Human Information Interaction

fa طراحی الگوی سواد مدیریت داده‌های پژوهشی اعضای هیئت علمی رشته‌های علوم انسانی و اجتماعی دانشگاه‌های دولتی ایران (وابسته به وزارت علوم) Designing a research data management literacy model for faculty members in humanities and social sciences at Iranian public universities (affiliated with the Ministry of Science) تخصصي Special پژوهشي Research <div style="text-align: justify;">هدف: نظر به پژوهش‌هایی که درباره سواد مدیریت داده‌های پژوهشی انجام گرفته است، هدف این پژوهش، تعیین میزان مولفه‌ها و شاخص‌های سواد مدیریت داده‌های پژوهشی اعضای هیئت علمی رشته‌های علوم انسانی و اجتماعی دانشگاههای دولتی ایران (وابسته به وزارت علوم) و ارائه الگوی مناسب با آن است. روش پژوهش: پژوهش حاضر با رویکرد کمی و روش پیمایشی و با هدف تأیید و اعتباریابی ابزار ساخته شده با استفاده از مدل پیشنهادی پژوهش انجام گرفته است. جامعه آماری شامل 360 نفر از اعضای هیئت علمی گروه علوم انسانی و اجتماعی دانشگاه‌های دولتی کشور که از طریق روش نمونه‌گیری خوشه‌ای انتخاب شدند، پرسشنامه تکمیل و برای تحلیل دادهها از روش آماری توصیفی (میانگین، انحراف معیار، جدول توزیع فراوانی) و آمار استنباطی (مدل سازی معادلات ساختاری و تحلیل عاملی اکتشافی) و نرم افزارهای SPSS و Smart Pls استفاده شده است. یافته‌ها: حاکی از آن است که شش عامل ذینفعان، خدمات، سیاست، انواع سواد، چرخه حیات داده و مسائل مالی روی هم رفته 60 درصد از واریانس کل متغیرها را تبیین می‌کنند. همچنین بالاترین میزان میانگین مربوط به عامل ذینفعان با میانگین 4/09 و انحراف معیار 0/57 است و پس از آن به ترتیب عامل خدمات، سیاست، چرخه حیات داده، انواع سواد و مسائل مالی در رتبه‌های بعدی قرار گرفتند. نتیجه‌گیری: رابطه مولفه‌ها و شاخص‌های سواد مدیریت داده‌های پژوهشی از دیدگاه اعضای هیئت علمی رشته‌های علوم انسانی و اجتماعی دانشگاه‌های دولتی ایران نشان دهنده اهمیت بالای هر یک از این مولفه‌ها در ارتقاء کیفیت و کارآمدی پژوهش‌ها است و تأثیر مثبتی در سواد مدیریت داده‌های پژوهشی دارد. تلاش برای شناخت فرآیندها و زیرساخت‌های مرتبط با مدیریت داده‌های پژوهشی به افراد جهت دستیابی به نتایج تحقیقات بهتر و گسترده‌تر ارزشمند است.  </div> <div style="text-align: justify;">Introduction Introduction There are many data collections in decision-making and every day a large number of these data are collected in research projects by humans or by devices and in this data, to better understand the issues related to data, we need to first understand the data and the literacy related to them. Data literacy is defined as information by reading, creating and communicating with data: that we can find data, make information about it, learn the tools to work with data, have less management of it. We can have, analyze and refine data, learn to share data and make simple decisions.  Research data management includes; production, access, tools, storage and reuse of research data with sufficient and easy-to-use help in virtual research infrastructures that form the main part of the monitoring cycle, which itself includes ideation. It is to create or receive, evaluate, select, ingest, preserve, store, access, reuse (Cox and Verban, 2014). Studies on research data management are now common, while there is a global ease of research data, but it continues to be difficult to keep data easily accessible. Session, we know more than yesterday about the role of research data in the design and implementation of new research, but the trends and infrastructure to support researchers in research data management, need. (Varana, 2024). Considering the research that has been conducted on research data management literacy, the aim of this study is to determine the components and indicators of management literacy. ) and to provide a suitable model for research data management literacy. Methods and Materoal The present study was conducted with a quantitative and survey method and aimed at evaluating and validating the tool built using the proposed research model. The statistical population of the National Institute of Higher Education Research and Planning was 112 academic centers affiliated with the Ministry of Science and the total number of faculty members of the humanities and social sciences of the country's public universities was 8,441. Due to the large volume of data, 360 people were selected using cluster sampling. Then, the questionnaire was completed and descriptive statistical methods (mean, deviation indices, frequency table) and inferential statistics (structural equation modeling and exploratory factor analysis) and SPSS and Smart Pls software were used to analyze the data. Resultss and Discussion The findings indicate that the six factors of stakeholders, services, policy, types of literacy, data cycle, and financial issues are critical together, explaining 60 percent of the total variance of changes. Also, the highest level of the level is related to the stakeholders factor with a mean of 4.09 and a standard deviation of 0.57, followed by the factors of services, policy, data life cycle, types of literacy, and financial issues, respectively. Using the Pearson correlation coefficient test, it was shown that all components of research data management literacy have a positive and significant correlation with the set at the 0.01 error level. The coefficients of the factor loadings of the subscales of research data management literacy also have a good understanding of the concept of their analysis and have a strong and significant correlation with their belief.  Conclusion Research data management contributes to scientific integrity at different levels. When research data management literacy is sufficient, research data are accurate, complete, valid, and reliable. The risk of losing or damaging data, as well as the risk of unauthorized access, is minimized. In addition, research data can be shared with others with minimal effort and individuals can easily confirm the results.  The relationships between the components and indicators of research data management literacy from the perspective of faculty members in the humanities and social sciences of Iranian public universities show that higher than any of these components in improving the quality and efficiency of research, research data management literacy has a positive effect. The search for understanding the methods and infrastructures related to data management is a research for individuals to achieve better research results and valuable results. The results of this study show that different levels of research data management literacy among university professors know, and also need to have literacy skills in research data management that they do and create. Collecting, processing, validating, publishing, sharing, and archiving data are involved, and this is a characteristic of good research data management.  </div> مدیریت داده‌های پژوهشی, سواد اطلاعاتی, مدیریت داده, سواد مدیریت داده‌های پژوهشی Research data management, Information literacy, Data management, Research data management literacy 1 20 http://hii.khu.ac.ir/browse.php?a_code=A-10-1035-1&slc_lang=fa&sid=1 mozhgan oroji مژگان عروجی orojim@yahoo.com 10031947532846006045 10031947532846006045 No Ph.D. Student in Knowledge and Information Science, Science and Research Branch, Islamic Azad University, Tehran, Iran *علم اطلاعات و دانش شناسی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران nadjla hariri نجلا حریری nadjlahariri@gmail.com 10031947532846006046 10031947532846006046 Yes Professor of Knowledge and Information Science, Department of Communication and Knowledge Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran گروه علوم ارتباطات و دانش شناسی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران fahimeh babalhavaeji فهیمه باب الحوائجی f.babalhavaeji@gmail.com 10031947532846006047 10031947532846006047 No Associate Professor of Knowledge and Information Science, Department of Communication and Knowledge Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran گروه علوم ارتباطات و دانش شناسی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران