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Journal articles on the topic 'Education indicators'

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1

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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2

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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3

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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4

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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5

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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6

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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8

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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10

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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11

King, Roger. "Evaluating Higher Education by Indicators." International Journal of Chinese Education 7, no. 2 (January 18, 2018): 181–92. http://dx.doi.org/10.1163/22125868-12340096.

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AbstractThis piece looks at indicators and data models in countries outside China to see if such approaches may contribute to the accountability and quality drives in higher education in China. It notes the policy movement in China from rapid student number expansion to more emphasis on quality and social purpose as desirable characteristics for its universities and colleges. The article remarks that establishing legibility to the center to enable effective but lighter-touch surveillance of higher education institutions is difficult in large mass sectors without a major commitment of resources and bureaucratic intervention which may not be desired by all stakeholders. Rather, it is suggested that utilizing good data and indicators may be one means of overcoming the difficulties in balancing central public control with the increased autonomy of universities in China.The article distinguishes between static data and dynamic data and goes on to consider the relevance of student posts on social media as an accurate guide to the student experience, a key component of the many institutional attempts in China to capture this dimension of quality.Overall, the chapter debates the extent to which an over-reliance on indicators and data may decontextualize the rich experiences and nuances found in the learning and teaching processes. There is the danger of over-simplification and the “exclusion of narrative” necessary for a full understanding of the knowledge process. Rather, the author supports a ‘variable geometry’ of approach to quality assessment and other forms of higher education accountability. This would seek to utilize both external data and indicators alongside a peer review methodology in which human opinion and assessment remains important.
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Scheerens, Jaap. "Perspectives on Education Quality, Education Indicators and Benchmarking." European Educational Research Journal 3, no. 1 (March 2004): 115–38. http://dx.doi.org/10.2304/eerj.2004.3.1.3.

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13

Sondari, Mery Citra. "Examining Job Description to Develop Job Performance Indicators for Higher Education Institution Based on MBNQA Education Criteria." Journal of Education and Vocational Research 4, no. 4 (April 30, 2013): 101–8. http://dx.doi.org/10.22610/jevr.v4i4.107.

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Higher Education Institution quality has important impact to national development, in this knowledge-based economy ages. However Higher Education Institutions (HEI) in Indonesia is far lag behind, compare to some of contries in the region of South East Asia.Therefore, HEI in Indonesia should benchmark to World Class Performance Frameworks, one of them is MBNQA. This paper aims to develop job performance indicators as guidance for HEI administrator to be able to achieve the MBNQA criteria. This paper linking organizational performance measurement indicators based on MBNQA, with individual job’s performance indicator. From case study at Faculty of Economics and Bussiness Universitas Padjadjaran, Indonesia, by using descriptive content analysis of actual job description, this research find that the MBNQA indicators are not fully covered in actual job description. Further research is still needed to validate the proposed job performance indicators.
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Costa, Giuseppe, and Teresa Spadea. "I dati per la misura delle disuguaglianze di salute: adeguatezza, accessibilitÀ, integrazione." SALUTE E SOCIETÀ, no. 1 (March 2009): 43–57. http://dx.doi.org/10.3280/ses2009-001005.

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- Scientific literature provides substantial evidence on how socioeconomic circumstances influence health, showing that this association holds with any indicator of socioeconomic position, independently of the theoretical approach on which is based. The open question on the indicators used to represent socioeconomic position is: are they equal proxy of a third variable, social classification or stratification, or do they capture specific dimensions of this stratification, the impact of which would be measurable independently of the others? This paper gives a tentative answer, from the epidemiological point of view, examining the indicators of socioeconomic position most used in health research (education, employment status, occupational class, income and goods), particularly focusing on their meaning, i.e. what they intend to measure, together with how data are elicited and the validity and limitations of the indicators. Keywords: indicators, education, social class, income, sources, epidemiology, social determinants of health. Parole chiave: indicatori, istruzione, classe sociale, reddito, fonti, epidemiologia, determinanti sociali di salute.
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15

Hoskins, Bryony. "Monitoring Active Citizenship in the European Union: the Process, the Results and initial Explanations." CADMO, no. 1 (June 2009): 55–71. http://dx.doi.org/10.3280/cad2009-001008.

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- This article is a descriptive account from an insider's perspective of the complex European process of the development of indicators on active citizenship. From this position, the article explains the process behind the development of two composite indicators that have been used to measure progress on active citizenship in Europe; The Active Citizenship Composite Indicator and the Youth Civic Competence Composite Indicator. The article details the results of these indexes for European Union countries and regions inside Europe. In addition, the article examines the differences between the results of the composite indicators, with correlations found between competence and action for Northern and Western European countries but not for Southern and Eastern European Countries. Using these results it discusses possible steps forward in the development of indicators on active citizenship looking towards new data from the IEA International Citizenship and Civic Education study.Keywords active citizenship, civic education, composite indicators, European Union, political participation.
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Ene, Andreea Bianca. "Distance Education in Romanian Higher Education." HOLISTICA – Journal of Business and Public Administration 9, no. 1 (May 1, 2018): 65–70. http://dx.doi.org/10.1515/hjbpa-2018-0005.

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Abstract The global diffusion of Internet involves economic, political and demographic factors that can predict in real time. In this article, we demonstrate that according to data provided by EUROSTAT, the number of people looking for a job in Romania it is correlated with specific query terms using Google Trends. Search engine data is used to “predict the present” values of different economic indicators. The obtained results are compared with the classical method of developing the economic indicators, with official EUROSTAT employment data. In this paper, we demonstrate that the new methods to extract the economic indicators from web technologies are accurate.
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17

Worgan, Pat. "Focus on Higher Education Performance Indicators in Higher Education." Management in Education 4, no. 2 (May 1990): 9–10. http://dx.doi.org/10.1177/089202069000400204.

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18

Artyukhov, A. Ye, T. A. Vasylieva, and S. V. Lyeonov. "An integrated method for evaluating the quality of education and university performance." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 3 (2021): 148–54. http://dx.doi.org/10.33271/nvngu/2021-3/148.

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Purpose. To create an integrated methodology for assessing educational and scientific activities of higher education institutions (HEI) following the recommendations of international ranking agencies and specific indicators that consider the institutions position at the national level. Methodology. The combined method of evaluation of the HEI activity is applied. Some evaluation indicators are inherent in the HEI (in whole or in part). Others have a specific numerical value. The calculation of the final ranking indicator is based on comparing universities according to the indicators from the methodology (ranking positions in the world educational and scientific space, education quality indicators, financial indicators, and quality of scientific activity) with the reference university, which has the best result for each indicator. Findings. An integrated methodology algorithm for assessing the educational and scientific activities of the HEI is presented and recommendations are given for the use of each of the indicators depending on the peculiarities of the ranking (for example, general ranking or ranking by direction). Originality. An integrated method of external evaluation of educational and scientific activities is proposed, considering both well-known indicators of world ranking agencies and specific (different from world ranking indicators) indicators for assessing universities activities at the national level. Practical value. The method allows determining some economic indicators of the dynamics (positive or negative) of university development and finding bottlenecks in the implementation of specific activities in the institutions educational and scientific activities. The methodology considers the actual educational activities (training of higher education institutions at all levels). It also allows us to assess the success of free economics in implementing scientific activities as a significant factor in creating new knowledge and improving educational services quality.
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KREIDEWEIS, JUDY. "Indicators of Success in Distance Education." CIN: Computers, Informatics, Nursing 23, no. 2 (March 2005): 68–72. http://dx.doi.org/10.1097/00024665-200503000-00005.

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20

Chen, I.-Shuo, Jui-Kuei Chen, and Fernando F. Padró. "Critical quality indicators of higher education." Total Quality Management & Business Excellence 28, no. 1-2 (June 8, 2015): 130–46. http://dx.doi.org/10.1080/14783363.2015.1050178.

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21

Pelgrum, Willem J., and Arjan T. Schipper. "Indicators of computer integration in education." Computers & Education 21, no. 1-2 (July 1993): 141–49. http://dx.doi.org/10.1016/0360-1315(93)90057-p.

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22

Salcedo, Hernando. "Quality indicators in Venezuelan higher education." Studies in Educational Evaluation 14, no. 1 (January 1988): 25–35. http://dx.doi.org/10.1016/0191-491x(88)90016-8.

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23

Skedsmo, Guri, and Stephan Gerhard Huber. "Data, indicators, and feedback in education." Educational Assessment, Evaluation and Accountability 33, no. 2 (May 2021): 251–54. http://dx.doi.org/10.1007/s11092-021-09362-y.

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24

Oveshnikova, Lyudmila Vladimirovna. "Information and Communication Technologies Indicators in Education: International and Russian Experience." Journal of Advanced Research in Dynamical and Control Systems 51, SP3 (February 28, 2020): 392–400. http://dx.doi.org/10.5373/jardcs/v12sp3/20201274.

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25

Xing, Danxia, and Chun Lu. "Evaluation of the Development Level of Information and Communications Technology in Education Based on the Entire-Array-Polygon Indicator Method: Taking the Questionnaire Survey Data of 13 Cities in Province W as an Example." Best Evidence in Chinese Education 7, no. 2 (March 30, 2021): 987–97. http://dx.doi.org/10.15354/bece.21.ar013.

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The objective assessment of the development level of information and communications technology (ICT) in education can support the government in formulating and implement ICT policies. The article first introduced the Entire-Array-Polygon (EAP) indicator method and then designed an evaluation indicator system which containing five first indicators and 31 secondary indicators. Finally, using the questionnaire survey data of 13 cities in Province W as an example, the EAP indicator method was used to carry out on the evaluation of ICT development level. The study drew the following conclusions: EAP indicator method can objectively assess the development level of ICT; the overall development level of ICT in the 13 cities in Province W is average and above, and most of them are level II. When using the EAP indicator method to assess the development level of ICT, experts do not need to determine the indicator's weight. Also, this method presents the evaluation results more concisely and intuitively, so it can be promoted as an essential method of evaluating on the development level of ICT in education.
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Climaco, Carmo. "Getting to Know Schools Using Performance Indicators: criteria, indicators and processes." Educational Review 44, no. 3 (January 1992): 295–308. http://dx.doi.org/10.1080/0013191920440307.

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Du, Guo Feng, Yan Zhao, Chao Ma, and Si Ping Yu. "Study on the Design of Co-Operative Education Quality Evaluation Indicators." Applied Mechanics and Materials 33 (October 2010): 583–87. http://dx.doi.org/10.4028/www.scientific.net/amm.33.583.

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In order to enrich the basic theory of co-operative education, in this paper, the author puts forward the basic concepts of co-operative education quality evaluation. On the basis of a large number of investigation and experts’ advice, reference to the influencing factors of co-operative education quality, fully considering the influence on the co-operative education quality as the school, the society and the students, three indicators in level one, 11 indicators in level two and 51 indicators in level three are constructed, which form the basic content of co-operative education quality evaluation indicator system. This research will further promote the development of co-operative education theory, and it is benefit to develop co-operation education better between universities and companies.
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Williams, J. Douglas, and Alan C. Kerckhoff. "The Challenge of Developing New Educational Indicators." Educational Evaluation and Policy Analysis 17, no. 1 (March 1995): 113–31. http://dx.doi.org/10.3102/01623737017001113.

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Proposals for national assessments of educational performance provide opportunities to develop valuable social indicators, but they also pose important problems of methodology and interpretation. Researchers in the U. S. have emphasized the importance of analyzing and reporting indicator data at the school level, mainly because much of the variation in schooling outcomes is at the school level, and because findings at this level are particularly relevant to policy and practice. We do not refute this, but contend that indicator data should be analyzed and reported also at state and district levels. We present an analysis of British data that shows there is important variation at higher levels of the system, and that it is possible to examine whether this variation is related to national or district-level policies. The article discusses the issues involved in conducting analyses at higher levels. We identify three kinds of indicators: gross productivity, net productivity, and inequality. Our analysis indicates the degree of interdistrict variation in Great Britain on all of these measures and the extent to which organizational features of the districts’ programs help explain that variation. Recommendations are made regarding the necessary features of any educational assessment if it is to produce useful social indicators.
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Villar, Luis M., Pedro S. de Vicente, Antonio Bolivar, Cristina Moral, Manuel Fernandez, Enriqueta Molina, Ma Jose Leon, Ma Jesus Gallego, and Purificación Perez. "Indicators of Staff Development." Educational Research and Evaluation 2, no. 3 (September 1996): 231–45. http://dx.doi.org/10.1080/1380361960020302.

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Watabe, Yuki, and Hiroshi Ota. "Developing a manageable system of internationalization indicators for universities in Asia." International Journal of Comparative Education and Development 23, no. 2 (April 29, 2021): 81–103. http://dx.doi.org/10.1108/ijced-11-2020-0081.

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PurposeThis study aims to construct a system of indicators for measuring the internationalization of universities allowing comparative self-assessment by universities in Asia.Design/methodology/approachTo achieve the aforementioned research purpose, the authors conducted three surveys and held an expert roundtable discussion. Two surveys were conducted, one in Japan and the other in Asia, to identify important indicators for measuring the internationalization of universities. Additionally, a survey of experts was conducted to identify effective indicators for benchmarking internationalization among universities in Asia. An analysis of each survey was examined during the roundtable discussion, and a system of internationalization indicators was constructed.FindingsThe three survey results showed similarities and differences between the relative importance accorded to 53 internationalization indicators by universities in Japan and in other Asian countries, as well as in the experts' perspectives on the effectiveness of each indicator for benchmarking. An analysis of those surveys resulted in 24 core internationalization indicators categorized into six key dimensions of university internationalization.Originality/valueThis study proposed a system of internationalization indicators based on an analysis of empirical research targeting universities in Asia. The resulting system reflects not only the opinions of academic experts but also the perspectives of its potential users, administrators in Asian universities. It consists of six internationalization dimensions with a manageable number of indicators, 24. These include both quantitative indicators and checklists of internationalization activities which can be used as quantitative or qualitative indicators.
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Maison, Maison, Darmaji Darmaji, Dwi Agus Kurniawan, Astalini Astalini, Utari Prisma Dewi, and Lia Kartina. "Analysis of science process skills in physics education students." Jurnal Penelitian dan Evaluasi Pendidikan 23, no. 2 (December 31, 2019): 197–205. http://dx.doi.org/10.21831/pep.v23i2.28123.

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This study aims to analyze students' science process skills on specific heat material by reviewing two aspects of basic science process skills indicators (observation and classification), and two indicators of integrated science process skills (identifying variables and making hypotheses). This research uses a descriptive quantitative method. In this study, the sample used was 35 students of physics education of batch 2018 who were randomly selected. The assessment instrument used was the science process skills observation sheet with the skill score used in the form of a Likert scale. The results of the study show that the students' mastery of basic science process skills on the observation indicator is 65% in the good category, 30% in the high category, and 10% in the category of not good to low, whereas, the classification indicators obtained are 54.3% and 37.1% of students have mastered classification skills in both good and high categories. The remaining 8.6% are classified in the not good category. For the mastery of integrated science process skills in the variable identification indicator, 60% of them are in the good category and 14.3% in the high category. The rest are in the category of not good and low. For the indicators of skills in making hypotheses, 65.7% and 14.3% are in the good and high categories. It proves that physics education students have mastery of science process skills that are in the good category.
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A. H. Elamir, Elsayed. "Determinant indicators for labor market efficiency and higher education and training: evidence from Middle East and North Africa countries." Problems and Perspectives in Management 18, no. 1 (March 12, 2020): 206–18. http://dx.doi.org/10.21511/ppm.18(1).2020.18.

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This study aims to explore the determinant indicators for the labor market efficiency and the higher education and training factors that can help in increasing the productivity in labor market and the quality in higher education and training, as well as pays attention to important relative indicators to improve the relationship between them. To achieve these aims the canonical correlation analysis is used as a bidirectional technique that allows studying the mutual relationship between two factors by taking advantage of available reports from 2012 to 2018 published by World Economic Forum (WEF). The results indicate that the extent of staff training, internet access, quality of education, and quality of management schools are the most important indicators in higher education and training and most correlated with labor market efficiency factor. The capacity to attract talent, pay and productivity, cooperation in labor-employer relations, and reliance on professional management are the most important indicators in labor market efficiency and the most correlated with higher education and training factor. The commonality analysis gives interesting results and shows that the explained variance in labor market efficiency and higher education and training depends on common indicators rather than a unique indicator.
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Oakes, Jeannie. "What Educational Indicators? The Case for Assessing the School Context." Educational Evaluation and Policy Analysis 11, no. 2 (June 1989): 181–99. http://dx.doi.org/10.3102/01623737011002181.

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A number of current federal and state efforts are attempting to create education indicator systems in the hope that these systems will improve the monitoring of the condition of education, inform policy decisions, and provide better accountability mechanisms. This article argues that the valid and useful indicator systems will include assessments of school context as well as of student outcomes. Context indicators can be used to monitor schooling resources and processes; they may help forestall educators’ tendency to narrow their programs in order to “look good” on limited outcome measures; and they can provide information about the context in which particular outcomes are achieved. A review of the schooling literature suggests three general constructs that can serve as grounding for developing school context indicators: access to knowledge, press for achievement, and professional teaching conditions.
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Schmitz, Constance C. "Assessing the Validity of Higher Education Indicators." Journal of Higher Education 64, no. 5 (September 1993): 503. http://dx.doi.org/10.2307/2959990.

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Lopez-Leyva, Santos, and Gary Rhoades. "Country Competitiveness Relationship with Higher Education Indicators." Journal of technology management & innovation 11, no. 4 (2016): 47–55. http://dx.doi.org/10.4067/s0718-27242016000400007.

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36

Gupta, Preeti, Deepti Mehrotra, and T. K. Sharma. "Identifying Knowledge Indicators in Higher Education Organization." Procedia Computer Science 46 (2015): 449–56. http://dx.doi.org/10.1016/j.procs.2015.02.043.

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37

Bourner, Tom. "Book Review: Performance Indicators in Higher Education." Industry and Higher Education 5, no. 3 (September 1991): 189–90. http://dx.doi.org/10.1177/095042229100500313.

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38

Supovitz, Jonathan, Ellen Foley, and Jacob Mishook. "In Search of Leading Indicators in Education." education policy analysis archives 20 (July 10, 2012): 19. http://dx.doi.org/10.14507/epaa.v20n19.2012.

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Data have long been considered a key factor in organizational decision-making (Simon, 1955; Lindblom & Cohen, 1979). Data offer perspective, guidance, and insights that inform policy and practice (Newell & Simon, 1972; Kennedy, 1984). Recently, education policymakers have invested in the use of data for organizational improvement in states and districts with such initiatives as Race to The Top (United States Department of Education, 2010) and the development of statewide longitudinal data systems (Institute for Education Sciences, 2010). These and other initiatives focus attention on how data can be used to foster learning and improvement. In other fields, including economics and business, much work has been done to identify leading indicators that predict organizational outcomes. In this paper, we conceptualize how leading indicators might be used in education, using examples from a small sample of school districts with reputations as strong users of data. We define leading indicators as systematically collected data on an activity or condition that is related to a subsequent and valued outcome, as well as the processes surrounding the investigation of those data and the associated responses. Identifying leading indicators often prompts improvements in a district’s system of supports. To develop this concept, we describe four examples of how districts identified and used key indicators to anticipate learning problems and improve student outcomes. We also describe the infrastructure and other supports that districts need to sustain this ambitious form of data use. We conclude by discussing how leading indicators can bring about more intelligent use of data in education.
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Lee, S. "Education, Other Socioeconomic Indicators, and Cognitive Function." American Journal of Epidemiology 157, no. 8 (April 15, 2003): 712–20. http://dx.doi.org/10.1093/aje/kwg042.

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Schmitz, Constance C. "Assessing the Validity of Higher Education Indicators." Journal of Higher Education 64, no. 5 (September 1993): 503–21. http://dx.doi.org/10.1080/00221546.1993.11778445.

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Bunting, Ian. "Performance indicators for South Africa's education systems." Social Dynamics 23, no. 1 (January 1997): 139–53. http://dx.doi.org/10.1080/02533959708458624.

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42

Haddow, Gaby, and Paul Genoni. "Australian Education Journals: Quantitative and Qualitative Indicators." Australian Academic & Research Libraries 40, no. 2 (June 2009): 88–104. http://dx.doi.org/10.1080/00048623.2009.10721388.

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43

Power, Colin. "Higher education indicators: An exercise in interpretation." International Journal of Educational Research 14, no. 4 (January 1990): 353–61. http://dx.doi.org/10.1016/0883-0355(90)90006-t.

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Mohd Yassin, Yasni Nurul Huda, Azianti Ismail, Awaluddin Mohd Shaharoum, and Akmal Aini Othman. "Institutional Reform Success Indicators in Higher Education." Jurnal Intelek 16, no. 1 (January 26, 2021): 225–32. http://dx.doi.org/10.24191/ji.v16i1.384.

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Reformation of higher education (HE) institutions is fundamental in improving and strengthening its academic institutions of HE independence. Moving on now to consider the present academic community must undergo a process of change to improve the teaching, research, management functions, and operations of the institutions, which are incremental in a sustainable manner. In essence, there are many indicators of success that have been identified in studies conducted for other industries. The major trend currently observed is the reformation of the HE institutions in major countries mimicking the for-profit industries to make them more competitive. This paper integrates and advances pertinent factors that enable an effective and successful reformation process from the Asian HE perspective by reviewing relevant reformation literature on the matter. This systematic review has developed three (3) core themes relating to the importance of leadership, policy development and governance, and autonomy, which regards higher institutional practices from within the Asian region reviewed. And to conclude, the internal factor is dominating the indicators for HE reforms success. This finding seeks to offer future research to be extended from established institutions from other developed countries as a comparison when planning and implementing change initiatives at the institutional level.
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Zgheib, Rosine, and Amira Van Loan. "Changes in Internationalization at Home in Arab Higher Education Institutions." Contemporary Arab Affairs 14, no. 1 (March 1, 2021): 91–112. http://dx.doi.org/10.1525/caa.2021.14.1.91.

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As global marketplace competition increases, higher education institutions (HEIs) in the Arab world purposefully integrate international and intercultural dimensions into their curriculum, known as internationalization at home (IaH), to empower graduates with the tools necessary to strengthen their economies and be productive global citizens. The purpose of this research is to report changes in the internationalization strategies of fourteen randomly selected Arab world HEIs by looking at six IaH indicators in their mission statements, course descriptions, and strategic plans. The results prioritize internationalization in the HEIs’ mission statements with a twenty per cent increase in the number of indicators between academic years 2014–15 and 2019–20. Additionally, through course descriptions/titles, we found some universities were offering up to 350 courses promoted per indicator, with others offering as few as one course per indicator. We also found sixty-five per cent of the HEIs do not have explicit strategic plans, or rather no or implicit strategic plans incorporating internationalization. As the Arab world attempts to strengthen its economies, HEIs should continue to increase IaH efforts by infusing more of the indicators in their mission statements, courses, and strategic plans.
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Hong, In-Kyoung, Hyung-Kwon Yun, Young-Bin Jung, Sang-Mi Lee, and Choon-soo Lee. "Resetting the Evaluation Indicators for School Garden Education Service." Journal of People, Plants, and Environment 24, no. 3 (June 30, 2021): 245–56. http://dx.doi.org/10.11628/ksppe.2021.24.3.245.

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Background and objective The vitalization of urban agriculture has increased various forms of experience-based education using school gardens, which raised the importance of school gardens in terms of value as well as the need to develop an implementation system for education-based agricultural experience service using school gardens. Thus, we reset the evaluation indicators from the previous study to establish objective evaluation indicators that enable quantitative comparison of school garden education services. Methods Analytic hierarchy process (AHP) and direct question (DQ) surveys were conducted on 20 experts from October 12 to 19, 2020 after establishing the purpose and subjects of evaluation, and then the weights were calculated using the Expert Choice 2010 program. Results First, we analyzed the problems of the previous indicators by categorizing the performance indicators and comparing and verifying them with six requirements of valuation. Then, we added ‘welfare values’ and established sub-indicators accordingly. The importance of value indicator in AHP was in the order of education values (0.544), health values (0.182), welfare values (0.164), environmental values (0.062), and economic values (0.049). The importance of environmental and economic values was relatively low, less than 0.1. The importance of sub-indicators was highest in cultivating character (0.144), followed by enhancing ecological sensitivity (0.141) > promoting mental health (0.134) > cultivating agricultural literacy (0.120) > improving social skills (0.104). And mitigating climate change in environmental values was lowest (0.009). Increase in income was the lowest (0.036). This can be regarded as the expression of change to increase the educational effect based on collective life and the connotative meaning of ‘school’. In the case of DQ, the AHP weight and order were the same, but the environmental and economic values were relatively low, and the result was different from AHP weight. For sub-indicators, the importance in DQ was highest in promoting mental health (0.136), followed by promoting physical health (0.085), ]cultivating character (0.082), social integration (0.072), and enhancing ecological sensitivity (0.071). After reviewing related experts, we came up with 5 evaluation indicators and 16 sub-indicators for school garden education service, which are objective evaluation indicators that enable quantitative comparison. Conclusion In the future, we will validate the socioeconomic values of school garden education services and contribute to revitalizing school gardens by establishing policy alternatives for effective operation and management of school gardens.
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O'Reilly, Elana M., and Richard R. Verdugo. "Safe School Indicators." Education and Urban Society 31, no. 3 (May 1999): 334–48. http://dx.doi.org/10.1177/0013124599031003005.

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Nowaczyk, Ronald H., and David G. Underwood. "Indicators of Research Quality." education policy analysis archives 3 (December 22, 1995): 20. http://dx.doi.org/10.14507/epaa.v3n20.1995.

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The move toward more public accountability of institutions of higher education has focused primarily on undergraduate education. Yet, many institutions view research as an important component of their mission. Much of the literature on assessing research quality has relied on quantitative measures such as level of outside funding and number of publications generated. Focus groups consisting of research faculty were conducted at a landgrant university. Faculty were asked to evaluate current indicators of research quality as well as to suggest additional measures. While faculty recognized the need for the traditional measures, they cautioned against over-reliance on these indicators. Additional indicators focusing on graduate education as well as external peer reviews were recommended. Developing indicators that provide evidence of long-term impact on social and scientific advancement was suggested.
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van Petegem, Peter, and Jan Vanhoof. "Feedback of Indicators to Schools." European Educational Research Journal 3, no. 1 (March 2004): 246–77. http://dx.doi.org/10.2304/eerj.2004.3.1.8.

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Walberg, Herbert J., Norberto Bottani, and Isabelle Delfau. "OECD Indicators of Educational Productivity." Educational Researcher 19, no. 5 (June 1990): 30. http://dx.doi.org/10.2307/1176104.

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