Abstract
This study aimed to investigate students’ awareness and perception toward the execution of Internet of Things (IoT) in library services of Indian Institute Technologies (IITs) of Northern India. This study consists of a quantitative research design in which a survey was conducted utilizing a stratified random sampling technique to survey 813 students from five IITs. A total of 780 correctly filled-out surveys were received, yielding a response rate of 95.94%. Statistical tools, including Microsoft Excel and the Statistical Package for the Social Sciences, were used to analyze the data. To assess the significance of the results at the 0.05% level, statistical analysis was carried out utilizing percentages and analysis of variance. This study will communicate the attitude, awareness, and perception of students regarding the implementation of IoT in libraries of IITs. It is conducted to understand the motive behind new technology acceptance in academic libraries. The findings reveal that most of the students got familiar with IoT from browsing on the Web/Internet, social networking sites, research projects, conferences, workshops, webinars and faculty development programs, professional discussions, and meetings, as part of the curriculum. Respondents were in favor of implementing IoT in library services. They believed that IoT will ensure better and more efficient utilization of library resources, followed by real-time information accessibility, recommend IoT-based library services, system content quality will be updated, and will increase the quality of the library; the efficiency of library services will increase with implementation of IoT. It will increase the productivity of library services, be useful in an emergency, and promote information literacy. The study’s findings would be beneficial to libraries and academic institutions interested in implementing IoT applications in their libraries.
1 Introduction
Since the Internet-of-Things (IoT) rule gained popularity in the 1980s, many countries have adopted the concepts of smart metropolises, smart cranes, smart flood warning systems, and smart gridirons, respectively. These countries include Canada, China, Brazil, and the United Arab Emirates. Experts predict that the number of linked IoT devices will increase to 19.9 billion by 2023 and 22 billion by 2025, up from 13.1 billion today. IoT is a novel concept that combines a variety of smart methodologies, foundations, smart tools, and sensors (Srivastava & Pandey, 2022). The incorporation of technology into educational institutions has ushered in a new era of learning and resource accessibility, and libraries are no exception. In this age of technological innovation, where the IoT is poised to revolutionize the way we interact with our surroundings, libraries are adapting to the changing landscape of information dissemination. Academic libraries are becoming smarter day by day as they incorporate new and creative technology for improved and expanded service delivery. Varnum (2017) asserted that technological advancement is inextricably linked to library development and that technological trends influence library services. As a result, there is a close link between library service innovation and technology advancement. With an increasingly pervasive approach, emerging technologies involving blockchain fragmentation, IoT, deep learning, big data analytics, machine learning, and artificial intelligence are intended to provide a secure, faster, and updated service with the least amount of human intervention. The major goal of IoT in the library is to create a seamless network of connections between things so that they may communicate with each other without human involvement. The network (mainly wireless) allows users to easily track resources and infrastructure using sensor-generated radio waves (De Sarkar, 2022; Igbinovia & Okuonghae, 2021).
The application of the IoT is not allocated much importance as far as the university libraries in India are concerned. Though university libraries are aware of the application of ICT in varying degrees of library services, it is often presumed that the onus of the application of the IoT in libraries is still lacking. Besides, it is also believed that students in Indian Institute Technologies (IITs) barely have experienced such technology in the library so far. Hence, to probe these various applications of IoT in library services and also keep in view the role of IoT in the seamless dissemination of information to encourage real-time updates information, it becomes necessary to develop a comprehensive understanding of the various aspects of IoT in library setup. This article explores the fascinating domain of student understanding and perception of IoT implementation in library services, with a specific focus on the prominent IITs located in Northern India. IITs have always been at the cutting edge of academic brilliance and technical progress. As a result, it is critical to investigate how students at these top-notch institutions perceive and adjust to changing library services. In India, university libraries do not place a high value on IoT applications. Though university libraries are aware of the use of ICT in varied degrees of library services, it is frequently assumed that the onus of IoT applications in libraries is still missing. To the best of the researcher’s knowledge, no effort has been made to comprehend the role of librarians in influencing attitudes about IoT acceptance in libraries and support in the context of library services in IITs. The IITs were chosen by the researcher for the current study because they are the institutes of eminence. The study’s findings will motivate the development of new IoT-enabled technological library services that cater to users’ needs in real time.
In light of the above, the problem under study is stated as:
Awareness and Perception of Students Toward Execution of Internet of Things in Library Services: A study of Indian Institute Technologies of Northern India
Objectives of the study
To determine the Status quo of library services.
To understand the demographic distribution of students of selected IITs.
To examine the level of awareness and perceptions of students regarding applications of IoT in library services.
2 Review of Literature
2.1 IoT and Libraries
One of the most significant technological developments of the twenty-first century is the IoT. Embedded devices allow for real-time internet-based communication between people, processes, and objects by connecting common objects (Veeraiah et al., 2022). The idea behind the IoT is to connect actual objects by providing them with sensors, actuators, and an Internet connection. According to Dijkman, Sprenkels, Peeters, and Janssen (2015), the IoT is a vast network that uses virtual objects or things with attributes, auto-IDs, and self-configuration. The IoT is a network of intangible, self-communicating, web-enabled objects that has demonstrated remarkable outcomes in real-time data generation through the use of smart sensors. Kevin Ashton coined the phrase “Internet-of-Things” in 1999 (Firouzi, Farahani, Weinberger, DePace, & Aliee, 2020). According to him, “I may be wrong, but I think the term ‘IoT’ came from the title of a talk I did at Procter & Gamble (P&G) back in 1999.” Connecting P&G’s supply chain’s new RFID technology to the hot subject of the day – the Internet – was more than just a shrewd way to get management attention. It summarized an important idea that is still frequently misinterpreted (Ashton, 2009; Kumar & Mallick, 2018). Tim Berner Lee’s vision for the IoT aimed to leverage web technology and protocols to make it simple to create web applications that took advantage of real-world objects (Gupta & Singh, 2018). IoT can improve many government services, including transportation, education, healthcare, and agriculture. It can also revolutionize society by increasing citizens’ desire to use technology in the digital society (Shammar & Zahary, 2019).
The rise of IoT technology has significantly changed how libraries conduct work, resulting in more efficient operations, better-automated management, and kinder services (Wang & Zhao, 2015). By creating a connection between readers and books, the IoT system gives consumers access to a variety of reader services. The IoT makes it feasible to conduct intelligent administration, analyze reader behavior, and enable intelligent self-borrowing and return of books (Fu, 2021). With these extensive capabilities, IoT can assist in redefining libraries by reengineering their services and putting a greater emphasis on total quality management or quality of services to attain overall customer satisfaction (Mohideen, Kiran, & Muhamad, 2017).
2.2 The Implication of IoT in Libraries
IoT has a lot to do with libraries, but it hasn’t quite found its way into the conventional library setting (Wójcik, 2016). Libraries can become self-communicating, fast-growing dynamic systems that can easily adapt to user demand in a supply chain by transforming from isolated systems through the power of the IoT. Academic libraries are transitioning from physical to more technologically oriented service delivery (Chiu & Wong, 2023) and providing users with access to library resources via mobile Internet (Dei, 2020). With the help of IoT, libraries can provide widely accessible self-contained virtual tours (Sinha, Panja, & Brar, 2022). IoT applications can be used in self-checkout, stock-taking, asset tracking, asset monitoring, access control, robot stock-taking in libraries, smart inventory, intelligent querying, and the fusion of books and information systems. It may also provide management systems with low-cost real-world data. IoT can provide new tools and opportunities in terms of information sharing, tracking and tracing services, and push notification services (Li, 2014; Liang, 2020). IoT applications in libraries, specifically sensors for fire alarms/lights/gate entry/temperature/locks/managing energy and water consumption, enhancing efficiency, and providing smart and easy control of library buildings with surveillance systems (Kumar, 2023). The potential impact of IoT on libraries includes the following: location-based services, appliance management, collection management, and availability of the library’s resources; additionally, novel approaches are suggested, such as the use of virtual library cards, smart digital shelves, cloud services, RFID tag integration into member cards for resource access, management of fine collections, and improved inventory control (Pujar & Satyanarayana, 2015). Through mobile technology, library mobile apps, automation, the Internet of Everything, service research and enhancement, and possible economic opportunities, IoT plays a part in location services for libraries (Hahn, 2017; Jim, 2017; Massis, 2016). A large number of contemporary libraries, particularly in Asia, do not fully integrate “smart technology” into their buildings which points to a lack of general adoption of the more sophisticated IoT strategies (Hussain & Ahmad, 2021). Libraries may boost efficiency and provide a better experience for patrons by combining facial recognition technology, modern RFID systems, and collection identification technology, as well as utilizing IoT to plot data and identify patterns. However, careful consideration of the potential repercussions, as well as collaboration between library staff and patrons, will be required to identify the most effective and feasible ways to implement these improvements (Cheung, Lo, Chiu, & Wei, 2023).
3 Methodology
To ensure the validity and reliability of the research instrument, the following steps were followed:
Face Validity Assessment: Experts in the field reviewed the questionnaire for clarity, relevance, and appropriateness. Necessary modifications were made based on their feedback.
Pilot Study: A pilot study was conducted with a group of experts to evaluate the accuracy and effectiveness of the questionnaire (Sinha et al., 2022). Negative or leading questions were identified and removed based on the results.
Feedback from Colleagues: Colleagues experienced in cross-sectional studies provided additional feedback to refine the questionnaire further.
Internal Consistency Assessment: Cronbach’s Alpha was used to assess the internal consistency of the questions, ensuring reliable results.
Final Questionnaire: Based on the assessment results, the final version of the questionnaire was prepared for data collection. The study questionnaire consists of two parts. Part one was for the demographic details of the respondents, part two was for the information about library space and its use, and part 3 was for the perception and awareness among students of selected IITs about applications of IoT in library services, which was measured by a five-point Likert scale of strongly agree (SA), agree (A), Neutral (N), disagree (D), and strongly disagree (SD), with a weighting of 5, 4, 3, 2, 1.
The research methodology used a quantitative survey to explore the significance of “IoT application in libraries” research and understand the level of awareness and perception about the application of IoT in library services among postgraduate students and research scholars of IITs of Northern India and the benefits of adopting library services.
3.1 Quantitative Study
3.1.1 Sampling
The study employed stratified random sampling; sample of 813 users will be taken comprising post-graduates and research scholars from the five selected IITs of Northern India, with a total population of 15,502. The sample size was determined based on the table given by Krejcie and Morgan formula (Sharma, Khosla, & Kumar, 2023), wherein the sample size for the population size of 15,502 was found to be 377 with a 95.0 % confidence level and 5.0% margin of error. Considering the non-response rate of up to 50.0 %, the size of the sample was increased to 754. The sample size of 754 is equivalent to 4.86% of the total population of 15,502 as shown in Tables 1 and 2. To draw a representative sample, the proposed study would adopt a stratified random sampling method and select a minimum of 100 users from each IIT and further at least 50 users from each category of users (postgraduate students and research scholars). The sample comprised 362 (46.41%) postgraduate students and 418 (53.58%) research scholars ensuring diverse representation and perspective on IoT in library services.
Estimated sample size
S. No. | Name of Institution and Place | PG | RS | Total |
---|---|---|---|---|
1. | IIT Delhi, Delhi | 106 | 142 | 248 |
2. | IIT Kanpur, Uttar Pradesh | 85 | 86 | 171 |
3. | IIT Roorkee, Uttarakhand | 90 | 103 | 193 |
4. | IIT (BHU) Varanasi, Uttar Pradesh | 40 | 51 | 91 |
5. | IIT Ropar, Punjab | 23 | 28 | 51 |
Total | 344 | 410 | 754 |
Final sample size of respondents in five IITs
S. No. | Name of Institution and Place | PG | RS | Total |
---|---|---|---|---|
1. | IIT Delhi, Delhi | 106 | 142 | 248 |
2. | IIT Kanpur, Uttar Pradesh | 85 | 86 | 171 |
3. | IIT Roorkee, Uttarakhand | 90 | 103 | 193 |
4. | IIT (BHU) Varanasi, Uttar Pradesh | 50 | 51 | 101 |
5. | IIT Ropar, Punjab | 50 | 50 | 100 |
Total | 381 | 432 | 813 |
3.1.2 Data Collection
A structured questionnaire was the primary data collection instrument. The questionnaire included multiple-choice questions and Likert-scale items to assess respondents’ awareness and perceptions regarding the potential benefits of adopting IoT technologies in library services.
3.1.3 Response Rate
Of the 813 selected participants, 780 completed responses were obtained, resulting in a response rate of 95.94%.
3.1.4 Theoretical Framework for Questionnaire
Technology Acceptance Model (TAM) is one of the user acceptance models that depict user acceptance and behavior toward new technology. Applying TAM to understand the acceptance of IoT in academic libraries provides a structured and comprehensive framework for investigating the complex interplay of factors influencing students’ awareness and perceptions. By delving into perceived usefulness, ease of use, attitudes, behavioral intentions, external variables, and trust, researchers and practitioners can gain valuable insights into the dynamics of IoT adoption in the academic library context. This application of TAM contributes to the broader discourse on technology acceptance and facilitates the development of strategies to enhance the successful integration of IoT in academic library services (Dalbehera, 2018). It is influenced by various external and internal variables, and these variables are as follows:
Perceived Usefulness (PU): It is related to the degree to which acceptance of new technology improves the work proficiency of a person.
Perceived Ease of Use (PEU): It is defined as “the degree to which an individual believes that using a specific system would be free of effort.”
Attitude toward Usage (ATU): It is defined as the degree to which a person is associated with technology or a particular behavior toward technology like an attitude toward IoT IoT-based library system.
Behavioral Intension (BI): It evaluates the degree to which a person’s intention to perform a particular behavior.
Actual system use: It is the measured frequency or duration of actual use of new technology.
Organizational competency: It refers to the competency of an organization to adopt new technology. It comprises available resources, support from top management, the strength of the organization, and technology inclination.
Technological factor: For adopting new technology, external and internal technology influence needs to be adopted in the workflow to ensure service and system quality.
Personal competency: It depends upon the personal willingness of the individual to adapt according to the new technology and try to develop self-efficiency toward a particular domain.
Environmental factors: This refers to the niche where the organization is functioning and is influenced by variables like work pressure, security, and collective trust.
3.1.5 Data Analysis
The quantitative data collected through the survey underwent a meticulous analytical process, encompassing both descriptive and inferential statistics. Descriptive statistics, including percentages, mean, and standard deviation, were harnessed to offer a detailed overview of the survey results. Additionally, inferential statistics, such as the F-test and Chi-square (P-value) chi-square analysis, were conducted to unearth deeper patterns and associations within the data. The statistical software SPSS played a pivotal role in executing a robust and sophisticated analysis, ensuring the extraction of meaningful insights. The confidence level of the study was kept at 95%; hence the p-value of < 0.05 significance value would indicate a statistically significant association.
4 Scope and Limitation of the Study
The scope of the study is to determine the application of the IoT in libraries of selected IITs. In India, there are currently 23 IITs. It is not practicable for the researcher to collect research data from all institutes; thus, the researcher has chosen IITs based on the NIRF 2022 ranking. The IoT is a new area of ICT, and there is practically little literature on this topic in library and information science (Gupta & Singh, 2018). According to the aforementioned literature, investigations were carried out to look into IoT applications in libraries all over the world. Most of the research was a review of the literature. In the context of Indian academic libraries, few studies used a quantitative research methodology (Dalbehera, 2018; Kumar, 2023; Sinha et al., 2022). More precisely, there is no information in the published literature about IoT applications in selected IIT libraries in India.
5 Data Analysis and Interpretation
5.1 Gender-Wise Distribution
The responses were elicited from male and female respondents from each undertaken IITs for the study. Table 3 presents the gender distribution of respondents (Postgraduate and Research Scholars) according to institutions. A careful effort has been made to distribute the questionnaire equally to male and female respondents. The results revealed that of the population size of 780 respondents, male respondents were 663(85%) and 117(15%) were female respondents. Based on category distribution, the total PG male respondents were 307(84.8%), RS male respondents were 356(85.2%), whereas PG female respondents were 55(15.2%) and RS female respondents were 62(14.8%).
Institution-wise distribution of gender
Gender | Category | Institution | Total, n (%) | Chi-Square (p-value) | |||||
---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | |||||
Male | PG | 94 (90.4%) | 72 (88.9%) | 72 (80%) | 28 (66.7%) | 41 (91.1%) | 307 (84.8%) | 663 (85%) | 1.680 (0.794) |
RS | 110 (79.7%) | 67 (81.7%) | 93 (92.1%) | 46 (93.9%) | 40 (83.3%) | 356 (85.2%) | |||
Female | PG | 10 (9.6%) | 9 (11.1%) | 18 (20%) | 14 (33.3%) | 4 (8.9%) | 55 (15.2%) | 117 (15%) | |
RS | 28 (20.3%) | 15 (18.3%) | 8 (7.9%) | 3 (6.1%) | 8 (16.7%) | 62 (14.8%) | |||
Total | 242 (31%) | 163 (20.9%) | 191 (24.5%) | 91 (11.7%) | 93 (11.9%) | 780 |
PG, Postgraduate; RS, research scholar. Note: Percentage in parenthesis.
According to the IIT-wise response rate, most of the respondents were from IIT Delhi (242, 31%) and the lowest was from IIT BHU (91, 11.7%). The response rate depends upon the sample size of the population which is highest in the case of IIT Delhi and lowest in the case of IIT BHU. Focusing on a low response rate of female respondents depends upon the lack of support; hesitation and non-availability of female respondents were the factors for the collection of a lower percentage of questionnaires and thus received higher responses from male respondents.
5.2 Age-Group Wise Distribution
The involvement of age groups in a survey study is crucial since it can have a considerable impact on the research and the overall insights gathered from the investigation. Different age groups frequently exhibit diverse behaviors, opinions, and attitudes, which can provide significant insights. Table 4 represents the institute-wise distribution of age groups of uses. The results elucidate that most of the respondents belong to the age group 26–30 years, i.e., 379 (48.6%), followed by 21–25 years, i.e., 321 (41.2%), and the least number of respondents from above 30-year age group 80 (10.3%). The result suggests that most of the respondents were in the middle age group of which RS had the highest number of contributors in the study.
Institution-wise distribution of age group
Age Group | Category | Institution | Total, n (%) | Chi-Square (p-value) | |||||
---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | |||||
21–25 Years | PG | 79 (76%) | 45 (55.6%) | 72 (80%) | 30 (71.4%) | 31 (68.9%) | 257 (71%) | 321 (41.2%) | 11.146 (0.194) |
RS | 28 (20.3%) | 14 (17.1%) | 12 (11.9%) | 8 (16.3%) | 2 (4.2%) | 64 (15.3%) | |||
26–30 Years | PG | 25 (24%) | 36 (44.4%) | 18 (20%) | 12 (28.6%) | 14 (31.1%) | 105 (29%) | 379 (48.6%) | |
RS | 84 (60.9%) | 53 (64.6%) | 75 (74.3%) | 26 (53.1%) | 36 (75%) | 274 (65.6%) | |||
Above 30 Years | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 80 (10.3%) | |
RS | 26 (18.8%) | 15 (18.3%) | 14 (13.9%) | 15 (30.6%) | 10 (20.8%) | 80 (19.1%) |
PG, postgraduate; RS, research scholar. Note: Percentage in parenthesis.
5.3 Year of Course-Wise Distribution
The year of the course-wise distribution of students can have a considerable impact on their comprehension of the IoT. Different years of a course may focus on different parts of IoT education and skill development. First- and second-year students set the groundwork for IoT knowledge and abilities, understanding the fundamental principles and tools. Third-year students begin to specialize and investigate certain areas of IoT, obtaining a deeper understanding of specific domains. Fourth-year or graduating students are required to have a broad understanding of IoT, be capable of handling challenging problems, and demonstrate their competency through capstone projects. The precise distribution of IoT-related content each year varies per educational institution and program. Table 5 reflects the year of course-wise distribution of postgraduate and research scholar respondents.
Institution-wise distribution of year of course of respondents
Year of Course | Category | Institution | Total, n (%) | Chi-square (p-value) | |||||
---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | |||||
First year | PG | 27 (26%) | 14 (17.3%) | 21 (23.3%) | 21 (50%) | 20 (44.4%) | 103 (28.5%) | 154 (19.7%) | 30.167 (0.017) |
RS | 19 (13.8%) | 11 (13.4%) | 15 (14.9%) | 2 (4.1%) | 4 (8.3%) | 51 (12.2%) | |||
Second year | PG | 77 (74%) | 67 (82.7%) | 69 (76.7%) | 21 (50%) | 25 (55.6%) | 259 (71.5%) | 346 (44.4%) | |
RS | 26 (18.8%) | 22 (26.8%) | 17 (16.8%) | 14 (28.6%) | 8 (16.7%) | 87 (20.8%) | |||
Third year | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 70 (9%) | |
RS | 23 (16.7%) | 14 (17.1%) | 15 (14.9%) | 6 (12.2%) | 12 (25%) | 70 (16.7%) | |||
Fourth year | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 101 (12.9%) | |
RS | 32 (23.2%) | 9 (11%) | 35 (34.7%) | 11 (22.4%) | 14 (29.2%) | 101 (24.2%) | |||
Fifth and above year | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 109 (14%) | |
RS | 38 (27.5%) | 26 (31.7%) | 19 (18.8%) | 16 (32.7%) | 10 (20.8%) | 109 (26.1%) |
PG, Postgraduate; RS, Research Scholar. Note: Percentage in parenthesis.
The first-year respondents were new entrants on the campus, and the fifth and above-year respondents had stayed on the campus for the past years (Table 3). Thus, this distribution helped in understanding better, whether users’ awareness and perception changed with a change in their academic years. Table 5 shows that 346 (44.4%) of the users were in the second year, followed by 154 (19.7%) in first year, 109 (14%) respondents in fifth and above year, and the least number of respondents in third year 70 (9%). Most of the respondents were from second year of their course as 259 (71%) of them belonged to PG and 87 (20.8%) were research scholars. This shows the maximum number of respondents due to the combined response of PG and RS.
5.4 Visit to the Library
Table 6 represents the relative frequency (N = 780) in accordance with the frequency of respondents' visits to the library of respondents (PG and RS) of selected five IITs of Northern India.
Frequency of visit to the library by respondents
Frequency of Visiting Library | Category | Institution | Total n (%) | Chi-Square (p-value) | |||||
---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | |||||
Daily | PG | 40 (38.5%) | 19 (23.5%) | 17 (18.9%) | 3 (7.1%) | 4 (8.9%) | 83 (22.9%) | 120 (15.4%) | 48.968 (0.000) |
RS | 11 (8%) | 6 (7.3%) | 7 (6.9%) | 11 (22.4%) | 2 (4.2%) | 37 (8.9%) | |||
Once in a week | PG | 18 (17.3%) | 14 (17.3%) | 31 (34.4%) | 3 (7.1%) | 9 (20%) | 75 (20.7%) | 136 (17.4%) | |
RS | 27 (19.6%) | 7 (8.5%) | 13 (12.9%) | 5 (10.2%) | 9 (18.8%) | 61 (14.6%) | |||
Once in a month | PG | 7 (6.7%) | 3 (3.7%) | 9 (10%) | 9 (21.4%) | 2 (4.4%) | 30 (8.3%) | 83 (10.6%) | |
RS | 12 (8.7%) | 7 (8.5%) | 14 (13.9%) | 11 (22.4%) | 9 (18.8%) | 53 (12.7%) | |||
Once in 2 months | PG | 0 (0%) | 0 (0%) | 1 (1.1%) | 0 (0%) | 1 (2.2%) | 2 (0.6%) | 22 (2.8%) | |
RS | 8 (5.8%) | 1 (1.2%) | 3 (3%) | 4 (8.2%) | 4 (8.3%) | 20 (4.8%) | |||
Occasionally | PG | 39 (37.5%) | 45 (55.6%) | 32 (35.6%) | 27 (64.3%) | 29 (64.4%) | 172 (47.5%) | 419 (53.7%) | |
RS | 80 (58%) | 61 (74.4%) | 64 (63.4%) | 18 (36.7%) | 24 (50%) | 247 (59.1%) |
PG, postgraduate; RS, research scholar. Note: Percentage in parenthesis.
In this study focusing on the implementation of the IoT in library services, the frequency of library visits can play a significant impact. Understanding how frequently users visit the library can provide significant insights into their interaction with library resources, familiarity with present services, and potential openness to adopting IoT-based upgrades. The results reveal a matter of concern as most of the respondents occasionally visit the library (419, 53.7%), followed by visitors once in a week (136, 17.4%). The Chi-square test was applied regarding the frequency of visiting the library among the respondents in two categories. Based on the test results, most of the p-values were lower (<0.05), indicating significant differences among the postgraduates and research scholars.
5.5 Library Services Availed by Students
Examining and investigating the library services that students use can be very important to the ongoing enhancement of library services. It offers insightful information on the requirements, preferences, and difficulties faced by library patrons and information that can help guide choices and develop effective plans for raising the caliber and applicability of library services. Table 7 represents the library services availed by postgraduate students and research scholars of selected IITs of Northern India.
Library services availed by students of IITs
Availing | Category | Institution | Total, n (%) | Chi-square (p-value) | |||||
---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | |||||
Library website | PG | 89 (85.6%) | 67 (82.7%) | 83 (92.2%) | 39 (92.9%) | 28 (62.2%) | 306 (84.5%) | 669 (85.8%) | 12.577 (0.014) |
RS | 122 (88.4%) | 72 (87.8%) | 86 (85.1%) | 42 (85.7%) | 41 (85.4%) | 363 (86.8%) | |||
Remote access to library | PG | 78 (75%) | 67 (82.7%) | 77 (85.6%) | 30 (71.4%) | 18 (40%) | 270 (74.6%) | 576 (73.8%) | 39.394 (0.0000) |
RS | 100 (72.5%) | 63 (76.8%) | 82 (81.2%) | 32 (65.3%) | 29 (60.4%) | 306 (73.2%) | |||
Real-time update | PG | 64 (61.5%) | 67 (82.7%) | 57 (63.3%) | 36 (85.7%) | 22 (48.9%) | 246 (68%) | 504 (64.6%) | 22.875 (0.00) |
RS | 81 (58.7%) | 64 (78%) | 57 (56.4%) | 22 (44.9%) | 34 (70.8%) | 258 (61.7%) | |||
Mobile library applications | PG | 52 (50%) | 30 (37%) | 47 (52.2%) | 12 (28.6%) | 6 (13.3%) | 147 (40.6%) | 266 (34.1%) | 28.076 (0.000) |
RS | 40 (29%) | 16 (19.5%) | 40 (39.6%) | 12 (24.5%) | 11 (22.9%) | 119 (28.5%) | |||
Cloud-based services | PG | 33 (31.7%) | 36 (44.4%) | 48 (53.3%) | 21 (50%) | 6 (13.3%) | 144 (39.8%) | 285 (36.5%) | 16.081 (0.003) |
RS | 48 (34.8%) | 28 (34.1%) | 39 (38.6%) | 11 (22.4%) | 15 (31.3%) | 141 (33.7%) | |||
QR Code for payments | PG | 34 (32.7%) | 35 (43.2%) | 51 (56.7%) | 24 (57.1%) | 15 (33.3%) | 159 (43.9%) | 304 (39%) | 14.883 (0.005) |
RS | 40 (29%) | 26 (31.7%) | 40 (39.6%) | 12 (24.5%) | 27 (56.3%) | 145 (34.7%) | |||
Location-based services | PG | 37 (35.6%) | 24 (29.6%) | 39 (43.3%) | 27 (64.3%) | 11 (24.4%) | 138 (38.1%) | 261 (33.5%) | 7.629 (0.106) |
RS | 30 (21.7%) | 30 (36.6%) | 32 (31.7%) | 11 (22.4%) | 20 (41.7%) | 123 (29.4%) | |||
Digital library | PG | 58 (55.8%) | 61 (75.3%) | 65 (72.2%) | 33 (78.6%) | 19 (42.2%) | 236 (65.2%) | 535 (68.6%) | 16.111 (0.003) |
RS | 95 (68.8%) | 58 (70.7%) | 81 (80.2%) | 31 (63.3%) | 34 (70.8%) | 299 (71.5%) | |||
Virtual library orientation | PG | 42 (40.4%) | 27 (33.3%) | 43 (47.8%) | 12 (28.6%) | 13 (28.9%) | 137 (37.8%) | 291 (37.3%) | 10.078 (0.039) |
RS | 53 (38.4%) | 29 (35.4%) | 38 (37.6%) | 10 (20.4%) | 24 (50%) | 154 (36.8%) | |||
Internet/Wifi | PG | 100 (96.2%) | 69 (85.2%) | 90 (100%) | 42 (100%) | 43 (95.6%) | 344 (95%) | 711 (91.2%) | 2.764 (0.598) |
RS | 122 (88.4%) | 75 (91.5%) | 88 (87.1%) | 41 (83.7%) | 41 (85.4%) | 367 (87.8%) | |||
Self-issue/return kiosk | PG | 65 (62.5%) | 53 (65.4%) | 48 (53.3%) | 24 (57.1%) | 32 (71.1%) | 222 (61.3%) | 453 (58.1%) | 31.596 (0.000) |
RS | 81 (58.7%) | 55 (67.1%) | 39 (38.6%) | 19 (38.8%) | 37 (77.1%) | 231 (55.3%) | |||
User authentication through Biometrics | PG | 76 (73.1%) | 36 (44.4%) | 72 (80%) | 18 (42.9%) | 26 (57.8%) | 228 (63%) | 460 (59%) | 62.205 (0.000) |
RS | 101 (73.2%) | 40 (48.8%) | 48 (47.5%) | 10 (20.4%) | 33 (68.8%) | 232 (55.5%) | |||
Auto recommendations for book purchasing | PG | 27 (26%) | 29 (35.8%) | 23 (25.6%) | 12 (28.6%) | 9 (20%) | 100 (27.6%) | 202 (25.9%) | 6.366 (0.173) |
RS | 35 (25.4%) | 24 (29.3%) | 21 (20.8%) | 6 (12.2%) | 16 (33.3%) | 102 (24.4%) | |||
Alert services for theft and disaster Management | PG | 23 (22.1%) | 37 (45.7%) | 42 (46.7%) | 15 (35.7%) | 11 (24.4%) | 128 (35.4%) | 248 (31.8%) | 6.963 (0.138) |
RS | 45 (32.6%) | 25 (30.5%) | 25 (24.8%) | 9 (18.4%) | 16 (33.3%) | 120 (28.7%) |
PG, postgraduate; RS, research scholar. Note: Percentage in parenthesis.
The findings revealed that most of the students avail following library services Internet/Wifi (711, 91.2%), followed by library website (669, 85.8%), remote access to library (576, 73.8%), digital library (535, 68.6%), real-time update (504, 64.6%), user authentication through biometrics (460, 59%), Self Issue/return kiosk (453, 58.1%), QR Code for payments (304, 39%), virtual library orientation (291, 37.3%), and least availed auto recommendations for book purchasing (202, 25.9%). The Chi-square test was applied regarding the library services availed among the respondents in two categories. Based on test results, most of the p-values were lower (<0.05) indicating significant differences among the postgraduates and research scholars.
5.6 Sources of Familiarity with IoT
Students’ acquaintance with the IoT can have a significant impact on their comprehension and engagement with this technology. The importance of various sources of familiarity varies based on the individual student’s interests, goals, and level of exposure to IoT. A mixture of these sources can help students gain a comprehensive grasp of IoT and prepare them for careers in this quickly evolving industry.
Table 8 reveals that most of the students got familiar with IoT from browsing on Web/Internet (471, 60.4%) of which 248 (68.5%) were PG students and 223 (53.3%) were research scholars, followed by those from social networking sites (397, 50.9%), from research projects (388, 49.7%), from conference, workshop, webinars and faculty development programs (338, 43.3%), professional discussion and meetings (333, 42.7%), part of curriculum (329, 42.2%), and least preferred from other sources (231, 29.6%). The Chi-square test was applied regarding the source of awareness about IoT among the respondents in two categories. Based on test results, it was concluded with mixed responses in the p-values. The p-values were greater (p > 0.05) for browsing on the Web/Internet and social networking sites, indicating that there were no significant variations among the postgraduates and research scholars.
Sources of familiarity with IoT
Category | Institution | Total, n (%) | Chi-Square (p-value) | ||||||
---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | |||||
Part of curriculum | PG | 65 (62.5%) | 39 (48.1%) | 60 (66.7%) | 12 (28.6%) | 26 (57.8%) | 202 (55.8%) | 329 (42.2%) | 17.094 (0.002) |
RS | 36 (26.1%) | 36 (43.9%) | 31 (30.7%) | 9 (18.4%) | 15 (31.3%) | 127 (30.4%) | |||
From research projects | PG | 46 (44.2%) | 36 (44.4%) | 43 (47.8%) | 27 (64.3%) | 20 (44.4%) | 172 (47.5%) | 388 (49.7%) | 11.451 (0.022) |
RS | 60 (43.5%) | 39 (47.6%) | 58 (57.4%) | 30 (61.2%) | 29 (60.4%) | 216 (51.7%) | |||
Professional discussion and meetings | PG | 40 (38.5%) | 46 (56.8%) | 30 (33.3%) | 12 (28.6%) | 18 (40%) | 146 (40.3%) | 333 (42.7%) | 13.745 (0.008) |
RS | 60 (43.5%) | 41 (50%) | 41 (40.6%) | 19 (38.8%) | 26 (54.2%) | 187 (44.7%) | |||
From Conference, workshop, webinars, and faculty development programs | PG | 37 (35.6%) | 24 (29.6%) | 44 (48.9%) | 21 (50%) | 16 (35.6%) | 142 (39.2%) | 338 (43.3%) | 12.491 (0.014) |
RS | 49 (35.5%) | 44 (53.7%) | 55 (54.5%) | 20 (40.8%) | 28 (58.3%) | 196 (46.9%) | |||
From social networking sites | PG | 58 (55.8%) | 44 (54.3%) | 45 (50%) | 21 (50%) | 23 (51.1%) | 191 (52.8%) | 397 (50.9%) | 5.237 (0.264) |
RS | 64 (46.4%) | 46 (56.1%) | 55 (54.5%) | 16 (32.7%) | 25 (52.1%) | 206 (49.3%) | |||
From browsing on web/Internet | PG | 63 (60.6%) | 64 (79%) | 62 (68.9%) | 30 (71.4%) | 29 (64.4%) | 248 (68.5%) | 471 (60.4%) | 8.233 (0.083) |
RS | 71 (51.4%) | 49 (59.8%) | 54 (53.5%) | 23 (46.9%) | 26 (54.2%) | 223 (53.3%) | |||
Other | PG | 22 (21.2%) | 32 (39.5%) | 43 (47.8%) | 6 (14.3%) | 16 (35.6%) | 119 (32.9%) | 231 (29.6%) | 19.172 (0.001) |
RS | 36 (26.1%) | 22 (26.8%) | 25 (24.8%) | 9 (18.4%) | 20 (41.7%) | 112 (26.8%) |
PG, postgraduate; RS, research scholar. Note: Percentage in parenthesis.
5.7 IoT Technology Implemented in Library Services
Table 9 depicts the possibility of implementing IoT in various library services IITs.
IoT Technology implemented in library services
Category | Institution | Total, n (%) | Chi-Square (p-value) | |||||||
---|---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | ||||||
Implementation of Commercial Model of IOT in Library Services | Extremely Likely | PG | 26 (25%) | 25 (30.9%) | 41 (45.6%) | 18 (42.9%) | 16 (35.6%) | 126 (34.8%) | 254 (32.6%) | 17.563 (0.350) |
RS | 41 (29.7%) | 30 (36.6%) | 30 (29.7%) | 11 (22.4%) | 16 (33.3%) | 128 (30.6%) | ||||
Likely | PG | 56 (53.8%) | 45 (55.6%) | 41 (45.6%) | 24 (57.1%) | 24 (53.3%) | 190 (52.5%) | 406 (52.1%) | ||
RS | 73 (52.9%) | 40 (48.8%) | 48 (47.5%) | 26 (53.1%) | 29 (60.4%) | 216 (51.7%) | ||||
N | PG | 19 (18.3%) | 11 (13.6%) | 8 (8.9%) | 0 (0%) | 4 (8.9%) | 42 (11.6%) | 110 (14.1%) | ||
RS | 20 (14.5%) | 12 (14.6%) | 21 (20.8%) | 12 (24.5%) | 3 (6.3%) | 68 (16.3%) | ||||
Unlikely | PG | 3 (2.9%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 4 (1.1%) | 9 (1.2%) | ||
RS | 3 (2.2%) | 0 (0%) | 2 (2%) | 0 (0%) | 0 (0%) | 5 (1.2%) | ||||
Extremely Unlikely | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.1%) | ||
RS | 1 (0.7%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.2%) |
PG, postgraduate; RS, research scholar. Note: Percentage in parenthesis.
The findings reveal that most of the respondents were in favor that commercial model of IoT technology can be implemented in various library services of IITs of Northern India 84.7%. While comparing categories, the results revealed that 87.3% of postgraduate students and 82.3% of research scholars were in favor of the commercial model of IoT technology that can be implemented in various library services of IITs of Northern India. On comparing IIT, most of the students from IIT Roorkee Postgraduate students, 91.2, and 77.2% of research scholars were in favor of the commercial model of IoT technology being implemented in various library services of IITs of Northern India. The Chi-square test was applied regarding the application of the commercial model of IoT in libraries among the respondents in two categories. Based upon test results, the p-values were greater (p > 0.05) indicating that there were no significant variations among the postgraduates and research scholars.
5.8 Acceptance of Implementation of IoT in Library Services of IITs
Table 10 represents the acceptance of postgraduate students and research scholars of IITs of Northern India toward the implementation of IoT in library services. The results revealed that most of the respondents were in favor of implementing IoT in library services, i.e., 349 (44.7%) out of which 161 were postgraduate (44.5%) and 188 were research scholars (45%). The Chi-square test was applied regarding the acceptance of the implementation of IoT in library services among the respondents in two categories. Based on test results, the p-values were greater (p > 0.05) indicating that there were no significant variations among the postgraduates and research scholars.
Acceptance of Implementation of IoT library services
Category | Institution | Total, n (%) | Chi-Square (p-value) | |||||||
---|---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | ||||||
Acceptance of implementation of IoT Library Services | Extremely Likely | PG | 43 (41.3%) | 36 (44.4%) | 42 (46.7%) | 18 (42.9%) | 22 (48.9%) | 161 (44.5%) | 349 (44.7%) | 14.047 (0.298) |
RS | 60 (43.5%) | 42 (51.2%) | 44 (43.6%) | 21 (42.9%) | 21 (43.8%) | 188 (45%) | ||||
Likely | PG | 40 (38.5%) | 37 (45.7%) | 35 (38.9%) | 21 (50%) | 20 (44.4%) | 153 (42.3%) | 342 (43.8%) | ||
RS | 61 (44.2%) | 38 (46.3%) | 46 (45.5%) | 21 (42.9%) | 23 (47.9%) | 189 (45.2%) | ||||
N | PG | 21 (20.2%) | 8 (9.9%) | 13 (14.4%) | 3 (7.1%) | 3 (6.7%) | 48 (13.3%) | 87 (11.2%) | ||
RS | 15 (10.9%) | 2 (2.4%) | 11 (10.9%) | 7 (14.3%) | 4 (8.3%) | 39 (9.3%) | ||||
Unlikely | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (0.3%) | ||
RS | 2 (1.4%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (0.5%) | ||||
Extremely Unlikely | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
PG, postgraduate; RS, research scholar. Note: Percentage in parenthesis.
5.9 Benefits to the Users by Implementation of IoT Library Services
Students’ perceptions of the benefits of IoT library services are important to the effective adoption and use of these services as discussed in Table 11. Students are major stakeholders and users of library resources, and their impressions of IoT-based services can have a substantial impact on their acceptance and effectiveness. The input from students on their experiences with IoT library services is invaluable. Their impressions and input assist in identifying areas for improvement, allowing libraries to refine and improve services to better meet the needs and expectations of users. The benefits of IoT library services that students perceive have a direct impact on their propensity to accept and use these services. Positive impressions, such as viewing IoT as a simple and fast method of accessing and interacting with library materials, can lead to increased adoption.
Perception regarding implementation of IoT in Library services
Category | Institution | Total n (%) | Chi-Square (p-value) | |||||||
---|---|---|---|---|---|---|---|---|---|---|
IIT Delhi, n (%) | IIT Kanpur, n (%) | IIT Roorkee, n (%) | IIT BHU, n (%) | IIT Ropar, n (%) | ||||||
Recommend IoT-Based Library Services | SA | PG | 81 (77.9%) | 75 (92.6%) | 84 (93.3%) | 39 (92.9%) | 43 (95.6%) | 322 (89%) | 690 (88.5%) | 18.067 (0.021) |
RS | 120 (87%) | 72 (87.8%) | 87 (86.1%) | 44 (89.8%) | 45 (93.8%) | 368 (88%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 23 (22.1%) | 6 (7.4%) | 6 (6.7%) | 3 (7.1%) | 1 (2.2%) | 39 (10.8%) | 88 (11.3%) | ||
RS | 18 (13%) | 9 (11%) | 14 (13.9%) | 5 (10.2%) | 3 (6.3%) | 49 (11.7%) | ||||
D | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 1 (0.3%) | 2 (0.3%) | ||
RS | 0 (0%) | 1 (1.2%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.2%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
The efficiency of our library services will increase with the implementation of IoT | SA | PG | 85 (81.7%) | 61 (75.3%) | 79 (87.8%) | 36 (85.7%) | 43 (95.6%) | 304 (84%) | 674 (86.4%) | 16.597 (0.035) |
RS | 124 (89.9%) | 73 (89%) | 85 (84.2%) | 43 (87.8%) | 45 (93.8%) | 370 (88.5%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 19 (18.3%) | 20 (24.7%) | 11 (12.2%) | 6 (14.3%) | 1 (2.2%) | 57 (15.7%) | 105 (13.5%) | ||
RS | 14 (10.1%) | 9 (11%) | 16 (15.8%) | 6 (12.2%) | 3 (6.3%) | 48 (11.5%) | ||||
D | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 1 (0.3%) | 1 (0.1%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
System content quality will be updated | SA | PG | 81 (77.9%) | 64 (79%) | 89 (98.9%) | 42 (100%) | 40 (88.9%) | 316 (87.3%) | 688 (88.2%) | 33.031 (0.00) |
RS | 124 (89.9%) | 70 (85.4%) | 88 (87.1%) | 45 (91.8%) | 45 (93.8%) | 372 (89%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 23 (22.1%) | 17 (21%) | 1 (1.1%) | 0 (0%) | 2 (4.4%) | 43 (11.9%) | 87 (11.2%) | ||
RS | 14 (10.1%) | 10 (12.2%) | 13 (12.9%) | 4 (8.2%) | 3 (6.3%) | 44 (10.5%) | ||||
D | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 3 (6.7%) | 3 (0.8%) | 5 (0.6%) | ||
RS | 0 (0%) | 2 (2.4%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (0.5%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
Reduce the Manpower Requirement | SA | PG | 88 (84.6%) | 60 (74.1%) | 80 (88.9%) | 39 (92.9%) | 41 (91.1%) | 308 (85.1%) | 636 (81.5%) | 26.358 (0.010) |
RS | 109 (79%) | 56 (68.3%) | 80 (79.2%) | 42 (85.7%) | 41 (85.4%) | 328 (78.5%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 16 (15.4%) | 21 (25.9%) | 6 (6.7%) | 3 (7.1%) | 3 (6.7%) | 49 (13.5%) | 128 (16.4%) | ||
RS | 24 (17.4%) | 21 (25.6%) | 21 (20.8%) | 7 (14.3%) | 6 (12.5%) | 79 (18.9%) | ||||
D | PG | 0 (0%) | 0 (0%) | 4 (4.4%) | 0 (0%) | 1 (2.2%) | 5 (1.4%) | 14 (1.8%) | ||
RS | 5 (3.6%) | 3 (3.7%) | 0 (0%) | 0 (0%) | 1 (2.1%) | 9 (2.2%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (0.3%) | ||
RS | 0 (0%) | 2 (2.4%) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (0.5%) | ||||
It will increase quality of library services | SA | PG | 88 (84.6%) | 67 (82.7%) | 85 (94.4%) | 42 (100%) | 43 (95.6%) | 325 (89.8%) | 686 (87.9%) | 14.767 (0.064) |
RS | 121 (87.7%) | 70 (85.4%) | 82 (81.2%) | 45 (91.8%) | 43 (89.6%) | 361 (86.4%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 16 (15.4%) | 14 (17.3%) | 5 (5.6%) | 0 (0%) | 1 (2.2%) | 36 (9.9%) | 92 (11.8%) | ||
RS | 17 (12.3%) | 11 (13.4%) | 19 (18.8%) | 4 (8.2%) | 5 (10.4%) | 56 (13.4%) | ||||
D | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 1 (0.3%) | 2 (0.3%) | ||
RS | 0 (0%) | 1 (1.2%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.2%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
Real-Time Information Accessibility | SA | PG | 88 (84.6%) | 67 (82.7%) | 84 (93.3%) | 36 (85.7%) | 43 (95.6%) | 318 (87.8%) | 691 (88.6%) | 10.878 (0.209) |
RS | 129 (93.5%) | 70 (85.4%) | 86 (85.1%) | 43 (87.8%) | 45 (93.8%) | 373 (89.2%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 16 (15.4%) | 14 (17.3%) | 6 (6.7%) | 6 (14.3%) | 1 (2.2%) | 43 (11.9%) | 85 (10.9%) | ||
RS | 7 (5.1%) | 11 (13.4%) | 15 (14.9%) | 6 (12.2%) | 3 (6.3%) | 42 (10%) | ||||
D | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 1 (0.3%) | 4 (0.5%) | ||
RS | 2 (1.4%) | 1 (1.2%) | 0 (0%) | 0 (0%) | 0 (0%) | 3 (0.7%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
Better & Efficient Utilization of Library Resources | SA | PG | 92 (88.5%) | 72 (88.9%) | 82 (91.1%) | 42 (100%) | 43 (95.6%) | 331 (91.4%) | 694 (89%) | 12.039 (0.149) |
RS | 124 (89.9%) | 71 (86.6%) | 81 (80.2%) | 45 (91.8%) | 42 (87.5%) | 363 (86.8%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 12 (11.5%) | 9 (11.1%) | 8 (8.9%) | 0 (0%) | 1 (2.2%) | 30 (8.3%) | 84 (10.8%) | ||
RS | 13 (9.4%) | 11 (13.4%) | 20 (19.8%) | 4 (8.2%) | 6 (12.5%) | 54 (12.9%) | ||||
D | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 1 (0.3%) | 2 (0.3%) | ||
RS | 1 (0.7%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (0.2%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
It will address the concerns of user data lost, user authentication, data storage, and inventory management. | SA | PG | 89 (85.6%) | 72 (88.9%) | 72 (80%) | 36 (85.7%) | 40 (88.9%) | 309 (85.4%) | 654 (83.8%) | 28.115 (0.000) |
RS | 119 (86.2%) | 65 (79.3%) | 83 (82.2%) | 37 (75.5%) | 41 (85.4%) | 345 (82.5%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 15 (14.4%) | 6 (7.4%) | 18 (20%) | 6 (14.3%) | 4 (8.9%) | 49 (13.5%) | 118 (15.1%) | ||
RS | 19 (13.8%) | 13 (15.9%) | 18 (17.8%) | 12 (24.5%) | 7 (14.6%) | 69 (16.5%) | ||||
D | PG | 0 (0%) | 3 (3.7%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 4 (1.1%) | 8 (1%) | ||
RS | 0 (0%) | 4 (4.9%) | 0 (0%) | 0 (0%) | 0 (0%) | 4 (1%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
It will increase the productivity of library services | SA | PG | 81 (77.9%) | 67 (82.7%) | 77 (85.6%) | 39 (92.9%) | 43 (95.6%) | 307 (84.8%) | 670 (85.9%) | 8.510 (0.385) |
RS | 125 (90.6%) | 68 (82.9%) | 86 (85.1%) | 42 (85.7%) | 42 (87.5%) | 363 (86.8%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 23 (22.1%) | 14 (17.3%) | 13 (14.4%) | 3 (7.1%) | 1 (2.2%) | 54 (14.9%) | 106 (13.6%) | ||
RS | 13 (9.4%) | 12 (14.6%) | 14 (13.9%) | 7 (14.3%) | 6 (12.5%) | 52 (12.4%) | ||||
D | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 1 (0.3%) | 4 (0.5%) | ||
RS | 0 (0%) | 2 (2.4%) | 1 (1%) | 0 (0%) | 0 (0%) | 3 (0.7%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
Flexible System to Interact | SA | PG | 89 (85.6%) | 68 (84%) | 75 (83.3%) | 36 (85.7%) | 38 (84.4%) | 306 (84.5%) | 649 (83.2%) | 9.896 (0.272) |
RS | 116 (84.1%) | 63 (76.8%) | 86 (85.1%) | 41 (83.7%) | 37 (77.1%) | 343 (82.1%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 15 (14.4%) | 10 (12.3%) | 15 (16.7%) | 6 (14.3%) | 6 (13.3%) | 52 (14.4%) | 127 (16.3%) | ||
RS | 22 (15.9%) | 19 (23.2%) | 15 (14.9%) | 8 (16.3%) | 11 (22.9%) | 75 (17.9%) | ||||
D | PG | 0 (0%) | 3 (3.7%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 4 (1.1%) | 4 (0.5%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
Useful in Emergency Situations | SA | PG | 77 (74%) | 61 (75.3%) | 85 (94.4%) | 42 (100%) | 42 (93.3%) | 307 (84.8%) | 663 (85%) | 19.942 (0.011) |
RS | 117 (84.8%) | 70 (85.4%) | 84 (83.2%) | 43 (87.8%) | 42 (87.5%) | 356 (85.2%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 23 (22.1%) | 20 (24.7%) | 5 (5.6%) | 0 (0%) | 2 (4.4%) | 50 (13.8%) | 109 (14%) | ||
RS | 21 (15.2%) | 10 (12.2%) | 17 (16.8%) | 6 (12.2%) | 5 (10.4%) | 59 (14.1%) | ||||
D | PG | 4 (3.8%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 5 (1.4%) | 8 (1%) | ||
RS | 0 (0%) | 2 (2.4%) | 0 (0%) | 0 (0%) | 1 (2.1%) | 3 (0.7%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
Promote Information Literacy | SA | PG | 86 (82.7%) | 70 (86.4%) | 83 (92.2%) | 39 (92.9%) | 42 (93.3%) | 320 (88.4%) | 662 (84.9%) | 10.294 (0.245) |
RS | 115 (83.3%) | 67 (81.7%) | 81 (80.2%) | 38 (77.6%) | 41 (85.4%) | 342 (81.8%) | ||||
A | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
N | PG | 18 (17.3%) | 11 (13.6%) | 7 (7.8%) | 3 (7.1%) | 2 (4.4%) | 41 (11.3%) | 117 (15%) | ||
RS | 23 (16.7%) | 15 (18.3%) | 20 (19.8%) | 11 (22.4%) | 7 (14.6%) | 76 (18.2%) | ||||
D | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (2.2%) | 1 (0.3%) | 1 (0.1%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||||
SD | PG | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | ||
RS | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
PG, postgraduate; RS, research scholar. Note: Percentage in parenthesis.
On observation of the response of postgraduate students and research scholars regarding the benefits to the users by implementation of IoT library services, the findings show that the IoT will ensure better and efficient utilization of library resources: postgraduate students, 331 (91.4%), and research scholars, 363 (86.8%), followed by real-time information accessibility: 318 postgraduate students (87.8%), and 373 research scholars (89.2%), recommend IoT-based library services: 322 postgraduate students (89%), and 368 research scholars (88%). System content quality will be updated postgraduate students, 316 (87.3%), and research scholars, 372 (89%); it will increase the quality of library services: postgraduate students, 325 (89.8%); and research scholars, 361 (86.4%); the efficiency of library services will increase with the implementation of IoT postgraduate students, 304 (84%), and research scholars, 370 (88.5%). It will increase the productivity of library services postgraduate students, 307 (84.8%), and research scholars, 363 (86.8%); be useful in emergencies for postgraduate students, 307 (84.8%), and research scholars, 356 (85.2%); promote information literacy postgraduate students, 320 (88.4%), and research scholars, 342 (81.8%); and least preferred reduce the manpower requirement postgraduate students, 308 (85.1%), and research scholars, 328 (78.5%). The Chi-square test was applied regarding the benefits of IoT in library services among the respondents in two categories. Based on test results, the p-values were lower (<0.05) for most of the variables indicating significant differences among the postgraduates and research scholars.
6 Discussion
The IoT concept is gaining popularity around the world. The notion has received substantial interest in recent years from various societies, and as a result, various experts have attempted to provide multiple definitions of IoT (Igbinovia & Okuonghae, 2021). IoT, an emerging technology, has a lot to offer libraries in terms of management and operation. The speed of delivery, platform for distribution, customer expectations, and the conviction that connecting devices are secure, and information or data are kept private which all influence IoT applications in library services. Through simplified manual proximity triggers, IoT acts as a value driver. These applications include self-checkout and inventory management in libraries, building access control, and simple payment methods. This application for the IoT helps users gain independence through self-service, minimizes human intervention in the library use process, and improves the service experience for users. These factors have a positive impact on users’ perceptions of convenience (Massis, 2016). The present study is focused on perceiving the awareness and perception of postgraduate students and research scholars of IITs of Northern India toward the application of IoT in library services as discussed below in detail relating to the observed research literature and discerned research problems. According to the study, including user feedback in the design and execution process is critical. This user-centric approach can assist libraries in developing IoT systems that suit not only technology needs but also user expectations, preferences, and considerations. The findings revealed that most of the respondents were male out of which maximum response was gained from IIT Delhi and active respondents belonging to the age group of 26–30 years were in second year.
6.1 Present Status of Library Service
The results revealed a matter of concern as most of the respondents occasionally visit the library and avail following library services like Internet/Wifi, followed by library website, remote access to the library, digital library, real-time updates, user authentication through biometrics, self-issue/return kiosk, QR code for payments, virtual library orientation.
6.2 Extent of Awareness and Perception Toward IoT-Based Library Services
For various reasons, increasing student understanding of the IoT and its uses in library services is critical. It not only prepares students for the digital age but also encourages them to use technology-driven library resources and services. Students are more likely to use IoT applications in libraries if they are aware of these services. They can, for example, use smartphone apps to find books, access digital resources, or collaborate in smart environments. IoT awareness helps libraries learn how to personalize services depending on customer preferences and behaviors. Customized recommendations, reminders, and notifications can help students. Students who are aware of IoT in libraries can actively participate in defining the direction of technology deployments by working with library personnel and administration. Their opinions can be useful in developing user-centered solutions.
The results revealed that most of the students got familiar with IoT from browsing on the Web/Internet, followed by social networking sites, research projects, conferences, workshops, webinars and faculty development programs, professional discussions, and meetings, part of the curriculum and least preferred from other sources as also observed by Gupta and Singh (2018). On observation of the response of postgraduate students and research scholars regarding the level of awareness and perception toward the application of IoT in library services, the findings show that the commercial model of IoT technology can be implemented in various library services of IITs of Northern India and respondents were in favor to implement IoT in library services. They believed that IoT will ensure better and more efficient utilization of library resources, followed by real-time information accessibility, and recommend IoT-based library services; system content quality will be updated; it will increase the quality of the library; the efficiency of library services will increase with the implementation of IoT; it will increase the productivity of library services, useful in an emergency situation, promote information literacy as also highlighted by Kumar (2023).
7 Conclusion
Libraries face substantial service issues in the modern day. Some issues are associated with information resource management, which includes the quick availability of information for decision-making. The IoT is a recent technical shift that users should be aware of since it has the potential to improve the experience of seeking information resources. The study’s goal is to highlight users’ willingness, awareness, and perceptions of IoT technology adoption in academic libraries. The findings clearly indicate the positive shift of users toward IoT technology and aggress to its potential benefits if applied in various library services. Based on the findings, it can be concluded that libraries have the major responsibility to introduce new IoT-based services based on initial testing and feedback from users in IITs. Libraries can also practice short technology-driven clubs for the voluntary participation of students to have discussions on how to introduce new services with existing resources and a limited budget.
Although student awareness and perception of IoT implementation in library services at selected IIT libraries gives useful insights, it is critical to recognize its limitations and identify some constraints that may affect the generalizability and reliability of the findings. The study may have largely focused on specific demographics (PG and research scholars) or IITs, limiting the findings’ generalizability to a larger student community. To ensure a full grasp of students’ opinions, future research should try for varied and representative samples. Students’ awareness and impression of IoT may change as new technologies arise and cultural attitudes toward technology shift. Considering these limitations, the study is a useful beginning point for assessing students’ awareness and perceptions of IoT deployment in library services.
The investigation discovered several insights that open the way for prospective future research fields. These sections are intended to fill gaps, increase awareness, and contribute to the changing environment of IoT in libraries, for example, performing longitudinal research to evaluate changes in students’ awareness and perception of IoT over time. This method captures the dynamic nature of technical advancement and societal views, providing a more complete understanding of long-term ramifications and trends. Examining the impact of educational efforts in libraries aimed at boosting awareness and comprehension of IoT. The most effective strategies are investigated for informing students about the capabilities, functionalities, and possible benefits of IoT technologies in order to develop a better-informed user base. Investigating collaborative research projects with industry partners to evaluate the practical consequences of using IoT technology in library services. Collaborate with technology providers, developers, and industry professionals to bridge the gap between academic research and real-world application, stimulating innovation and practical solutions.
8 Recommendations
The study’s findings provide fresh subjects and conceptions for future research on related topics or longitudinal studies to widen the frontiers of the current study. The following areas for future investigation are suggested based on the current study's findings:
Similar investigations on IITs may be conducted in various geographical regions of India to determine whether or not there is a parallel or disparity in the outcomes.
Libraries can extend their resource monitoring capabilities beyond their local area network (LAN) by integrating RFID technology with the MQTT protocol through the use of IoT architecture. With their smartphone acting as a client and providing access to all available information on the subject, librarians will benefit from the remote monitoring capability, which will enable them to access the complete inventory at any time and from any location.
IoT-integrated library catalog search can be experimented as being able to follow users' search intents by monitoring and analyzing their search activity and informing users when new items related to their interests are released. As soon as a user approaches a specific section, the IoT network will alert them to the documents within their preferred domain and any additional content that the section may hold.
A virtual library tour for remote monitoring of library resources is an essential step towards easy access to resources in real-time. By using this facility, users can exactly locate the resources without wasting much time.
Acknowledgments
The authors of this article appreciate the continuous technical support from Panjab University, Department of Library and Information Science for support with research materials from the databases. The authors also like to extend their sincere gratitude to all the participants who provided valuable support throughout this research article. Their contributions were invaluable in shaping the outcome of this study.
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Funding information: Authors state no funding involved.
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Author contributions: Priyanka Sinha: conceptualization, methodology, software, validation, formal analysis, investigation, resources, and visualization; writing – original draft in contribution of First author. Dr Khushpreet Singh Brar: reviewing draft and data curation. All authors have read and agreed to the published version of the manuscript.
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Conflict of interest: Authors state no conflict of interest.
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Data availability statement: The survey data used in this research article are available upon request from the corresponding author.
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Articles in the same Issue
- Regular Articles
- FSLSM-Based Analysis of Student Performance Information in a Blended Learning Course Using Moodle LMS
- AI in Indian Libraries: Prospects and Perceptions from Library Professionals
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