Undergraduates’ Perceptions and Use of the University
Libraries Web Portal: Can Information Literacy Instruction
Make a Difference?
Yu-Hui Chen
University at Albany Libraries, State University of New York
University Library LI-304, 1400 Washington Avenue, Albany, New York, 12222, USA [email protected]
ABSTRACT
There is a common concern among academic libraries that their library Web portals are being underutilized. Literature pertaining to technology acceptance and information systems success indicates that user training plays a pivotal role in fostering favorable attitudes, and facilitating information systems usage among users. However, no study had been conducted to investigate the effect of user education on the acceptance and use of academic library Web portals. To address this gap in the literature, the researcher took the initiative to explore the impact of a semester-long credit-bearing information literacy course on undergraduate students’ perceptions and use of the University at Albany Libraries Web portal. Data were collected through two rounds of survey over a period of an academic semester. Results showed that the information literacy course positively influenced participants’ perceptions of the Libraries Web portal in terms of perceived ease of use, information quality, system quality, and user satisfaction. Yet, the course did not have an impact on their perceptions of service quality. In addition, statistically significant differences were not found in the overall frequency and duration of use, but in other dimensions of use, namely purpose and task.
Keywords
Technology acceptance model, IS success model, information literacy, instruction, user training, satisfaction, library Web portal, perceptions, use.
INTRODUCTION
As digital resources increased exponentially over the last decade, academic libraries have heavily invested in electronic books, research databases, as well as electronic journals, and made them accessible via their library Web
portals. Some libraries also undertake usability initiatives to improve their Web portals in order to provide users with better and easier access to their electronic collections and services. Despite these great efforts, it has been observed that instead of accessing a wealth of electronic content through the library Web portal, students tend to rely on Internet search engines (e.g., Google), and public Web portals (e.g., Yahoo) even though scholarly information is not always readily available there (Low, 2003), and they often have difficulty distinguishing authoritative from non-authoritative information on the Internet. As a result, underutilization of library electronic resources has become a common concern (e.g., Hong, Thong, Wong, & Tam, 2002; Thomsett-Scott & May, 2009).
There has been a considerable amount of research in the information science and technology field examining the determinants of information technology (IT) acceptance and utilization among users (e.g., Venkatesh, 2000; Heo & Han, 2003; Shih, 2004). Most of such research was based on the technology acceptance model (TAM) (Davis, Bagozzi, & Warshaw, 1989). TAM proposes that an individual’s behavioral intention to use a technology is determined by two salient beliefs: perceived usefulness (PU), and perceived ease of use (PEOU). Intention to use leads to actual system use.
While PU and PEOU have been used to predict users’ initial adoption or use of a new information technology, the construct of users’ satisfaction has been widely adopted in information systems (IS) research as an indicator of IS success and use (e.g., Delone & McLean, 1992, 2003; Doll & Torkzadeh, 1988). According to DeLone and McLean model of IS success (1992, 2003), system quality, information quality, and service quality significantly affect both use and user satisfaction. Like TAM, the IS success models have been empirically tested and expanded in numerous studies (e.g., Wang, 2008; Häkkinen & Hilmola, 2008; Schaupp, Bélanger, & Fan, 2009).
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Copyright notice continues right here. In addition to PU, PEOU, information quality, system
quality, service quality, and user satisfaction, researchers indicate that availability of training would directly affect information system usage as well (e.g., Al-Gahtani & King, 1999; Gallivan, Spitler, & Koufaris, 2005; Igbaria, Zinatelli, Gragg, & Cavaye, 1997). The effects of user 1
training on the acceptance and use of information technology, promoting greater understanding, and fostering favorable attitudes have also been discussed in the literature (e.g., Nelson & Cheney 1987; Raymond, 1988; Rouibah, Hamdy, & Al-Enezi, 2009).
Despite an overwhelming literature validating or extending the TAM and the IS success models, longitudinal studies examining the IS use patterns over time are generally lacking. This is especially manifest in research pertaining to library information systems. Additionally, effects of credit-bearing instruction on library users’ perceptions and use of academic library Web portals remain unexplored. Based on the theoretical constructs derived from TAM and the IS success models, the researcher initiated this study to address these gaps in the literature by examining the effect of a semester-long 3-credit information literacy course on undergraduate students’ perceptions and use of an academic library Web portal. Data were collected at both start and end of a semester to allow for observation of the impact on perceptions and use.
Research Context
The University Libraries at the researcher’s institution, a member of the State University of New York, is a mid-size research library in the United States. It is also one of the 126 members of the Association of Research Libraries in North America. For the 2009 academic year, the University Libraries invested more than one third of its collection acquisitions budget in electronic resources. The University Libraries Web portal serves as a gateway to access the digital information, and provides information on non-digital materials owned by the Libraries via the online public access catalog. In addition, it delivers online services such as research assistance, book renewals, interlibrary loans, class sign-up, and so forth. The Libraries Web portal is intended to effectively facilitate learning, teaching, and research.
Every semester the College of Computing and Information offers Internet and Information Access, one of the three-credit information literacy courses meeting the general education requirements, to the university’s undergraduate students. This course is required for both those who major in Information Studies and minor in Informatics, and it is an elective course for the other students. It is taught by a library faculty member, and the course content includes an introduction to the Internet and World Wide Web, Internet security, Web directories, online information resources, social networking services, search engines, as well as finding, evaluating, and producing information on the Internet. Part of this course introduces students to the University Libraries Web portal teaching them how to use library resources, such as the online public access catalog, electronic databases, and library tutorials, for their research and assignments. Traditionally, this class has a good mix of undergraduate students. By using students enrolled in this
course as the research population, the researcher aims to answer the following question:
Does the information literacy course have any impact on undergraduate students’ perceptions and use of the University Libraries Web portal?
Understanding the influence of information literacy courses on students’ perceptions and their use of academic library Web portals could provide insights into the prospect of facilitating the use of library resources through credit-bearing information literacy instruction.
LITERATURE REVIEW Theoretical Underpinnings
Studies on user technology acceptance have proliferated in the IS literature, and a large body of technology acceptance research is connected to behavioral intention. TAM (Davis, et al., 1989) is a seminal work for predicting an individual’s intention to use and acceptance of information systems (IS) and information technology (IT). TAM theorizes that a person’s attitude toward using a technology is determined by two user beliefs: PU and PEOU which lead to an individual’s behavioral intention to use the IS or IT in question. PU is defined as "the degree to which a person believes that using a particular system would enhance his or her job performance” (Davis, 1989, p. 320). PEOU refers to "the degree to which a person believes that using a particular system would be free of effort" (Davis, 1989, p. 320).
Figure 1. Technology Acceptance Model (Davis et al., 1989, p. 985)
Behavioral intention is defined as “a measure of the strength of one’s intention to perform a specified behavior” (Davis et al., 1989, p. 984). As depicted in the model, attitude toward using an information system and perceived usefulness jointly determine behavioral intention which leads to actual system usage. In addition, PEOU has an impact on PU. External variables can influence both PEOU and PU, which subsequently affect usage behavior.
TAM has been well-referenced in the IS literature. However, most studies have tested it on relatively simple systems with homogeneous participants. Thus, its applicability to a complex information system, such as an academic research library Web portal, and diverse populations (e.g., students in different grade levels and academic programs) can be questioned.
Parallel to the TAM model and its variations, another research stream, information systems (IS) success models 2
(e.g., DeLone & McLean, 1992, 2003; Seddon, 1997), investigates user satisfaction and technology acceptance. Based on a comprehensive literature review of the IS success definitions and measures, DeLone & McLean (1992) developed a taxonomy consisting of six dimensions of IS success (see Figure 2):
Figure 2. Information Systems Success Model (DeLone & McLean, 1992, p. 87)
1. System Quality refers to measures of the information processing system itself;
2. Information Quality refers to measures of information system output;
3. Use refers to recipient consumption of the output of an information system;
4. User Satisfaction refers to recipient response to the use of the output of an information system;
5. Individual Impact, closely related to performance, refers to the effect of information on the behavior of the recipient, and
6. Organizational Impact refers to the effect of
information on organizational performance.
As illustrated above, both System Quality and Information Quality affect Use and User Satisfaction. The realization of system benefits for individual users and the organization as a whole depends on the significant impact of Use and User Satisfaction.
With the advent of Web technology and the growing popularity of e-commerce, DeLone and McLean (2003) updated their original model by including Service Quality to reflect the critical aspect of online service and support in e-commerce systems. Intention to Use was added to measure user attitude. Also, individual and organizational impacts were collapsed into a single benefit impact called Net Benefits (see Figure 3).
Figure 3. DeLone & McLean’s Updated IS Success Model (DeLone & McLean 2003, p. 24)
Through analyzing IS models, dimensions, measures, and interrelationships, Petter, DeLone, and McLean (2008) indicate that the relationships between Use and User Satisfaction, as well as the correlation between Use and Net Benefits have received moderate support from the IS literature. Additionally, the path from User Satisfaction to Net Benefits is strongly supported. Although the updated DeLone and McLean’s (2003) IS success model has been widely applied to research in the areas of e-commerce, knowledge management systems, and specialized business applications, it has not been broadly validated in academic settings. Library-based studies grounded in this conceptual model are minimal.
Research Relevant to Academic Library Web Site Usage
Although there is a wide array of literature discussing determinants of technology acceptance and information systems success, research on how the IT/IS acceptance and success factors impact students’ acceptance and use of academic library Web portals has been very limited. Kim (2006) conducted a study exploring factors affecting user acceptance of Web-based subscription databases using the TAM2 model as theoretical framework. Contrary to the findings of prior studies (e.g., Bradley & Lee, 2007; Hu, Clark, & Ma, 2003), user training did not correlate with either PEOU or PU for participants who had received database training. Nevertheless, the training intervention used in Kim’s (2006) study was single workshops; the impact of a semester-long, credit-bearing user instruction course could be significantly different.
Expanding the scope from web-based subscription databases to a digital library Web site, Hong et al. (2002) studied the acceptance of the Open University of Hong Kong’s E-Library based on the TAM model. They explored the effect of some critical external variables on the intention to use the electronic collections by distance learners. Their research results showed that both individual differences and the system characteristics significantly influenced PEOU. Additionally, relevance was the only system characteristics that positively impacted PU. Their research demonstrated the effect of external variables on behavior intention through users’ beliefs postulated in TAM. In their subsequent study on the E-Library, Thong, Hong, and Tam (2002) examined the effect of system interface, organizational context, and individual differences on the adoption intention of users. Their research outcomes indicated that both PU and PEOU determined user acceptance. Mirroring their initial study, both system interface and individual differences influenced PEOU. Organizational context (i.e., relevance of the system to users’ information needs, system accessibility, and system visibility) affected both PEOU and PU. An academic library Web portal has a wider scope than E-library; hence, the results need to be verified in such a context.
To test the applicability of the TAM model in developing countries, Park, Roman, Lee, and Chung (2009) studied the 3
determinants of users’ acceptance and usage of the Essential Electronic Agricultural Library (TEEAL) in 16 institutions in Africa, Asia, and Central/Latin America. Their results showed that PEOU significantly influenced PU which in turn led to behavioral intention to use. Similar to the findings in the study by Hong et al. (2002), individual differences and system characteristics played essential roles in facilitating the successful adoption of the digital library. Both research by Hong et al., and Park et al. reveals the importance of user-centered information system design. User training allows end users to obtain the required skills and the confidence for effective use of the target system. According to Heany (1972), one of the critical factors for the successful introduction to an information system is developing its users’ abilities through a system-related training program. Nelson and Cheney (1987) mentioned that information systems can have a significant positive impact on task performance if organizations provide all levels of users with sufficient education or training. An information literacy course can help students with different levels of experience effectively use a library Web portal for their study-related work; thus, it has the potential to facilitate user acceptance of this information system. The reviewed literature pertaining to library information systems use is grounded in TAM and the usage is captured at a single point of time. In addition, electronic resources and digital libraries are the dominant research agendas. As the Web is an emerging technology that keeps evolving, and academic library Web portals have become the major mechanism to disseminate information and deliver services, exploring the University Libraries Web portal as a whole to broaden the research scope will be a significant addition to the knowledge base. To date, no study has been conducted to review the use of academic library Web portals based on the IS success frameworks. Neither is there any research identifying the relationship between information literacy instruction and the use of library Web portals. Therefore, incorporating constructs derived from the TAM and IS success models to examine the impact of a credit-bearing information literacy course on students’ perceptions and use of the University Libraries Web portal will provide a fresh perspective and fill a gap in the literature.
Research Proposition
The goal of this study is to identify the effect of credit-bearing instruction on the perceptions and use of the University Libraries Web portal. To compare students’ views and usage of the Web portal before and after receiving the information literacy instruction, the researcher drew on constructs from TAM and the IS success models. They are perceived ease of use, perceived usefulness, information quality, system quality, service quality, user satisfaction, and use.
User training ininformation systems refers to the extent to which an individual has been trained about information systems through college courses, vendor training, in-house
training, and self-study (Igbaria, Guimaraes, & Davis, 1995). Prior research indicates that training helps users shape their perceptions of information systems and become well-versed in how to best use the systems (e.g., Shachak & Fine, 2008).
User training can be an external factor in the TAM model (Davis et al., 1989) that influences perceived ease of use. Several empirical studies have tested and support the positive relationship between user training and perceived ease of use (e.g., Igbaria et al., 1995, 1997; Taylor & Todd, 1995; Thompson, Higgins, & Howell, 1991). Likewise, examples of positive impact of user training/user education on perceived usefulness and user acceptance of information systems are evident in the literature (e.g., Igbaria, et al., 1995; Rouibah et al., 2009; Sabherwal, Jeyaraj, & Chowa, 2006; Venkatesh & Davis, 2000). User education enables users to identify system capabilities, as well as understand the fit between their tasks and the system functions, thus significantly affecting users’ perceptions of usefulness of a system (Santhanam & Sein, 1994; Venkatesh, 1999). Since there are many empirical studies signifying the favorable relationship between user training and users’ beliefs, the following hypotheses are proposed:
H1: Information literacy instruction has a positive impact on perceived ease of use of the University Libraries Web portal.
H2: Information literacy instruction has a positive impact on perceived usefulness of the University Libraries Web portal.
Training guides users to better understand the organization of an information system and the logic of the design, thus alleviating the gap between the mental model of the system and that of the users. The effect of training on users’ perceptions of system quality is also mentioned in the literature (e.g., Sabherwal, et al., 2006). Since searching for authoritative information and evaluating information are part of the course content, the researcher suggests that instruction will help students recognize the quality of information provided through the Libraries Web portal. Additionally, as the course instructor introduces students to various online library services, such as e-mail and Instant Messenger for research assistance, the researcher speculates that the instruction will raise students’ awareness of online services available to them. This, in turn, can have a positive impact on their perceptions of the service quality of the Libraries Web portal. Therefore, the following hypotheses are generated:
H3: Information literacy instruction has a positive impact on perceptions of information quality. H4: Information literacy instruction has a positive
impact on perceptions of system quality.
H5: Information literacy instruction has a positive impact on perceptions of service quality.
User satisfaction is broadly used in IS research as an indicator of user perception of the effectiveness of an information system (e.g., DeLone and McLean, 1992, 2003). It reflects one's attitudes toward factors related to information systems. As it is postulated that there will be a positive change in students’ perceptions of perceived ease of use, perceived usefulness, information quality, system quality, and service quality after the instruction, it is logical to assume that the information literacy course will positively influence students’ satisfaction toward the Web portal. In addition, the impact of user training on information system usage is also supported by many researchers (e.g., Al-Gahtami & King, 1999; Gallivan et al., 2005; Igbaria et al., 1995, 1997). Therefore, the following hypotheses are proposed:
H6: There will be a positive change in students’ satisfaction toward the Libraries Web portal after the information literacy instruction.
H7: There will be a positive change in students’ use of the Libraries Web portal after the information literacy instruction.
METHODOLOGY
To test the proposed hypotheses, a survey instrument consisting of measurements for each construct was developed. The survey questionnaires were composed of multiple choice questions and Likert scales. Multiple choice questions were used to collect demographic information; while Likert scales were applied to measure participants' perceptions and use of the University Libraries Web portal.
In order to develop a comprehensive instrument, multiple items were used to measure each construct. All of the construct indicators were derived from previously validated instruments based on a comprehensive literature review. Three items, selected from studies by Heinrichs, Lim, Lim, and Spangenberg (2007) and Kim (2010), were used to measure the ease of finding information and navigation. Four items for the perceived usefulness construct were adapted from Davis (1989), Heinrichs, et al. (2007), and Hong, et al. (2002) to capture the perceived benefits as a result of using the Libraries Web portal. The information quality construct comprises six items (Kim, Lee, & Law, 2008; Lin & Lee, 2006; Schaupp, et al, 2009) to measure aspects of content and timeliness. The system quality construct was composed of four items (Hong, et al., 2002; Roca, Chiu, & Martínez, 2006; Yen & Lu, 2008) to assess availability, speed, task-flow, and layout. Three items were used to measure service quality regarding online support and assistance (Roca, et al, 2006; Ozkan, Koseler, & Baykal, 2009). The indicators used to determine user satisfaction focus on effectiveness, efficiency, and users’ overall attitude (McGill & Hobbs, 2008; Wang & Wang, 2009). Likert scales (1-5), with anchors ranging from ‘1= strongly disagree’ to ‘5 = strongly agree’ were used for all questions.
Use was measured in terms of frequency, duration, purpose, and task (Igbaria, Iivari, & Maragahh, 1995; Igbaria, et al., 1997;Kellar, Watters, & Shepherd, 2007;McGill & Hobbs, 2008). Frequency was measured on a 5-point scale from ‘0’ to ‘over 8’ times per week. Similarly, duration was measured on a five-point scale from ‘0’ to ‘over 8’ hours per week. Items for purposes and tasks were measured in a 7-point scale with anchors ranging from ‘Never’ to ‘Daily’ (see Appendix).
Wording for each question was slightly modified to fit the context of the current study. A faculty panel specializing in information science and technology reviewed the questions to ensure the measures can be categorized as per theoretical predictions. To estimate the duration of time needed for completing the questionnaire, and to find any ambiguity in questions for refinement, prior to the initial data collection, the survey was tested by five undergraduate students who had not taken the Internet and Information Access course. As permitted by the course instructor and approved by the University’s Institutional Review Board, the researcher recruited participants from the 405 students enrolled in the Internet and Information Access course for the Fall 2010 semester on the first day of the class. The researcher explained the study to the students, indicating that the participation was voluntary. Students completing the pre- or the post- survey or both surveys would receive extra credit. In order not to make students feel coerced to participate, it was made clear that those who chose not to participate in the surveys could receive the same amount of extra credit by writing up to two short reports on the Libraries Web portal. In addition, to minimize the effects of social desirability bias, the students were told that there were no right or wrong answers, and their responses would be kept in confidence. Two rounds of surveys were administered at two points in time: the first day of the class, and the end of the course. Both pre- and post-course surveys were conducted in class. Data were analyzed using SPSS.
RESULTS and DISCUSSION Participants
Of the 405 students enrolled in this information literacy course, 357 participated in either pre-course, or post-course, or both suveys. The number of participants for the pre-course and post-pre-course surveys was 306 each for a response rate of 75.5%. Since first semester freshmen and transfer students had not had opportunities to explore or use the Libraries Web portal when the pre-course suvery was conducted, their data were removed, leaving a sample of 145 students taking both pre- and post-course surveys for investigating the impact of the information literacy class. These participants were from 30 academic departments; some programs were more heavily represented than the others. A summary of the demographic characteristics is shown in Table 1.
Participant characteristics Frequency Percent Gender Male 91 63% Female 54 37% Year Freshman 2 1% Sophomore 64 44% Junior 52 36% Senior 27 19% Academic Program Business 45 31% Humanities 10 7% Social Sciences 66 46%
Science & Technology 24 16%
Table 1. Descriptive statistics of participants for both pre-course and post- course surveys (n = 145). The Impact of the Information Literacy Instruction on Participants’ Perceptions of the University Libraries Web Portal
Contrary to Kim’s (2006) findings that training in Web-based subscription databases did not positively influence PEOU, the outcome of this current study showed a strong relationship between user education on University Libraries Web portal and PEOU. The paired samples t-test results showed that there were statistically significant differences in participants’ perceptions of perceived ease of use before and after the information literacy instruction (see Table 2). After receiving instruction, participants found it easier to understand the organization of the University Libraries Web portal and navigate for needed information. Thus, Hypothesis 1 was supported.
Perceived Ease of Use Pre-course survey Post-course survey Mean SD Mean SD t p* easy to find information 3.63 1.00 3.89 0.91 2.84*** 0.003 organization of information is easy to understand 3.57 1.04 3.86 0.90 2.85*** 0.003 easy to navigate 3.54 1.11 3.88 0.98 3.19*** 0.001 *One-tailed. ***p < .005, ** p < .05
Table 2. Participants’ perceptions of perceived ease of use before and after the course (n = 145).
The t-test presented mixed results for PU. Participants’ perception of the Libraries Web portal’s leading them to better research was positively impacted by the instruction (p
< 0.005). The other indicators of PU did not show statistically significant differences (see Table 3). Therefore, Hypothesis 2 was partially supported.This could be an issue of fit between the participants’ tasks and the Libraries Web portal. For example, when a student needs to look up a mathematical theorem, using Google will likely be easier and faster than the Libraries Web portal. Individual differences can influence PEOU and PU. Users with more computer experience and better knowledge of subject domain are more proficient in formulating proper queries
and interpreting search results (Thong, Hong, & Tam,
2004). Thus, participants’ domain knowledge, experience in using the Libraries Web portal, and their abilities to synthesize information retrieved could be another set of factors that mediate the influencial power of instruction over perceived usefulness.
Perceived Usefulness Pre-course survey Post-course survey Mean SD Mean SD t p* better research 3.68 1.09 4.09 0.89 3.79*** 0.000 easier to do assignments 3.55 1.17 3.71 1.04 1.33 0.092 academic performance 3.53 1.11 3.60 1.04 0.62 0.267 productivity 3.43 1.14 3.55 0.98 1.03 0.152 *One-tailed. ***p < .005, ** p < .05
Table 3. Participants’ perceptions of perceived usefulness before and after the course (n = 145).
As shown in Table 4, the positive influence of the information literacy course on participants’ perceptions of information quality was evident in each indicator. Hence, Hypothesis 3 was supported. In a way, this outcome reflects the perceptions of usefulness that the Libraries Web portal leads to better research.
Information Quality Pre-course survey Post-course survey Mean SD Mean SD t p* sufficient information 3.77 1.02 4.03 0.84 2.94*** 0.002 accurate information 4.05 1.03 4.26 0.92 2.12** 0.018 up-to-date information 3.89 1.00 4.28 0.84 4.18*** 0.000 timely information 3.81 1.02 4.14 0.93 3.49*** 0.001 information that is helpful 4.03 1.01 4.25 0.70 2.51** 0.007 *One-tailed. ***p < .005, ** p < .05
Table 4. Participants’ perceptions of information quality before and after the course (n = 145).
Positive changes in participants’ perceptions of system quality after course instruction were also observed in all of the indicators (see Table 5). These positive associations echo prior studies on the relationship between training and system acceptance (e.g., Santhanam & Sein, 1994; Venkatesh, 1999). Instruction bridges the gap of mental models between participants and the Libraries Web portal. As a result, participants could better appreciate the design logic, and the layout of the University Libraries Web portal more than before taking the course. Thereby, Hypothesis 4 was supported.
System Quality Pre-course survey Post-course survey Mean SD Mean SD t p* Is always available 3.97 1.12 4.15 1.04 1.81** 0.037 displays information quickly 3.63 1.12 4.03 1.05 3.73*** 0.000 follows a logical sequence 3.61 1.11 3.94 0.93 3.20*** 0.001 layout is user-friendly 3.64 1.21 3.93 0.98 2.82*** 0.003 *One-tailed. ***p < .005, ** p < .05
Table 5. Participants’ perceptions of information quality before and after the course (n = 145).
Service Quality Pre-course survey Post-course survey Mean SD Mean SD t p* provides quick responses to service requests 3.63 1.08 3.66 0.98 0.33 0.369 has a good interface to commu-nicate my needs 3.72 1.06 3.78 0.95 0.58 0.283 easy to get online assistance via IM or e-mail 3.39 1.19 3.06 0.83 -2.95 0.998 *One-tailed. ***p < .005, ** p < .05
Table 6. Participants’ perceptions of service quality before and after the course (n = 145).
Different from information quality and system quality, participants’ perceptions of service quality did not show any significant change after the instruction (see Table 6). Therefore, Hypothesis 5 was not supported. The attributes of service quality are either technical or human related issues for which the University Libraries should be held accountable; they are not something over which participants had control. Thus, it seems reasonable that the impact of instruction was absent. This finding raises a serious concern because in the Web environment, face-to-face interaction is replaced by the system’s interface. The quality of service delivered electronically can either enhance or hamper user support experience (Jiang, Klein, & Carr, 2002; DeLone & McLean, 2003). Academic libraries increasingly provide information resources and services through their virtual presences. Being responsive to library users’ requests and having a seamless online communication mechanism to interact with users are essential to promoting positive user experience. Like e-commerce systems, poor quality of online service will most likely turn their users away.
The information literacy course notably raised the level of participants’ satisfaction (see Table 7). Shachak and Fine (2008) indicate that user training not only enables users to become experienced in using the information systems but also shapes their perceptions. This positive outcome might be due to the fact that instruction helped participants get familiar with the functions/features of the Libraries Web portal and shortened their learning curves. Thus, Hypothesis 6 was supported.
Satisfac-tion Pre-course survey Post-course survey Mean SD Mean SD t p* efficient 3.70 1.02 3.97 0.97 2.51** 0.007 effective 3.63 1.03 3.92 0.97 2.93*** 0.002 satisfied 3.78 1.02 4.00 0.91 2.41** 0.009 *One-tailed. ***p < .005, ** p < .05
Table 7. Participants’ satisfaction towards the Libraries Web portal before and after the course (n = 145). The Impact of Information Literacy Course on Participants’ Use of the University Libraries Web Portal
Participants’ use of the Libraries Web portal was examined from multiple angles. Statistically significant differences were non-existent in both frequency and duration. Possible explanations for no increase in these two dimensions could be: availability of alternative tools, such as Internet search engines and public Web portals; and limited number of assignments required participants to use the Libraries Web portal.
On the other hand, instruction exhibited a strong positive influence on most of the indicators of purposes (see Table 8). As each purpose might require multiple activities to fulfill, frequencies of tasks performed relevant to these purposes (i.e, find books, find journals, find articles, retrieve course readings on electronic reserves, look up citation guides, take library virtual tours, and use e-mails for research assistance) also showed statistically significant increases. Hence, Hypothesis 7 was partially supported.
Purpose Pre-course survey Post-course survey Mean SD Mean SD t p* Fact Finding 2.60 1.59 2.76 1.61 0.95 0.171 Assignments 3.03 1.57 3.58 1.66 3.24*** 0.001 In-depth Research 2.66 1.31 3.18 1.51 3.34*** 0.001 Transactions 1.82 1.27 3.17 1.85 7.13*** 0.000 Communica-tions 3.20 2.47 4.10 2.55 3.56*** 0.000 *One-tailed. ***p < .005, ** p < .05
Table 8. Participants’ purposes of using the Libraries Web portal before and after the course (n = 145).
CONCLUSION
This current study explored the effect of a credit-bearing information literacy course on undergraduate students’ perceptions and use of the University Libraries Web portal. The outcome, to a great extent, resonates with prior studies that user training can shape user beliefs, foster favorable attitudes, and facilitate use. The fact that this 3-credit course exerts positive influences on PEOU, information quality, system quality, satisfaction, as well as the purpose and task dimensions of use sends out a strong signal that integrating information literacy instruction into credit-bearing courses can help facilitate the acceptance of the Libraries Web portal among undergraduates. Yet, based on the findings of this study, user education alone cannot fully affect users’ perceptions. Intuitive, interactive, and responsive online support and services have to be in place to cultivate positive user experiences and attitudes.
As the results signified an increase in user satisfaction after the course instruction, the next step is to follow-up with participants to determine if higher user satisfaction leads to more use and vice versa. This is an area lacking empirical research, and remains unexplored in the academic library setting. Additionally, developing a conceptual model to examine the dynamic relationships among the constructs would allow the researcher to identify factors influencing undergraduates’ use patterns of the Libraries Web portal. The discovery resulting from the intended research could help library practitioners address issues deterring patrons from visiting their library Web portals and formulate strategies for promoting use.
REFERENCES
Al-Gahtani, S. S., & King, M. (1999). Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology. Behaviour & Information Technology, 18(4), 277-297.
Bradley, J., & Lee, C. C. (2007). ERP training and user satisfaction: A case study. International Journal of Enterprise Information Systems, 3(4), 33-50.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable.
Information Systems Research, 3(1), 60-95.
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A
ten-year update. Journal of Management Information
Systems, 19(4), 9-30.
Doll, W. J., & Torkzadeh, G. (1988). The measurement of end user computing satisfaction. MIS Quarterly, 12(2), 259-274.
Gallivan, M. J., Spitler, V. K. & Koufaris, M. (2005). Does technology training really matter? A social information processing analysis of co-workers’ influence on IT usage in the workplace. Journal of Management Information System, 22(1), 153-192.
Häkkinen, L., & Hilmola, O-P. (2008). Life after ERP implementation: Long-term development of user perceptions of system success in an after-sales
environment. Journal of Enterprise Information
Management, 21(3), 285-310.
Heany, D. E. (1972). Education: The critical link in getting managers to use management systems. Interfaces, 2(3), 1-7.
Heinrichs, J. H., Lim, K-S., Lim, J-S., & Spangenberg, M. A. (2007). Determining factors of academic library Web site usage. The Journal of the American society for Information Science and Technology, 58(14), 2325-2334. Heo, J., & Han, I. (2003). Performance measure of
information systems (IS) in evolving computing environments: An empirical investigation. Information & Management, 40(4), 243-256.
Hong, W., Thong, J. Y. L., Wong, W-M., & Tam, K-Y. (2002). Determinants of user acceptance of digital libraries: An empirical examination of individual differences and system characteristics. Journal of Management Information Systems, 18(3), 97-124.
Hu, P. J-H., Clark, T. H. K., & Ma, W. W. (2003). Examining technology acceptance by school teachers: A longitudinal study. Information and Management, 41(2), 227-241.
Igbaria, M., Guimaraes, T. & Davis, G. B. (1995). Testing the determinants of microcomputer usage via a structural equation model. Journal of Management Information Systems, 11(4), 87-114.
Igbaria, M., Iivari, J., & Maragahh, H. (1995). Why do individuals use computer technology? Information and Management, 29(5), 227-238.
Igbaria, M., Zinatelli, N., Gragg, P. & Cavaye, A. L. M. (1997). Personal computing acceptance factors in small firms: A structural equation models. MIS Quarterly, 21(3), 279-305.
Jiang, J. J., Klein, G., & Carr, C. L. (2002). Measuring information system service quality: SERVQUAL from the other side. MIS Quarterly, 26(2), 145-166.
Kellar, M., Watters, C., & Shepherd, M. (2007). A field study characterizing web-based information-seeking tasks. Journal of the American Society for Information Science and Technology, 58(7), 999-1018.
Kim, J-A. (2006). Toward an understanding of Web-based subscription database acceptance. The Journal of the
American Society for Information Science and Technology, 57(13), 1715-1728.
Kim, Y-M. (2010). The adoption of university library Web site resources: A multigroup analysis. The Journal of the American Society for Information Science and Technology, 61(5), 978-993.
Kim, T. G., Lee, J. H., & Law, R. (2008). An empirical examination of the acceptance behavior of hotel front office systems: An extended technology acceptance model. Tourism Management, 29(3), 500-513.
Lin, H-F., & Lee, G-G. (2006). Determinants of success for online communities: An empirical study. Behaviour and Information Technology, 25(6), 479-488.
Low, A. (2003). Research rules to live by: Eight strategies to ensure that students use an on-line database effectively. School Libraries in Canada, 22(4), 30-31. McGill, T. J., & Hobbs, V. J. (2008). How students and
instructors using a virtual learning environment perceive the fit between technology and task. Journal of Computer Assisted Learning, 24(3), 191-202.
Nelson, R.R., & Cheney, P.H. (1987). Training end users: An exploratory study. MIS Quarterly, 11(4), 547-559. Ozkan, S., Koseler, R., & Baykal, N. (2009). Evaluating
learning management systems: Adoption of hexagonal e-learning assessment model in higher education.
Transforming Government: People, Process, and Policy, 3(2), 111-130.
Park, N., Roman, R., Lee, S., & Chung, J. E. (2009). User acceptance of a digital library system in developing countries: An application of the technology acceptance
model. International Journal of Information
Management, 29(3), 196-209.
Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3), 236-263.
Raymond, L. (1988). The impact of computer training on the attitudes and usage behavior of small business managers. Journal of Small Business Management, 26(3), 8-13.
Roca, J. C., Chiu, C-M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model.
International Journal of Human Computer Studies, 64(8), 683-696.
Rouibah, K., Hamdy, H. I., & Al-Enezi, M. Z. (2009). Effect of management support, training, and user involvement on system usage and satisfaction in Kuwait. Industrial Management and Data Systems, 109(3), 338-356.
Sabherwal, R., Jeyaraj, A., & Chowa, C. (2006). Information system success: Individual and
organizational determinants. Management Science, 52(12), 1849-1864.
Santhanam, R., & Sein, M. K. (1994). Improving end-user proficiency: Effects of conceptual training and nature of interaction. Information Systems Research, 5(4), 378-399. Schaupp, L. C., Bélanger, F., & Fan, W. (2009). Examining the success of websites beyond e-commerce: An extension of the IS success model. Journal of Computer Information Systems, 49(4), 42-52.
Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8(3), 240-253.
Shachak, A. & Fine, S. (2008). The effect of training on biologists acceptance of bioinformatics tools: A field experiment. The Journal of American Society for Information Science and Technology, 59(5), 719-730. Shih, H. (2004). Extended technology acceptance model of
Internet utilization behavior. Information & Management, 41(6), 719-729.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991).
Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124-143.
Thomsett-Scott, B., & May, F. (2009). How may we help you? Online education faculty tell us what they need from libraries and librarians. Journal of Librarian Administration, 49(1-2), 111-135.
Thong, J. Y. L., Hong, W., & Tam, K-Y. (2002). Understanding user acceptance of digital libraries: What are the roles of interface characteristics, organizational context and individual differences? International Journal of Human Computer Studies, 57(3), 215-242.
Thong, J. Y. L., Hong, W., & Tam, K-Y. (2004). What leads to user acceptance of digital libraries?
Communications of the ACM, 47(11), 79-83.
Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of intrinsic motivation.
MIS Quarterly, 23(2), 239-260.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
Wang, Y-S. (2008). Assessing e-commerce systems success: A respecification and validation of the DeLone and McLean model of IS success. Information Systems Journal, 18(5), 529-557.
10 Wang, Y-S., Wang, H-Y., & Shee, D. Y. (2007). Measuring
e-learning systems success in an organization context: Scale development and validation. Computers in Human Behavior, 23(4), 1792-1808.
Yen, C-H., & Lu, H-P. (2008). Effects of e-service quality on loyalty intention: An empirical study in online auction. Managing Service Quality, 18(2), 127-146.
APPENDIX
1. What is your gender? 2. What year are you in?
3. Are you a first semester transfer student? 4. What is your major or intended major? 5. Perceived Ease of Use
• I find it easy to use the Libraries’ Web portal to find the information I need online.
• The organization of information on the Libraries’ Web portal is easy to understand.
• The Libraries’ Web portal is easy to navigate. 6. Perceived Usefulness
• Using the University Libraries’ website provides me with information that would lead to better research.
• Using the Libraries’ Web portal makes it easier for me to do my assignments and prepare for examinations.
• Using the University Libraries’ Web portal
increases my academic performance.
• Using the Libraries’ Web portal increases my productivity.
7. Information Quality
• The Libraries’ Web portal provides sufficient information to accomplish your task.
• The Libraries’ Web portal provides accurate information.
• The Libraries’ Web portal provides up-to-date information.
• The Libraries’ Web portal provides timely
information.
• The Libraries’ Web portal provides information that is helpful.
8. System Quality
• The Libraries’ Web portal is always available.
• The Libraries’ Web portal displays information quickly.
• Steps to complete a task in the Libraries’ Web portal follow a logical sequence.
•
Layout of the Libraries’ Web portal is clear and consistent.9. Service Quality
• The Libraries’ Web portal provides quick
responses to library service requests I make.
• The Libraries’ Web portal has a good interface to communicate my needs.
• It is easy to get online assistance when I have trouble finding information using the Libraries’ Web portal.
10. Satisfaction
• The Libraries’ Web portal is efficient.
• The Libraries’ Web portal is effective.
• Overall I am satisfied with the Libraries’ Web portal.
11. How often do you use the University Libraries’ Web portal for each of the following purposes?
• Fact finding
• Assignments
• In-depth research
• Transactions (e.g., placing an online request for interlibrary loan)
• Communications (e.g., using e-mail, Instant Messenger for research assistance)
12. How many times per week do you use the University Libraries’ Web portal?
13. How many hours per week do you use the University Libraries’ Web portal?
14. How often do you use the University Libraries’ Web portal to perform each of the following tasks?
• Find books on a specific topic
• Find journals in print and electronic formats
• Find full-text journal articles
• Retrieve readings on electronic reserve
• Look up an online encyclopedia or dictionary
• Sign up for training courses provided by the Interactive Media Center
• Renew books online
• Have the Libraries scan an article and deliver it to you electronically
• Look up library hours
• Use IM to ask a research question
