity of Maribor Press, 2018. http://dx.doi.org/10.18690/978-961-286-161-2.9.

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Morais, Carlos, Paulo Alves, and Luisa Miranda. "Learning analytics and performance indicators in higher education." In 2017 12th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2017. http://dx.doi.org/10.23919/cisti.2017.7975812.

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Reymond, David, Khadija Dib, and Henri Kromm. "Data-mining and indicators in cyberinfrastructure." In 2012 IEEE Global Engineering Education Conference (EDUCON). IEEE, 2012. http://dx.doi.org/10.1109/educon.2012.6201068.

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Reports on the topic "Education indicators"

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Sanz, E., P. Alonso, B. Haidar, H. Ghaemi, and L. García. Key performance indicators (KPIs). Scipedia, 2021. http://dx.doi.org/10.23967/prodphd.2021.9.002.

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The project “Social network tools and procedures for developing entrepreneurial skills in PhD programmes” (prodPhD) aims to implement innovative social network-based methodologies for teaching and learning entrepreneurship in PhD programmes. The multidisciplinary teaching and learning methodologies to be developed will enable entrepreneurship education to be introduced into any PhD programme, providing students with the knowledge, skills, and motivation to engage in entrepreneurial activities. However, the use of the output of the project will depend on the nature and profile of the research or scientific field. In this context, key performance indicators (KPIs) form the base on which the quality and scope of the methodologies developed in the project will be quantified and benchmarked. The project’s final product will be an online tool that higher education students can use to learn entrepreneurship from a social network perspective. Performance measurement is one of the first steps of any project and involves the choice and use of indicators to measure the effectiveness and success of the project’s methods and results. All the KPIs have been selected according to criteria of relevance, measurability, reliability, and adequacy, and they cover the process, dissemination methods, and overall quality of the project. In this document, each KPI is defined together with the units and instruments for measuring it. In the case of qualitative KPIs, five-level Likert scales are defined to improve indicator measurability and reliability. The KPIs for prodPhD are divided into three main dimensions, depending on the stage of the project they evaluate. The three main dimensions are performance and development (which are highly related to the project’s process), dissemination and impact (which are more closely correlated with the project’s output), and overall project quality. Different sources (i.e., European projects and papers) have been drawn upon to define a set of 51 KPIs classified into six categories, according to the project phase they aim to evaluate. An Excel tool has been developed that collects all the KPIs analysed in the production of this document. This tool is shared in the Scipedia repository.
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Van Dusen, Matthew S. Identifying and Embedding Common Indicators of Compromise in Virtual Machines for Lab-Based Incident Response Education. Fort Belvoir, VA: Defense Technical Information Center, September 2015. http://dx.doi.org/10.21236/ada632497.

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Nelson, Gena. Special Education Math Interventions. Boise State University, March 2021. http://dx.doi.org/10.18122/sped_facpubs/133/boisestate.

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The purpose of document is to provide readers with the coding protocol that authors used to code 22 mathematics intervention meta-analyses focused on participants with or at-risk of disabilities. The author drafted this coding protocol based on the meta-analysis quality indicators recommended by Talbott et al. (2018, pp. 248–249); specifically, the author considered the variables presented in Table 1 of Talbott et al. and supplemented the information so that the variables and definitions were specific to the purpose of this systematic review. We coded each meta-analysis for 53 variables across eight categories, including: Quality of Clear Research Questions, Quality of Eligibility Criteria, Quality of Search Procedures, Quality of Screening Criteria, Quality of Coding Procedures, Quality of Research Participants and Contexts, Quality of Data Analysis Plan, and Quality of Reporting Results. The mean interrater reliability across all codes using this protocol was 87.8% (range across categories = 74% –100%).
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Nelson, Gena. Proportional Reasoning Interventions in Special Education Synthesis Coding Protocol. Boise State University, April 2021. http://dx.doi.org/10.18122/sped136.boisestate.

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The purpose of document is to provide readers with the coding protocol that authors used to code nine group and single case design intervention studies focused on proportional reasoning interventions for students (grades 5-9) with learning disabilities (LD) or mathematics difficulty (MD). The studies yielded intervention effects ranging from g = −0.10 to 1.87 and from Tau-U = 0.88 to 1.00. We coded all of the studies for variables in the following categories: study information, intervention features, dependent measures, participant demographics, LD and MD criteria and definitions, instructional content, study results, and quality indicators for group and single case design. The study quality indicator coding portion of this coding protocol was adapted from Gersten et al. (2005) and Horner et al. (2005). This code book contains variable names, code options, and code definitions. The mean interrater reliability across all codes using this protocol was 91% (range across categories = 82%–96%). The publication associated with this coding protocol is Nelson et al. (2020).
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Hogan, Michael, and Michael Gallaher. Quantitative Indicators for Country-Level Innovation Ecosystems. RTI Press, May 2018. http://dx.doi.org/10.3768/rtipress.2018.op.0051.1805.

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Innovation has been shown to be a key factor in determining a country’s competitiveness and economic growth potential. Through investments in education and research and development, many developing countries have tried to avoid the “middle income trap” of stagnation by working to create high-value employment opportunities. To better understand country-level readiness to innovate, we have compiled a set of publicly available data indicators and created a data tool to illustrate innovation capabilities and infrastructure by country. Our approach builds on and advances existing national innovation metrics by constructing transparent, publicly sourced indicators that emphasize changes over time and interrelationships between different indicators, as opposed to creating simple indices across groups of indicators. This occasional paper is targeted to an applied audience, explaining the methods used to assemble the data, an overview of the indicators, practical applications of the data, summary statistics, and data limitations. The data are not intended to be a tool for providing answers about innovation, but rather a starting point for future work including market landscaping, country-level diagnostics, and qualitative protocols for research.
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Schulz, Florian, Jörg Wolstein, and Henriette Engelhardt-Wölfler. The choice of indicators influences conclusions about the educational gradient of sex-specific alcohol consumption. OPUS, 2019. http://dx.doi.org/10.20378/irbo-55267.

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There has been considerable public interest in reports on harmful alcohol consumption of higher educated females. This study assesses the robustness of this finding with representative German data using ten different indicators of alcohol consumption. This cross-sectional study used data of the Epidemiological Survey on Substance Abuse from 2012. 4,225 females and 3,239 males represent the German population aged 18–64. It presents ten indicators of alcohol consumption by sex and education and provides group specific means and 95 %-confidence intervals. The main results are: (1) Higher educated males and females are drinking alcohol more frequently than lower educated males and females. (2) When drinking, higher educated males and females tend to drink less alcohol than lower educated males and females. (3) Only when using an indicator for hazardous alcohol consumption with different thresholds for males and females, the results indicate a pattern that significantly exposes hazardous alcohol consumption in the group of higher educated females. Concerning the choice of indicators, this study shows that sex-specific threshold-based indicators of alcohol consumption may lead to different conclusions as the majority of other indicators.
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Douglas, Bettina, and Ann Bonner. Nephrology-specific Clinical Performance Indicators for Nurse Practitioner Education in Australia: A Resource for Students and Clinical Support Team Members. Queensland, Australia: Queensland University of Technology, June 2017. http://dx.doi.org/10.5204/rep.eprints.106890.

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Schelzig, Karin, and Kirsty Newman. Promoting Inclusive Education in Mongolia. Asian Development Bank, November 2020. http://dx.doi.org/10.22617/wps200305-2.

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Children with disabilities suffer disproportionately from the learning crisis. Although they represent only about 1.5% to 5% of the child population, they comprise more than half of out-of-school children globally. Inspired by a commitment that every child has the right to quality education, a growing global drive for inclusive education promotes an education system where children with disabilities receive an appropriate and high-quality education that is delivered alongside their peers. The global commitment to inclusive education is captured in the Sustainable Development Goal 4—ensuring inclusive and equitable education and promoting lifelong learning opportunities for all. This paper explores inclusive education for children with disabilities in Mongolia’s mainstream education system, based on a 2019 survey of more than 5,000 households; interviews with teachers, school administrators, education ministry officials, and social workers; and visits to schools and kindergartens in four provinces and one district of the capital city. Mongolia has developed a strong legal and policy framework for inclusive education aligned with international best practice, but implementation and capacity are lagging. This is illustrated using four indicators of inclusive education: inclusive culture, inclusive policies, inclusive practices, and inclusive physical environments. The conclusion presents a matrix of recommendations for government and education sector development partners.
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Montefusco, Maria, and Kai Koivumäki. Nordic indicators for cooperation on disability – Monitoring the implementation of UNCRPD and Agenda 2030. Edited by Christina Lindström. Nordens välfärdscenter, June 2021. http://dx.doi.org/10.52746/ovbi5427.

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No person with a disability shall be left behind. This report presents suggested indicators for monitoring the implementation of the UN Convention on the Rights of Persons with Disability and Agenda 2030 in the Nordic region. The vision of the Nordic cooperation is to become the most integrated and sustainable in the world by 2030. The vision mirrors the sustainable development goals of Agenda 2030, according to which no-one shall be left behind. Persons with disabilities have the right to inclusion, and the Nordic countries monitor the developments of living conditions for persons with disabilities. All countries have also ratified the Convention on the rights of persons with disabilities and have high ambitions with regard to Agenda 2030. Throughout the region we face similar challenges concerning inclusion. Participation is not equal, not in employment, nor in education, economy, or health. But to improve this we need to see it. Even if a set of indicators is not the only way forward, they can help us measure if we are on the right track. In this report, we suggest a set of indicators that could be developed further and used to follow the developments towards inclusion and measure living conditions. By developing such a set of comparable indicators in the Nordic countries, we can see whether the countries separately and collectively follow the intentions of the UNCRPD to improve the living conditions of people with disabilities. The indicators are also an aid in the work to identify whether we are working correctly to achieve the Agenda 2030 targets.
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McGinnity, Frances, Emma Quinn, Philip J. O'Connell, Emer Smyth, Helen Russell, Bertrand Maître, Merike Darmody, and Samantha Arnold. Monitoring report on integration 2016. Edited by Alan Barrett, Frances McGinnitty, and Emma Quinn. ESRI, March 2017. http://dx.doi.org/10.26504/bkmnext330.

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This report examines migrant integration in Ireland in the areas of employment, education, social inclusion and active citizenship, and includes a special theme on migrant skills and competencies.The report presents a range of findings, including that a significant proportion of immigrants in Ireland are now Irish citizens, income poverty is higher among non-Irish groups than Irish, and employment rates are lower among African nationals than any other nationality grouping. The report uses indicators to measure different aspects of immigrant inclusion in Irish society, using the most recently available data.
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