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M Narmenji, N Riahinia, M Nowkarizi, M Zerehsaz,
Volume 7, Issue 1 (6-2020)
Volume 7, Issue 1 (6-2020)
Abstract
Aim: The main purpose was to investigate the students’ information sharing behavior in social network sites with a qualitative approach.
Methodology: An applied research with qualitative approach - A Thematic Analysis method was used. Population consisted of all the students at the Universities in South Khorasan Province affiliated with the Ministry of Science, Research and Technology who had a minimum of six months experience in using one of the social network sites such as: Telegram, Instagram or WhatsApp. A non-probability (non-random), and a snowball sampling procedure was used and 17 persons were interviewed. The semi-structured type of interview was incorporated.
Findings: Results showed that most students’ information sharing was done on Telegram and Instagram, respectively. Eighteen primary codes were provided by students as motives for information sharing in social network sites. These primary codes were categorized into two main categories (personal and social motives) and seven subcategories. Among all the primary codes of the two main categories, the sub-category of “net-surfing and entertainment” had the highest occurrence. For the types of information shared on social network sites by student, 24 primary codes were obtained. These primary codes were categorized into eight sub-categories and two main categories (knowledge and entertaining information). Among the sub-categories identified, the most recurrently shared types of information were “literary-artistic information” and “scientific-educational information”.
Conclusion: For surfing and entertainments’ own good - information sharing on social network sites could lead to admittance of valuable information. If properly planned, it may function as a suitable platform (available to diverse strata of the society, especially the students, at the lowest possible cost) to attain the best possible practice especially in educational settings.
Hoda Khodashenas, , Zobeideh Khodashenas,
Volume 8, Issue 3 (11-2021)
Volume 8, Issue 3 (11-2021)
Abstract
Background and Aim: The purpose is to identify the components of health literacy amongst University library users.
Methodology: This purpose-based research is a qualitative-quantitative survey study. The qualitative part concentrates on the individuals with background in health literacy and research. In the quantitative part students at the libraries of the University of Tehran were surveyed. The research instrument was a structural questionnaire on health literacy of individuals in the community. Reliability of more than 0.7 was obtained via Cronbach’s alpha
Findings: It is important to mention that understanding health information stood at the desirable level and other components stood at a comparatively appropriate stage among the elements of health literacy of users at the University Library of Tehran. Although there is a significant relationship between health literacy skills with income, there is no significant relationship among gender, age, faculty, and level of education with health literacy skills.
Conclusion: It is necessary to measure health literacy practically and apply the results in the community and other comparable communities. The level of health literacy could increase considerably by using programs to promote the health literacy of the community.
Maryam Bomery, Dr. Reza Karimi, Dr. Rouhallah Khademi,
Volume 9, Issue 1 (5-2022)
Volume 9, Issue 1 (5-2022)
Abstract
Objective: Health information on diseases could help prevent the spread and the treatment and is the most vital needs of people in daily life. One health issue that has plagued the world in recent years is the corona virus. Therefore, the main purpose of this study was to investigate the health information behavior of graduate students at Qom University.
Methodology: Applied descriptive survey method was used. Population was all 3000 graduate students at Qom University. Using Morgan table, sample of 300 students were seleted, out of which 200 studnts answered the questionnaires. Data was collected through the standard Lango questionnaire. Research hypotheses were scrutinized using independent t and one-way ANOVA. Age, gender, place of residence, income and information seeking behavior of graduate students were investigated.
Findings: The most information sources were Internet, Social networks, TV and the family. while the least go to brochures and pamphlets. Althugh, graduate students could obtain corona information from social networks and Internet, nonetheless their active use of corona information is slightly more from traditional sources of television and radio. There was no significant relation of behavior variables in information retrieval, perception in information retrieval, interpersonal interaction in information retrieval, impact of information on disease, active retrieval of information and passive retrieval of information with regard to age, gender and place of residence of graduate students.
Conclusion: Results revealed that the students have health information literacy and could identify and use related health information. In spite of increasing use of new sources such as social networks and Internet, information obtained from traditional sources has been more trusted and used. Non of the variables of gender, age, income and place of residence had any effect on health information seeking behavior of students. All subjects had the same information seeking behavior.
Methodology: Applied descriptive survey method was used. Population was all 3000 graduate students at Qom University. Using Morgan table, sample of 300 students were seleted, out of which 200 studnts answered the questionnaires. Data was collected through the standard Lango questionnaire. Research hypotheses were scrutinized using independent t and one-way ANOVA. Age, gender, place of residence, income and information seeking behavior of graduate students were investigated.
Findings: The most information sources were Internet, Social networks, TV and the family. while the least go to brochures and pamphlets. Althugh, graduate students could obtain corona information from social networks and Internet, nonetheless their active use of corona information is slightly more from traditional sources of television and radio. There was no significant relation of behavior variables in information retrieval, perception in information retrieval, interpersonal interaction in information retrieval, impact of information on disease, active retrieval of information and passive retrieval of information with regard to age, gender and place of residence of graduate students.
Conclusion: Results revealed that the students have health information literacy and could identify and use related health information. In spite of increasing use of new sources such as social networks and Internet, information obtained from traditional sources has been more trusted and used. Non of the variables of gender, age, income and place of residence had any effect on health information seeking behavior of students. All subjects had the same information seeking behavior.
Mrs Khatoon Vakili,
Volume 9, Issue 1 (5-2022)
Volume 9, Issue 1 (5-2022)
Abstract
Background and Aim: The aim was to investigate the effect of membership in social networks and mental rumination on cognitive flexibility of female law students at Islamic Azad University of Ghaemshahr.
Method: The research method was correlational. Sample of 70 law students randomly selected by Krejcie Morgan. Instruments used were: 1. A questionnaire to study the effects of membership in social networks and; 2. Cognitive flexibility questionnaire (Taghizadeh and Nikkhah) and mental rumination scale questionnaire (Taghizadeh).
Results: Results showed that the intensity of the effect of membership in social networks (24.5%) was higher than the intensity of the effect of mental rumination (12.8%). The intensity of the effect could also be seen for all three subscales of the two variables. The results of structural equations to reject or confirm the hypotheses had shown that both variables of membership in social networks (P = 0.001 and β = 0.526) and rumination (P = 0.002 and (β = -0.379) on flexibility Cognitive have had a significant effect that giving the value of the path coefficient could be said that membership in social networks has a positive effect and mental rumination has a negative effect.
Conclusion: Membership in social networks has had far greater and more destructive effects than mental rumination on students' cognitive flexibility, and it could be said that both the variables of membership in social networks and mental rumination have affected cognitive flexibility.
Method: The research method was correlational. Sample of 70 law students randomly selected by Krejcie Morgan. Instruments used were: 1. A questionnaire to study the effects of membership in social networks and; 2. Cognitive flexibility questionnaire (Taghizadeh and Nikkhah) and mental rumination scale questionnaire (Taghizadeh).
Results: Results showed that the intensity of the effect of membership in social networks (24.5%) was higher than the intensity of the effect of mental rumination (12.8%). The intensity of the effect could also be seen for all three subscales of the two variables. The results of structural equations to reject or confirm the hypotheses had shown that both variables of membership in social networks (P = 0.001 and β = 0.526) and rumination (P = 0.002 and (β = -0.379) on flexibility Cognitive have had a significant effect that giving the value of the path coefficient could be said that membership in social networks has a positive effect and mental rumination has a negative effect.
Conclusion: Membership in social networks has had far greater and more destructive effects than mental rumination on students' cognitive flexibility, and it could be said that both the variables of membership in social networks and mental rumination have affected cognitive flexibility.
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.
Dr Mohammad Reza Shekari, Dr Mohammad Hassan Zadeh,
Volume 9, Issue 4 (1-2023)
Volume 9, Issue 4 (1-2023)
Abstract
Introduction: A thorough understanding of the drivers and inhabitants to the study can provide the basis for effective planning to improve the study. The aim of this study was to investigate the driving and inhibitory factors affecting the tendency of Iranian knowledge and information science PhD students towards study.
Methods: This research was conducted with a qualitative approach and using content analysis method. The data collection tool was an in-depth semi-structured interview. The interviews were conducted through face-to-face visits, telephone calls, e-mails, sending and receiving audio files and conversations on social media. PhD students in knowledge and information science at state universities, Payame-Nour Universities, and Islamic Azad Universities form the research community, and 33 people were selected as the research sample using targeted sampling.
Results: The results show that four factors of "professor", "compulsion", "personal promotion" and "interest" were the driving factors among doctoral students and seven factors were "professor", "family". "Access problems", "ambiguous future", "problems and weaknesses of the educational system", "growth of the spirit of need to study" and "non-participation in teaching" have been identified as deterrents factors.
Conclusion: The drivers and inhabitants of the study are very intertwined and interrelated. Some of these factors affect others and are in some way the cause and effect of each other. To strengthen effective factors and reduce barriers to study, it requires more effort from professors and programmers at the macro level, libraries and librarians, politicians, and more effort and planning from doctoral students themselves. It is necessary for the education system and the education system in universities to get out of the monolithic system and to be the speaker of unity. In this way, students are less likely to study and research until there are fundamental changes in teaching methods and curriculum content in the education system. For the first time, this study examines the most important factors and barriers to the advancement of PhD students in information science, and the results provide qualitative factors for the context of the research community. And it can be used in planning and policy making for the doctoral program of the field. Since no research has been done in this field so far, the present study can be considered as a new research in this field.
Zahra Poorpir, Mohammadreza Kiyani, Mohammad Ali Rostaminegad, Seyyed Ebrahim Hosseini Zargaz,
Volume 10, Issue 2 (9-2023)
Volume 10, Issue 2 (9-2023)
Abstract
Introduction and Objective: Covid-19 is an infectious respiratory disease that, like other infectious diseases, has affected people's health. As an important source for obtaining health information, social media have made a major contribution in meeting the need for information about Covid-19. The role of people's health information-seeking behavior is important in disease management and control, and it has an impact on the health of the society in the future.
Methodology: This research was practical and survey type. Statistical population, all students were studying at Birjand University at the time of the study. Sampling was done based on proportional classification random sampling (370 people). The research tool was a researcher-made questionnaire. The validity of the questionnaire was measured by using the opinions of experts and experts in information science, epistemology and medical sciences, and its reliability was measured using Cronbach's alpha (0.897).
Findings: The findings of the research showed that students used more search engines, foreign social networks and news media to get information about Covid-19 than reliable sources such as official specialized medical websites. Telegram and Instagram were the most used. They paid more attention to news related to covid-19 and preventive behaviors than getting information about treatment methods. The amount of negative and positive consequences of obtaining information about this disease on students was less than expected and among the components of information-seeking behavior, they paid the least attention to information sharing. In the field of aspects related to Covid-19, they paid the most attention to the educational aspect and the least attention to the political aspect.
Conclusion: Information and realizing its value and importance in human life today, leads to the concern of how to access the required information from among the multitude of available information. Information-seeking behavior follows the need for information, which includes activities such as information search, search tools, the type of information sought, search problems, and factors affecting it. Since the need for health information due to the spread of the Covid-19 disease creates concerns. Therefore, it leads to health information-seeking behavior, which includes actions related to searching and finding health-related problems, information about diseases, risk factors, and health promotion (Jalilian et al., 2021). In the course of searching for information, a person may use a manual information system or a computer-based system (Wilson, 2000).
Social media, as a platform that provides a lot of information, including health-related information, has been distinguished from other information systems due to components such as quick and easy access, interactive and comprehensible, and convenience. In the process of health information seeking behavior, the role of social media as a tool for searching for information and its effect on people's behavior is important (Liu, 2020). The types of information about which the search helps to meet the need for information and curiosities in the midst of this pandemic, information such as news related to Covid-19 (the number of patients and deaths), preventive behaviors (washing hands regularly, wearing masks) , vaccination, etc.) and various medical methods and related drugs.
Covid-19 is a respiratory disease caused by the corona virus and spread in late 2019. The Corona pandemic was declared by the World Health Organization as a public health emergency (Jalilian et al., 2021). This epidemic prompted scientists in different disciplines to investigate various issues arising from this phenomenon (Shehata, 2020). Access to health information is essential for any country and this is more important in developing countries where health challenges are more (Ankama et al., 2021). Progress in the prevention of Covid-19 is partially dependent on understanding the process of health information seeking behavior and its tools. To promote effective health knowledge, behavior change must be done at the individual level, and health messages must be accurate, transparent, and comprehensible. Also, be available and appropriate to the cultural environment of the society (Jalilian et al., 2021). Due to the epidemic nature of this disease and its unexpected consequences, the role of people and their information behaviors in fighting and controlling this disease is very important (Ostadi, 2019).
The main variables of the research included: the amount of use of each type of social media, the amount of use of each type of social network, the types of information obtained, the amount of negative and positive consequences of obtaining information about Covid-19, the amount of each From health information seeking behaviors and aspects related to covid 19.
To carry out the research, the researcher-made questionnaire was used as a data collection tool. This questionnaire was compiled in two parts based on the objectives and questions of the research. The first part includes questions related to the objectives of the research, and in the second part, three questions are asked about the personal characteristics of the respondents.
This questionnaire had 42 items and was measured in 7 variables, which are: social media (items 1-9), social networks (items 10-16), types of information obtained (item 17-21), negative consequences of information acquisition (items 22-26), positive consequences of information acquisition (items 27-33), types of health information-seeking behavior (items 34-37) and related dimensions with covid 19 (items 42-38). The mentioned questionnaire was distributed among the statistical population after checking and testing the validity and reliability. In this research, in order to measure the content validity of the questionnaire, the questions of the questionnaire were prepared by studying and reviewing related study sources, and then using the opinions of experts and experts in information science, philology, and medical sciences, they were reviewed and modified.
Out of a total of 224 respondents, that is, 58% of the people were women and 162 of them, equal to 42%, were men. Students in the study field of humanities with 167 people (43%) have the highest frequency among the respondents. After that, engineering science group with 112 people (29 percent), basic science group with 63 people (16 percent) and agricultural science group with 44 people (12 percent) respectively.
The number of respondents in the undergraduate level was the highest with 319 people (83 percent), as well as 47 people (12 percent) in the master's degree and 20 people (5 percent) in the doctoral level.
In the social media variable, the results showed that the average amount of social media use was generally lower than average. In the components of official medical websites, doctors' websites, unofficial websites, internal social networks, Wikipedia and encyclopedias, discussion groups and forums are also less than It was average. According to Zhang and Zhao (2017) and Haider et al. (2009), concern about the quality of information reduces the amount of social media use and consumer participation.
In the variable of social networks, the findings show that the average amount of use of the variable of social networks was generally lower than the average. Due to the filtering of YouTube, Twitter, and Clubhouse platforms, their use was quite logically lower than average. In the components of the Telegram and Instagram platforms, the average amount of use was more than average. The researchers' field observations of the users' use of these networks are consistent with the obtained results, as a result, the use of social networks due to their accessibility and the widely used role of mobile phone technology today is a source of information dissemination and information acquisition. Since the specialized information on websites and official sources is valuable, it is necessary to pay attention to the reason why they are not given much attention, and it should be carefully rooted and investigated.
The search rate of Birjand University students regarding each type of health information about Covid-19, the research indicates that, in general, the search rate in the variable of types of information about Covid-19 was equal to the average. But in the components of news related to Covid-19, preventive behaviors were more than average. Since the purpose of searching users during the Covid-19 pandemic was to deal with the said disease; Therefore, the results refer to the consumption of health information related to the news of Covid-19 and various preventive behaviors, because obtaining health information about each of the information related to Covid-19 is important in the process of managing and controlling this disease.
The rate of negative consequences of acquiring information about Covid-19 was below average. Also, in all components of worry, anxiety, lack of trust in information, confusion and confusion, and cognitive avoidance were also below the average level. What causes worry and anxiety in people is often lack of awareness and lack of ability to manage a crisis. In Nakheizadeh's new research (2019), the level of anxiety caused by covid-19 was high, as Nakheizadeh's study shows, his research is related to the early period of the corona epidemic. What is remarkable at the beginning of the matter, with the indiscriminate spread and the lack of sufficient and correct information about this disease, as well as the lack of a related vaccine, the influx of this amount of anxiety and worry among people can be considered normal. Moreover, the data of the current research was collected after about two years of the corona virus, when the students were in the approximate routine of life before the corona virus, right at the same time as face-to-face education in the university, and this change in the results can be completely logically explained. Justified. Also, the study of Bigdali et al. (2013) also expressed the positive view of users towards health information on the web. Montsi (2020) also stated that even receiving fake information does not affect people's physical or mental health, and its results are completely intangible, which can be roughly generalized to the results of this research and considered consistent.
In the variable of positive outcomes of acquiring information about Covid-19, it was below average. Also, in the components of the ability to recognize the need for information, search skills, the spirit of cooperation and information sharing, and the promotion of critical thinking, it was also below average. Also, in the components of knowledge of information sources and ability to evaluate information sources, it was equal to the average level. As a result, considering that in some components of the skill of recognizing the need for information and the ability to evaluate information sources, their average score was equal to the average level, which indicates that their health literacy is average; Because the results are consistent with the acquisition of their health information sources (social networks), so it is in line with the results of Apok and Ellis.
The average rate of performing various types of information-seeking behavior about Covid-19 was higher than average. Also, in the components of information search, identifying the need for information and changing health and treatment behavior, seeking more information was more than average. In the information sharing component, the average score of this component was equal to the average; Considering that the sources of obtaining health information about this disease are basically the media and social networks. What emerges from the evidence is that following a crisis or problem related to health and feeling the need for related information, people start searching for related sources and if it is noticeable, their health information seeking behavior is an increasing trend. has it. Therefore, the present study is consistent with all previous studies.
The results of the present study show that the average of information acquisition in the variable of information dimensions related to Covid-19 was higher than the average and also in all components, including dimensions related to health, economic, political, social and educational, the average score was higher. It was average. In other words, the findings show the students' concerns about each of the dimensions related to economy, health, politics, social justice, and especially about education and concerns about holding classes, not having the necessary infrastructure in an optimal way. In some people, lack of concentration and anxiety is caused by the situation.
The findings showed that the most sources of obtaining health information for students of Birjand University are search engines, foreign social networks and news media, and they paid less attention to reliable media such as official specialized medical websites. Also, the results point to the important and prominent role of Telegram and Instagram platforms. In addition, what the studied community sought to obtain information about covid-19 was mostly preventive behaviors and news related to covid-19 rather than its treatment methods. Also, the results showed that the health information-seeking behavior of Birjand University students has generally increased during this pandemic; But they have done the behavior of sharing information related to Covid less. Meanwhile, the role of dimensions related to Covid-19, including dimensions related to health, economic, political, social and educational, and obtaining information about each of these dimensions was of great importance for students, and the most important aspect for them was the educational dimension. .
The results showed that women used reliable sources such as official specialized medical websites and news media compared to men, and men used social networks (Telegram, Instagram, Twitter and YouTube) and search engines to get information about Covid. 19 have used. The influence of the role of gender showed that women are more interested in obtaining all kinds of information about this disease, and also paid more attention to the negative consequences of women; After creating negative consequences in women, they sought to obtain information about preventive behaviors. Because a significant relationship has been established between negative consequences and preventive behaviors in past studies. In addition, the role of gender had no effect on the positive outcomes and dimensions related to Covid-19, except for the economic dimension component. The field of study and level of study did not make a significant difference in the research variables. Based on this, it is suggested to hold training courses to improve the quality and awareness of health information literacy in social networks and news media for students of different levels. Also, policy makers and decision makers should pay more attention to providing authentic information on social media for the audience. Social networks and internal messengers should be adapted in the field of providing health information. Future researches can examine the subject of study in other societies and use different research methods to collect data or analyze findings.
Methodology: This research was practical and survey type. Statistical population, all students were studying at Birjand University at the time of the study. Sampling was done based on proportional classification random sampling (370 people). The research tool was a researcher-made questionnaire. The validity of the questionnaire was measured by using the opinions of experts and experts in information science, epistemology and medical sciences, and its reliability was measured using Cronbach's alpha (0.897).
Findings: The findings of the research showed that students used more search engines, foreign social networks and news media to get information about Covid-19 than reliable sources such as official specialized medical websites. Telegram and Instagram were the most used. They paid more attention to news related to covid-19 and preventive behaviors than getting information about treatment methods. The amount of negative and positive consequences of obtaining information about this disease on students was less than expected and among the components of information-seeking behavior, they paid the least attention to information sharing. In the field of aspects related to Covid-19, they paid the most attention to the educational aspect and the least attention to the political aspect.
Conclusion: Information and realizing its value and importance in human life today, leads to the concern of how to access the required information from among the multitude of available information. Information-seeking behavior follows the need for information, which includes activities such as information search, search tools, the type of information sought, search problems, and factors affecting it. Since the need for health information due to the spread of the Covid-19 disease creates concerns. Therefore, it leads to health information-seeking behavior, which includes actions related to searching and finding health-related problems, information about diseases, risk factors, and health promotion (Jalilian et al., 2021). In the course of searching for information, a person may use a manual information system or a computer-based system (Wilson, 2000).
Social media, as a platform that provides a lot of information, including health-related information, has been distinguished from other information systems due to components such as quick and easy access, interactive and comprehensible, and convenience. In the process of health information seeking behavior, the role of social media as a tool for searching for information and its effect on people's behavior is important (Liu, 2020). The types of information about which the search helps to meet the need for information and curiosities in the midst of this pandemic, information such as news related to Covid-19 (the number of patients and deaths), preventive behaviors (washing hands regularly, wearing masks) , vaccination, etc.) and various medical methods and related drugs.
Covid-19 is a respiratory disease caused by the corona virus and spread in late 2019. The Corona pandemic was declared by the World Health Organization as a public health emergency (Jalilian et al., 2021). This epidemic prompted scientists in different disciplines to investigate various issues arising from this phenomenon (Shehata, 2020). Access to health information is essential for any country and this is more important in developing countries where health challenges are more (Ankama et al., 2021). Progress in the prevention of Covid-19 is partially dependent on understanding the process of health information seeking behavior and its tools. To promote effective health knowledge, behavior change must be done at the individual level, and health messages must be accurate, transparent, and comprehensible. Also, be available and appropriate to the cultural environment of the society (Jalilian et al., 2021). Due to the epidemic nature of this disease and its unexpected consequences, the role of people and their information behaviors in fighting and controlling this disease is very important (Ostadi, 2019).
The main variables of the research included: the amount of use of each type of social media, the amount of use of each type of social network, the types of information obtained, the amount of negative and positive consequences of obtaining information about Covid-19, the amount of each From health information seeking behaviors and aspects related to covid 19.
To carry out the research, the researcher-made questionnaire was used as a data collection tool. This questionnaire was compiled in two parts based on the objectives and questions of the research. The first part includes questions related to the objectives of the research, and in the second part, three questions are asked about the personal characteristics of the respondents.
This questionnaire had 42 items and was measured in 7 variables, which are: social media (items 1-9), social networks (items 10-16), types of information obtained (item 17-21), negative consequences of information acquisition (items 22-26), positive consequences of information acquisition (items 27-33), types of health information-seeking behavior (items 34-37) and related dimensions with covid 19 (items 42-38). The mentioned questionnaire was distributed among the statistical population after checking and testing the validity and reliability. In this research, in order to measure the content validity of the questionnaire, the questions of the questionnaire were prepared by studying and reviewing related study sources, and then using the opinions of experts and experts in information science, philology, and medical sciences, they were reviewed and modified.
Out of a total of 224 respondents, that is, 58% of the people were women and 162 of them, equal to 42%, were men. Students in the study field of humanities with 167 people (43%) have the highest frequency among the respondents. After that, engineering science group with 112 people (29 percent), basic science group with 63 people (16 percent) and agricultural science group with 44 people (12 percent) respectively.
The number of respondents in the undergraduate level was the highest with 319 people (83 percent), as well as 47 people (12 percent) in the master's degree and 20 people (5 percent) in the doctoral level.
In the social media variable, the results showed that the average amount of social media use was generally lower than average. In the components of official medical websites, doctors' websites, unofficial websites, internal social networks, Wikipedia and encyclopedias, discussion groups and forums are also less than It was average. According to Zhang and Zhao (2017) and Haider et al. (2009), concern about the quality of information reduces the amount of social media use and consumer participation.
In the variable of social networks, the findings show that the average amount of use of the variable of social networks was generally lower than the average. Due to the filtering of YouTube, Twitter, and Clubhouse platforms, their use was quite logically lower than average. In the components of the Telegram and Instagram platforms, the average amount of use was more than average. The researchers' field observations of the users' use of these networks are consistent with the obtained results, as a result, the use of social networks due to their accessibility and the widely used role of mobile phone technology today is a source of information dissemination and information acquisition. Since the specialized information on websites and official sources is valuable, it is necessary to pay attention to the reason why they are not given much attention, and it should be carefully rooted and investigated.
The search rate of Birjand University students regarding each type of health information about Covid-19, the research indicates that, in general, the search rate in the variable of types of information about Covid-19 was equal to the average. But in the components of news related to Covid-19, preventive behaviors were more than average. Since the purpose of searching users during the Covid-19 pandemic was to deal with the said disease; Therefore, the results refer to the consumption of health information related to the news of Covid-19 and various preventive behaviors, because obtaining health information about each of the information related to Covid-19 is important in the process of managing and controlling this disease.
The rate of negative consequences of acquiring information about Covid-19 was below average. Also, in all components of worry, anxiety, lack of trust in information, confusion and confusion, and cognitive avoidance were also below the average level. What causes worry and anxiety in people is often lack of awareness and lack of ability to manage a crisis. In Nakheizadeh's new research (2019), the level of anxiety caused by covid-19 was high, as Nakheizadeh's study shows, his research is related to the early period of the corona epidemic. What is remarkable at the beginning of the matter, with the indiscriminate spread and the lack of sufficient and correct information about this disease, as well as the lack of a related vaccine, the influx of this amount of anxiety and worry among people can be considered normal. Moreover, the data of the current research was collected after about two years of the corona virus, when the students were in the approximate routine of life before the corona virus, right at the same time as face-to-face education in the university, and this change in the results can be completely logically explained. Justified. Also, the study of Bigdali et al. (2013) also expressed the positive view of users towards health information on the web. Montsi (2020) also stated that even receiving fake information does not affect people's physical or mental health, and its results are completely intangible, which can be roughly generalized to the results of this research and considered consistent.
In the variable of positive outcomes of acquiring information about Covid-19, it was below average. Also, in the components of the ability to recognize the need for information, search skills, the spirit of cooperation and information sharing, and the promotion of critical thinking, it was also below average. Also, in the components of knowledge of information sources and ability to evaluate information sources, it was equal to the average level. As a result, considering that in some components of the skill of recognizing the need for information and the ability to evaluate information sources, their average score was equal to the average level, which indicates that their health literacy is average; Because the results are consistent with the acquisition of their health information sources (social networks), so it is in line with the results of Apok and Ellis.
The average rate of performing various types of information-seeking behavior about Covid-19 was higher than average. Also, in the components of information search, identifying the need for information and changing health and treatment behavior, seeking more information was more than average. In the information sharing component, the average score of this component was equal to the average; Considering that the sources of obtaining health information about this disease are basically the media and social networks. What emerges from the evidence is that following a crisis or problem related to health and feeling the need for related information, people start searching for related sources and if it is noticeable, their health information seeking behavior is an increasing trend. has it. Therefore, the present study is consistent with all previous studies.
The results of the present study show that the average of information acquisition in the variable of information dimensions related to Covid-19 was higher than the average and also in all components, including dimensions related to health, economic, political, social and educational, the average score was higher. It was average. In other words, the findings show the students' concerns about each of the dimensions related to economy, health, politics, social justice, and especially about education and concerns about holding classes, not having the necessary infrastructure in an optimal way. In some people, lack of concentration and anxiety is caused by the situation.
The findings showed that the most sources of obtaining health information for students of Birjand University are search engines, foreign social networks and news media, and they paid less attention to reliable media such as official specialized medical websites. Also, the results point to the important and prominent role of Telegram and Instagram platforms. In addition, what the studied community sought to obtain information about covid-19 was mostly preventive behaviors and news related to covid-19 rather than its treatment methods. Also, the results showed that the health information-seeking behavior of Birjand University students has generally increased during this pandemic; But they have done the behavior of sharing information related to Covid less. Meanwhile, the role of dimensions related to Covid-19, including dimensions related to health, economic, political, social and educational, and obtaining information about each of these dimensions was of great importance for students, and the most important aspect for them was the educational dimension. .
The results showed that women used reliable sources such as official specialized medical websites and news media compared to men, and men used social networks (Telegram, Instagram, Twitter and YouTube) and search engines to get information about Covid. 19 have used. The influence of the role of gender showed that women are more interested in obtaining all kinds of information about this disease, and also paid more attention to the negative consequences of women; After creating negative consequences in women, they sought to obtain information about preventive behaviors. Because a significant relationship has been established between negative consequences and preventive behaviors in past studies. In addition, the role of gender had no effect on the positive outcomes and dimensions related to Covid-19, except for the economic dimension component. The field of study and level of study did not make a significant difference in the research variables. Based on this, it is suggested to hold training courses to improve the quality and awareness of health information literacy in social networks and news media for students of different levels. Also, policy makers and decision makers should pay more attention to providing authentic information on social media for the audience. Social networks and internal messengers should be adapted in the field of providing health information. Future researches can examine the subject of study in other societies and use different research methods to collect data or analyze findings.
Afshin Motaghi Destenaei, Ali Karami, Milad Piri Fath Abad,
Volume 11, Issue 2 (9-2024)
Volume 11, Issue 2 (9-2024)
Abstract
Introduction
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
Resultss and Discussion
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 well prepared 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.
Conclusion
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 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
Resultss and Discussion
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 well prepared 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.
Conclusion
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
Dr. Afshin Hamdipour, Dr. Hashem Atapour, Negin Kajaiee,
Volume 11, Issue 3 (12-2024)
Volume 11, Issue 3 (12-2024)
Abstract
Information Seeking Behavior is a broad term encompassing a series of actions undertaken to articulate individuals’ information needs, search for information, evaluate it and select relevant data, ultimately leading to its use (Ozowa and Aba, 2017). According to Case and Given (2016), information-seeking is an integral part of human life. They note that humans frequently feel the need for information and actively seek it throughout their daily lives. In their research, which examined the information-seeking behaviors of professionals from various fields, including physicians, nurses, managers, engineers, journalists, customers, and other groups, the authors found significant differences in the information-seeking behaviors of various professions. These differences can be attributed to professional roles, work environments, and specific information needs. As a dimension of human behavior, information-seeking is influenced by numerous factors. Given the critical role of psychological aspects in shaping human information-seeking behavior and their impact on the interaction between humans and information, addressing these factors is vital. The increasing focus on user-centered (human-centered) studies in recent decades highlights the importance of such studies. This research explores personality traits that influence the information-seeking behavior of graduate students at the University of Tabriz.
Methods and Materials
This study used a descriptive-survey method. The statistical population comprised 2,826 graduate students (2,258 master’s and 568 doctoral students from 17 faculties at the University of Tabriz, excluding dependent units and the international campus, during the first semester of the 2022-2023 academic year. The students were enrolled in four fields: humanities, basic sciences, engineering, and agriculture. Using Cochran’s formula, the sample size was calculated to be 338 students selected through stratified random sampling. The study employed a localized version of John and Srivastava’s (1999) questionnaire for data collection. The questionnaire included two sections: six demographic items and 42 items rated on a five-point Likert scale to assess information-seeking behavior and five personality traits (Extraversion, Conscientiousness, Agreeableness, Openness to Experience, Neuroticism). Validity was ensured through expert review by five faculty members, and reliability was confirmed using Cronbach’s alpha, with coefficients ranging from 0.588 to 0.903. Data were analyzed using descriptive statistics (frequency, mean, standard deviation) and inferential statistics (multiple linear regression). Skewness and kurtosis coefficients that fell within ±2 confirmed the normal distribution of the data.
Results and Discussion
The findings of the present study showed that all five dimensions of personality traits (extroversion, conscientiousness, adaptability, acceptance of experience, and neuroticism with averages of 4.13, 3.94, 3.99, 4.11, and 2.69 respectively) have a significant effect on the information-seeking behavior of graduate students at Tabriz University; Specifically, Extraversion, Conscientiousness, Agreeableness, and Openness to Experience demonstrated positive effects, while Neuroticism exhibited a negative effect. Other results showed that among information-seeking behaviors, "referring to the Internet to obtain information" has the highest priority among students, with an average of 4.72. In the extraversion dimension, "being friendly in the process of acquiring information" is the most important, with an average of 4.34. In the dimension of conscientiousness, "observance of order in the process of obtaining information" has the highest average score, with an average score of 4.22. In the adaptability dimension, "tendency to cooperate with others during information searching" has the highest score with an average of 4.29. In the experience acceptance dimension, "having an active imagination in the information seeking process" has the highest rank with an average of 4.42. In the dimension of neuroticism, "being nervous in the process of finding information" is the highest average score (3.03). The results of multiple linear regression also showed that the independent variables, extroversion, conscientiousness, adaptability, acceptance of experience, and neuroticism are significant predictors of information-seeking behavior, which explain 25.6% of the changes related to the dependent variable. Among the 5 independent variables, the conscientiousness variable, with a beta coefficient of 0.220, made a greater contribution than the other variables.
Conclusion
The findings of this study confirmed the effect of five important personality traits on information-seeking behavior. It is expected that librarians and information specialists will consider the different aspects of personality traits in information-seeking behavior and pay attention to the fact that knowledge of these issues will help them to provide effective information services to students. According to the findings of the present study, it is recommended that the libraries of University of Tabriz establish information systems based on individual student differences to facilitate an optimal environment for information searching. In addition, organizing workshops on communication skills can help students perform more effectively in information-seeking activities. These skills can be beneficial for both extroverted and even neurotic students. It is also recommended that information system designers tailor their systems and services based on the needs and personality traits of students. Furthermore, it is recommended that librarians receive the necessary training to identify students’ individual characteristics and differences and provide information services tailored to their personality traits during interactions with users. Finally, offering psychological counseling and stress management support for students can help them reduce their anxiety and improve their performance in information-seeking activities. This is particularly beneficial for students with high neuroticism levels.
Methods and Materials
This study used a descriptive-survey method. The statistical population comprised 2,826 graduate students (2,258 master’s and 568 doctoral students from 17 faculties at the University of Tabriz, excluding dependent units and the international campus, during the first semester of the 2022-2023 academic year. The students were enrolled in four fields: humanities, basic sciences, engineering, and agriculture. Using Cochran’s formula, the sample size was calculated to be 338 students selected through stratified random sampling. The study employed a localized version of John and Srivastava’s (1999) questionnaire for data collection. The questionnaire included two sections: six demographic items and 42 items rated on a five-point Likert scale to assess information-seeking behavior and five personality traits (Extraversion, Conscientiousness, Agreeableness, Openness to Experience, Neuroticism). Validity was ensured through expert review by five faculty members, and reliability was confirmed using Cronbach’s alpha, with coefficients ranging from 0.588 to 0.903. Data were analyzed using descriptive statistics (frequency, mean, standard deviation) and inferential statistics (multiple linear regression). Skewness and kurtosis coefficients that fell within ±2 confirmed the normal distribution of the data.
Results and Discussion
The findings of the present study showed that all five dimensions of personality traits (extroversion, conscientiousness, adaptability, acceptance of experience, and neuroticism with averages of 4.13, 3.94, 3.99, 4.11, and 2.69 respectively) have a significant effect on the information-seeking behavior of graduate students at Tabriz University; Specifically, Extraversion, Conscientiousness, Agreeableness, and Openness to Experience demonstrated positive effects, while Neuroticism exhibited a negative effect. Other results showed that among information-seeking behaviors, "referring to the Internet to obtain information" has the highest priority among students, with an average of 4.72. In the extraversion dimension, "being friendly in the process of acquiring information" is the most important, with an average of 4.34. In the dimension of conscientiousness, "observance of order in the process of obtaining information" has the highest average score, with an average score of 4.22. In the adaptability dimension, "tendency to cooperate with others during information searching" has the highest score with an average of 4.29. In the experience acceptance dimension, "having an active imagination in the information seeking process" has the highest rank with an average of 4.42. In the dimension of neuroticism, "being nervous in the process of finding information" is the highest average score (3.03). The results of multiple linear regression also showed that the independent variables, extroversion, conscientiousness, adaptability, acceptance of experience, and neuroticism are significant predictors of information-seeking behavior, which explain 25.6% of the changes related to the dependent variable. Among the 5 independent variables, the conscientiousness variable, with a beta coefficient of 0.220, made a greater contribution than the other variables.
Conclusion
The findings of this study confirmed the effect of five important personality traits on information-seeking behavior. It is expected that librarians and information specialists will consider the different aspects of personality traits in information-seeking behavior and pay attention to the fact that knowledge of these issues will help them to provide effective information services to students. According to the findings of the present study, it is recommended that the libraries of University of Tabriz establish information systems based on individual student differences to facilitate an optimal environment for information searching. In addition, organizing workshops on communication skills can help students perform more effectively in information-seeking activities. These skills can be beneficial for both extroverted and even neurotic students. It is also recommended that information system designers tailor their systems and services based on the needs and personality traits of students. Furthermore, it is recommended that librarians receive the necessary training to identify students’ individual characteristics and differences and provide information services tailored to their personality traits during interactions with users. Finally, offering psychological counseling and stress management support for students can help them reduce their anxiety and improve their performance in information-seeking activities. This is particularly beneficial for students with high neuroticism levels.
Dr Mahdieh Mirzabeigi, Ms Reihaneh Bahri,
Volume 12, Issue 1 (5-2025)
Volume 12, Issue 1 (5-2025)
Abstract
Introduction
Given the important impact of information literacy in today's societies and in line with the efficiency of individuals, especially students, information literacy can be predicted and planned for its management through indicators. Therefore, the present study aims to examine the relationships between the variables of cognitive flexibility and openness to experience with the level of information literacy by examining students of Shiraz University, a university that enjoys a distinguished scientific position in the country and the results of this study may contribute to its scientific growth through further understanding of the factors affecting the information literacy of its students, and to test the extent of the impact of the two variables in predicting the level of information literacy of the said society, if a relationship exists.
Methods and Materoal
This research is descriptive in terms of data collection and quantitative in terms of data nature. The statistical population also includes students of Shiraz University in the academic year 1400-1401, about 17,000 people, and the sample size was calculated as 375 people using the Cochran formula. The members of the research sample were selected using convenience sampling. Data collection was carried out through a questionnaire. To measure the level of information literacy, the research questionnaires of Seng et al. (2020), Pinto et al. (2020), and Lee et al. (2020) were used, based on the classification of the Information Literacy Framework for Higher Education (2016). To measure face and content validity, the questionnaire was sent to seven information science and knowledge experts, and the final version was obtained based on their opinions. The reliability of the research tool was obtained using Cronbach's alpha coefficient of 0.937. To measure cognitive flexibility, the cognitive flexibility questionnaire developed by Dennis & Vander Wal (2010) was used, whose validity was measured by these researchers, and its convergent validity with the cognitive flexibility scale of Martin and Robin (1995) was 0.75. The reliability of this questionnaire was also obtained using Cronbach's alpha, which was 0.787. To measure openness to experience, the Big Five Personality Factors questionnaire by Goldberg (1999) was used, whose validity was proven in the Khormai study (2006) using factor analysis. The reliability of this questionnaire was obtained using Cronbach's alpha, which was 0.788. Pearson correlation tests, linear regression, and stepwise regression were also used to analyze the data.
Resultss and Discussion
in order to examine the power of each variable in predicting the level of information literacy, the correlation between the variables was first calculated through the Pearson correlation test, and the results showed that cognitive flexibility, openness to experience, and information literacy have a positive and significant relationship with each other.
Then, a simple linear regression test was used to examine the role of cognitive flexibility in predicting the level of information literacy of the subjects, and the cognitive flexibility variable was entered as a predictor variable and information literacy as a criterion variable in the regression equation. The findings showed that the regression model of the predictive power of the cognitive flexibility variable on information literacy (F(1/278)=(43/682 p=0/000) with a coefficient of determination R2=/136 is significant. For each unit increase in cognitive flexibility, the information literacy score increases by 58/567 units. In other words, according to the calculated standard regression coefficient, cognitive flexibility explains 36/8 percent of the variance in information literacy (Table 2). Then, a simple linear regression test was used to examine the role of openness to experience in predicting the level of information literacy of the subjects, and the openness to experience variable as a predictor variable and information literacy as a criterion variable was entered into the regression equation and the findings showed that the regression model of the predictive power of the variable of openness to experience on information literacy is significant F(1/ 298) = (97/167 p = 0/000) with a coefficient of determination R2 = /246. For each unit increase in openness to experience, the information literacy score increases by 112/313 units. In other words, according to the calculated standard regression coefficient, openness to experience explains 49/6 percent of the variance in information literacy (Table 3). Finally, the stepwise regression test was used to predict the level of information literacy of users based on the variables of cognitive flexibility and openness to experience. The results of the stepwise regression test showed that among the predictor variables in the first step, the component of openness to experience was able to be the strongest The variable was significantly able to predict the level of information literacy of the subjects (p= /000). This variable alone was able to explain about 50/9 percent of the variance in the level of information literacy. In the second step, the variable of openness to experience explained about 43/1 percent of the variance in the level of information literacy, and cognitive flexibility was able to enter the model and explained 19/5 percent of the variance in the level of information literacy (p= /000). Accordingly, in total, the two variables of openness to experience and cognitive flexibility were able to explain 62/6 percent of the variance in information literacy (Table 4).
Conclusion
The results of this study can be an effort to improve the existing knowledge about information literacy and identify more factors that influence it. Also, the results of this study can help universities, with the help of information literacy experts, design curricula and training workshops to strengthen these components and improve the level of information literacy and to develop students who have higher information literacy and are prepared for future life and careers. Students, also aware of the important role of openness to experience and cognitive flexibility, can overcome the potential problems associated with their lack of information literacy by improving their level of openness to experience and cognitive flexibility by participating in workshops related to these components and also by increasing their information literacy skills by participating in workshops and information literacy training courses.
Given the important impact of information literacy in today's societies and in line with the efficiency of individuals, especially students, information literacy can be predicted and planned for its management through indicators. Therefore, the present study aims to examine the relationships between the variables of cognitive flexibility and openness to experience with the level of information literacy by examining students of Shiraz University, a university that enjoys a distinguished scientific position in the country and the results of this study may contribute to its scientific growth through further understanding of the factors affecting the information literacy of its students, and to test the extent of the impact of the two variables in predicting the level of information literacy of the said society, if a relationship exists.
Methods and Materoal
This research is descriptive in terms of data collection and quantitative in terms of data nature. The statistical population also includes students of Shiraz University in the academic year 1400-1401, about 17,000 people, and the sample size was calculated as 375 people using the Cochran formula. The members of the research sample were selected using convenience sampling. Data collection was carried out through a questionnaire. To measure the level of information literacy, the research questionnaires of Seng et al. (2020), Pinto et al. (2020), and Lee et al. (2020) were used, based on the classification of the Information Literacy Framework for Higher Education (2016). To measure face and content validity, the questionnaire was sent to seven information science and knowledge experts, and the final version was obtained based on their opinions. The reliability of the research tool was obtained using Cronbach's alpha coefficient of 0.937. To measure cognitive flexibility, the cognitive flexibility questionnaire developed by Dennis & Vander Wal (2010) was used, whose validity was measured by these researchers, and its convergent validity with the cognitive flexibility scale of Martin and Robin (1995) was 0.75. The reliability of this questionnaire was also obtained using Cronbach's alpha, which was 0.787. To measure openness to experience, the Big Five Personality Factors questionnaire by Goldberg (1999) was used, whose validity was proven in the Khormai study (2006) using factor analysis. The reliability of this questionnaire was obtained using Cronbach's alpha, which was 0.788. Pearson correlation tests, linear regression, and stepwise regression were also used to analyze the data.
Resultss and Discussion
in order to examine the power of each variable in predicting the level of information literacy, the correlation between the variables was first calculated through the Pearson correlation test, and the results showed that cognitive flexibility, openness to experience, and information literacy have a positive and significant relationship with each other.
Then, a simple linear regression test was used to examine the role of cognitive flexibility in predicting the level of information literacy of the subjects, and the cognitive flexibility variable was entered as a predictor variable and information literacy as a criterion variable in the regression equation. The findings showed that the regression model of the predictive power of the cognitive flexibility variable on information literacy (F(1/278)=(43/682 p=0/000) with a coefficient of determination R2=/136 is significant. For each unit increase in cognitive flexibility, the information literacy score increases by 58/567 units. In other words, according to the calculated standard regression coefficient, cognitive flexibility explains 36/8 percent of the variance in information literacy (Table 2). Then, a simple linear regression test was used to examine the role of openness to experience in predicting the level of information literacy of the subjects, and the openness to experience variable as a predictor variable and information literacy as a criterion variable was entered into the regression equation and the findings showed that the regression model of the predictive power of the variable of openness to experience on information literacy is significant F(1/ 298) = (97/167 p = 0/000) with a coefficient of determination R2 = /246. For each unit increase in openness to experience, the information literacy score increases by 112/313 units. In other words, according to the calculated standard regression coefficient, openness to experience explains 49/6 percent of the variance in information literacy (Table 3). Finally, the stepwise regression test was used to predict the level of information literacy of users based on the variables of cognitive flexibility and openness to experience. The results of the stepwise regression test showed that among the predictor variables in the first step, the component of openness to experience was able to be the strongest The variable was significantly able to predict the level of information literacy of the subjects (p= /000). This variable alone was able to explain about 50/9 percent of the variance in the level of information literacy. In the second step, the variable of openness to experience explained about 43/1 percent of the variance in the level of information literacy, and cognitive flexibility was able to enter the model and explained 19/5 percent of the variance in the level of information literacy (p= /000). Accordingly, in total, the two variables of openness to experience and cognitive flexibility were able to explain 62/6 percent of the variance in information literacy (Table 4).
Conclusion
The results of this study can be an effort to improve the existing knowledge about information literacy and identify more factors that influence it. Also, the results of this study can help universities, with the help of information literacy experts, design curricula and training workshops to strengthen these components and improve the level of information literacy and to develop students who have higher information literacy and are prepared for future life and careers. Students, also aware of the important role of openness to experience and cognitive flexibility, can overcome the potential problems associated with their lack of information literacy by improving their level of openness to experience and cognitive flexibility by participating in workshops related to these components and also by increasing their information literacy skills by participating in workshops and information literacy training courses.
Rahman Marefat, Mahmood Sangari,
Volume 12, Issue 1 (5-2025)
Volume 12, Issue 1 (5-2025)
Abstract
Background and purpose: The present study was conducted with the aim of identifying methods of validating methods of resources among sports science students of Birjand University. In numerous classes involving students from various disciplines, a recurring challenge reported by students was their unfamiliarity with source validation methods. Students, consistently indicated a lack of knowledge on how to assess the credibility of sources. When provided with examples of valid and invalid sources, many students struggled to properly evaluate them. Some students even expressed the belief that source validation was unnecessary, emphasizing merely the importance of using sources rather than verifying their validity. The researchers focused on a specific group—sports science students at Birjand University—to investigate how these students evaluate the sources they need and what challenges they encounter in the process.
Studies suggest that students often lack the skills to assess the credibility of articles found in databases or general websites like Wikipedia and online encyclopedias (Marefat, 1401; Azarang, 1399). For printed sources, students typically consider the author's credibility, organizational affiliation, and the publisher’s reputation as indicators of source reliability (Moradi, 1384). Marefat identified ten main categories related to evaluating sources, including institutional credibility, author credibility, content accuracy, observational reliability, referential validation, publication date, information distortion, credibility doubts, recognition of source credibility, and citation rate, particularly from psychology students’ perspectives (Marefat, 1396).
Research by Keshavarz, Vasfi, and Sha'bani (1393) examined the credibility of internet health information and how personality traits like conscientiousness influence evaluation methods among health-medical professionals. They found that many struggle to assess quality, relying mainly on impartiality, timeliness, and author credibility. Similarly, Roozbahani and Riahi-nia (1395) highlighted that faculty members prioritize content accuracy, data reliability, logical consistency, and relevance in determining source credibility. Kader’s study (Kader, 2013) on nurses identified a six-stage process for evaluating online health information, depending on skills, time, and website quality. Liu and Huang’s research (2005) among Chinese students revealed that current students often base their judgments on author name, affiliation, and website reputation, whereas graduates focus more on the information’s accuracy and quality.
Despite many evaluation efforts, challenges remain: first, understanding how users process unobservable information is difficult; second, differing information needs lead to varied processing approaches; and third, establishing a universal criterion for correct information processing is often impossible outside controlled environments. These issues highlight the complexity of assessing information credibility and the ongoing need for effective evaluation strategies (Liu, 2000).The main questions of the present study are:
1. What are the challenges faced by sports science students at Birjand University in evaluating their required resources?
2. How do sports science students at Birjand University evaluate their required resources?
Method:The statistical population of the present study consisted of 67 sports science students at Birjand University at the time of the research. Given the effort to collect maximum data, all 67 individuals were considered part of the research population, and no sampling was performed. Semi-structured interviews were used for data collection. In total, twenty master's students in sports science were interviewed. The interview process continued until saturation was reached, after interviewing sixteen students. From the sixteenth to the twentieth interview, the data obtained were repetitive, and based on this, the researchers decided to stop data collection. The initial codes were placed under sub-categories and main categories. In the present study, member checking was used to determine the research's credibility. In the present study, the constructivist approach in grounded theory, as proposed by Charmaz (2014), was adopted as the basis for the work, therefore, there is no need to present a paradigmatic model. Data analysis was also performed using MAXQDA 2020 software.
Findings: Among the 67 members of the research population, a total of 20 sports science students from Birjand University were interviewed. A totoal of 50% of the interviewees were women (10 people), and 10 (50%) were men. Categorizes and presents the concepts and codes extracted from the interviews related to the research questions. In the axial coding of the data, a total of 6 main challenges related to the validation methods of resources of sports students present in the interviews were found, such as lack of familiarity with investigating research violations, lack of familiarity with plagiarism, lack of familiarity with plagiarism software, etc. Also, 15 core codes related to the second research question, how to accredit sports students, were obtained.
Conclusion: Interviews with the research population revealed that students in the research population face certain challenges in validating sources. They highlighted "unfamiliarity with examining research misconduct, unfamiliarity with plagiarism, unfamiliarity with plagiarism software, unfamiliarity with citation styles and citation management software, disregard for the author's academic rank, and unfamiliarity with the credibility of open-access articles" in their conversations with researchers.
These points were derived from the overall final concepts identified during the interviews, which included "unfamiliarity with how to examine research misconduct, unfamiliarity with examining research misconduct, unfamiliarity with examining plagiarism, unfamiliarity with plagiarism software, unfamiliarity with citation styles, unfamiliarity with EndNote, disregard for the author's academic rank, and unfamiliarity with the credibility of open-access articles." The findings of the present study emphasize the need for serious attention from all students, including sports science students and other students, to the issue of information credibility and quality, and the necessity of sufficient and continuous training and skills in this area. Skill training in determining the quality and credibility of sources, based on specific and strong criteria, in the form of training courses, workshops, laboratories, projects, and research, are among the immediate actions in this field.
Especially, It is suggested that to better understand the problems and provide better solutions, other qualitative and mixed methods such as foresight and videography with highly standardized checklists be conducted in more extensive and broader research to achieve more generalizable and broader results. It seems that training in source validation methods is needed for the sports science students participating in the research, and their training can reduce the challenges of source validation among students and improve their source validation methods. It is suggested that the data from this research be measured as a quantitative study among students of Birjand University and other various universities across the country.
Studies suggest that students often lack the skills to assess the credibility of articles found in databases or general websites like Wikipedia and online encyclopedias (Marefat, 1401; Azarang, 1399). For printed sources, students typically consider the author's credibility, organizational affiliation, and the publisher’s reputation as indicators of source reliability (Moradi, 1384). Marefat identified ten main categories related to evaluating sources, including institutional credibility, author credibility, content accuracy, observational reliability, referential validation, publication date, information distortion, credibility doubts, recognition of source credibility, and citation rate, particularly from psychology students’ perspectives (Marefat, 1396).
Research by Keshavarz, Vasfi, and Sha'bani (1393) examined the credibility of internet health information and how personality traits like conscientiousness influence evaluation methods among health-medical professionals. They found that many struggle to assess quality, relying mainly on impartiality, timeliness, and author credibility. Similarly, Roozbahani and Riahi-nia (1395) highlighted that faculty members prioritize content accuracy, data reliability, logical consistency, and relevance in determining source credibility. Kader’s study (Kader, 2013) on nurses identified a six-stage process for evaluating online health information, depending on skills, time, and website quality. Liu and Huang’s research (2005) among Chinese students revealed that current students often base their judgments on author name, affiliation, and website reputation, whereas graduates focus more on the information’s accuracy and quality.
Despite many evaluation efforts, challenges remain: first, understanding how users process unobservable information is difficult; second, differing information needs lead to varied processing approaches; and third, establishing a universal criterion for correct information processing is often impossible outside controlled environments. These issues highlight the complexity of assessing information credibility and the ongoing need for effective evaluation strategies (Liu, 2000).The main questions of the present study are:
1. What are the challenges faced by sports science students at Birjand University in evaluating their required resources?
2. How do sports science students at Birjand University evaluate their required resources?
Method:The statistical population of the present study consisted of 67 sports science students at Birjand University at the time of the research. Given the effort to collect maximum data, all 67 individuals were considered part of the research population, and no sampling was performed. Semi-structured interviews were used for data collection. In total, twenty master's students in sports science were interviewed. The interview process continued until saturation was reached, after interviewing sixteen students. From the sixteenth to the twentieth interview, the data obtained were repetitive, and based on this, the researchers decided to stop data collection. The initial codes were placed under sub-categories and main categories. In the present study, member checking was used to determine the research's credibility. In the present study, the constructivist approach in grounded theory, as proposed by Charmaz (2014), was adopted as the basis for the work, therefore, there is no need to present a paradigmatic model. Data analysis was also performed using MAXQDA 2020 software.
Findings: Among the 67 members of the research population, a total of 20 sports science students from Birjand University were interviewed. A totoal of 50% of the interviewees were women (10 people), and 10 (50%) were men. Categorizes and presents the concepts and codes extracted from the interviews related to the research questions. In the axial coding of the data, a total of 6 main challenges related to the validation methods of resources of sports students present in the interviews were found, such as lack of familiarity with investigating research violations, lack of familiarity with plagiarism, lack of familiarity with plagiarism software, etc. Also, 15 core codes related to the second research question, how to accredit sports students, were obtained.
Conclusion: Interviews with the research population revealed that students in the research population face certain challenges in validating sources. They highlighted "unfamiliarity with examining research misconduct, unfamiliarity with plagiarism, unfamiliarity with plagiarism software, unfamiliarity with citation styles and citation management software, disregard for the author's academic rank, and unfamiliarity with the credibility of open-access articles" in their conversations with researchers.
These points were derived from the overall final concepts identified during the interviews, which included "unfamiliarity with how to examine research misconduct, unfamiliarity with examining research misconduct, unfamiliarity with examining plagiarism, unfamiliarity with plagiarism software, unfamiliarity with citation styles, unfamiliarity with EndNote, disregard for the author's academic rank, and unfamiliarity with the credibility of open-access articles." The findings of the present study emphasize the need for serious attention from all students, including sports science students and other students, to the issue of information credibility and quality, and the necessity of sufficient and continuous training and skills in this area. Skill training in determining the quality and credibility of sources, based on specific and strong criteria, in the form of training courses, workshops, laboratories, projects, and research, are among the immediate actions in this field.
Especially, It is suggested that to better understand the problems and provide better solutions, other qualitative and mixed methods such as foresight and videography with highly standardized checklists be conducted in more extensive and broader research to achieve more generalizable and broader results. It seems that training in source validation methods is needed for the sports science students participating in the research, and their training can reduce the challenges of source validation among students and improve their source validation methods. It is suggested that the data from this research be measured as a quantitative study among students of Birjand University and other various universities across the country.
Dr. Mohammad Moradi, ,
Volume 12, Issue 1 (5-2025)
Volume 12, Issue 1 (5-2025)
Abstract
In order to know whether the quality standards are being met, universities evaluate the educational quality of professors every semester using professor evaluation by students based on evaluation criteria determined by the Ministry of Science. However, it has never been investigated which of the criteria has had the greatest impact on increasing student interaction with professors and course content, and consequently increasing student learning and productivity. Also, methods such as Multiple Attribute Decision Making (MADM) techniques only measure the opinions of experts for each of the evaluation criteria, which may be in contradiction with reality. Therefore, the purpose of this study is to investigate the importance of each of the professor evaluation criteria related to student-professor interaction and course content based on students' performance and their average scores, as well as the results of professor evaluations by students. For this purpose, data mining techniques and regression models have been used. Also, a decision tree classification model has been presented to predict the academic status of students based on the characteristics of a professor.
Methods and Materials
The research method consists of 4 phases. In the first phase, the evaluation criteria for university professors related to student interaction with professors and course content were reviewed based on the items announced by the Ministry of Science. Then, in the second phase, data and information on the evaluation of professors by students and the average efficiency and grades of students were collected. In the third phase, the collected data were analyzed using data mining techniques and regression models, and the importance of each evaluation criteria was examined. In the fourth phase, a decision tree classification model was presented to predict the academic status of students according to the characteristics of the professor. The presented model will help professors and educational administrators determine teaching and classroom management methods to increase student interaction with professors and course content, and as a result, achieve the desired academic status of students.
Resultss and Discussion
Based on the results obtained, the evaluation criterion "having an appropriate lesson plan and comprehensiveness and continuity in presenting the material" with a coefficient of 28.907 had the greatest impact on increasing student interaction with professors and, as a result, increasing student productivity and grades. This emphasizes the need to use organization in teaching and learning, and the teacher should pay special attention to setting the lesson plan as planning and organizing the set of activities in relation to educational goals, lesson content, and students' abilities for the duration of the semester. The evaluation criterion "social manners and behavior with students and mutual respect" with a coefficient of 12.069 is the second factor affecting student efficiency. The evaluation criterion "classroom order and time management" with a coefficient of 11.597 is the third factor affecting student efficiency and scores. "Teacher's mastery of the subject matter" with a coefficient of 8.316 has been identified as the fourth factor affecting student efficiency and scores. The evaluation criterion "appropriateness of teaching strategies and methods to the course objectives" with a coefficient of 7.775 has been identified as the fifth factor affecting students' scores. The evaluation criterion "using appropriate student evaluation methods according to the course objectives" with a coefficient of 7.769 has been the sixth factor affecting students' average scores. "Possibility of communication (face-to-face and offline) with the professor outside the classroom" with a coefficient of 1.571 is the seventh factor affecting students' efficiency. Also, solutions were presented to strengthen the evaluation criterion with high weight and importance, namely the criterion "having an appropriate lesson plan and comprehensiveness and continuity in presenting the material".
Conclusion
The level of importance obtained for each evaluation criterion and the classification model created can help professors and educational administrators determine teaching and classroom management methods to increase student interaction with professors and course content, and as a result, increase their efficiency and average grades.
Methods and Materials
The research method consists of 4 phases. In the first phase, the evaluation criteria for university professors related to student interaction with professors and course content were reviewed based on the items announced by the Ministry of Science. Then, in the second phase, data and information on the evaluation of professors by students and the average efficiency and grades of students were collected. In the third phase, the collected data were analyzed using data mining techniques and regression models, and the importance of each evaluation criteria was examined. In the fourth phase, a decision tree classification model was presented to predict the academic status of students according to the characteristics of the professor. The presented model will help professors and educational administrators determine teaching and classroom management methods to increase student interaction with professors and course content, and as a result, achieve the desired academic status of students.
Resultss and Discussion
Based on the results obtained, the evaluation criterion "having an appropriate lesson plan and comprehensiveness and continuity in presenting the material" with a coefficient of 28.907 had the greatest impact on increasing student interaction with professors and, as a result, increasing student productivity and grades. This emphasizes the need to use organization in teaching and learning, and the teacher should pay special attention to setting the lesson plan as planning and organizing the set of activities in relation to educational goals, lesson content, and students' abilities for the duration of the semester. The evaluation criterion "social manners and behavior with students and mutual respect" with a coefficient of 12.069 is the second factor affecting student efficiency. The evaluation criterion "classroom order and time management" with a coefficient of 11.597 is the third factor affecting student efficiency and scores. "Teacher's mastery of the subject matter" with a coefficient of 8.316 has been identified as the fourth factor affecting student efficiency and scores. The evaluation criterion "appropriateness of teaching strategies and methods to the course objectives" with a coefficient of 7.775 has been identified as the fifth factor affecting students' scores. The evaluation criterion "using appropriate student evaluation methods according to the course objectives" with a coefficient of 7.769 has been the sixth factor affecting students' average scores. "Possibility of communication (face-to-face and offline) with the professor outside the classroom" with a coefficient of 1.571 is the seventh factor affecting students' efficiency. Also, solutions were presented to strengthen the evaluation criterion with high weight and importance, namely the criterion "having an appropriate lesson plan and comprehensiveness and continuity in presenting the material".
Conclusion
The level of importance obtained for each evaluation criterion and the classification model created can help professors and educational administrators determine teaching and classroom management methods to increase student interaction with professors and course content, and as a result, increase their efficiency and average grades.
Mis Shahla Bouazzar, Dr Alireza Ghorbani, Dr Nazmohammad Ounagh,
Volume 12, Issue 2 (9-2025)
Volume 12, Issue 2 (9-2025)
Abstract
Aims: This study investigates the relationship between the use of virtual social networks and both cultural capital and social capital among high school students in Ahvaz, Iran. Method: A descriptive-survey research method was employed, with the statistical population consisting of all high school students in Ahvaz. Using Cochran’s formula, a sample of 320 participants was selected through multi-stage random cluster sampling. Data were collected using Bourdieu’s social capital and cultural capital questionnaires, along with Lee’s (2005) virtual networks usage scale. The data were analyzed using SPSS software. Finding: The findings revealed a significant positive correlation between the components of usefulness, compatibility, social influence, and perceived enjoyment and the variables of social capital and cultural capital. Specifically, virtual social networks enhance individuals' social and cultural capital by improving adaptability, reinforcing social influence on behavior, increasing perceived enjoyment, and maximizing the perceived utility of these platforms. Furthermore, the results indicated that both virtual social network usage and cultural capital can predict the level of social capital among high school students in Ahvaz. Conclusion: Leveraging the potential of social networks can effectively increase students' cultural and social capital.
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