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1 |
Teachers’ Attitudes towards the Environment and Environmental Education: An Empirical StudyFilippos Zachariou, Eleni Tsami, Christos Chalkias, Sotirios Bersimis
pp. 1567-1593 | Article Number: ijese.2017.100
Abstract The aim of this study is to explore teachers’ attitudes towards environmental education (EE), and the relation of these attitudes with other socio-demographic factors, such as area of residence and local environmental conditions. We focus on the case of Viotia prefecture. Our results indicate that the teachers’ attitudes towards EE are strongly related to their attitudes towards the environment and environmental problems in their areas of residence, while knowledge and information on environmental issues are strongly related to the positive attitudes towards EE. The results of this study indicate possible factors involved in the formation of the attitudes of EE teachers and also possible aspects to be considered for the design of effective policies for EE teacher training. Keywords: Environment, Environmental Education, Teachers’ Attitudes, environmental problems, Greece References Ajzen, I. & Fishbein,M. (1980). Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs, N.J.: Prentice-Hall. Bartholomew, D. J., Steele, F., Galbraith, J., & Moustaki, I. (2008). Analysis of Multivariate Social Science Data (2 ed.). New York: Chapman & Hall/Crc. Beder S. (2006). Environmental Principles and Policies: An Interdisciplinary Introduction, UNSW Press, Sydney, Australia. Berenguer J. (2007). The Effect of Empathy in Pro-environmental Attitudes and Behaviors. Environment and Behavior, 39: 269 Borg, C., Gericke, N., Höglund, H. O., & Bergman, E. (2012). The barriers encountered by teachers implementing education for sustainable development: discipline bound differences and teaching traditions. Research in Science & Technological Education, 30(2), 185-207. Brody, S.D., Highfield, W., & Alston, L. (2004). Does location matter?: Measuring environmental perceptions creeks in two San Antonio watersheds. Environment and Behavior 36(2), 229-250. Buttell, F. H. (1987). New directions in environmental sociology. Annual Review of Sociology, 13, 465-488. Chawla L. & Cushing Debra Flanders (2007). Education for strategic environmental behavior, Environmental Education Research, 13: 4, 437-452. Cochran, William G. (1977). Sampling techniques (Third ed.). Wiley. Connell, S., Fien, J.,Sykes, H. & Yencken, D. (1998). Young people and the environment in Australia: beliefs, knowledge, commitment and educational implications, Australia Journal of Environmental Education. Corraliza, J. A., & Berenguer, J. (2000). Environmental Values, Beliefs, and Actions A Situational Approach. Environment and behavior, 32(6), 832-848. Dretske F.The Role of the Percept in Visual Cognition, Minnesota Studies in the Philosophy of Science: Perception and Cognition, vol. 9, ed. W. Savage, pp. 107-125. Esa, N. (2010). Environmental knowledge, attitude and practices of student teachers. International Research in Geographical and Environmental Education, 19(1), 39-50. Filippou G. – Christou K. (2001). Education Texts. Sentimental factors and learning of mathematics Atrapos (in Greek). Foster, R. H., & McBeth, M. K. (1994). Urban-rural influences in U.S. environmental and economic development policy. Journal of Rural Studies, 12(4), 387-397. Harris P. G. (2006). Environmental Perspectives and Behavior in China: Synopsis and Bibliography. Environment and Behavior 38: 5. Hart P., (2003). Teachers' Thinking in Environmental Education (Rethinking Childhood, V. 29), New York: Peter Lang. Huckle, J, (1999). Locating Environmental Education between modern capitalism and postmodern socialism: a reply to Lucie Sauve. Canadian journal of Environmental Education. Hungerford, H. R., Volk, T. L., Knapp, D. H. & Bluhm, M. (1990). Global Change Environmental Education Module. UNESCO-UNAPT International Environmental Education Program. IEEP. Hwang S. (2009). Teachers’ environmental education as creating cracks and ruptures in school education: a narrative inquiry and an analysis of teacher rhetoric, Environmental Education Research, 15: 6, 697-714. Jones, R. E., & Dunlap, R. E. (1992). The social bases of environmental concern: Have they changed over time? Rural Sociology, 57(1), 28-47. Kish L. (1995). Survey Sampling Wiley. New York. Liarakou, G., Gavrilakis, C., & Flouri, E. (2009). Secondary school teachers’ knowledge and attitudes towards renewable energy sources. Journal of Science Education and Technology, 18(2), 120-129. Liarakou, G., Athanasiadis, I., & Gavrilakis, C. (2011). What Greek Secondary School Students Believe about Climate Change?. International Journal of Environmental and Science Education, 6(1), 79-98. McLeod D. B. & McLeod S. H. (2002). Beliefs and mathematics education: Implications for learning, teaching, and research. In G. Leder, E. Pehkonen, & G. Toerner (Eds.), Beliefs: A Hidden Variable in Mathematics Education?, Dordrecht: Kluwer, 115-123. Megalofonos S. (2001). Special issues in quality and quality and environment, Hellenic Open University Patra (in Greek). Nannos N, Bersimis S, Georgakellos D. (2013). Evaluating climate change in Greece through the insurance compensations of the rural production damages. Global and Planetary Change. Orr D. W., (2004). Earth in Mind: On Education, Environment, and the Human Prospect. Palmer J. (1998). Environmental Education in the 21st Century: Theory, Practice, Progress and Promise, London: Routledge. Papadopoulos D. (2005). Development, implementation and evaluation of environmental education programs on solid waste management. National & Kapodistrian University of Athens (in Greek). Raudsepp, M. (2001). Some socio-demographic and socio-psychological predictors of environmentalism. Trames, 5(55/50), 3, 355-367. Ruffell, M., Mason, J., Allen, B. (1998). Studying attitude to mathematics, Educational Studies in Mathematics. 1, 1-18. Samdahl, D. M.,&Robertson, R. (1989). Social determinants of environmental concern: Specification and test of the model. Environment and Behavior, 22, 57-81. Schiza K. (2005). Environmental Education: an education for the reality and the area we share, Environmental Policy, 5, 11-17 (in Greek). Schultz, P. W. (2000). Empathizing with nature: The effects of perspective taking on concern for environmental issues. Journal of Social Issues, 56, 391-406. Schultz, P. W., Shriver, C., Tabanico, J. J., & Khazian, A. M. (2004). Implicit connections with nature. Journal of Environmental Psychology, 24, 31-42. Shephard K., Samuel M., Smith N. and Deaker L., (2009). Benchmarking the environmental values and attitudes of students in New Zealand’s post-compulsory education, Environmental Education Research, 15: 5, 571-587. Skinner B. F. (1953). Science and Human Behavior. New York: McMillan. Smith A. D., (2001), "Perception and Belief", Philosophy and Phenomenological Research, vol. LXII, no 2, March 2001 Spiropoulou D. (2002). Environmental Education in the flexible zone: weather and climate-protection of atmosphere. Review of Scientific and Educational Issues 6, 160-171 (in Greek). Trikaliti, A. (1995). Exploration of cognitive, sociological and psychological factors in Environmental Education. National & Kapodistrian University of Athens (in Greek). Tsantas N., Moysiadis Ch., Bayiatis D. and Chadjipantelis T. (1999). Data Analysis using statistical packages (in Greek). Zitis Publications, Thessaloniki. Van Liere, K. D.,&Dunlap, R. E. (1980). The social bases of environmental concern: A review of hypotheses, explanations and empirical evidence. Public Opinion Quarterly, 44(2), 181-197. Waktola D. K., (2009). Challenges and opportunities in mainstreaming environmental education into the curricula of teachers’ colleges in Ethiopia, Environmental Education Research, 15: 5, 589-605. Zachariou F. (2008). Views on environmental quality by students and teachers in Viotia prefecture. Hellenic Open University (in Greek). |
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Identifying Variables to Incorporate in an Extended TPB Model with Regards to HIV Testing in Kinshasa, DR CongoLutete Christian Ayikwa & Johan W. de Jager
pp. 1595-1603 | Article Number: ijese.2017.101
Abstract The present study intended to identify environmental and socio-demographic factors that are predictive of acceptance of HIV testing in order to extend the Theory of Planned Behaviour model (TPB), which will better explain the health-related behaviour under investigation. Data analysed using multiple regression were obtained by means of a cross-sectional face-to-face questionnaire administered by trained interviewers. The study proceeded to a mixed two-stage stratified random, cluster random and quota sampling to sample the population of under investigation. It is clear from the findings that only the levels of education and knowledge about the meaning of HIV/AIDS are eligible to be incorporated alongside the traditional TPB components in order to improve the model. Although both level of education and level of knowledge are statistically significant predictors of acceptance of HIV testing, the first variable made the strongest contribution. Keywords: HIV/AIDS, Kinshasa, Social marketing, Testing, Theory of Planned Behaviour (TPB) References Ayikwa, L.C., De Jager, J.W., and Van Rensburg, D.B.J. (2014). Scrutiny of the association between the socio-economic status and magnitude of HIV/AIDS in the general population of Kinshasa. Journal of Economics and Behavioural Studies, 6(3), 181-187. Bhattacharya, S. (2012). Unrealised obligations: Implementing HIV and AIDS policy in a large international development organisation. University of Pretoria, Department of Sociology. Unpublished PhD Thesis. Blythe, J. (2013). Introduction to consumer behaviour. Sage Publications: London. Chapter 1, 1-22. Cai, Y., Ye, X., Shi, R., Xu, G., Shen, L., Ren, L., and Huang, H. (2013). Predictors of consistent condom use based on the Information-Motivation-Behavior Skill (IMB) model among senior high school students in three coastal cities in China. BMC infectious Diseases, 13, 262-269. Cha, E.S., Kim, K.H., and Patrick, T.E. (2008). Predictors of intention to practise safer sex among Korean college students. Archives of Sexual Behavior, 37, 641-651. Corno, L. & De Walque, D. 2007. The determinants of HIV infection and related sexual behaviours: evidence from Lesotho. Policy Research, Working Paper Series 4421. The World Bank. Heirman, W & Walrave, M. (2012). Predicting adolescent perpetration in cyberbullying: An application of the theory of planned behavior. Psicothema, 24(4), 614-620. Pallant, J. (2010). SPSS Survival Manual: European Edition: Berkshire: McGraw-Hill. Protogerou, C. & Turner-Cobb, J. (2011). Predictors of non-condom use intention by university students in Britain and Greece: The impact of attitudes, time perspective, relationship status and habit. Journal of Child & Adolescent Mental Health, 23(2): 91-106. ProVIC. (June, 2012). Combating HIV/AIDS in the Democratic Republic of Congo. Available at: http://www.path.org%2Fpublications%2Ffiles%2FHIV_provic_bro.pdf&ei=kISLVIuMGtfZavzjgKgD&usg=AFQjCNEny0gQ2WnmTZQqc1gpq6B5C3gkmw&bvm=bv.81456516,bs.1,d.d24. Accessed on the 13th December 2014. Robinson, N.G., Masser, B.M., White, K.M., Hyde, M.K., and Terry, D.J. (2008). Predicting intentions to donate blood among non-donors in Australia: An extended Theory of Planned Behavior. Transfusion, 48(12). 2559-2567. Sutton, S. (2004). Determinants of Health-Related Behaviours: Theoretical and Methodological Issues. The Sage Handbook of Health Psychology. Chapter 4, 94-126. Tabachnick, B.G. & Fidell, L.S. (2007). Using multivariate statistics: American edition: Boston: Pearson Education. Taylor, D., Bury, M., Campling, N., Carter, S., Garfied, S., Newbould, J., and Rennie, T. (2006). A Review of the use of the Health Belief Model (HBM), Theory of Reasoned Action (TRA), Theory of Planned Behaviour (TPB), and Trans-Theoretical Model (TTM) to study and to predict health-related behaviour change. The Department of Practice and Policy. The School of Pharmacy, University of London. Turchik, J.A. (2010). The Prediction of Sexual Risk Behaviour among College Students using the Theory of Planned Behaviour. Ohio University, College of Arts and Sciences. Unpublished PhD Thesis. |
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Teacher Educators & Teacher Trainees Awareness and Application towards Bloom’s Taxonomy in Thiruvannamalai DistrictS. Senthilkumara & Bharathi K Kumar
pp. 1605-1615 | Article Number: ijese.2017.102
Abstract Education plays a vital role in development of any country. In this context, Bloom’s taxonomy play a key role in defining learning objectives and assessment of the courses. The purpose of the study is to identify the teacher educators’ and teacher trainees’ awareness and application towards the Bloom’s taxonomy in Thiruvannamalai District, Tamil Nadu. The factors taken for the study are perceived easy of use, perceived usefulness, perceived barriers, adoption of bloom’s taxonomy and its effectiveness. The main study of this research was conducted among 150 samples, in which 50 samples includes teacher educators and another 100 samples includes teacher trainees from five different teacher training institutes located at Tiruvannamalai District. The samples were chosen based on Non-Probability sampling (i.e. Quota sampling technique), since few teacher educators and trainees were not shown their interest to respond to the research. The data collected were analyzed through IBM SPSS 24.0 and IBM AMOS 24.0 software package and descriptive statistical analysis and Structural Equation Modeling analysis were performed. The results of study evident that perceived easy of use, perceived usefulness, perceived barriers, adoption of bloom’s taxonomy is having impact on perceived effectiveness of Bloom’s taxonomy, however teacher educators and Teacher trainees still need more training programmes to be well-versed in this concept in order to minimize the perceived barriers effect on implementation of Bloom’s taxonomy, which will improve perceived easy of use, perceived usefulness and its adoption in their teaching learning process effectively. Keywords: Bloom’s taxonomy, Perceived Easy of use, Perceived usefulness, Perceived Barriers, Adoption References Aviles, Christopher B, Teaching and Testing for Critical Thinking with Bloom's Taxonomy of Educational Objectives, available at https://eric.ed.gov/?id=ED446023 Daire Hooper D, Coughlan J, Mullen M. (2008). Structural Equation Modelling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods, 6(1), 53-60. Deal, John; Hegde, S. Aaron (2013). Seinfeld and Economics: How to Achieve the Revised Bloom's Taxonomy in an Introductory Economics Class., International Journal of Teaching & Learning in Higher Education, 25 (3), 388-395. Hair, J. F., Anderson, R. E., Tatham, R. L., and Black, W. C. (1998). Multivariate Data Analysis (5th Edition), Prentice-Hall International, Inc.: Newjersy. Hair, J., Black, W., Babin, B., Anderson, R., Tatham, R. (2006). Multivariate data analysis (6th ed.). Pearson Prentice Hall: Uppersaddle River, N.J., 172-175. Hamad I. Odhabi (2007). Investigating the impact of laptops on students’ learning using Bloom's learning taxonomy, June, DOI: 10.1111/j.1467-8535.2007.00730.x. John W. Hansen, Cognitive Styles and Technology-Based Education, available at http://scholar.lib.vt.edu/ejournals/JOTS/Winter-Spring-1997/PDF/4-Hansen-article. Martin Valcke, Bram De Wever, Chang Zhu, and Craig Deed (2009). Supporting active cognitive processing in collaborative groups: The potential of Bloom's taxonomy as a labeling tool, December, DOI: 10.1016/j.iheduc.2009.08.003. Razzouk, N., & Razzouk, J. (2011). Analysis In Teaching With Cases: A Revisit To Blooms Taxonomy Of Learning Objectives. College Teaching Methods & Styles Journal (CTMS), 4(1), 49-56. doi:http://dx.doi.org/10.19030/ctms.v4i1.5049 Robert Horner, Anita Zavodska, and John Rushing, (2005). How Challenging? Using Bloom's Taxonomy To Assess Learning Objectives In A Degree Completion ProgramJournal of College Teaching & Learning, 2(3), 47-52. Tabachnick, Barbara G, and Linda S. Fidell (2007), “Using Multivariate Statistics”, Boston: Pearson / Allyn& Bacon, pp. 120-124. Toni Noble (2004). Integrating the Revised Bloom’s Taxonomy With Multiple Intelligences: A Planning Tool for Curriculum Differentiation, Teachers College Record, 106(1), 193–211. Wheaton, B., Muthen, B., Alwin, D., F., and Summers, G. (1977), Assessing Reliability and Stability in Panel Models, Sociological Methodology, 8(1), 84-136. |
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The Influence of Jigsaw Learning Model on the Ability of Resolution Natural Science of Middle East Junior High School Students IndonesiaMamik Suendarti
pp. 1617-1622 | Article Number: ijese.2017.103
Abstract The purpose of this research is to know the influence of jigsaw learning model on the ability of problem solving of Natural Science. The research method used is experiment method. Samples were taken as many as 60 students with 30 control class students and 30 students of experimental class. Data collection was done by direct questionnaire to sample. Data analysis uses descriptive statistics such as searching for mean, median, mode, standard deviation, and inferential statistics to find coefficients. The results showed: There is influence of jigsaw learning model to the ability of problem solving of Natural Science. Keywords: Mamik Suendarti References Arikunto, S. (2010). Research Procedures A Practice Approach. Jakarta: Rineka Cipta. Isjoni. (2007). Cooperative Learning. Bandung: Alfabeta Kirno, S. 2010). Efforts to Increase Achievement of Science Learning-Fission Ka through Implementation of Guided Inquiry Learning Strategy In Grade VIII Students at MTsN. Journal of Educational Science, 3, 192-193 Lie, A. (2006). Cooperative Learning: Practicing Cooperative Learning at. Classrooms. Jakarta: Grasindo Muhsetyo, G. (2007). Elementary Mathematics Learning. Jakarta: Open University. Portoles and Sanjose. (2008). Pedagogy problem solving. Direct access: http://sondangrina.blogspot.com/2013/03/pedagogi-black-masalah.html accessed 9 May 2017 Selcuk, (2008). The Effects of Problem Solving Instruction on Physics Achievement, Problem Solving Performance and Strategy Use. Direct access: http://www.lajpe.org/sep08/01_Gamze_Sezgin.pdf Sugiono. (2013). Educational Research Methods Quantitative Approach. Bandung: Alfabeta Suprijono, A. (2009). Cooperative Learning. Surabaya: Student Library |
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Impact of Self-Regulated Learning on Teaching-Learning Process among Teacher Educators in Tiruvannamalai DistrictN. Mahendiran & Bharathi K Kumar
pp. 1623-1632 | Article Number: ijese.2017.104
Abstract Self-regulation is a comprehensive concept includes a number of interdependent aspects. It includes both affective capacities (i.e. moods, feelings and emotions) and cognitive capacities (i.e. beliefs, perceptions and knowledge). Learning and attainment are best understood when we acknowledge the interactions between affective and cognitive processes. The purpose of this study is to explore the impact of impact of self-regulated learning on teaching-learning process among teacher educators in Tiruvannamalai District. This study followed descriptive research design. The primary data of the research was collected through structured questionnaire. The main study was conducted among the sample of 110 teacher educators working in ten different Teacher Training Institute located at various part of Tiruvannamalai District. The quota sampling technique was adopted to select samples from population (i.e. from each training institute 11 teacher educators were chosen as sample). The descriptive statistical tools and inferential statistical tools were used for primary data analysis. The results of the study proved that there is a significant attitudinal difference among the teacher educators based on their gender and age group, however, the mean difference among them very nominal and at the same time their mean score is high, which indicates that they accepts self-regulated learning has positive impact on teaching-learning process through use of latest teaching pedagogics and sharing latest information happening in education sector. Keywords: Self-regulated learning, Teaching-Learning Process, Teacher Educators, Teaching Education References Carolina Mega, Lucia Ronconi, and Rossana De Beni, What Makes a Good Student? How Emotions, Self-Regulated Learning, and Motivation Contribute to Academic Achievement, February 2014, DOI: 10.1037/a0033546. Diamond, A., Barnett, W.S., Thomas, J. and Munroe, S. (2007) Preschool program improves cognitive control. Science, 318, 1387–88. Duncan, G.J., Dowsett, C.J., Claessens, A., Magnuson, K., Huston, A.C., Klebanov, P., Pagani, L.S., Feinstein, L., Engel, M., Brooks-Gunn, J., Sexton, H., Duckworth, K. and Japel, C. (2007) School readiness and later achievement. Developmental Psychology, 43(6), 1428–46. Education Sector in India - https://www.ibef.org/download/education-report-291012.pdf Indian Education System, Industry - IBEF -https://www.ibef.org/industry/education-sector-india.aspx McClelland, M., Morrison, F.J. and Holmes, D.L. (2000) Children at risk for early academic problems: The role of learning-related social skills. Early Childhood Research Quarterly, 15, 307–29. Roll, I., & Winne, P. H. (2015). Understanding, evaluating, and supporting self-regulated learning using learning analytics. Journal of Learning Analytics, 2(1), 7-12. Schunk, D. and Ertmer, P. (2000) Self-regulation and academic learning: Self-efficacy enhancing interventions. In J. Boekarts, P. Pintrich and M. Zeidner (eds) Handbook of Self-Regulation. Burlington, MA: Elsevier Academic Press. Senemoğlu, N. (2005). Gelişim Öğrenme ve Öğretim: Kuramdan Uygulamaya, (12. Baski). Ankara: Gazi Kitabevi. Yen, C., Konold, T.R. and McDermott, P.A. (2004) Does learning behavior augment cognitive ability as an indicator of academic achievement? Journal of School Psychology, 42, 157–69. Zimmerman, B. (2000) Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. Pintrich and M. Zeidner (eds) Handbook of Self-Regulation.Burlington, MA: Elsevier Academic Press. Zimmerman, B. (2008) Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166–83. |
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Implementation Imprisonment Penalty as Subsidiary of Fine Penalty: Inconsistency of State Financial LossesRonald Hasudungan Sianturi & Ahmad Feri Tanjung
pp. 1633-1640 | Article Number: ijese.2017.105
Abstract The Supreme Court has issued Supreme Court Regulation No. 5 Year 2014 as guidance on fine penalty and imprisonment. This study aims to evaluate the consistency of imprisonment penalty as replacement penalty after the issuance of Indonesia Supreme Court Regulation Number 5 Year 2014 on Fine Penalty as Additional Penalty in Corruption. This research is normative juridical research with cases approach. The data used in the 140 verdicts of the district court in the period January - December 2015. The results show the district court verdicts are inconsistent in converting fines into imprisonment because The Indonesia Supreme Court Indonesia has no regulation or parameters to convert it. Unavailable regulation or parameters makes an obstacle in the effort to return the state financial losses. Keywords: corruption, fine, imprisonment, penalty, replacement, Indonesia References Arief, B. N. (2011). Bunga Rampai Kebijakan Hukum Pidana: (Perkembangan Penyusunan Konsep KUHP Baru). Jakarta: Kencana. Fauzan, H.M. (2013).Peranan Perma dan Sema Sebagai Pengisi Kekosongan Hukum Indonesia Menuju Terwujudnya Peradilan yang Agung. Jakarta: Kencana. Gunarto, M. P. (2009). Sikap Memidana yang Berorientasi pada Tujuan Pemidanaan. Jurnal Mimbar Hukum, 21(1), 93-108. Gunawan, T. J. (2015). Konsep Pemidanaan Berbasis Nilai Kerugian Ekonomi. Yogyakarta: Genta. Hamzah, A. (1987a).Undang-Undang Hukum Pidana Argentina Sebagai Perbandingan. Jakarta: Ghalia Indonesia. Hamzah, A. (1987b).Undang-Undang Hukum Pidana Austria, Sebagai Perbandingan. Jakarta: Ghalia Indonesia. Indonesia, Indonesian Constitution 1945. (1945). Direct access:http://www.ilo.org/wcmsp5/groups/public/---ed_protect/---protrav/---ilo_aids/documents/legaldocument/wcms_174556.pdf Indonesia, Law Number 8 Year 1999 Concerning Consumer Protection. (1999). Direct access:http://www.bu.edu/bucflp/files/2012/01/Law-No.-8-Concerning-Consumer-Protection.pdf Indonesia, Law Number 31 Year 1999 Concerning Eradication of Corruption. (1999). Direct access:http://publicofficialsfinancialdisclosure.worldbank.org/sites/fdl/files/assets/law-library-files/Indonesia_Corruption%20Eradication%20Law_1999_en.pdf Indonesia, Law Number 32 Year 2009 Concerning Environmental Management. (2009). Direct access:www.apbi-icma.org/wp.../02/UU-No.-32-Tahun-2009.pdf Indonesia, Law Number 11 Year 2012 Concerning Child Criminal Justice System. (2012). Direct access:http://www.ilo.org/dyn/natlex/natlex4.detail?p_lang=en&p_isn=91044&p_country=IDN&p_count=611 Indonesia, Law Number 21 Year 2014 Concerning Geothermal. (2014). http://www.elexica.com/en/legal-topics/projects/29-indonesia-relaxes-regulation-of-the-geothermal-market Indonesia, The Supreme Court Regulation Number 5 Year 2014. (2014).Concerning Additional Fine Penalty In Corruption. Direct access: http://www.abnrlaw.com/news_detail.php?send_n-ews_id=290&year=2017 Lamintang, P.A.&Lamintang, T. (2012).Hukum Penitensier Indonesia. Jakarta: Sinar Grafika. Loqman, L. (2002).HAM dalam HAP. Jakarta: Datacom. Muladi, A.&Arief, B. N. (1998).Teori-Teori dan Kebijakan Pidana. Bandung: Alumni. Nababan, H. (2015). Hukum Tanpa Takaran, Penjara Korupsi Bagi Korban Penipuan. Jakarta: Q Communication. Rutkowski, C. P. (2017). Fogel's Justice Model: Will Illinois accept it?Direct access: http://www.lib.niu.edu/1976/ii760318.html Surihaiyono, A.R. (2012).Pembaruan Pidana Denda di Indonesia, Pidana Denda Sebagai Sanksi Alternatif. Jakarta: Papas Sinar Sinanti. The Judicial Commission of the Republic of Indonesia. (2014). Disparitas Putusan Hakim, Identifikasi dan Implikasi. Jakarta: Sekretariat Jenderal Komisi Yudisial Republik Indonesia. The Supreme Court of the Republic of Indonesia. (2015). Reviu Rencana Strategis (Renstra) Mahkamah Agung RI 2015-2019. Jakarta: Mahkamah Agung. Watimena, R.A.(2012).Filsafat Anti Korupsi. Yogyakarta: Kanisius. |
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Predict the Physical Development of the Shiraz City and Its Impact on the Vegetation Dynamics Using Cellular Automata, Fuzzy Techniques and Satellite ImageryMehran Ghobadiannejad, Gholamreza Fallahi
pp. 1641-1653 | Article Number: ijese.2017.106
Abstract Remote sensing is the main technology for assessing expansion and rate of change of land cover. Knowing the different kinds of land cover changes and human activities in different parts, as a basis for a variety of planning has special importance. Accordingly this study aimed to evaluate the physical growth of the Shiraz city during the years 2009 to 2016 and forecasts until 2021 and also calculate the amount and intensity of the destruction of vegetation in the study area using satellite images. To achieve this, the data of remote sensing and geographic information system is used. Calculation of trends in physical growth, stating that the area of the city from 13160.07 hectares in 2009 reached to 17350.29 hectares in 2016, over a period of 7 years. If these conditions persist, area of the city in 2021 with 19.21 percent growth will be 20683.58 hectares. Assessment NDVI index show that the density of vegetation in the Shiraz city had a significant decreasing trend. So that the sum of very good and good vegetation cover results NDVI index, in 2009 was equal to 6128.37 hectares, while this amount has decreased to 4282.47 hectares in 2016, that this means a 43.10 percent reduction in vegetation cover in this period. The results showed that between 2009 to 2016 more than 1891 hectares of vegetation and gardens has become built lands. Keywords: Land cover map, Comparison of classification, Detection of changes, Remote Sensing, Cellular Automata, Fuzzy method References Ahadnejhad Roshani, Mohsen; Zolfi, Ali; Shokripour Dizaj, Hossein. (2011). Assessing the physical growth of cities using multi-temporal satellite images and geographic information system (Case Study:Ardabil 1984-2021). Quarterly Journal of Enviromental Based Territorial Planning, 15, 107-124. Alavi Panah, Kazem. (2003). Remote Sensing Application in Earth Sciences (Soil Science). First Print, Tehran University Publishing. Asghari Zamani, Asghar; Ahadnejhad Roshani, Mohsen; Khodavandi, Abdollah. (2016). Analytical assessment of the spatial-spatial extent of urban areas and its effect on land use changes using GIS and RS (Case study: Shiraz during the period of 1950-1987). Geographical Space, 53, 57-76. Azizi Ghalati, Sara; Rangzan, Kazem; Taghizadeh, Ayyoub; Ahmadi, Shahram. (2014). Land use change modeling using logistic regression method in LCM model (Case study: Kouhe Mare Sorkhi of Fars province). Iranian journal of Forests and Poplar Research, 4, 585-596. Bhatta, B., Saraswati, S. and Bandyopadhyay, D., (2010), Quantifying the Degree-of-freedom, Degree-of-sprawl, and Degree-of-goodness of Urban Growth from Remote Sensing Data. Applied Geography, 30(1), 96-111.
Eastman, J.R. Van Fossen, M.E. and Solarzano, L.A. (2012). Transition potential modeling for land cover change. In: Maguire, D. Good Child, M. Batty, M. (Eds.), GIS, Spatial Analysis and Modeling. ESRI Press, Redlands, California. Ebrahimzadeh, Issa; Rafiei, Ghassem. (2008). Optimal Locating of Urban Expansions Using Geographic Information System, Case Study: Marvdasht. Geography and development, 15, 35-70. El-Kawy, A. O. R., Rød, J. K., Ismail, H. A. and Suliman, A.S., (2011), Land Use and Land Cover Change Detection in the Western Nile Delta of Egypt Using Remote Sensing Data. Applied Geography, 31(2), 483-494. Fang, S., George, Z., Gertnera, G.Z., Sun, Z., Andersonc, A.A., (2005). The impact of interactions in spatial simulation of the dynamics of urban sprawl. Landscape and Urban Planning, 73, 294–306. Gandaseca, S., Sabang, J., Ahmed, O. H. and Majid, N. M. A., (2009), Vegetation Assessment of Peat Swamp Forest Using Remote Sensing. American Journal of Agricultural and Biological Sciences, 4(2), 167-172. Kristine Lien Skoga, Margrete Steinnes. (2016). How do centrality, population growth and urban sprawl impactfarmland conversion in Norway? Land Use Policy, 59, 185–196. McConnel, W.J. Sweeney, S.P. and Mulley, B. (2004). Physical and social access to land: spatiotemporal patterns of agricultural expansion in Madagascar. Agriculture, Ecosystems & Environment, 101, 171-184. Mir Katouli, Jaafar; Hosseini, Ali; Rezaeinia, Hassan; Neshat, Abdolreza. (2012). Detection of land cover changes and land use by approach to fuzzy sets, case study: Gorgan city. Human Geography Research Quaterly, 79, 33-54. Norouzi Aghdam, Elnaz; Behbahani, Mahmoodreza; Rahimi Khoob, Ali; Aghighi, Hossein. (2008). Soil Moisture Model Using NDVI Index. Journal of Environmental Studies, 34th Year, 48, 127-136. Park, S., Jeonb, S., Kimc, SH,. Choia, CH.(2011), Prediction and comparison of urban growth by land suitability index mapping using GIS and RS in South Korea, Landscape and Urban Pla Peng, J., Wang, Y.L., Zhang, Y., Wu, J.S., Li, W.F., You Li, Y., 2010. Evaluating theeffectiveness of landscape metrics in quantifying spatial patterns. Ecological Indicators, 10 (2), 217–223. Pham, H.M., Yamaguchi, Y., Bui, T.Q., 2011. A case study on the relation between city planning and urban growth using remote sensing and spatial metrics. Landscape and Urban Planning, 100 (3), 223–230. Pourahmad, Ahmad; Faldini, Ferank C.; Parnoun, Ziba. (2011). Immigration and land use change in Islamshahr, Journal of Arid regions Geographic Studies, Second Year, 5. Pourahmad, Ahmad; Salehi, Heidar; Romiani, Ahmad. (2014). Optimization of physical development of Urmia city in order to preserve vegetation and agricultural lands. Geoplanning, 19, 83-87. Reid Ewinga,, Shima Hamidib, James B. Gracec, Yehua Dennis Weid(2016), Does urban sprawl hold down upward mobility? Landscape and Urban Planning, 148, 80–88. Seif-Al-Dinni, F. (2011), Explaining the distribution and density of Amol urban form with sustainable urban form approach. Journal of Urban Geography studies; Summer, 2012, 80, 155-176. Shiea, Esmaeil. (1998). An Introduction to the Basics of Urban Planning. Iran University of Science & Technology Publishing. Soltani, Kambiz. (1992). Topics and methods of urban planning, Environment, Center for Urban Studies and Architecture of Iran. Soyoung Parka, Seongwoo Jeonb, Shinyup Kimc, Chuluong Choia,(2011), Prediction and comparison of urban growth by land suitability index mapping using GIS and RS in South Korea,Elsevier, Contents lists available at ScienceDirect Landscape and Urban. Talkhabi, Hamidreza; Ziaeian, Parviz; Soleimani, Mohhammad; Zangane, Ahmad. (2016). Investigating the trend of landslide changes in Arak city during the period of 1973-2011. Geography and Urban Regional Logistics, 19, 43-54. Václavík, T. and Rogan, J. (2009). Identifying trends in land use/land cover changes in the context of post-socialist transformation in central Europe. GIS Science and Remote Sensing, 49(1), 1-32. Zaeri Amirani, Azadeh; Sofianian, Alireza. (2012). Using FUZZY ARTMAP and Multilayer Perceptron Neural Network for Land Cover Mapping (Case Study: Isfahan City). Physical Geography Research Quarterly, 79, 127-143. |
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Investigate the effect of agility capabilities in the automotive industry supply chain network (Case Study: Sapko parts supply network)Mehdi Khastoo, Abbas Raad
pp. 1655-1677 | Article Number: ijese.2017.107
Abstract Nowadays, supply chain management is raised as one of the infrastructural foundations of implementation the businesses in the world. Formally supply chain is an integrated process that the raw materials were converted into finished products and then are delivered to customers. The aim of this study is to investigate the rate of effect the agility capabilities on agility of Sapko parts of supply network. The used method is descriptive - survey method in this research that for this purpose with the use of questionnaire of collected data and for test the hypotheses was used structural equation modeling technique by using Lisrel software. The statistical population including senior managers and experts of Sapco that was used in terms of data and information needed in the period of 2011 to 2014. 220 persons were determined as a studied sample by using the Kocaran formulate. The results show that components of consciousness, accessibility, decisiveness, flexibility and speed have a significant impact on agility of supply chain network. So the impact of all of the research components was confirmed. Keywords: capabilities of agility - the supply chain - structural equations References Agrell, P., Hatami, J., Marbini, A. (2013). Frontier-based performance analysis models for supply chain management: State of the art and research directions. Computers & Industrial Engineering, 66 (3): 567-583. Azar, Adel. (2010). Agile supply chain model; Interpretative - structural modeling approach. Humanities teacher. Management research in Iran. Volume 14, Issue 4. Bratić, D. (2011). Achieving A Competitive Advantage By Scm. Ibima Business Review, Article Id 957583, DOI: 10.5171 / 2011.957583. http: // www. ibimapublishing.com/journals/IBIMABR/ibimabr.html. Cohn, S., Roussel, J. (2005). Strategic Supply Chain Management: Five Disciplines for Top Performance. Mc Grew-Hill: New York. Davoudi SMM & Fartash K (2012). Electronic human resource management: New Avenue which leads to organizational success. Spectrum: A journal of multidisciplinary research, 2012, volume 1, issue 2, pp. 75-87. Davoudi SMM & Fartash K (2012). Integrating human resource management with firm’s strategy: A key concept to achieve firm’s superior performance. Arth Prabhand: A journal of economics and management, 2012, volume 1, issue 2, pp. 100-115. Davoudi SMM & Shabaani E (2012). Human resource management in virtual organizations. Asian journal of research in social science and humanities, 2012, volume 2, issue 6, pp. 224-234. Davoudi SMM, Fartash K, Abbasian M (2012). Perception of Justice as an Antecedent of Organizational Citizenship Behavior: A Survey in Iran's Insurance Industry. Pacific business review international, volume 4, issue 4, pp. 18-26. Davoudi SMM, Kaur R (2012). International human resource management: Managing people in multinational enterprises. Spectrum: A journal of multidisciplinary research, 2012, volume 1, issue 2, pp. 41-56. Devaraj, D., Hollingworth, D. G., and Schroeder, R. G. (2004). Generic manufacturing strategies and plant performance. Journal of Operations Management, 22, pp. 313-333. Faizi, i. (1386). Principles of organization and management. Ninth edition. Tehran: PNU. Jafarnejad, A. Shahabi, b. (2012). Organizational agility and agile manufacturing. Kind book publishing firm. Jafarnejad, Ahmed. (2010). Provide a method to measure supply chain agility by combining graph theory. Matrix approach and fuzzy logic. Quarterly Journal of Commerce. (54). Jayaram, J., Dorge, C., and Vickery, S. K. (1999). the impact of human resource management practices on manufacturing performance. Journal of Operations Management, 18, pp. 1-20. Joshi, M.P., Kathuria, R., and Porth, S. J. (2003). Alignment of strategic priorities and performance: an integration of operations and strategic management perspectives. Journal of Operations Management, 21, pp. 353-369. Klidbery Rezaei, Hamid. (2014). The impact of supply chain management to improve performance through competitive automotive parts industry. Faculty of Tehran University Management: Business Management. Volume 6, Issue 1. Lambert DM, Cooper M C. (2010); "Issues in Supply Chain Management", Industrial Marketing Management, pp. 65-83. Li, S., Ragu-Nathanb, B., Ragu-Nathanb, T.S., Raob, S. (2006). The Impact of Supply Chain Management Practices on Competitive Advantage and Organizational Performance. The International Journal of Management Science- Omega, 34: 107 - 124. www.elsevier.com/locate/omega. Lou P, Zhou Z, Chen Y.P, Ai W. (2004); "Study on Multi-Agent-Based Agile Supply Chain Management", Int J Adv Manuf Technol, pp. 23: 197-203. Mary C. Holcomb, and Theodore P. Stank. (2013). Journal of Business Logistics, 34 (2): 94-108 © Council of Supply Chain Management Professionals. A Multidisciplinary Approach to Supply Chain Agility: Conceptualization and Scale Development David M. Gligor Mason-Jones R., Naylor B., Towill D. R .; (2009). Engineering the agile supply chain; International Journal of Agile Management systems, Vol.2, No.1. Meredith, M. and Francis, D. (2000). Journey towards agility: the agile wheel explored. The TQM Magazine, Vol. 12, No. 2, pp. 137-143. Narasimhan, R., Swink, M. & Soo Wook, k. (2006), Disentangling Leanness and agility: An empirical investigation, Journal of Operation Management, No.24, pp.440-457 Rahmanseresht, h. Afsar, A. (2008). The effect of information sharing on competitive strategies and supply chain performance. Journal of Information Technology Management. Pages 37-48. Rastgar AA, Davoudi SMM, Oraji S, Abbasian M (2012). A study of the relationship between employees’ spiritual intelligence and job satisfaction: A survey in Iran’s banking industry. Spectrum: A journal of multidisciplinary research, volume 1, issue 2, pp. 57-74. Rastgar AA, Pourebrahimi N & Davoudi SMM (2012). Leader-Member Exchange and organizational citizenship behavior: A survey in Iran's food industry. Pacific business review international, volume 5, issue 5, pp. 13-18. Ren, J., Yusuf, Y. Y., and Burns, N. D. (2003). the effects of agile attributes on competitive priorities: a neural network approach. Integrated Manufacturing Systems, Vol. 14, No. 6, pp. 489-497. Saremi, Mahmoud. Azhdari, Behnam. (2009). Agility effect on the performance of companies manufacturer of automotive parts and assembly Bayesian network approach. Journal of Teacher Human Sciences, Volume 13. Simons, R.. (2006). The military are able to monitor and assess the performance of the strategy. Translator: M. Asadi, Tehran, Ariana industry research group. Tastan, SB & Davoudi, SMM (2017). The Relationship between Organisational Climate and Organizational Innovativeness: Testing the Moderating Effect of Individual Values of Power and Achievement. International Journal of Business Innovation and Research, Inderscience Publishers, 12(4): 465-483. Tastan, Secil Bal & Davoudi, S.M.M. (2015). A Research On The Relevance Of Intellectual Capital Zhang, Q., Cao, M. (2011). Supply chain collaboration: Impact on collaborative advantage and firm Performance. Journal of Operations Management, 29 (3): 163-180. |
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Structural model of the effects of total quality management components on job performance considering the moderating effects of ppersonal factorsA. Keshavarzi, S. Rajaeepour, H. Samavatyan
pp. 1679-1687 | Article Number: ijese.2017.108
Abstract This study aims to explore the structural model of the effect of TQM components on the job performance of the staff employees, considering the moderating effect of personal factors in teacher education universities of Iran. A sample of 335 subjects was obtained. through random cluster sampling method. Data collection was done using four questionnaires TQM’ questionnaire developed by US Federal Quality Institute, Paterson’s job performance questionnaire and two researcher designed questionnaires on the personal knowledge and skill factors. Considering the knowledge factor as a moderating variable, a relationship was observed between some components of TQM and job performance. Also, considering skills as of moderating variable, a relationship was observed between a few TQM components and job performance. Keywords: Total quality management (TQM) , Job performance, Personal knowledge, Personal skills References Austin J. T., & Villanova P. (1992). The criterion problem. Journal of Applied Psychology, 77, 836- 874. Barati Ahmedabad A. (2010). The relationship between organizational climate and work ethic and job performance. Journal of Applied Psychology, (in Persian), 13, 65. Chen D. N. & Liang T. P. (2011). Knowledge evolution strategies and organizational performance: A strategic fit analysis. Electronic Commerce Research and Applications, 10(2), 75–84. Cho J., Darren C-T. (2011). "Organizational identification and perceived organizational support as mediators of the procedural justice-citizenship behavior relationship: A cross-cultural constructive replication". European Journal of Work and Organizational Psychology, 5, 631-653. Davoudi SMM & Fartash K (2012). Electronic human resource management: New Avenue which leads to organizational success. Spectrum: A journal of multidisciplinary research, 1(2), 75-87. Davoudi SMM & Fartash K (2012). Integrating human resource management with firm’s strategy: A key concept to achieve firm’s superior performance. Arth Prabhand: A journal of economics and management, 1(2), 100-115. Davoudi SMM & Shabaani E (2012). Human resource management in virtual organizations. Asian journal of research in social science and humanities, 2(6), 224-234. Davoudi SMM, Fartash K, Abbasian M (2012). Perception of Justice as an Antecedent of Organizational Citizenship Behavior: A Survey in Iran's Insurance Industry. Pacific business review international, 4(4), 18-26. Davoudi SMM, Kaur R (2012). International human resource management: Managing people in multinational enterprises. Spectrum: A journal of multidisciplinary research, 1(2), 41-56. Dubey R., & Singh T. (2013). Soft TQM for sustainability: An empirical study on Indian cement industry and its impact on organizational performance, pp.77-Retrieved from. http://link.springer.com/search?facet-author= Rameshwar+ Dubey. Haghighi A.M. (2011). "Evaluation of employee empowerment by establishing Total Quality Management in Islamic Azad University, Darab", Abstracts of the First National Conference of change and innovation in higher education management, Islamic Azad University Firuz Abad, (In Persian). 24 March p. 104. Hung R.Y.Y, liens b.y.yang b.kuo y. (2011). Impacted tam and organizational learning on innovation performance in the high teeth industry. International business review, 20, 213-225. Keramati A., & Albadvi A. (2009). .Exploring the relationship between use of information technology in total quality management and SMEs performance using canonical correlation analysis: A survey on Swedish car part supplier sector. International Journal of Information Technology and Management archive, 8(4), 442-462. (in Persian). Khakbazan H. R. (2008). Examining the relationship between personality traits and skills Police University communication professors. Payan a Master of Science, University of A. Military Sciences, 4(11), 55-82. (Persian). Krejcie R.V., & Morgan D.W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, 607-610 Narimani M., Allame M., Soltani F. (2014). "The role of variable moderator of social capital on the relationship between talent management and knowledge sharing in organization: National Iranian Oil Company and Subsidiaries staff areas in Tehran". Management Researches in Iran, 18 (2), 121-148. (In Persian) Peterson C. (2006). The future of optimism. Am Psychol, 55, 44-55. Rastgar AA, Davoudi SMM, Oraji S, Abbasian M (2012). A study of the relationship between employees’ spiritual intelligence and job satisfaction: A survey in Iran’s banking industry. Spectrum: A journal of multidisciplinary research, 1(2), 57-74. Rastgar AA, Pourebrahimi N & Davoudi SMM (2012). Leader-Member Exchange and organizational citizenship behavior: A survey in Iran's food industry. Pacific business review international, 5(5), 13-18. Sajjad F. & Amjad D.S. (2012). “Role of Benchmarking in Total Quality Management: case of Telecom Service Sector of Pakistan”. Business Management Dynamics, 1(8), 34-44. Saleh A. S., Piaw C. Y., Idris A. R. (2015). Factors Influencing the Employees’ Service Performance in Ministry of Education in Sultanate of Oman. Procedia-Social and Behavioral Sciences, 197, 23-30. Shahin A., Vaez Shahrestani H. & Bagheri Iraj E. (2014). Proposing an integrated approach of Kano Model and Taguchi Design of Experiments based on Kansei Engineering to product design based on customer needs in the automotive industry. Industrial Management, 6(2), 317-336. (in Persian). Shekarshekan H. (2001). Examine the relationship between job satisfaction citizenship behavior) organizational and job performance of the staff of some factories. Ahvaz. Journal of Education and Psychology University of Ahvaz, 4, 22,1. (in Persian). Tastan, SB & Davoudi, SMM (2017). The Relationship between Organisational Climate and Organizational Innovativeness: Testing the Moderating Effect of Individual Values of Power and Achievement. International Journal of Business Innovation and Research, Inderscience Publishers, 12(4), 465-483. Tastan, Secil Bal & Davoudi, S.M.M. (2015). A Research On The Relevance Of Intellectual Capital Vajargahi Fathi K., 2005, The Evaluating of Educational Patterns. Tehran: Aeezh Publication. in Persian, 3(10), 13-32. Zoualfaghari-Zaferani R., Kalantari M. (2008). An analysis of the level of implementation of Total Quality Management in Islamic Azad University Roudehen Branch. The Journal of Modern Thoughts in Education, 3(10), 63-76. (in Persian). |
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