تعامل

The purpose of this survey research was to investigate the use of virtual social networks by librarians and users of public libraries located in Iran.

The current research is applied in terms of its purpose and descriptive-analytical in terms of its type and methodology. The statistical population of this research are librarians and users of social networks (Instagram and Bale platforms) used in public libraries. According to the statistics of the managers of the Instagram page and Bale page, 80% of the users of these pages are librarians of public libraries across the country, and 20% of them are regular or usual users. Therefore, out of 5000 people following these pages in June 2022, nearly 4000 people were librarians and the rest were normal users. Based on Morgan's table, the number of research samples was estimated to be 357, which were selected according to the population of each group. According to the overall response rate, which was about 80.15%, finally 204 samples from the librarian community and 81 samples from the user community were selected using convenience sampling method.

The findings of the research showed that there is a significantly positive relationship between the information format (how to display information) and the level of interaction of users and librarians (liking, commenting, etc.). In terms of the level of interaction of librarians and users with social network pages, it was found that librarians have more communication and interaction with the studied platforms than users due to the employment relationship and the need to produce content on these pages as part of librarians assigned tasks and duties. Also, according to librarians, the use of relevant information available on social media pages is effective in their organizational performance. Also, considering that foreign platforms such as Instagram sometimes face some legal restrictions in the country, it is suggested that domestic platforms increase the tendency of users by upgrading their services from a technical point of view in order to use them. Based on this, the most important result of the current research is that public libraries started to operate in social networks and this action is currently at the level of an organizational task and they still could not attract users and interact properly with them in these social networks. Therefore, it is necessary for Iran's public libraries to take action and plan for more interaction with users in these networks.

Originality/ Value: 

The most important result of the current research is that public libraries started to operate in social networks and this action is currently at the level of an organizational task and they still could not attract users and interact properly with them in these social networks. Therefore, it is necessary for Iran's public libraries to take action and plan for more interaction with users active in these networks.

The idea of creating smart machines and artificial intelligence has been around for centuries and dates back to at least the 14th century. Although the application of artificial intelligence in education is a very new field, but during the last 25 years, artificial intelligence has made achievements in some fields. Which has also affected education of course, criticisms have also been raised against excessive optimism towards contemporary artificial intelligence research. Little research has been done on the expectations of the role of artificial intelligence in education and its potential impact on education. The purpose of this study is to analyze and investigate the role of artificial intelligence in education.

Methods and Materoal:

This study was done using SWOT analysis method and its data collection method is also a library

Text In general, artificial intelligence as a catalyst for teaching and learning with the help of computers is a field with many applications. The teaching of science, technology, engineering and mathematics subjects can be enhanced with artificial intelligence-based software systems. Another potential strength is the potential of AI systems to serve learners across schools, borders, and platforms in creating ecosystems of interactive learning tools. Additionally, AI systems in education may be used to evaluate different learning models throughout the school. Without strong artificial intelligence, tutoring systems cannot provide rapid feedback to learners and enable stimulating interaction. With a realistic view, weak to moderate and strong artificial intelligence have a good ability to support teaching and learning and facilitate the daily work of teachers.Intelligent learning systems often have less artificial intelligence than expected, especially when it comes to interacting with students. Baker (2016) in a critical position classified many of the existing education systems under stupid education systems. His concept for online learning is to enhance data-driven human intelligence rather than data-driven artificial intelligence. In order to more dynamically use AI in education, there is a need for training data, one of the problems that arise is how to ensure that the data is real and free from bias. As stated by Popenici and Kerr (2017), complex AI algorithms are designed by human programmers who are likely to include their own agendas or biases in the development of the system. An important aspect of high-level machine intelligence is that it customizes learning for each student, but in doing so it intervenes by standardizing content and what is expected of the student.As reviewed by Lakin et al. (2016), it is hard to see a future where teachers are replaced by artificial intelligence systems or robots. A more positive and realistic scenario is that the role of the teacher evolves and transforms, freeing teachers from tedious daily tasks. In addition, AI in education has the potential to relieve the teacher of the burden of having all the knowledge and information that can be relevant to students. A possible use of artificial intelligence in education in the future is in the form of robots (collaborative robots) that help teachers in their daily work and tailor the learning experience to each student, for example in recording and analyzing the work of these students. And report to the teacher. The use of intelligent learning systems can provide customized instruction or instant feedback to students at any time of the day. But the depth of customization is one of the truly critical features, not superficial and personalized learning. Studies show that developers of intelligent instructional systems have been successful in their goal of adapting and surpassing computer-assisted instruction (CAI) and human teacher training in raising student test scores.The negative change in the role of the teacher may be caused by the design of stereotypical courses with low-level multiple-choice questions and the use of teachers as content developers. Most school curricula and teacher training programs are not wellprepared to take advantage of the benefits of artificial intelligence in education due to not providing artificial intelligence courses to their teachers. If teachers are not trained in the use of artificial intelligence, this can lead to misuse of the technology, for example in protecting privacy and using personal data for influence. According to Nicholas and Holmes (2018), an ethical framework should be established for the use of artificial intelligence in education, and even if adopted, it should be continuously discussed and updated to allow for the capabilities and scope of artificial intelligence and the potential use of reflect it. A growing concern among many education workers is the fear of unemployment as high-level machine intelligence systems completely take over the teaching profession. According to Popenici and Kerr (2017), artificial intelligence currently has the potential to replace a large number of teaching assistants and administrative staff in education, and therefore it is more important to investigate its impact on education. Studies show that widespread use of high-level AI systems may disrupt students' ability to learn independently and develop 21st century skills such as problem solving and critical thinking. Finally, the most severe threat to students may be AI. Surveillance cameras with built-in facial recognition. Along with machine learning, facial recognition is one area where AI is advancing much faster than AI ethics. By using this technology, schools may collect students' biometric information, for example, under the pretext of reducing the many working hours that employees spend on registration and attendance. Support using artificial intelligence systems in education and robotics is certainly an opportunity, but social robots are still in their infancy and have limited social skills. In the near future, a realistic opportunity lies in the development of robots that can provide personalized content and rapid feedback. As in the manufacturing industry, teachers will soon be able to reprogram the cobots using block programming code that doesn't require advanced programming skills. Of course, there are also threats, and for purely economic reasons, we will probably experience cases where teachers are replaced by artificial intelligence solutions in education. Universities with financial problems may be tempted to try solutions, such as Deakin University in Australia, which offers a service where any student who asks can expect tailored information and advice. However, since the common concern is how to submit assignments and how to pay for parking, such systems pose a threat to administrative staff rather than teachers. Finally, as with AI in general, ethics is a major and immediate challenge in the use of AI in education, even though the threats posed by AI in education may not be as dramatic as in other AI areas. Automatic will not be useful. Quality teaching is a complex and creative profession involving improvisation and spontaneity where humans are not easily replaced. In general evaluation, it can be said that there are many ways that artificial intelligence can help students. From identifying signs of effort to creating a more interactive and personalized learning program.Here are four ways that artificial intelligence can have a positive impact on student learning; Personalized learning: The ability to respond to personalized learning needs is one of the most positive benefits of artificial intelligence in education. Artificial intelligence technology can easily adapt to different learning styles. AI technology can analyze students' past performance and create tailored curricula and settings based on past performance. When it comes to personalized learning, AI can also point students in the right direction for resources and other useful data and information. Artificial intelligence has the ability to provide personalized study plans for students without having to wait for interventions from learning professionals. All while meeting the overall goal of making learning easier and helping students engage with content more effectively. Ultimately, where AI really helps personalized learning is in its ability to reach students on a massive scale. With overcrowded classrooms at the elementary school level and classrooms of hundreds at the secondary level, AI can help personalize education for all students at once, making it easier for everyone to succeed. Tutoring: Sometimes students need extra help, and AI allows you to access on-demand tutoring without an in-person or live tutoring session. Because the AI uses algorithms to adapt, it can quickly change to cover the areas where students need the most support. Just like a human tutor who adapts to a student's learning style and ability to absorb information, AI tutoring systems are very useful in their ability to focus on improving and deepening student learning as a whole. The main advantage of AI-based tutoring technology is the ability to help students understand complex concepts and terms on a mass level. Finally, with artificial intelligence, access to tutoring is no longer limited to those who can afford it. In addition, instructors can spend less time helping those who do not understand the concepts. Assessment and grading: A large part of teachers' time is spent grading assignments. Artificial intelligence technology can help speed up this process. Additionally, when it comes to grading assignments, AI technology can help analyze and get feedback from students on things like grammar, content, and vocabulary. By removing this part of teachers' duties, they can focus on other aspects of teaching that are more important, such as lesson planning and student engagement. Finally, one of the biggest benefits of automated assessment is that it eliminates human error, biases, and mistakes. It can also give each student an outline of where they went wrong and how they can improve, without taking up extra time from teachers. Improving student interaction: Artificial intelligence can engage students in educational content and make learning more interesting. One of the ways that educators and teachers can incorporate artificial intelligence into the classroom is through the use of catboats. The ability of catboats to personalize and adapt to students' learning styles creates more opportunities to keep students engaged, and the fact that catboats can be accessed anytime or anywhere means that students they can work at their own pace and continue their learning outside of traditional classroom time. The fact that AI improves engagement is exciting for course planners and administrators. This means they can deliver highly personalized and interactive learning in their courses, regardless of the subject, helping to amplify the impact on people's lives. Discussed how artificial intelligence can be useful for students. In addition there is great potential impact on coaches and teachers – particularly in ways it can save time.The three advantages of artificial intelligence in education for teachers are: 1- Predictive analysis an interesting and emerging area of artificial intelligence in education is prediction. AI can analyze data and predict which students might fall behind due to the educational gap. Predictive analytics is exciting for educators because it means students struggling with learning challenges can be identified earlier and given the tools they need to succeed. Additionally, early intervention means that students who otherwise fail or struggle might have the opportunity to become successful students by giving them the right tools to help them succeed. 2-Advanced educational methods one of the methods of using artificial intelligence in education is to improve teaching methods. Today, due to the vast amount of content and information, teachers often have little time to organize alternative learning methods without spending more than hours of classroom time. Using artificial intelligence technology, teachers have the ability to quickly put together games and simulations that help students practice and learn the lessons being taught without spending more time on lesson planning. It saves a lot of time for teachers. 3- Facilitating evaluations and grading if you ask any teacher, they will tell you that assessment is one of the most time-consuming parts of the job. One of the exciting areas of artificial intelligence in education is the use of artificial intelligence technology to improve and speed up the assessment and grading process. For example, assessments can be done in real time instead of lengthy home marking. This not only saves time for teachers, but also improves students' understanding of the material in the moment.

The research findings show that there are both opportunities and threats regarding the role of artificial intelligence in contemporary education. In many ways, AI appears to have a promotional mode. But like other areas of advertising, it has the potential to grow with specific applications in educational and learning activities. The results of the research show that the awareness of artificial intelligence and the study of the role of artificial intelligence in education will reduce the risk of substituting artificial intelligence instead of using artificial intelligence in education

The clinical staff encounter important and common information problems which solving them often requires accurate, valid and reliable information that can be accessed and used in the shortest time. The purpose of this study was to investigate the effect of education and awareness components on the collaborative information seeking behavior among the clinical staff of the Qazvin University of Medical Sciences during the implementation of research projects in 2020.

This research was a semi-experimental study based on pre-test, post-test design. The statistical population of this study consists of 40 clinical staff working in hospitals. Data collection was done through a questionnaire.

Educational intervention had a significant effect on increasing the level of collaborative awareness of individuals as well as their participation in the information seeking process (P<0.05). Evaluation of the structural equation model of CIS behavior with RMSEA= 0.058 and P value <0.05 showed that the model had a good fit.

The results of evaluating the collaborative information seeking behavior of clinical staff showed with increasing people's awareness about collaboration methods, the level of interaction and group cooperation has increased and its representation in increasing team communication and division of tasks is well visible. Information sharing as an activity that is the result of cooperation and collaboration of individuals, enables participants to create collective knowledge, maintain collaborative awareness and create a common understanding. It can include the transfer of information needs and retrieved results, knowledge processing, and transfer in the team's knowledge repositories.

It is necessary to pay attention to the dimensions of interaction as a basic concept in computer environments to understand and draw the psychological function and users’ behaviors and the optimal design of Interactive Information Retrieval systems. Also the issue of interaction, due to its complex nature, requires the simultaneous attention of personal-cognitive, behavioral, environmental factors of users related to the process of information retrieval and correct understanding of these components. Hence, the main aim of this study is presenting a framework for main and sub elements of information retrieval interaction based on social-cognitive theory and to develop a checklist for Interactive Information Retrieval based on this theory in digital libraries. The present study was conducted using library and survey methods. In this regard the survey of experts and Delphi panels were used in two stages. Initially, the extraction and evaluation of various components of Interactive Information Retrieval in digital library systems as well as the effective components of social-cognitive theory were done via the study of different texts. Then, the dimensions and components of interaction, based on social-cognitive theory were calculated using academic experts’ opinions. These elements were set and validated in a five-option Likert scale questionnaire. The main components include three dimensions of interaction with information, interaction with interface and interaction with tasks and sub-components, each of which forms the effect group and social-cognitive theory with the three main components of personality, environment and behavior form the causes group. The community of experts included 17 experts in the field of information retrieval based on the snowball sampling method. Considering the high values of Kendall consensus coefficient in two components of personality and behavior of about 0.77 and the coefficient of 0.72 in the environment component, a total of 60 components in these three dimensions were agreed. Based on the research findings and in addition to the two stages of Delphi and after removing the components with an average of less than three in the Likert scale, 21 components in the personal dimension, 20 components in the behavior dimension and 19 components in the environment dimension were approved by the research experts. The results indicated that the authenticity item of all three components of personality, behavior and environment and comprehensiveness, objective work task complexity items of environment and subjective work task difficulity item of behavior dimension were recognized as unimportant items according to the opinion of research experts and were eliminated. The framework obtained from this study can be used as the basis for future research to apply these components with emphasis on three basic aspects of user behavior in the optimal design of Interactive Information Retrieval systems.

Throughout the concrete operational stage children gradually become socialized. This is the result of the reduction in egocentrism and the increase in decentralization and personal identity. Piaget believes that both the manipulation of concrete objects and interaction with people can form an active experience while facilitating children socialization. This results in their cognitive development. Therefore, this research aimed to investigate the extent to which children’s websites, as concrete objects, are well-equipped with the necessary features to facilitate their socialization.
This research employed mixed methods including qualitative and quantitative approach for the data gathering. The research population included 11 available Persian websites and 30 English websites which were selected from the list of The Great Websites for Children through systematic sampling method.
Findings: The findings indicate that, in general, children’s websites are not completely capable of fostering socialization in children. However, some particular websites such as Disney, PBS, and KOL were equipped with suitable features to the facilitate socialization processes in children. Despite the developmental importance of children’s websites and the possible role that they can play in facilitating the process of socialisation, no research is conducted or implemented a tool to evaluate the capability of children’s websites in this regard.