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Data-Driven Decision Making in the Pre-Referral Process for Risk Group Students

Yıl 2021, , 593 - 612, 25.06.2021
https://doi.org/10.37217/tebd.906636

Öz

This study aims to reveal the situation regarding the use of data driven decision making in the process before students’ being guided by classroom teachers to be an academically or behaviorally at risk group for special education services. In the study, in-class monitoring and evaluation processes, the pre-referral process and the importance of this process in terms of students' educational life, the importance of data-driven decision making and data-driven decision making in the pre-referral process were tried to be explained. Learning about a student's learning characteristics depends on when, how much and how data is collected through in-class monitoring and evaluation. In the classroom, each student progresses with his or her own learning characteristics. These features are also indicators of students' need for support. It is important for teachers to collect data, classify data and use the data-driven decision making process, in which they turn their decisions into action, so that they can make appropriate adjustments to the learning characteristics of each student. For students who are considered as a risk group, making decisions driven on data significantly affects students' ability to benefit from the educational environment they are in.

Kaynakça

  • Anderson, L. W. (2003). Classroom assessment: Enhancing the quality of teacher decision making. New Jersey: Routledge.
  • Black, H. D. (1983). Introducing diagnostic assessment. Programmed Learning and Educational Technology, 20(1), 58-63.
  • Black, P., Wilson, M., & Yao, S. Y. (2011). Road maps for learning: A guide to the navigation of learning progressions. Measurement: Interdisciplinary Research & Perspective, 9(2-3), 71-123.
  • Campbell, C., & Levin, B. (2009). Using data to support educational improvement. Educational Assessment, Evaluation and Accountability (formerly: Journal of Personnel Evaluation in Education), 21(1), 47.
  • Carlson, D., Borman, G. D., & Robinson, M. (2011). A multistate district-level cluster randomized trial of the impact of data-driven reform on reading and mathematics achievement. Educational Evaluation and Policy Analysis, 33(3), 378-398.
  • Chen, P. P., & Bonner, S. M. (2020). A framework for classroom assessment, learning, and self-regulation. Assessment in Education: Principles, Policy & Practice, 27(4), 373-393. doi: 10.1080/0969594X.2019.1619515
  • Choppin, J. (2002, April). Data use in practice: Examples from the school level. Annual meeting of the American Educational Research Association’da sunulmuş bildiri. New Orleans, LA.
  • Coburn, C. E., & Turner, E. O. (2011). Research on data use: A framework and analysis. Measurement: Interdisciplinary Research & Perspective, 9(4), 173-206.
  • Çuhadar, S. (2017). Sınıf öğretmenlerinin eğitsel değerlendirme sürecine ilişkin görüşleri. Trakya Üniversitesi Eğitim Fakültesi Dergisi, 7(2), 526-549.
  • Datnow, A., Park, V., & Kennedy‐Lewis, B. (2013). Affordances and constraints in the context of teacher collaboration for the purpose of data use. Journal of Educational Administration, 51(3), 341-362.
  • Dunn, K. E., Airola, D. T., Lo, W. J., & Garrison, M. (2013). Becoming data driven: The influence of teachers’ sense of efficacy on concerns related to data-driven decision making. The Journal of Experimental Education, 81(2), 222-241. doi: 10.1080/00220973.2012.699899
  • Ebbeler, J., Poortman, C. L., Schildkamp, K., & Pieters, J. M. (2017). The effects of a data use intervention on educators’ satisfaction and data literacy. Educational Assessment, Evaluation and Accountability, 29(1), 83-105.
  • Flaherty, L. T., & Osher, D. (2003). History of school-based mental health services in the United States. M. D. Weist, S. W. Evans, & N. A. Lever (Ed.), Handbook of school mental health advancing practice and research içinde (s. 11-22). Boston, MA: Springer.
  • Frey, J. R. (2019). Assessment for special education: Diagnosis and placement. The ANNALS of the American Academy of Political and Social Science, 683(1), 149-161.
  • Fuchs, D., Fuchs, L. S., Bahr, M. W., Fernstrom, P., & Stecker, P. M. (1990). Prereferral intervention: A prescriptive approach. Exceptional Children, 56(6), 493-513.
  • Good, K. I. (2004). The experiences of parents with the pre-referral process: An evolutionary perspective (Doctoral dissertation). ProQuest Dissertations and Theses database. (UMI No. 3124507).
  • Gresham, F. M. (1997). Social competence and students with behavior disorders: Where we've been, where we are, and where we should go. Education and Treatment of Children, 20(3), 233-249.
  • Halverson, R. (2010). School formative feedback systems. Peabody Journal of Education, 85(2), 130–146. doi: 10.1080/01619561003685270
  • Hamilton, L., Halverson, R., Jackson, S. S., Mandinach, E., Supovitz, J. A., & Wayman, J. C. (2009). Using Student Achievement Data to Support Instructional Decision Making. IES Practice Guide. NCEE 2009-4067. National Center for Education Evaluation and Regional Assistance.
  • Hanson, M. J., Horn, E., Sandall, S., Beckman, P., Morgan, M., Marquart, J., ..., & Chou, H. Y. (2001). After preschool inclusion: Children's educational pathways over the early school years. Exceptional Children, 68(1), 65-83.
  • Ikemoto, G. S., & Marsh, J. A. (2007). Chapter 5 cutting through the “data‐driven” mantra: Different conceptions of data‐driven decision making. Yearbook of the National Society for the Study of Education, 106(1), 105-131.
  • Kane, M. T., & Wools, S. (2020). Perspectives on the validity of classroom assessments. S. M. Brookhart, & J. H. McMillan (Ed.), Classroom assessment and educational measurement içinde (s. 11-26). New York: Routledge.
  • Kargın, T. (2007). Eğitsel değerlendirme ve bireyselleştirilmiş eğitim programı hazırlama süreci. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Özel Eğitim Dergisi, 8(01), 1-15.
  • Kippers, W. B., Poortman, C. L., Schildkamp, K., & Visscher, A. J. (2018). Data literacy: What do educators learn and struggle with during a data use intervention? Studies in Educational Evaluation, 56(2018), 21-31.
  • Küpper, L. (2000). A Guide to the Individualized Education Program. Office of Special Education an Rehabilitative Services, Washington, DC.
  • Lai, M. K., McNaughton, S., Timperley, H., & Hsiao, S. (2009). Sustaining continued acceleration in reading comprehension achievement following an intervention. Educational Assessment, Evaluation and Accountability (formerly: Journal of Personnel Evaluation in Education), 21(1), 81-100.
  • Lai, M., & Schildkamp, K. (2013). Data-based decision making: An overview. Schildkamp, K., Lai M., & Earl, L. (Ed.) Data-based decision making in education: Studies in educational leadership. Dordrecht: Springer. https://doi.org/10.1007/978-94-007-4816-3_2
  • Lai, M. K., Wilson, A., McNaughton, S., & Hsiao, S. (2014). Improving achievement in secondary schools: Impact of a literacy project on reading comprehension and secondary school qualifications. Reading Research Quarterly, 49(3), 305-334. doi: 10.1002/rrq.2014.49.issue-3
  • Light, D., Wexler, D., & Heinze, J. (2004). How practitioners interpret and link data to instruction: Research findings on New York City Schools’ implementation of the Grow Network. Annual Meeting of the American Educational Research Association’da sunulmuş bildiri, San Diego, CA.
  • Mandinach, E. B. (2012). A perfect time for data use: Using data-driven decision making to inform practice. Educational Psychologist, 47(2), 71-85.
  • Mandinach, E. B., & Gummer, E. S. (2013a). Defining data literacy: A report on a convening of experts. Journal of Educational Research and Policy Studies, 13(2), 6-28.
  • Mandinach, E. B., & Gummer, E. S. (2013b). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30-37.
  • Mandinach, E. B., & Gummer, E. S. (2016). What does it mean for teachers to be data literate: Laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60, 366-376.
  • Marsh, J. (2012). Interventions promoting educators’ use of data: Research insights and gaps. Teachers College Record, 114(11), 1-48.
  • Marsh, J. A., Pane, J. F., & Hamilton, L. S. (2006). Making Sense of Data-Driven Decision Making in Education: Evidence from Recent RAND Research. Occasional Paper. Rand Corporation.
  • McAlenney, A. L., & Coyne, M. D. (2011). Identifying at-risk students for early reading intervention: Challenges and possible solutions. Reading & Writing Quarterly, 27(4), 306-323.
  • McMillan, J. H. (2017). Classroom assessment: Principles and practice that enhance student learning and motivation. New York: Pearson.
  • McNaughton, S., Lai, M., & Hsaio, S. (2012). Testing the effectiveness of an ıntervention model based on data use: A replication series across clusters of schools. School Effectiveness and School Improvement, 23(2), 203–228. doi: 10.1080/09243453.2011.652126
  • Means, B., Chen, E., DeBarger, A., & Padilla, C. (2011). Teachers' Ability to Use Data to Inform Instruction: Challenges and Supports. Office of Planning, Evaluation and Policy Development, US Department of Education.
  • MEB. (2018a). Rehberlik ve Araştırma Merkezi Kılavuzu. https://orgm.meb.gov.tr/meb_iys_dosyalar/2018_01/17234231_ram_kilavuzu_2018.pdf sayfasından erişilmiştir.
  • MEB. (2018b). Özel Eğitim Hizmetleri Yönetmeliği. http://orgm. meb.gov.tr/ sayfasından erişilmiştir.
  • Militello, M., Fusarelli, B., Alsbury, T., & Warren, T. P. (2013). How professional standards guide practice for school principals. International Journal of Educational Management, 27(1), 74-90. https://doi.org/10.1108/09513541311289837
  • Noll, M. B., Kamps, D., & Seaborn, C. F. (1993). Prereferral intervention for students with emotional or behavioral risks: Use of a behavioral consultation model. Journal of Emotional and Behavioral Disorders, 1(4), 203-214.
  • Overton, T. (2012). Assessing learners with special needs an applied approach. (7th Ed.). New Jersey: Pearson Education.
  • Özmen, E. R. (2012). Zihin engellilerde öğretmenlik uygulaması öğrencilikten öğretmenliğe geçiş süreci. Ankara: Pegem Akademi.
  • Özyürek, M. (2015). Özel eğitimde ölçümleme ve değerlendirme. Ankara: Kök Yayıncılık.
  • Paet-Bullaoit, S. (2019). Policy documents and the pre-referral process in BC schools (Master’s Thesis). http://dx.doi.org/10.25316/IR-5510
  • Pierangelo, R., & Giuliani, G. (Ed.). (2007). Understanding assessment in the special education process: A step-by-step guide for educators. California: Corwin Press.
  • Poortman, C. L., & Schildkamp, K. (2016). Solving student achievement focused problems with a data use ıntervention for teachers. Teaching and Teacher Education, 60, 425–433. doi: 10.1016/j.tate.2016.06.010
  • Rallis, S. F., & MacMullen, M. M. (2000). Inquiry-minded schools: Opening doors for accountability. Phi Delta Kappan, 81(10), 766-773.
  • Reschly, D. J. (1996). Identification and assessment of students with disabilities. The Future of Children, 6(1), 40-53.
  • Russell, M. K., & Airasian, P. W. (2012). Classroom assessment: Concepts and applications. New York: McGraw-Hill Companies.
  • Saefurrohman, S., & Balinas, E. S. (2016). English teachers classroom assessment practices. International Journal of Evaluation and Research in Education, 5(1), 82-92.
  • Sagor, R., & Cox, J. (2013). At risk students: Reaching and teaching them. New York: Routledge.
  • Salvia, J., Ysseldyke, J., & Bolt, S. (2010). Assessment: In special and inclusive education, (11th Ed.). Belmont: Wadsworth, Cengage Learning.
  • Schildkamp, K., Karbautzki, L., & Vanhoof, J. (2014). Exploring data use practices around Europe: Identifying enablers and barriers. Studies in Educational Evaluation, 42, 15-24.
  • Schildkamp, K., & Kuiper, W. (2010). Data-informed curriculum reform: Which data, what purposes, and promoting and hindering factors. Teaching and Teacher Education, 26(3), 482-496.
  • Shermis, M. D., & DiVesta, F. J. (2011). Classroom assessment in action. Maryland: Rowman & Littlefield Publishers.
  • Slavin, R. E., & Madden, N. A. (1989). What works for students at risk: A research synthesis. Educational leadership, 46(5), 4-13.
  • Soukup, J. H., Wehmeyer, M. L., Bashinski, S. M., & Bovaird, J. A. (2007). Classroom variables and access to the general curriculum for students with disabilities. Exceptional Children, 74(1), 101-120.
  • Spinelli, C. G. (2012). Classroom assessment for students in special and general education. New Jersey: Pearson Education.
  • Strickland, B. B., & Turnbull, A. P. (1990). Developing and implementing individualized education programs. Columbus, OH: Merrill.
  • Terrill, T. A. (2018). Data-driven instruction from the perspective of administrators and teachers. (Doctoral Thesis). http://cardinalscholar.bsu.edu/handle/123456789/201495 sayfasından erişilmiştir.
  • Tomlinson, C. A., & Moon, T. R. (2013). Assessment and student success in a differentiated classroom. Virginia: ASCD.
  • Tunç, Z. (2011). Sınıf öğretmenlerinin risk taşıyan öğrenciler için gönderme öncesi sürece ilişkin görüşleri. (Yüksek lisans tezi). https://tez.yok.gov.tr sayfasından erişilmiştir.
  • Van Geel, M., Keuning, T., Visscher, A. J., & Fox, J. P. (2016). Assessing the effects of a school-wide data-based decision-making intervention on student achievement growth in primary schools. American Educational Research Journal, 53(2), 360-394.
  • Vaughn, S., Bos, C. S., & Schumm, J. S. (2018). Teaching students who are exceptional, diverse, and at risk in the general education classroom. New York: Pearson.
  • Weist, M. D. (1997) Expanded school mental health services. T. H. Ollendick, & R. J. Prinz (Ed.) Advances in clinical child psychology. Boston, MA: Springer. https://doi.org/10.1007/978-1-4757-9035-1_9
  • Wood, J. W. (2002). Adapting instruction to accommodate students in inclusive settings (3rd Ed.). Columbus. OH: Merrill/Prentice Hall.

Risk Grubu Öğrenciler İçin Gönderme Öncesi Süreçte Veriye Dayalı Karar Verme

Yıl 2021, , 593 - 612, 25.06.2021
https://doi.org/10.37217/tebd.906636

Öz

Bu çalışma, sınıf öğretmenleri tarafından akademik ya da davranışsal olarak risk grubu olduğu düşünülen öğrencilerin özel eğitim hizmetlerine uygunluğu için yönlendirilmesinden önceki süreçte veriye dayalı karar vermenin kullanılmasına ilişkin durumu ortaya koymayı amaçlamaktadır. Çalışmada, sınıf içi izleme ve değerlendirme süreçleri, gönderme öncesi süreç ve bu sürecin öğrencilerin eğitim hayatı açısından önemi, veriye dayalı karar verme ve gönderme öncesi süreçte veriye dayalı karar vermenin önemi açıklanmaya çalışılmıştır. Bir öğrencinin öğrenme özellikleri hakkında bilgi sahibi olunması sınıf içi izleme ve değerlendirme ile öğrenciye ilişkin ne zaman, ne kadar ve nasıl veri toplandığına bağlıdır. Sınıf içerisinde her bir öğrenci kendi öğrenme özellikleri ile ilerlemektedir ve bu özellikler öğrencilerin destek ihtiyacının da göstergesidir. Öğretmenlerin her bir öğrencisinin öğrenme özelliğine uygun düzenlemeleri yapabilmesi için veri toplamaları, verileri sınıflamaları ve kararlarını eyleme dönüştürdükleri veriye dayalı karar verme sürecini etkin kullanmaları önemlidir. Risk grubu olarak düşünülen öğrencilere yönelik ise veriye dayalı kararların alınması öğrencilerin bulundukları eğitim ortamından yararlanmalarını önemli ölçüde etkilemektedir.

Kaynakça

  • Anderson, L. W. (2003). Classroom assessment: Enhancing the quality of teacher decision making. New Jersey: Routledge.
  • Black, H. D. (1983). Introducing diagnostic assessment. Programmed Learning and Educational Technology, 20(1), 58-63.
  • Black, P., Wilson, M., & Yao, S. Y. (2011). Road maps for learning: A guide to the navigation of learning progressions. Measurement: Interdisciplinary Research & Perspective, 9(2-3), 71-123.
  • Campbell, C., & Levin, B. (2009). Using data to support educational improvement. Educational Assessment, Evaluation and Accountability (formerly: Journal of Personnel Evaluation in Education), 21(1), 47.
  • Carlson, D., Borman, G. D., & Robinson, M. (2011). A multistate district-level cluster randomized trial of the impact of data-driven reform on reading and mathematics achievement. Educational Evaluation and Policy Analysis, 33(3), 378-398.
  • Chen, P. P., & Bonner, S. M. (2020). A framework for classroom assessment, learning, and self-regulation. Assessment in Education: Principles, Policy & Practice, 27(4), 373-393. doi: 10.1080/0969594X.2019.1619515
  • Choppin, J. (2002, April). Data use in practice: Examples from the school level. Annual meeting of the American Educational Research Association’da sunulmuş bildiri. New Orleans, LA.
  • Coburn, C. E., & Turner, E. O. (2011). Research on data use: A framework and analysis. Measurement: Interdisciplinary Research & Perspective, 9(4), 173-206.
  • Çuhadar, S. (2017). Sınıf öğretmenlerinin eğitsel değerlendirme sürecine ilişkin görüşleri. Trakya Üniversitesi Eğitim Fakültesi Dergisi, 7(2), 526-549.
  • Datnow, A., Park, V., & Kennedy‐Lewis, B. (2013). Affordances and constraints in the context of teacher collaboration for the purpose of data use. Journal of Educational Administration, 51(3), 341-362.
  • Dunn, K. E., Airola, D. T., Lo, W. J., & Garrison, M. (2013). Becoming data driven: The influence of teachers’ sense of efficacy on concerns related to data-driven decision making. The Journal of Experimental Education, 81(2), 222-241. doi: 10.1080/00220973.2012.699899
  • Ebbeler, J., Poortman, C. L., Schildkamp, K., & Pieters, J. M. (2017). The effects of a data use intervention on educators’ satisfaction and data literacy. Educational Assessment, Evaluation and Accountability, 29(1), 83-105.
  • Flaherty, L. T., & Osher, D. (2003). History of school-based mental health services in the United States. M. D. Weist, S. W. Evans, & N. A. Lever (Ed.), Handbook of school mental health advancing practice and research içinde (s. 11-22). Boston, MA: Springer.
  • Frey, J. R. (2019). Assessment for special education: Diagnosis and placement. The ANNALS of the American Academy of Political and Social Science, 683(1), 149-161.
  • Fuchs, D., Fuchs, L. S., Bahr, M. W., Fernstrom, P., & Stecker, P. M. (1990). Prereferral intervention: A prescriptive approach. Exceptional Children, 56(6), 493-513.
  • Good, K. I. (2004). The experiences of parents with the pre-referral process: An evolutionary perspective (Doctoral dissertation). ProQuest Dissertations and Theses database. (UMI No. 3124507).
  • Gresham, F. M. (1997). Social competence and students with behavior disorders: Where we've been, where we are, and where we should go. Education and Treatment of Children, 20(3), 233-249.
  • Halverson, R. (2010). School formative feedback systems. Peabody Journal of Education, 85(2), 130–146. doi: 10.1080/01619561003685270
  • Hamilton, L., Halverson, R., Jackson, S. S., Mandinach, E., Supovitz, J. A., & Wayman, J. C. (2009). Using Student Achievement Data to Support Instructional Decision Making. IES Practice Guide. NCEE 2009-4067. National Center for Education Evaluation and Regional Assistance.
  • Hanson, M. J., Horn, E., Sandall, S., Beckman, P., Morgan, M., Marquart, J., ..., & Chou, H. Y. (2001). After preschool inclusion: Children's educational pathways over the early school years. Exceptional Children, 68(1), 65-83.
  • Ikemoto, G. S., & Marsh, J. A. (2007). Chapter 5 cutting through the “data‐driven” mantra: Different conceptions of data‐driven decision making. Yearbook of the National Society for the Study of Education, 106(1), 105-131.
  • Kane, M. T., & Wools, S. (2020). Perspectives on the validity of classroom assessments. S. M. Brookhart, & J. H. McMillan (Ed.), Classroom assessment and educational measurement içinde (s. 11-26). New York: Routledge.
  • Kargın, T. (2007). Eğitsel değerlendirme ve bireyselleştirilmiş eğitim programı hazırlama süreci. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Özel Eğitim Dergisi, 8(01), 1-15.
  • Kippers, W. B., Poortman, C. L., Schildkamp, K., & Visscher, A. J. (2018). Data literacy: What do educators learn and struggle with during a data use intervention? Studies in Educational Evaluation, 56(2018), 21-31.
  • Küpper, L. (2000). A Guide to the Individualized Education Program. Office of Special Education an Rehabilitative Services, Washington, DC.
  • Lai, M. K., McNaughton, S., Timperley, H., & Hsiao, S. (2009). Sustaining continued acceleration in reading comprehension achievement following an intervention. Educational Assessment, Evaluation and Accountability (formerly: Journal of Personnel Evaluation in Education), 21(1), 81-100.
  • Lai, M., & Schildkamp, K. (2013). Data-based decision making: An overview. Schildkamp, K., Lai M., & Earl, L. (Ed.) Data-based decision making in education: Studies in educational leadership. Dordrecht: Springer. https://doi.org/10.1007/978-94-007-4816-3_2
  • Lai, M. K., Wilson, A., McNaughton, S., & Hsiao, S. (2014). Improving achievement in secondary schools: Impact of a literacy project on reading comprehension and secondary school qualifications. Reading Research Quarterly, 49(3), 305-334. doi: 10.1002/rrq.2014.49.issue-3
  • Light, D., Wexler, D., & Heinze, J. (2004). How practitioners interpret and link data to instruction: Research findings on New York City Schools’ implementation of the Grow Network. Annual Meeting of the American Educational Research Association’da sunulmuş bildiri, San Diego, CA.
  • Mandinach, E. B. (2012). A perfect time for data use: Using data-driven decision making to inform practice. Educational Psychologist, 47(2), 71-85.
  • Mandinach, E. B., & Gummer, E. S. (2013a). Defining data literacy: A report on a convening of experts. Journal of Educational Research and Policy Studies, 13(2), 6-28.
  • Mandinach, E. B., & Gummer, E. S. (2013b). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30-37.
  • Mandinach, E. B., & Gummer, E. S. (2016). What does it mean for teachers to be data literate: Laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60, 366-376.
  • Marsh, J. (2012). Interventions promoting educators’ use of data: Research insights and gaps. Teachers College Record, 114(11), 1-48.
  • Marsh, J. A., Pane, J. F., & Hamilton, L. S. (2006). Making Sense of Data-Driven Decision Making in Education: Evidence from Recent RAND Research. Occasional Paper. Rand Corporation.
  • McAlenney, A. L., & Coyne, M. D. (2011). Identifying at-risk students for early reading intervention: Challenges and possible solutions. Reading & Writing Quarterly, 27(4), 306-323.
  • McMillan, J. H. (2017). Classroom assessment: Principles and practice that enhance student learning and motivation. New York: Pearson.
  • McNaughton, S., Lai, M., & Hsaio, S. (2012). Testing the effectiveness of an ıntervention model based on data use: A replication series across clusters of schools. School Effectiveness and School Improvement, 23(2), 203–228. doi: 10.1080/09243453.2011.652126
  • Means, B., Chen, E., DeBarger, A., & Padilla, C. (2011). Teachers' Ability to Use Data to Inform Instruction: Challenges and Supports. Office of Planning, Evaluation and Policy Development, US Department of Education.
  • MEB. (2018a). Rehberlik ve Araştırma Merkezi Kılavuzu. https://orgm.meb.gov.tr/meb_iys_dosyalar/2018_01/17234231_ram_kilavuzu_2018.pdf sayfasından erişilmiştir.
  • MEB. (2018b). Özel Eğitim Hizmetleri Yönetmeliği. http://orgm. meb.gov.tr/ sayfasından erişilmiştir.
  • Militello, M., Fusarelli, B., Alsbury, T., & Warren, T. P. (2013). How professional standards guide practice for school principals. International Journal of Educational Management, 27(1), 74-90. https://doi.org/10.1108/09513541311289837
  • Noll, M. B., Kamps, D., & Seaborn, C. F. (1993). Prereferral intervention for students with emotional or behavioral risks: Use of a behavioral consultation model. Journal of Emotional and Behavioral Disorders, 1(4), 203-214.
  • Overton, T. (2012). Assessing learners with special needs an applied approach. (7th Ed.). New Jersey: Pearson Education.
  • Özmen, E. R. (2012). Zihin engellilerde öğretmenlik uygulaması öğrencilikten öğretmenliğe geçiş süreci. Ankara: Pegem Akademi.
  • Özyürek, M. (2015). Özel eğitimde ölçümleme ve değerlendirme. Ankara: Kök Yayıncılık.
  • Paet-Bullaoit, S. (2019). Policy documents and the pre-referral process in BC schools (Master’s Thesis). http://dx.doi.org/10.25316/IR-5510
  • Pierangelo, R., & Giuliani, G. (Ed.). (2007). Understanding assessment in the special education process: A step-by-step guide for educators. California: Corwin Press.
  • Poortman, C. L., & Schildkamp, K. (2016). Solving student achievement focused problems with a data use ıntervention for teachers. Teaching and Teacher Education, 60, 425–433. doi: 10.1016/j.tate.2016.06.010
  • Rallis, S. F., & MacMullen, M. M. (2000). Inquiry-minded schools: Opening doors for accountability. Phi Delta Kappan, 81(10), 766-773.
  • Reschly, D. J. (1996). Identification and assessment of students with disabilities. The Future of Children, 6(1), 40-53.
  • Russell, M. K., & Airasian, P. W. (2012). Classroom assessment: Concepts and applications. New York: McGraw-Hill Companies.
  • Saefurrohman, S., & Balinas, E. S. (2016). English teachers classroom assessment practices. International Journal of Evaluation and Research in Education, 5(1), 82-92.
  • Sagor, R., & Cox, J. (2013). At risk students: Reaching and teaching them. New York: Routledge.
  • Salvia, J., Ysseldyke, J., & Bolt, S. (2010). Assessment: In special and inclusive education, (11th Ed.). Belmont: Wadsworth, Cengage Learning.
  • Schildkamp, K., Karbautzki, L., & Vanhoof, J. (2014). Exploring data use practices around Europe: Identifying enablers and barriers. Studies in Educational Evaluation, 42, 15-24.
  • Schildkamp, K., & Kuiper, W. (2010). Data-informed curriculum reform: Which data, what purposes, and promoting and hindering factors. Teaching and Teacher Education, 26(3), 482-496.
  • Shermis, M. D., & DiVesta, F. J. (2011). Classroom assessment in action. Maryland: Rowman & Littlefield Publishers.
  • Slavin, R. E., & Madden, N. A. (1989). What works for students at risk: A research synthesis. Educational leadership, 46(5), 4-13.
  • Soukup, J. H., Wehmeyer, M. L., Bashinski, S. M., & Bovaird, J. A. (2007). Classroom variables and access to the general curriculum for students with disabilities. Exceptional Children, 74(1), 101-120.
  • Spinelli, C. G. (2012). Classroom assessment for students in special and general education. New Jersey: Pearson Education.
  • Strickland, B. B., & Turnbull, A. P. (1990). Developing and implementing individualized education programs. Columbus, OH: Merrill.
  • Terrill, T. A. (2018). Data-driven instruction from the perspective of administrators and teachers. (Doctoral Thesis). http://cardinalscholar.bsu.edu/handle/123456789/201495 sayfasından erişilmiştir.
  • Tomlinson, C. A., & Moon, T. R. (2013). Assessment and student success in a differentiated classroom. Virginia: ASCD.
  • Tunç, Z. (2011). Sınıf öğretmenlerinin risk taşıyan öğrenciler için gönderme öncesi sürece ilişkin görüşleri. (Yüksek lisans tezi). https://tez.yok.gov.tr sayfasından erişilmiştir.
  • Van Geel, M., Keuning, T., Visscher, A. J., & Fox, J. P. (2016). Assessing the effects of a school-wide data-based decision-making intervention on student achievement growth in primary schools. American Educational Research Journal, 53(2), 360-394.
  • Vaughn, S., Bos, C. S., & Schumm, J. S. (2018). Teaching students who are exceptional, diverse, and at risk in the general education classroom. New York: Pearson.
  • Weist, M. D. (1997) Expanded school mental health services. T. H. Ollendick, & R. J. Prinz (Ed.) Advances in clinical child psychology. Boston, MA: Springer. https://doi.org/10.1007/978-1-4757-9035-1_9
  • Wood, J. W. (2002). Adapting instruction to accommodate students in inclusive settings (3rd Ed.). Columbus. OH: Merrill/Prentice Hall.
Toplam 69 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Eğitim Üzerine Çalışmalar
Bölüm Makaleler
Yazarlar

Nilüfer Altun 0000-0001-8502-0286

Necdet Karasu 0000-0001-7507-4109

Yayımlanma Tarihi 25 Haziran 2021
Gönderilme Tarihi 30 Mart 2021
Kabul Tarihi 1 Mayıs 2021
Yayımlandığı Sayı Yıl 2021

Kaynak Göster

APA Altun, N., & Karasu, N. (2021). Risk Grubu Öğrenciler İçin Gönderme Öncesi Süreçte Veriye Dayalı Karar Verme. Türk Eğitim Bilimleri Dergisi, 19(1), 593-612. https://doi.org/10.37217/tebd.906636

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