نقش میانجی مشغولیت تحصیلی در رابطه میان حمایت اجتماعی و رضایت‌مندی دانشجویان در محیط‌های یادگیری آنلاین

تقی زاده, عباس; اکبری بلوطبنگان, افضل

doi:10.22061/tej.2026.113160.3395

نوع مقاله : مقاله پژوهشی-شماره انگلیسی

نویسندگان

¹ گروه آموزشی علوم تربیتی، دانشگاه فرهنگیان، کد پستی ۸۸۹-14665، تهران، ایران

² گروه آموزشی روان‌شناسی و مشاوره، دانشگاه فرهنگیان، کد پستی ۸۸۹-۱۴۶۶۵، تهران، ایران

https://doi.org/10.22061/tej.2026.113160.3395

چکیده

پیشینه و اهداف: حمایت اجتماعی ادراک‌شده یکی از عوامل حیاتی در افزایش مشغولیت تحصیلی و رضایت‌مندی فراگیر در محیط‌های یادگیری آنلاین محسوب می‌شود. بااین‌حال، سازوکارهایی که از طریق آن‌ها حمایت اجتماعی بر رضایت‌مندی تأثیر می‌گذارد، به‌ویژه نقش واسطه‌ای ابعاد متمایز مشغولیت تحصیلی هنوز به طور کافی بررسی نشده است؛ بنابراین، پژوهش حاضر باهدف تدوین و آزمون یک مدل ساختاری انجام شد تا نقش میانجی مؤلفه‌های عاطفی و رفتاری مشغولیت تحصیلی در رابطه میان حمایت اجتماعی ادراک‌شده و رضایت‌مندی دانشجویان کارشناسی‌ارشد شاغل به تحصیل در محیط‌های یادگیری آنلاین در مؤسسات آموزش عالی ایران مورد کاوش قرار گیرد.
روش‌ها‌: در این پژوهش، ۳۹۱ نفر از دانشجویان کارشناسی‌ارشد چندین دانشگاه در ایران از طریق یک پیمایش برخط که در فروردین‌ماه سال ۱۴۰۳ انجام شد، شرکت کردند. شرکت‌کنندگان سه ابزار را تکمیل نمودند: پرسش‌نامه حمایت اجتماعی در محیط‌های یادگیری آنلاین، پرسش‌نامه مشغولیت تحصیلی در محیط‌های یادگیری آنلاین، و پرسش‌نامه رضایت‌مندی از یادگیری الکترونیکی. برای ارزیابی برازش مدل ساختاری مفروض از مدل‌یابی معادلات ساختاری (SEM) استفاده شد. سپس، به‌منظور آزمون معناداری اثرات غیرمستقیم (واسطه‌ای)، از روش بوت‌استرپ (با ۵۰۰۰ بازنموده) بهره گرفته شد.
یافته‌ها: نتایج به‌دست‌آمده نشان داد که حمایت اجتماعی دارای اثر مستقیم مثبت و معنادار بر رضایت‌مندی فراگیر است ( 37/0β = ، 01/0 p < ). افزون بر این، حمایت اجتماعی به طور معناداری هم مشغولیت عاطفی ( 90/0β = ، 001/0 p < ) و هم مشغولیت رفتاری ( 92/0β = ، 001/0 p < ) را پیش‌بینی می کند. هر دو مؤلفه مشغولیت عاطفی ( 41/0β = ، 001/0 p < ) و مشغولیت رفتاری( 25/0β = ، 05/0 p < ) تأثیر مثبتی بر رضایت‌مندی داشتند. تحلیل میانجی نشان داد که مشغولیت عاطفی ( 37/0β = )، بافاصله اطمینان 95% (26/0، 64/0) و مشغولیت رفتاری ( 23/0β =)، بافاصله اطمینان 95% (05/0، 57/0) به طور جزئی رابطه میان حمایت اجتماعی و رضایت‌مندی را میانجیگری می‌کنند که در این میان مشغولیت عاطفی دارای اثر میانجیگری قوی‌تری است. مدل ساختاری پیشنهادی از برازش مطلوبی (34/3 CMIN/df =، 92/0 CFI =، 07/0 RMSEA =، 05/0 SRMR =) با داده‌ها برخوردار بود.
نتیجه‌گیری: حمایت اجتماعی ادراک‌شده به طور مستقیم و همچنین به واسطه مشغولیت تحصیلی، رضایت‌مندی از یادگیری الکترونیکی را افزایش می‌دهد. مشغولیت عاطفی این رابطه را باقدرت بیشتری نسبت به مشغولیت رفتاری واسطه‌گری می‌کند که حاکی از نقش حیاتی پیوند عاطفی، به‌ویژه در بافت‌های فرهنگی جمع‌گرا، است. به‌منظور افزایش رضایت‌مندی دانشجویان، باید محیط‌های یادگیری الکترونیکی با طراحی هدفمند، به‌گونه‌ای ساماندهی شوند که پویایی‌های میان‌فردی حمایت‌کننده و نیز مشغولیت تحصیلی معنادار را در کنار مشارکت فعال، پرورش دهند.

کلیدواژه‌ها

موضوعات

محیط های یادگیری مبتنی بر فناوری

عنوان مقاله [English]

The Mediating Role of Academic Engagement in the Relationship between Social Support and Student Satisfaction in Online Learning Environments

نویسندگان [English]

A. Taghizadeh ¹
A. Akbari Balootbangan ²

¹ Department of Educational Sciences, Farhangian University, P.O. Box14665-889, Tehran, Iran

² Department of Psychology and Counseling, Farhangian University, P.O. Box14665-889, Tehran, Iran

چکیده [English]

Background and Objectives: Perceived social support is a critical factor in enhancing academic engagement and satisfaction in online learning environments. However, the mechanisms through which social support influences satisfaction, particularly the mediating role of distinct dimensions of academic engagement, remain underexplored. So, the current study seeks to develop and test a structural model that explores how academic engagement, specifically its affective and behavioral components, mediates the relationship between perceived social support and satisfaction among master’s students enrolled in online learning environments within Iranian higher education institutions.
Materials and Methods: A total of 391 master's students from several universities in Iran participated in this study through an online survey conducted in April 2024. Participants completed validated Persian versions of three instruments: the Online Social Support Questionnaire, the Online Student Engagement Questionnaire, and the Satisfaction with E-learning Scale. Structural equation modeling (SEM) was employed to assess the fit of the hypothesized structural model. Bootstrapping procedures (5,000 resamples) were subsequently used to test the significance of the indirect (mediating) effects.
Findings: The results revealed that social support had a significant positive direct effect on satisfaction (β = 0.37, p < 0.01). Additionally, social support significantly predicted both affective engagement (β = 0.90, p < 0.001) and behavioral engagement (β = 0.92, p < 0.001). Both affective engagement (β = 0.41, p < 0.001) and behavioral engagement (β = 0.25, p < 0.05) positively influenced satisfaction. Mediation analyses confirmed that affective engagement (β = 0.37, 95% CI [0.26, 0.64]) and behavioral engagement (β = 0.23, 95% CI [0.05, 0.57]) partially mediated the relationship between social support and satisfaction, with affective engagement demonstrating a stronger mediating effect. The proposed structural model exhibited good fit to the data (CMIN/df = 3.34, CFI = 0.92, RMSEA = 0.07, SRMR = 0.05). Conclusions: Perceived social support enhances e-learning satisfaction both directly and indirectly through academic engagement. Affective engagement mediates this relationship more strongly than behavioral engagement, highlighting the critical role of emotional connection, particularly in collectivist cultural contexts. To enhance student satisfaction, eLearning environments should be deliberately designed to cultivate supportive interpersonal dynamics and foster meaningful academic engagement alongside active participation.

کلیدواژه‌ها [English]

Social Support
Academic Engagement
Learner Satisfaction
Online Learning

COPYRIGHTS
© 2026 The Author(s). This is an open-access article distributed under the terms and conditions of the Creative Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/)

مراجع

[1] Maican CI, Cazan AM, Cocoradă E, Dovleac L, Lixăndroiu RC, Maican MA, et al. The role of contextual and individual factors in successful e-learning experiences during and after the pandemic: a two-year study. J Comput Educ. 2025;12(2):589–624. doi:10.1007/s40692-024-00323-0.

[2] Mensah C, Kugbonu MA, Appietu ME, Nti GA, Forson MA. Social support, computer self-efficacy, online learning engagement and satisfaction among undergraduate hospitality students. Cogent Educ. 2024;11(1):2335803.

doi:10.1080/2331186X.2024.2335803.

[3] Singh A, Ishrat A. The role of social support in enhancing self-efficacy and learning satisfaction in online education among secondary school students. On Horiz. 2025;33(3):320–37.

doi:10.1108/OTH-03-2025-0033.

[4] Sanders LD, Daly AP, Fitzgerald K. Predicting retention, understanding attrition: a prospective study of foundation year students. Widening Particip Lifelong Learn. 2016;18(2):50–83.

doi:10.5456/WPLL.18.2.50.

[5] Henrie CR, Halverson LR, Graham CR. Measuring student engagement in technology-mediated learning: a review. Comput Educ. 2015;90:36–53.

doi:10.1016/j.compedu.2015.09.005.

[6] Miller CJ, Perera HN, Maghsoudlou A. Students multidimensional profiles of math engagement: Predictors and outcomes from a self-system motivational perspective. Br J Educ Psychol. 2021;91(1):261–85. doi:10.1111/bjep.12358.

[7] Wang MT, Fredricks JA, Ye F, Hofkens TL, Linn JS. The math and science engagement scales: scale development, validation, and psychometric properties. Learn Instr. 2016;43:16–26.

doi:10.1016/j.learninstruc.2016.01.008.

[8] Dixson MD. Measuring student engagement in the online course: the Online Student Engagement scale (OSE). Online Learn. 2015;19(4). doi:10.24059/olj.v19i4.561.

[9] Toor KK. Parent-child relationship and students’ academic achievement: a study of secondary school students. MIER J Educ Stud Trends Pract. 2018;8(1):38–56.

doi:10.52634/mier/2018/v8/i1/1418.

[10] Pfeifer MA, Cordero JJ, Stanton JD. What I wish my instructor knew: how active learning influences the classroom experiences and self-advocacy of STEM majors with ADHD and specific learning disabilities. CBE Life Sci Educ. 2023;22(1):ar2. doi:10.1187/cbe.21-12-0329.

[11] Hsu JY, Chen CC, Ting PF. Understanding MOOC continuance: an empirical examination of social support theory. Interact Learn Environ. 2018;26(8):1100–18.

doi:10.1080/10494820.2018.1446990.

[12] Apker J. College student accounts of coping and social support during COVID-19-impacted learning. Commun Q. 2022;70(3):296–316. doi:10.1080/01463373.2022.2051574.

[13] Tannert S, Gröschner A. Joy of distance learning? How student self-efficacy and emotions relate to social support and school environment. Eur Educ Res J. 2021;20(4):498–519.

doi:10.1177/14749041211024784.

[14] Federici RA, Skaalvik EM. Students’ perception of instrumental support and effort in mathematics: the mediating role of subjective task values. Soc Psychol Educ. 2014;17(3):527–40. doi:10.1007/s11218-014-9264-8.

[15] Kok XF, Pua CY, Puah S, Devilly OZ, Wang PC, Chua EC. The mediating role of student engagement in the relationship between teacher and digital support and learner satisfaction in blended learning environments at higher education. Br Educ Res J. 2025;51(3):1313–41. doi:10.1002/berj.4123.

[16] Wortman CB, Dunkel-Schetter C. Conceptual and methodological issues in the study of social support. In: Baum A, Singer JE, editors. Handbook of psychology and health. Vol. 5, Stress. Hillsdale (NJ): Lawrence Erlbaum Associates; 1987. p. 63–108.

[17] Cohen S, Hoberman HM. Positive events and social supports as buffers of life change stress. J Appl Soc Psychol. 1983;13(2):99–125. doi:10.1111/j.1559-1816.1983.tb02325.x.

[18] Hu X, Song Y, Zhu R, He S, Zhou B, Li X, et al. Understanding the impact of emotional support on mental health resilience of the community in social media during the COVID-19 pandemic. J Affect Disord. 2022;308:360–8.

doi:10.1016/j.jad.2022.04.105.

[19] Lin TC, Hsu JSC, Cheng HL, Chiu CM. Exploring the relationship between receiving and offering online social support: a dual social support model. Inf Manag. 2015;52(3):371–83. doi:10.1016/j.im.2015.01.003.

[20] Liu C, Ma J. Social support through online social networking sites and addiction among college students: the mediating roles of fear of missing out and problematic smartphone use. Curr Psychol. 2020;39(6):1892–9. doi:10.1007/s12144-018-0075-5.

[21] Yao Z, Tang P, Fan J, Luan J. Influence of online social support on the public’s belief in overcoming COVID-19. Inf Process Manag. 2021;58(4):102583.

doi:10.1016/j.ipm.2021.102583.

[22] Vasconcellos D, Parker PD, Hilland T, Cinelli R, Owen KB, Kapsal N, et al. Self-determination theory applied to physical education: a systematic review and meta-analysis. J Educ Psychol. 2020;112(7):1444–69. doi:10.1037/edu0000420.

[23] Yan L, Tan Y. Feeling blue? Go online: an empirical study of social support among patients. Inf Syst Res. 2014;25(4):690–709. doi:10.1287/isre.2014.0538.

[24] Weng C, Tsai CC, Weng A. Social support as a neglected e-learning motivator affecting trainees’ decisions of continuous intentions of usage. Australas J Educ Technol. 2015;31(2):177–92. doi:10.14742/ajet.1311.

[25] Wong L. Student engagement with online resources and its impact on learning outcomes. J Inf Technol Educ Innov Pract. 2013;12:129–46. doi:10.28945/1829.

[26] Lin LC, Hung IC, Kinshuk, Chen NS. The impact of student engagement on learning outcomes in a cyber-flipped course. Educ Technol Res Dev. 2019;67:1573–91.

doi:10.1007/s11423-019-09698-9.

[27] Wang C, Mirzaei T, Xu T, Lin H. How learner engagement impacts non-formal online learning outcomes through value co-creation: an empirical analysis. Int J Educ Technol High Educ. 2022;19(1):32. doi:10.1186/s41239-022-00341-x.

[28] Bergdahl N, Nouri J, Fors U, Knutsson O. Engagement, disengagement and performance when learning with technologies in upper secondary school. Comput Educ. 2020;149:103783. doi:10.1016/j.compedu.2019.103783.

[29] Wang MT, Peck SC. Adolescent educational success and mental health vary across school engagement profiles. Dev Psychol. 2013;49(7):1266–76. doi:10.1037/a0030028.

[30] Fredricks JA, Blumenfeld PC, Paris AH. School engagement: potential of the concept, state of the evidence. Rev Educ Res. 2004;74(1):59–109. doi:10.3102/00346543074001059.

[31] Deng R, Benckendorff P, Gannaway D. Learner engagement in MOOCs: scale development and validation. Br J Educ Technol. 2020;51(1):245–62. doi:10.1111/bjet.12810.

[32] Fredricks JA, Hofkens TL, Wang MT. Addressing the challenge of measuring student engagement. In: Renninger KA, Hidi SE, editors. The Cambridge handbook of motivation and learning. Cambridge: Cambridge University Press; 2019. p. 689–712. doi:10.1017/9781316823279.029.

[33] Fredricks JA, McColskey W. The measurement of student engagement: a comparative analysis of various methods and student self-report instruments. In: Christenson SL, Reschly AL, Wylie C, editors. Handbook of research on student engagement. New York: Springer; 2012. p. 763–82.

doi:10.1007/978-1-4614-2018-7_37.

[34] Hernandez D, Jacomino G, Swamy U, Donis K, Eddy SL. Measuring supports from learning assistants that promote engagement in active learning: evaluating a novel social support instrument. Int J STEM Educ. 2021;8(1):22.

doi:10.1186/s40594-021-00286-z.

[35] Quin D. Longitudinal and contextual associations between teacher-student relationships and student engagement: a systematic review. Rev Educ Res. 2017;87(2):345–87.

doi:10.3102/0034654316669434.

[36] Wentzel KR, Muenks K, McNeish D, Russell S. Peer and teacher supports in relation to motivation and effort: a multilevel study. Contemp Educ Psychol. 2017;49:32–45. doi:10.1016/j.cedpsych.2016.11.002.

[37] Havik T, Westergård E. Do teachers matter? Students’ perceptions of classroom interactions and student engagement. Scand J Educ Res. 2020;64(4):488–507.

doi:10.1080/00313831.2019.1577754.

[38] Basith A, Rosmaiyadi R, Triani SN, Fitri F. Investigation of online learning satisfaction during COVID-19: in relation to academic achievement. J Educ Sci Technol. 2020;6(3):265–75. doi:10.26858/est.v1i1.14803.

[39] Barrutia I, Danielli JJ, Seminario R, Monzón P. Qualitative analysis of the level of satisfaction with virtual education in university students in times of pandemic. New Trends Qual Res. 2021;7:220–8. doi:10.36367/ntqr.7.2021.220-228.

[40] Moore JC, Shelton K. The Sloan Consortium pillars and quality scorecard. In: Shattuck K, editor. Assuring quality in online education: practices and processes at the teaching, resource, and program levels. Sterling (VA): Stylus Publishing; 2014. p. 40–9.

[41] Meyer KA. Student engagement in online learning: what works and why. ASHE High Educ Rep. 2014;40(6):1–114. doi:10.1002/aehe.20018.

[42] Croxton RA. The role of interactivity in student satisfaction and persistence in online learning. J Online Learn Teach. 2014;10(2):314–24.

[43] Gao BW, Jiang J, Tang Y. The effect of blended learning platform and engagement on students’ satisfaction: the case from tourism management teaching. J Hosp Leis Sport Tour Educ. 2020;27:100272. doi:10.1016/j.jhlste.2020.100272.

[44] Fisher R, Perényi A, Birdthistle N. The positive relationship between flipped and blended learning and student engagement, performance and satisfaction. Act Learn High Educ. 2021;22(2):97–113. doi:10.1177/1469787418801702.

[45] Yousaf HQ, Rehman S, Ahmed M, Munawar S. Investigating students’ satisfaction in online learning: the role of students’ interaction and engagement in universities. Interact Learn Environ. 2023;31(10):7104–21.

doi:10.1080/10494820.2022.2061009.

[46] Swedberg R. Exploratory research. In: Elman C, Gerring J, Mahoney J, editors. The production of knowledge: enhancing progress in social science. Cambridge: Cambridge University Press; 2020. p. 17–41. doi:10.1017/9781108762519.002.

[47] Soper DS. A priori sample size calculator for structural equation models [Internet].

[48] Kline RB. Principles and practice of structural equation modeling. 5th ed. New York: Guilford Press; 2023.

[49] Hair JF Jr, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. 7th ed. Upper Saddle River (NJ): Pearson Prentice Hall; 2010.

[50] Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6(1):1–55.

doi:10.1080/10705519909540118.

[51] Bollen KA. Structural equations with latent variables. New York: John Wiley & Sons; 1989.

[52] Malecki CK, Demaray MK. What type of support do they need? Investigating student adjustment as related to emotional, informational, appraisal, and instrumental support. Sch Psychol Q. 2003;18(3):231–52.

doi:10.1521/scpq.18.3.231.22576.

[53] Tan JS, Hurd NM, Albright JN. Attachment, appraisal support, and the transition to college among underrepresented students. Emerg Adulthood. 2019;7(1):52–8.

doi:10.1177/2167696817745454.

[54] Taghizade A, Hosseini Largani M. Psychometric properties of the Persian version of the Social Support Questionnaire in online courses: a transcultural adaptation and psychometric study. Interdiscip J Virtual Learn Med Sci. 2025;16(3):254–68. doi:10.30476/ijvlms.2025.107766.1346.

[55] Hoi VN, Le Hang H. The structure of student engagement in online learning: a bifactor exploratory structural equation modelling approach. J Comput Assist Learn. 2021;37(4):1141–53. doi:10.1111/jcal.12551.

[56] Taghizade A, Musavian SS, Hosseininik SS. Psychometric properties of the Persian version of the Online Student Engagement Questionnaire: a transcultural adaptation and psychometric study. Interdiscip J Virtual Learn Med Sci. 2024;15(3):226–40. doi:10.30476/ijvlms.2024.102125.1299.

[57] Chang KY. Factors affecting student satisfaction in different learning deliveries [dissertation]. Normal (IL): Illinois State University; 2011.

[58] Taghizade A, Safdari Z, Saedi N. Psychometric properties of the Persian version of Learner Satisfaction Survey in online courses: a transcultural adaptation and psychometric study. Interdiscip J Virtual Learn Med Sci. 2023;14(1):47–59. doi:10.30476/ijvlms.2023.97699.1203.

[59] Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39–50. doi:10.1177/002224378101800104.

[60] Mehrvarz M, Heidari E, Farrokhnia M, Noroozi O. The mediating role of digital informal learning in the relationship between students’ digital competence and their academic performance. Comput Educ. 2021;167:104184.

doi:10.1016/j.compedu.2021.104184.

[61] Cho MH, Cho Y. Instructor scaffolding for interaction and students’ academic engagement in online learning: mediating role of perceived online class goal structures. Internet High Educ. 2014;21:25–30. doi:10.1016/j.iheduc.2013.10.008.

[62] Rovai AP. Building sense of community at a distance. Int Rev Res Open Distrib Learn. 2002;3(1):1–16.

doi:10.19173/irrodl.v3i1.79.

[63] Connell JP, Wellborn JG. Competence, autonomy, and relatedness: a motivational analysis of self-system processes. In: Gunnar MR, Sroufe LA, editors. Self processes and development: Minnesota Symposium on Child Psychology. Vol. 23. Hillsdale (NJ): Lawrence Erlbaum Associates; 1991. p. 43–77.

[64] Skinner E, Furrer C, Marchand G, Kindermann T. Engagement and disaffection in the classroom: part of a larger motivational dynamic? J Educ Psychol. 2008;100(4):765–81. doi:10.1037/a0012840.

[65] Kuh GD, Cruce TM, Shoup R, Kinzie J, Gonyea RM. Unmasking the effects of student engagement on first-year college grades and persistence. J Higher Educ. 2008;79(5):540–63. doi:10.1353/jhe.0.0019.

[66] Reeve J. A self-determination theory perspective on student engagement. In: Christenson SL, Reschly AL, Wylie C, editors. Handbook of research on student engagement. New York: Springer; 2012. p. 149–72.

doi:10.1007/978-1-4614-2018-7_7.

[67] Reschly AL, Christenson SL. Jingle, jangle, and conceptual haziness: evolution and future directions of the engagement construct. In: Christenson SL, Reschly AL, Wylie C, editors. Handbook of research on student engagement. New York: Springer; 2012. p. 3–19. doi:10.1007/978-1-4614-2018-7_1.

[68] Hofstede G. Culture’s consequences: comparing values, behaviors, institutions, and organizations across nations. 2nd ed. Thousand Oaks (CA): Sage Publications; 2001.

[69] Hayes AF. Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. New York: Guilford Press; 2013.

[70] Zhao X, Lynch JG Jr, Chen Q. Reconsidering Baron and Kenny: myths and truths about mediation analysis. J Consum Res. 2010;37(2):197–206. doi:10.1086/651257.

[71] Cole JS, Gonyea RM. Accuracy of self-reported SAT and ACT test scores: implications for research. Res High Educ. 2010;51(4):305–19. doi:10.1007/s11162-009-9160-9.

[72] Akyol Z, Garrison DR. Understanding cognitive presence in an online and blended community of inquiry: assessing outcomes and processes for deep approaches to learning. Br J Educ Technol. 2011;42(2):233–50.

doi:10.1111/j.1467-8535.2009.01029.x.

[73] Cole DA, Maxwell SE. Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling. J Abnorm Psychol. 2003;112(4):558–77. doi:10.1037/0021-843X.112.4.558.

نامه به سردبیر

سر دبیر نشریه فناوری آموزش، با تواضع انتشار نامه های واصله از نویسندگان و خوانندگان و بحث در سامانه نشریه را ظرف 3 ماه از تاریخ انتشار آنلاین مقاله در سامانه و یا قبل از انتشار چاپی نشریه، به منظور اصلاح و نظردهی امکان پذیر نموده است.، البته این شامل نقد در مورد تحقیقات اصلی مقاله نمی باشد.

توچه به موارد ذیل پیش از ارسال نامه به سردبیر لازم است در نظر گرفته شود:

[1]نامه هایی که شامل گزارش از آمار، واقعیت ها، تحقیقات یا نظریه ها هستند، لازم است همراه با منابع معتبر و مناسب باشند، اگرچه ارسال بیش از زمان 3 نامه توصیه نمی گردد

[2] نامه هایی که بجای انتقاد سازنده به ایده های تحقیق، مشتمل بر حملات شخصی به نویسنده باشند، توجه و چاپ نمی شود

[3] نامه ها نباید بیش از 300 کلمه باشد

[4] نویسندگان نامه لازم است در ابتدای نامه تمایل یا عدم تمایل خود را نسبت به چاپ نظریه ارسالی نسبت به یک مقاله خاص اعلام نمایند

[5] به نامه های ناشناس ترتیب اثر داده نمی شود

[6] شهر، کشور و محل سکونت نویسندگان نامه باید در نامه مشخص باشد.

[7] به منظور شفافیت بیشتر و محدودیت حجم نامه، ویرایش بر روی آن انجام می پذیرد.