ظرفیت نظریه میدان برای توسعۀ الگوهای تحلیلی در عرصۀ آموزش عالی زمینه توسعه الگو: منش‌یابی اعضای هیأت علمی در قبال طیف‌های تحصیلی | ||
| مدیریت و برنامه ریزی در نظام های آموزشی | ||
| مقاله 10، دوره 13، شماره 1، 1399، صفحه 283-314 اصل مقاله (1.17 M) | ||
| نوع مقاله: علمی - پژوهشی | ||
| شناسه دیجیتال (DOI): 10.29252/mpes.13.1.283 | ||
| نویسندگان | ||
| احمد نامنی* 1؛ محمد فتحیان بروجنی2؛ مهدی دانا طوسی3 | ||
| 1رئیس گروه برنامه ریزی و مطالعات راهبردی، دانشگاه علم و صنعت ایران. | ||
| 2رییس دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران. | ||
| 3رئیس دایره ساماندهی امور مدرسان و منابع آموزشی بانک مسکن. | ||
| چکیده | ||
| هدف: معرفی ظرفیت بالای نظریۀ میدان برای توسعۀ الگوهای مفهومی و تحلیلی در عرصۀ آموزش عالی بوده است. در این راستا تلاش گردیده با بهره‌گیری از چهارچوب روش‌شناختی پیر بوردیو، یک پژوهش دو سطحی انجام شود. این دو سطح عبارت بوده‌اند از: الف- توسعۀ یک الگوی تشخیصی (مفهومی- تحلیلی) برای شناسائی منش (عادت واره) اعضای هیأت علمی در قبال تفاوت‌های یادگیری دانشجویان (پژوهش سطح اول). ب- اجرای الگو (پژوهش سطح دوم). مواد و روش‌ها: روش پژوهش در سطح اول، نظریه‌پردازی در چهارچوب نظریه میدان و در سطح دوم از نوع پیمایشی بوده است. جامعۀ آماری پژوهش در سطح دوم تحقیق، شامل اعضای هیأت علمی دانشگاه‌های علم و صنعت ایران، علم و فناوری مازندران و صنعتی اراک، مجموعاً 480 نفر بوده است. اعتبارسنجی الگو از طریق مصاحبه با خبرگان به صورت حضوری (نیمه ساختاریافته) و پیمایش نظر اعضای جامعۀ آماری در مورد سؤالات پژوهش از طریق پرسشنامه صورت پذیرفته است. پاسخ‌های دریافتی با مقیاس افتراق معنائی، مورد تحلیل قرار گرفته‌اند. یافته‌ها: طبق مدل حاصل از پژوهش، منش هر عضو هیأت علمی در قبال تفاوت‌های یادگیری با سنجش نگرش وی در دو بُعد؛ "اعتقاد به تفاوت در نیازهای آموزشی" و "تمایل نسبی به حمایت از طیف میانی، ممتاز یا ضعیف"، قابل مدلسازی است. بر این اساس، می‌توان اعضای هیأت علمی را به سه گروه "یکسان‌نگر"، "ممتازگرا" و "ضعیف‌گرا" طبقه‌بندی نمود. بحث و نتیجه‌گیری: موفقیت در توسعه و کاربرد یک مدل مفهومی-تحلیلی تحت پارادایم نظریۀ میدان در این پژوهش نشان داد که چهارچوب روش شناختی بوردیو در عرصۀ نهادهای آموزش عالی (دانشگاه‌ها) هم‌چون دیگر عرصه‌های اجتماعی از ظرفیت بالائی برای مدلسازی‌های رفتاری- اجتماعی برخوردار است. پیام این مقاله به نظریه‌پردازان و دانشجویان دکتری حوزۀ علوم تربیتی این است که می‌توان به جای استفاده از روش‌شناختی سازمان و رفتار سازمانی، با بهره‌گیری از روش‌شناختی نظریۀ میدان، در عرصۀ آموزش عالی به شیوه نوینی از الگوپردازی برای تحلیل رفتارها و وقایع اجتماعی پرداخت. هم‌چنین به لحاظ اجرایی می‌توان بکارگیری مدل پیشنهادی این مقاله در شناخت منش اعضای هیأت علمی در قبال تفاوت‌های یادگیری را به پژوهشگران کاربردی و دانشجویان کارشناسی ارشد توصیه نمود. | ||
| کلیدواژه‌ها | ||
| نظریه میدان؛ هیأت علمی؛ یادگیری تمایزیافته | ||
| عنوان مقاله [English] | ||
| The potential of field theory for developing analytic model in higher education | ||
| نویسندگان [English] | ||
| Ahmad Nameni1؛ Mohammad Fathian Boroojeni2؛ Mehdi Danaye toosi3 | ||
| 1Head of Strategic Planning Group, Iran University of Science and Technology. | ||
| 2Head of Industrial Engineering Department, Iran University of Science and Technology. | ||
| 3Principal of Teachers Organizing and Educational Resource in Maskan Bank. | ||
| چکیده [English] | ||
| Objective: Developing a diagnostic model for identifying the habitus of faculty members about educational spectrums using Field Theory was the main goal of this research. By the way, introducing and exploiting the capacity of Field Theory for developing analytical models in the field of higher education was the secondary aim. Materials and Method: The methodology of research in model development was conceptual theorizing by using Pierre Bourdieu's methodological principles in the field theory. In the test and accreditation of the model, the research method was of surveying kind. Participants were faculty members of Iran University of Science and Technology, Mazandaran University of Science and Technology, and the Industrial University of Arak, including a total of 480 members. Research questions were asked via questionnaire. Replies analysis was performed based on a semantic differential scale. Results and Conclusion: The habitus of each faculty member about educational spectrums can be determined through his/ her attitude in two dimensions: "belief to the difference in students training needs" and "relative willing to support privileged or poor margin." By these two dimensions, faculty members can be classified into three groups: "identical-looking," "distinguished oriented," and "poorly oriented." The most effective supportive educational programs are in place to be aligned with the collective habitus of faculty members. The framework of Field Theory has a high capacity for developing an analytical model in higher education organizations like other social fields. This framework can even be considered as a better substitute for organizational behavior theory for theorizing and modeling in educational management. | ||
| کلیدواژه‌ها [English] | ||
| field theory, Academic members, differentiated learning | ||
| مراجع | ||
|
Abolghasemi, M. & Mirali Rostami. O. (2013). The investigation of the effective factors on the academic achievements of Tehran engineering departments students for submitting a model to predicting their academic achievements. Iranian Journal of Engineering education.58, 67-84. Biggs, J. and Tang. C. (2011). Teaching for Quality Learning at University. London. Open University Press. Blass, E., Jasman, A. & Shelley, S. (2010). Visioning 2035: The Future of the Higher Education Sector in the UK. Futures, 42, 445–453. Changhui, K. (2007). Classroom Peer Effects and Academic Achievement: Quasi-Randomization Evidence from South Korea. Journal of Urban Economics, 61, 458–495. Chen, S. and Voyles, D. (2013). HESI Admission Assessment Scores: Predicting Student Success. Journal of Professional Nursing, 9(25): 32–37 Cristescu.M. s. (2013). Differenced instruction – methodological and practical demarches. Procedia - Social and Behavioral Sciences, 76, 759 – 764 Delaram, M., Aein, F. & Foroozandeh, N. (2012). The effective factors on dropout in students of Shahrekord University of Medical Sciences. Hormozgan Medical Journal, 16(2), 163- 172 Figen, A. (2010). Talented and Average Intelligent Children’s Levels of Using Emotional Intelligence, Procedia Social and Behavioral Sciences, 5, 553–558 Fischer, K. and Müller, K. (2014). Gifted Education and Talent Support in Germany.CEPS Journal,4(3), 31-43 Jonassen, D. H. and Grabowski.B. L. Handbook of individual differences, learning and instruction. Lawrence Erlbaum Associates Publishers, New Jercy. 1993. Fry, H., ketteridge, S. and Marshal, S. A Handbook for Teaching and Learning in Higher Education: Enhancing academic practice. Routledge. 2014. England. Gil-Galván, R., & Gil-Galván, F. J. (2013). How to Use Professional and Life Projects to Guide University Students towards Optimal Professional Development. Procedia - Social and Behavioral Sciences, 93, 1901 – 1905. Gqweta, N. (2012). A perspective of final year diagnostic radiography students. Radiography,18, 212-217 Hardinger, K. L., Schauner, S., Graham, M., &Garavalia, L. (2013). Admission Predictors of Academic Dismissal for Provisional and Traditionally Admitted Students. Currents in Pharmacy Teaching and Learning, 5, 33–38 Javanmard, Sh. & Safaee Movahhed, S. (2018). Educational Needs Assessment of Kharazmi University New Faculty Members in 2014-Academic Year of 2013- 2014. Journal of Management and Planning in Educational Systems, 10 (2), 87-106 Kuznetsova, E. and Regnier. J. C. (2014). Individualization of Educational Process according to C. Freinet: A Pilot Experiment in a Group of Language Learners. Procedia - Social and Behavioral Sciences, 154, 87 – 91 Knauss, P. J. &Wilsson, P. (2013). Predicting Early Academic Success: HESI Admissions Assessment Exam. Journal of Professional Nursing, 29, 28-31 Mahmoodi, D. P. & Raboo, A. (2018). Using Educational Data Mining for Grouping Learners in an E-Learning Environment for Customizing Learning Program. Journal of Management and Planning in Educational Systems, 11 (1), 83-108 McCaffery, P. The Higher Education Manager's Handbook: Effective Leadership and Management in Universities and Colleges. Routledge, England, 2010. Monzurur Rahman. S. M. (2006). Data Mining Using Neural Networks. A thesis Submitted in fulfillment of the requirements for the Degree of Doctor of Philosophy. RMIT University Mutai, E. K., Cheruiyot, T. K. and Kirui, J. K. (2015). Impact of participatory Management on employee performance: a case of MOI University. Global institute for research and education,4(2), 54- 59 National Association for Gifted Children. (2010). Pre-K to Grade 12 Gifted Programming Standards. Nistor, N., & Neubauer, K. (2010). From Participation to Dropout: Quantitative Participation Patterns in Online University Courses. Computers &Education, 55, 663-672. Nonis, S. A., Hudson, G., Philhours, M. J., &Teng, J. K. (2005). Changes in College Student Composition and Implications for Marketing Education: Revisiting Predictors of Academic Success. Journal of Business Research, 58, 321– 329. Operating Standards for Identifying and Serving Gifted Students, (2008). Ohio Administrative report. Parter, M. A. (2010). Inclusion of Students with Special Needs in General Education Classrooms.International Encyclopedia of Education. 4 (3), 721-726 Pena, A, A. (2014). Educational data mining: a survey and a data mining based analysis of recent work. Expert Systems with Applications, 41 1432–1462 Pooshneh, k. & Malmir, F. (2017). Elementary school teacher`s attitude toward inclusive education. Journal of Management and Planning in Educational Systems 2017, 10 (1), 147-157 Supreme Council of the Cultural Revolution. (1390). Naghsheye jame elmie keshvar. Dabirkhaneye shoraye aalie enghelabe farhangi. Ramsden, p. Learning to Teach in Higher Education. Psychology Press, 2007. London & New York. Rodgers, S., Stenhouse, R., McCreaddie, M., & Small, P. (2013). Recruitment, Selection and Retention of Nursing and Midwifery Students in Scottish Universities. Nurse Education Today, 33, 1301–131. Rosander, P., Bäckström, M., & Stenberg, G. (2011). Personality Traits and General Intelligence as Predictors of Academic Performance: A Structural Equation Modeling Approach. Learning and Individual Differences, 21, 590–596 Shagholi, R. and Sufean, H. (2009). Participatory management: an opportunity for human resources in education. Procedia Social and Behavioral Sciences, 1, 1939–1943 Stukalina, Y. (2013). Management of the Educational Environment: The Context in Which Strategic Decisions Are Made. Procedia - Social and Behavioral Sciences, 99, 1054 – 1062 Su, Y., Feng, L. Yang, C. & Chen, T. (2012). How Teachers Support University Students’ Lifelong Learning Development for Sustainable Futures: The Student’s Perspective. Futures, 44, 158–165 Tamana, S. & Samadi, S. (2016). The Relationship Between Students' Awareness of Academic Culture and Social and Cultural Capital. Quarterly journal of research and planning in higher education, 22(1), 99-126. Tamannaifar , M. R., Niazi , M. & Amini, M. (2007). Factors Influencing Students' Underachievement. Biannual peer review Journal ofTraining and Learning Research. 24(1), 39- 52 Tulbure, C. (2013). The Effects of Differentiated Approach in Higher Education: An Experimental Investigation. Procedia - Social and Behavioral Sciences, 76, 832–836 U.S. Department of Education, for Each and Every Child—A Strategy for Education Equity and Excellence, Washington, D.C., 2013 Willcockson, I. U., Johnson, C. W., Hersh, W. & Bernstam, E. V. (2009). Predictors of Student Success in Graduate Biomedical Informatics Training: Introductory Course and Program Success. Journal of the American Medical Informatics Association,16, 837–846 | ||
|
آمار تعداد مشاهده مقاله: 3,929 تعداد دریافت فایل اصل مقاله: 2,274 |
||