Search published articles
Showing 285 results for Type of Study: Research
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.
Soheila Shirezhian, Seyed Mehdi Mirmehdi,
Volume 12, Issue 1 (5-2025)
Volume 12, Issue 1 (5-2025)
Abstract
Introduction
In recent years, advancements in technology, particularly in artificial intelligence, have significantly transformed how customers interact with businesses. One of the most prominent manifestations of this transformation is the emergence of chatbots as intelligent digital agents in marketing and customer service. Chatbots are AI-powered programs capable of responding to user inquiries through text or voice interactions, playing a crucial role in enhancing the efficiency of customer-organization communication. These tools enable companies to provide 24/7 services, reduce response times, increase customer loyalty, and save human resources. Unlike human agents, chatbots are unaffected by factors such as fatigue or holidays, ensuring constant availability. However, traditional customer service channels like email, websites, or phone calls remain popular among some customers.
In the retail sector, chatbots facilitate effective customer-brand interactions by offering convenience, flexibility, and easy access. They streamline the online shopping process by providing quick responses and guiding users, creating a seamless and satisfying experience while addressing the impersonal nature of e-commerce. Recent advancements in natural language processing have enabled chatbots to perform complex tasks, such as analyzing customer preferences and delivering personalized responses. These capabilities, combined with the widespread use of messaging platforms, have driven the growth of the chatbot industry. Nevertheless, concerns like data security and privacy pose significant barriers to widespread adoption, requiring careful consideration from system designers. This study, grounded in the Technology Acceptance Model, examines factors such as trust, personal innovativeness, ease of use, social influence, and hedonic motivation to understand the reasons behind users’ acceptance or rejection of chatbots.
Methods and Materoal
This study adopts a quantitative approach with an applied objective, utilizing a descriptive-survey design. The target population consists of Iranian users with experience using AI-based chatbots in online customer service platforms, such as websites, apps, or messaging services. Inclusion criteria required participants to have used at least one service-oriented chatbot and to be familiar with digital tools. Exclusion criteria included incomplete questionnaires, lack of actual chatbot experience, or use of chatbots for non-customer-service purposes (e.g., entertainment or language learning). To enhance accuracy and minimize bias, the influence of the chatbot’s application domain (e.g., retail, banking, education, or healthcare) was analyzed using variance analysis and control of contextual variables.
Data were collected through three primary methods: documentary studies, electronic resources, and field research. The data collection tool was a questionnaire based on a 5-point Likert scale (ranging from “strongly disagree” to “strongly agree”), measuring variables such as trust, hedonic motivation, social influence, personal innovativeness, perceived usefulness, ease of use, attitude, and intention to use. The questionnaire was designed based on standardized scales from prior research, and its content validity was confirmed by experts.
Resultss and Discussion
The findings indicate that trust, personal innovativeness, and ease of use significantly influence the perceived usefulness of chatbots. Trust enhances perceived usefulness by providing accurate and prompt responses. Personal innovativeness strengthens this perception by aligning chatbots with users’ needs, while ease of use, by simplifying interactions, positively affects both perceived usefulness and users’ attitudes. Both perceived usefulness and positive attitudes directly increase the intention to use chatbots. However, social influence and hedonic motivation did not show a significant impact on perceived usefulness, possibly due to customers’ preference for traditional channels or the functional focus of chatbots over entertainment.
Conclusion
This study reveals that trust, personal innovativeness, and ease of use are critical drivers of chatbot adoption. Trust, fostered through reliable and swift responses, enhances the perception of chatbots’ usefulness. Personal innovativeness aligns chatbot functionalities with users’ creative needs, further boosting this perception. Ease of use simplifies interactions, fostering positive attitudes and increasing the intention to use chatbots. The lack of significant impact from social influence may stem from customers’ preference for traditional channels like email or phone calls. Similarly, hedonic motivation’s limited effect could be attributed to the service-oriented nature of chatbots, which prioritizes efficiency over enjoyment.
Chatbots, by automating routine tasks, offering predictive analytics, and enhancing customer experiences, serve as innovative tools in digital services. However, challenges such as data security and privacy concerns remain barriers to broader adoption. Designing user-friendly and trustworthy chatbots can enhance their acceptance and improve the digital customer experience. This study recommends further research on non-users and environmental factors that may hinder the impact of social influence and hedonic motivation to better understand adoption barriers.
In recent years, advancements in technology, particularly in artificial intelligence, have significantly transformed how customers interact with businesses. One of the most prominent manifestations of this transformation is the emergence of chatbots as intelligent digital agents in marketing and customer service. Chatbots are AI-powered programs capable of responding to user inquiries through text or voice interactions, playing a crucial role in enhancing the efficiency of customer-organization communication. These tools enable companies to provide 24/7 services, reduce response times, increase customer loyalty, and save human resources. Unlike human agents, chatbots are unaffected by factors such as fatigue or holidays, ensuring constant availability. However, traditional customer service channels like email, websites, or phone calls remain popular among some customers.
In the retail sector, chatbots facilitate effective customer-brand interactions by offering convenience, flexibility, and easy access. They streamline the online shopping process by providing quick responses and guiding users, creating a seamless and satisfying experience while addressing the impersonal nature of e-commerce. Recent advancements in natural language processing have enabled chatbots to perform complex tasks, such as analyzing customer preferences and delivering personalized responses. These capabilities, combined with the widespread use of messaging platforms, have driven the growth of the chatbot industry. Nevertheless, concerns like data security and privacy pose significant barriers to widespread adoption, requiring careful consideration from system designers. This study, grounded in the Technology Acceptance Model, examines factors such as trust, personal innovativeness, ease of use, social influence, and hedonic motivation to understand the reasons behind users’ acceptance or rejection of chatbots.
Methods and Materoal
This study adopts a quantitative approach with an applied objective, utilizing a descriptive-survey design. The target population consists of Iranian users with experience using AI-based chatbots in online customer service platforms, such as websites, apps, or messaging services. Inclusion criteria required participants to have used at least one service-oriented chatbot and to be familiar with digital tools. Exclusion criteria included incomplete questionnaires, lack of actual chatbot experience, or use of chatbots for non-customer-service purposes (e.g., entertainment or language learning). To enhance accuracy and minimize bias, the influence of the chatbot’s application domain (e.g., retail, banking, education, or healthcare) was analyzed using variance analysis and control of contextual variables.
Data were collected through three primary methods: documentary studies, electronic resources, and field research. The data collection tool was a questionnaire based on a 5-point Likert scale (ranging from “strongly disagree” to “strongly agree”), measuring variables such as trust, hedonic motivation, social influence, personal innovativeness, perceived usefulness, ease of use, attitude, and intention to use. The questionnaire was designed based on standardized scales from prior research, and its content validity was confirmed by experts.
Resultss and Discussion
The findings indicate that trust, personal innovativeness, and ease of use significantly influence the perceived usefulness of chatbots. Trust enhances perceived usefulness by providing accurate and prompt responses. Personal innovativeness strengthens this perception by aligning chatbots with users’ needs, while ease of use, by simplifying interactions, positively affects both perceived usefulness and users’ attitudes. Both perceived usefulness and positive attitudes directly increase the intention to use chatbots. However, social influence and hedonic motivation did not show a significant impact on perceived usefulness, possibly due to customers’ preference for traditional channels or the functional focus of chatbots over entertainment.
Conclusion
This study reveals that trust, personal innovativeness, and ease of use are critical drivers of chatbot adoption. Trust, fostered through reliable and swift responses, enhances the perception of chatbots’ usefulness. Personal innovativeness aligns chatbot functionalities with users’ creative needs, further boosting this perception. Ease of use simplifies interactions, fostering positive attitudes and increasing the intention to use chatbots. The lack of significant impact from social influence may stem from customers’ preference for traditional channels like email or phone calls. Similarly, hedonic motivation’s limited effect could be attributed to the service-oriented nature of chatbots, which prioritizes efficiency over enjoyment.
Chatbots, by automating routine tasks, offering predictive analytics, and enhancing customer experiences, serve as innovative tools in digital services. However, challenges such as data security and privacy concerns remain barriers to broader adoption. Designing user-friendly and trustworthy chatbots can enhance their acceptance and improve the digital customer experience. This study recommends further research on non-users and environmental factors that may hinder the impact of social influence and hedonic motivation to better understand adoption barriers.
Ali Saatchi, , ,
Volume 12, Issue 1 (5-2025)
Volume 12, Issue 1 (5-2025)
Abstract
Introduction
The quantitative and qualitative increase in digital libraries is a phenomenon that has emerged in response to the growing need of society to access information. Therefore, digital libraries are facing a major challenge of copyright. This issue can prevent them from providing effective and needed services to the user community.
Methods and Materoal
The present study, while examining the factors affecting copyright in digital libraries, has presented a model in the field of copyright in digital libraries.The present study was qualitative in terms of its applied purpose and type of data collection and was conducted using the meta-synthesis method. Also, the data and information collection tool was scientific research articles published in reputable Persian and English journals in the last 12 years. From 342 articles extracted during the meta-synthesis stages, 58 articles were selected using the Persian keywords "copyright", "intellectual property", "digital libraries" and the English keywords "Copyright, intellectual property, digital libraries" in the databases Normags, Magiran, SID, Science Direct, Emerald, Springer EBSCO, SEVIER, Wiley. Due to the qualitative nature of the data (text), open coding was used to analyze the data. In this coding method, codes are extracted from the text of the article (first-order coding), and then these extracted codes are recoded to form concepts (second-order coding), and finally, concepts are recoded to form categories (text-code-concept-category). In this study, first a code was considered for all the factors extracted from previous studies and then, considering the meaning of each code, they were categorized into a similar concept. Two coders were used to control the extracted codes and categories, and the index in question in this field is the "Kappa" index.
Resultss and Discussion
: Based on the proposed research model, policy-making, the nature of content, the development of technologies, support for users, support for creators, content producers, culture-building, and the nature of use are the most important factors influencing the application of copyright laws to make information accessible to users of digital libraries. Policymaking: In general, policymakers, governments, and national officials play a key role in the policymaking and enforcement of copyright regulations. Copyright laws are usually developed by high-level national authorities and legislators, and digital library managers and operators do not have much involvement in the development of laws, and this can be one of the challenges of legislating copyright in digital libraries. Nature of content: Unlike traditional libraries, digital libraries use different sources to provide information services. These sources do not have the same content and range from software programs to traditional books. Type of use: In terms of type of use, the purpose of the user, the type of library, the status of digitization, and electronic lending are effective components. The provisions of the laws indicate that digital libraries are only able to provide digitized works in the form of digital lending. Protection of authors' rights: Digital libraries can create the possibility of reproducing copyrighted works for themselves by developing legal contracts with publishers and authors. In this case, creating clear legal procedures helps to protect the rights of authors. Protecting the rights of users: The main goal of copyright law is to protect the material and moral rights of creators and to ensure that society has access to the information it needs. With the advancement of information technology, legal challenges in the field of copyright are inevitable, and overcoming copyright infringements through file sharing requires finding preventive solutions and using technology, such as metadata standards, to create a balance between the rights of copyright holders and the use of scientific innovations. Content producers: Digital libraries use the method of digitization (Reproduction) to temporarily reproduce first-class works and make them available to users through electronic lending. It is necessary to pay attention to the credibility of the systems and databases and the laws of the countries providing this content in digital libraries. Culture building: In this dimension, three components have been identified: public awareness, transparency of laws, awareness of managers, and determination of civil responsibilities. Transparency of laws is related to cases where copyright laws have been ambiguously worded and have caused misunderstandings by users and managers of digital libraries. Friedman test was used to rank the factors. The test results showed that in this test, the highest mean value is 12.84, thus the factor "Development of technologies" has the highest degree of importance and the first rank. Also, the factors "Nature of use" and "Support for creators" are ranked as the second and third most important. On the other hand, the factors "Nature of content", "Content producers" and "Support for users" have the lowest degree of importance, respectively.
Conclusion
This research shows that copyright laws in digital libraries are very different from traditional libraries. According to the research results, digital libraries need to take a deeper look at copyright laws in order to provide services to their users, with the aim of respecting the rights of producers and users of information resources.
The quantitative and qualitative increase in digital libraries is a phenomenon that has emerged in response to the growing need of society to access information. Therefore, digital libraries are facing a major challenge of copyright. This issue can prevent them from providing effective and needed services to the user community.
Methods and Materoal
The present study, while examining the factors affecting copyright in digital libraries, has presented a model in the field of copyright in digital libraries.The present study was qualitative in terms of its applied purpose and type of data collection and was conducted using the meta-synthesis method. Also, the data and information collection tool was scientific research articles published in reputable Persian and English journals in the last 12 years. From 342 articles extracted during the meta-synthesis stages, 58 articles were selected using the Persian keywords "copyright", "intellectual property", "digital libraries" and the English keywords "Copyright, intellectual property, digital libraries" in the databases Normags, Magiran, SID, Science Direct, Emerald, Springer EBSCO, SEVIER, Wiley. Due to the qualitative nature of the data (text), open coding was used to analyze the data. In this coding method, codes are extracted from the text of the article (first-order coding), and then these extracted codes are recoded to form concepts (second-order coding), and finally, concepts are recoded to form categories (text-code-concept-category). In this study, first a code was considered for all the factors extracted from previous studies and then, considering the meaning of each code, they were categorized into a similar concept. Two coders were used to control the extracted codes and categories, and the index in question in this field is the "Kappa" index.
Resultss and Discussion
: Based on the proposed research model, policy-making, the nature of content, the development of technologies, support for users, support for creators, content producers, culture-building, and the nature of use are the most important factors influencing the application of copyright laws to make information accessible to users of digital libraries. Policymaking: In general, policymakers, governments, and national officials play a key role in the policymaking and enforcement of copyright regulations. Copyright laws are usually developed by high-level national authorities and legislators, and digital library managers and operators do not have much involvement in the development of laws, and this can be one of the challenges of legislating copyright in digital libraries. Nature of content: Unlike traditional libraries, digital libraries use different sources to provide information services. These sources do not have the same content and range from software programs to traditional books. Type of use: In terms of type of use, the purpose of the user, the type of library, the status of digitization, and electronic lending are effective components. The provisions of the laws indicate that digital libraries are only able to provide digitized works in the form of digital lending. Protection of authors' rights: Digital libraries can create the possibility of reproducing copyrighted works for themselves by developing legal contracts with publishers and authors. In this case, creating clear legal procedures helps to protect the rights of authors. Protecting the rights of users: The main goal of copyright law is to protect the material and moral rights of creators and to ensure that society has access to the information it needs. With the advancement of information technology, legal challenges in the field of copyright are inevitable, and overcoming copyright infringements through file sharing requires finding preventive solutions and using technology, such as metadata standards, to create a balance between the rights of copyright holders and the use of scientific innovations. Content producers: Digital libraries use the method of digitization (Reproduction) to temporarily reproduce first-class works and make them available to users through electronic lending. It is necessary to pay attention to the credibility of the systems and databases and the laws of the countries providing this content in digital libraries. Culture building: In this dimension, three components have been identified: public awareness, transparency of laws, awareness of managers, and determination of civil responsibilities. Transparency of laws is related to cases where copyright laws have been ambiguously worded and have caused misunderstandings by users and managers of digital libraries. Friedman test was used to rank the factors. The test results showed that in this test, the highest mean value is 12.84, thus the factor "Development of technologies" has the highest degree of importance and the first rank. Also, the factors "Nature of use" and "Support for creators" are ranked as the second and third most important. On the other hand, the factors "Nature of content", "Content producers" and "Support for users" have the lowest degree of importance, respectively.
Conclusion
This research shows that copyright laws in digital libraries are very different from traditional libraries. According to the research results, digital libraries need to take a deeper look at copyright laws in order to provide services to their users, with the aim of respecting the rights of producers and users of information resources.
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.
Related Websites
Site Keywords
نشریه, Academic Journal, Scientific Article, کلمه شماره یک, کلمه شماره یک, کلمه شماره یک, کلمه شماره یک, کلمه شماره دو, کلمه شماره یک, کلمه دوVote
© 2025 CC BY-NC 4.0 | Human Information Interaction
Designed & Developed by : Yektaweb