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Showing 23 results for Literacy
Mazhar Babaee, Hedyeh Azagh, Shima Yazdanpanah,
Volume 9, Issue 4 (1-2023)
Volume 9, Issue 4 (1-2023)
Abstract
Introduction: Information literacy is the ability to identify and critically evaluate information to solve problems in a specific field. The use of this procedure in the environment of universities and for students depends on their awareness of the many angles of information measurement in this field.
Methods: this study was to investigate the information literacy status of students and teachers of the Farhangian University of Kurdistan Province From six perspectives: information review, information source recognition, information dissemination, information recognition, flexibility, and information search. This research is practical and of a survey type and was carried out between January and March 2022. The study population consisted of all students of Farhangian University of Kurdistan Province in the academic year 2021-2022, which numbered over 1500 people. Using random sampling, 350 student-teachers were selected as a statistical sample. The data collection tool was a researcher-made 66-item information literacy questionnaire based on a 3-point Likert scale. The reliability of the questionnaire was 86% using Cronbach's alpha method. And for its validity, the views of university professors were used. Multivariate analysis of variance, one-way analysis of variance, and Pearson torque correlation coefficient test was used to analyze the data using SPSS software.
Results: The results showed that there is a significant relationship between the components of information literacy of male and female student teachers (P = 0.0001). Therefore, in this study, gender has a small effect on the components of information literacy. Also, there is no significant difference between information literacy in its 6 components and the different educational disciplines of Farhangian University (P> 0.05). Finally, there is no significant relationship between information literacy in its 6 components and the age of Farhangian University students and teachers. Therefore, the information literacy situation of the students of the Farhangian University of Kurdistan is at an Intermediate level.
Conclusion: Information literacy is the set of skills and qualifications needed in the information society for teachers, therefore, by considering factors such as review, knowledge of sources, dissemination, recognition, flexibility, and search for information, it can be enriched. Building information literacy skills.
Mahmmoud Ahmadisharif,
Volume 10, Issue 1 (6-2023)
Volume 10, Issue 1 (6-2023)
Abstract
Purpose: This study was conducted to know the relationship between monitoring the relationship between information literacy components of marketing experts in manufacturing industries with their success rate in marketing and their success rate in marketing.
Methodology: The research method is a descriptive survey of correlation type. The statistical population of the study is all marketing experts of food production industries in Tehran, due to the size of the statistical population, 384 of them were selected as a sample. Katz and McLean's (2007) ICT questionnaire was used to collect information related to information literacy and a researcher-made questionnaire was used to measure the success of experts in marketing. Overall reliability of the Information Literacy Questionnaire based on Cronbach's alpha coefficient formula / 78. And the reliability of the researcher-made questionnaire was estimated to be 0.72.
Findings: Pearson's formula was used to analyze the data in the inferential statistics section on the correlation coefficient and Kolmogorov-Smirnov test was used to determine the normality of the data.
Conclusion: The results of the study showed that there is a relationship between ICT literacy and each of its dimensions (describing, achieving, evaluating, managing, combining, creating, and communicating) with the success of experts in marketing. has it.
Methodology: The research method is a descriptive survey of correlation type. The statistical population of the study is all marketing experts of food production industries in Tehran, due to the size of the statistical population, 384 of them were selected as a sample. Katz and McLean's (2007) ICT questionnaire was used to collect information related to information literacy and a researcher-made questionnaire was used to measure the success of experts in marketing. Overall reliability of the Information Literacy Questionnaire based on Cronbach's alpha coefficient formula / 78. And the reliability of the researcher-made questionnaire was estimated to be 0.72.
Findings: Pearson's formula was used to analyze the data in the inferential statistics section on the correlation coefficient and Kolmogorov-Smirnov test was used to determine the normality of the data.
Conclusion: The results of the study showed that there is a relationship between ICT literacy and each of its dimensions (describing, achieving, evaluating, managing, combining, creating, and communicating) with the success of experts in marketing. has it.
Mozhgan Oroji, Nadjla Hariri, Fahimeh Babalhavaeji,
Volume 11, Issue 3 (12-2024)
Volume 11, Issue 3 (12-2024)
Abstract
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.
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.
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