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To provide a review of the log analysis studies of use and users of scholarly electronic journals.

The advantages and limitations of log analysis are described and then past studies of e‐journals' use and users that applied this methodology are critiqued. The results of these studies will be very briefly compared with some survey studies. Those aspects of online journals' use and users studies that log analysis can investigate well and those aspects that log analysis can not disclose enough information about are highlighted.

The review indicates that although there is a debate about reliability of the results of log analysis, this methodology has great potential for studying online journals' use and their users' information seeking behaviour.

This paper highlights the strengths and weaknesses of log analysis for studying digital journals and raises a couple of questions to be investigated by further studies.

The purpose of this paper is to demonstrate a novel form of deep log analysis by linking questionnaire data with transactional server log data generated by the same users; and to provide a richer understanding of the information‐seeking behaviour of a strategic community of virtual scholars.

Usage statistics were obtained from logs for an 18‐month period: 16,865 sessions were covered and 110,029 pages were viewed. Searching behaviour was studied in regard to number of returned hits and number of searches in a session. A questionnaire survey was also conducted to identify ScienceDirect users according to the subject/discipline to which they belonged and attitude towards some scholarly communication issues. The answers of more than 750 ScienceDirect users to the questionnaire were linked to the usage logs of the same users through matching internet protocol (IP) addresses.

The study reveals large differences between scholars in different subjects in terms of information‐seeking behaviour and their interaction with electronic journal systems.

The findings can be utilised to improve electronic journal systems such as ScienceDirect in order to provide more suitable service for users in different subjects.

The originality of the paper lies in its methodology that links questionnaire attitudinal data to the web log data of the same users at individual level to gain a better understanding of users' behaviour.

This study explored spatial usage of a public library based on activity logs produced by real users. The purpose of this paper is to provide preliminary data for decision-making when establishing the library operation policy.

To achieve the goal, the author collected a variety of data including 274,242 seat reservations logs, 3,361,284 collection usage logs, and 96,098 user information for the four years in which the National Library of Korea, Sejong actually operated. The crawled data were analyzed statistically in terms of demography, month, day of week, time of day and room by room. The author conducted additional in-depth analysis according to the external factors such as weather or social demographic environment. Finally, the author discussed several issues and verified feasibility of the proposals to support decision-making in operating a library in conclusion with a secondary librarian interview.

The usage rate in all the spaces of the National Library of Korea, Sejong, has been increasing since its opening, and, in particular, the usage rate increases sharply in January, February, July and August. In addition, the usage rate during weekends was higher than that during weekdays, and all the four spaces had a high usage rate during the afternoon. These results seem to be related to weather, users’ life pattern, users’ age, and position of PCs and seats. Based on the circulation logs analysis of children’s collections, users in their 10s and 40s showed the same space usage pattern.

This study has significance in that it attempted to analyze logs produced by real users during the actual library operation period, which has not been frequently attempted in the previous studies on libraries. The findings will be provided as basic data to support decision-making for efficient operation of libraries.

The paper seeks to emphasize the necessity of evaluating the library resources in terms of their quality, cost benefit and usefulness.

In the context of subscribing to the latest e‐journal databases in university libraries, different types of usage studies are discussed, including the recent application of usage log data or vendor reports. The genesis, standardization of usage reports and the significance of COUNTER statistics in establishing the usefulness of the e‐journals are described. The use of various electronic databases by the University of Hyderabad academic community is referred to according to these statistics/reports, mentioning the way in which it is helpful to university library in assessing their actual usage and usefulness.

The paper highlights the application of usage reports by the university library in decision making during renewals/subscriptions, i.e. the selection of databases, upgrading the versions, increasing licences, cancellation of subscriptions, etc.

All in all, it is established that the usage reports are to be taken as a support to library decision‐making activity, since it reflects the true value of e‐journals/databases.

This study provides necessary direction to library management regarding the utilization of log data for assessing the true value of e‐journals/databases. Thus the usage statistics can be studied and this analysis will invariably support the complex decision‐making activity of serials management in university libraries.

The purpose of this paper is to present data that begin to detail the deficiencies of log file analytics reporting methods that are commonly built into institutional repository (IR) platforms. The authors propose a new method for collecting and reporting IR item download metrics. This paper introduces a web service prototype that captures activity that current analytics methods are likely to either miss or over-report.

Data were extracted from DSpace Solr logs of an IR and were cross-referenced with Google Analytics and Google Search Console data to directly compare Citable Content Downloads recorded by each method.

This study provides evidence that log file analytics data appear to grossly over-report due to traffic from robots that are difficult to identify and screen. The study also introduces a proof-of-concept prototype that makes the research method easily accessible to IR managers who seek accurate counts of Citable Content Downloads.

The method described in this paper does not account for direct access to Citable Content Downloads that originate outside Google Search properties.

This paper proposes that IR managers adopt a new reporting framework that classifies IR page views and download activity into three categories that communicate metrics about user activity related to the research process. It also proposes that IR managers rely on a hybrid of existing Google Services to improve reporting of Citable Content Downloads and offers a prototype web service where IR managers can test results for their repositories.

In the digital library era, library websites are recognized as the extension of library services. The usability and findability of library websites are growing more and more important to patrons. No matter how these websites have been built, they should offer the capability that patrons can find their required information quickly and intuitively. The website logs keep tracks of users' factual behaviors of finding their required information. Based on the evidences, the author attempts to reconstruct the websites to promote their internal findability.

In the past, the card sorting method has generally been applied to reconstruct websites to improve their internal findability. Alternately, in this research, a first attempt is made to try to use website log data to implement website reconstruction. The website log data was cleaned and user sub‐sessions were extracted according to their respective critical time of session navigation. Each sub‐session's threshold time of target page was then calculated with different weights to determine its navigating parent pages. The different weighted parent pages were utilized to reconstruct various websites. A task‐oriented experiment of four tasks and 25 participants was conducted to measure the effects of findability between the constructed websites.

By analysis of the variance of time to complete the tasks, it is shown that the reconstructed websites have better findability performance in the time spent to complete the tasks than the current one, if focusing much more on the target pages. The result clearly explores that when the parent pages of a page are selected, whether it is a target page is the most important issue to improve website findability. The target page plays a critical role in website reconstruction. Furthermore, the traditional card sorting method is applied to the case website to reconstruct it. The findability experiment is then conducted and its time to complete the tasks is compared to those of websites that are reconstructed. The approach proposed here has better effects than card sorting.

Mining web log data to discover user behaviors on the library website, this research applies a heuristic method to analyze the data collected to reconstruct websites. Focusing on the target pages, the reconstructed websites will have better findability. Besides traditional card sorting techniques, this paper provides an alternative way to reconstruct websites such that users can find what they need more conveniently and intuitively.

This paper examines the general value to users of a range of electronic journal functions and their usefulness in the specific context of the SuperJournal Project. For the evaluation of each of the functions three types of data were analysed in relation to each other and in light of other contextual data: logged data of usage, survey data on user satisfaction, and survey data on the perceived importance of the function. The analysis shows that basic browsing, printing and search make up the core functions of electronic journals; other functions, such as saving of bibliographic data, alerting, customising, links with external resources and communication, serve as peripheral functions. The usefulness of both the core functions and the peripheral functions in a specific service is influenced by various implementation factors. However, it is the realised usefulness of the core functions which determines the use of a service.

Interest is currently growing in open social learner modeling (OSLM), which means making peer models and a learner's own model visible to encourage users in e-learning. The purpose of this study is to examine students' views about the OSLM in an e-learning system.

This case study was conducted with 40 undergraduate students enrolled in advanced programming and database management system courses. A Likert-type questionnaire and open-ended questions were used to obtain the students' views. System usage data were also analyzed to ensure the richness and diversity of the overall data set.

The quantitative data of the students' views were analyzed with descriptive statistics; the results are presented as graphics. The qualitative data of the students' views were examined by content analysis to derive themes. These themes are organized into four subtopics: the students' positive views, their negative views, their improvement suggestions and their preferences about using similar OSLM visualizations in other e-learning systems. The students' subjective views are discussed in the context of their recorded interactions with the system.

Competition due to seeing peer models was considered by participants both as positive and negative features of the learning system. So, this study revealed that, the ways to combine peer learner models to e-learning systems that promote positive competition without resulting social pressure, still need to be explored.

By combining open learner models with open peer models, OSLM enhances the learning process in three different ways: it supports self-regulation, encourages competition and empowers self-evaluation. To take advantage of these positive contributions, practitioners should consider enhancing e-learning systems with both own learner and peer model features.

Despite increasing interest in OSLM studies, several limitations and problems must be addressed such as sparsity of data and lack of study of different contexts and cultures. To date, no published study in this area exists in Turkey. The purpose of this study is to fill this gap by examining OSLM features in an e-learning system from the perspectives of Turkish students by using both their system interaction data and their subjective views.

The purpose of this paper is to highlight the importance of quantitative and qualitative analysis of the usage of e‐resources in academic libraries. It also describes various studies undertaken to study the users' behavior and attitude towards e‐journals.

The paper provides a comprehensive review of the recent published literature on the importance of the usage statistics of e‐resources subscribed to by the academic libraries.

The findings show that the usage statistics help in studying and evaluating the users' behavior in an online environment. The library services can be extended and modified, to reflect user interests suiting the users the most, in the light of the evaluation and analyses done.

The paper has pertinence and wider implications for library staff engaged in providing e‐resources' services to readers.

The purpose of this study was to better understand K-12 district leaders' reasoning and processes for selecting and deploying EdTech instructional products, including which, if any, types of data are used to support decision-making.

This multisite case study of educational technology (EdTech) decision-making comprises five purposely selected districts at the leading edge of EdTech innovation. The unit of analysis was a recent purchase they had made of an instructional, classroom-oriented digital product (defined as a product used by teachers and/or students in the classroom for the purposes of student learning). The key leader heading up the purchase was interviewed, as were other leaders and a teacher who were involved in the decision-making process.

The processes districts used to make their purchasing decisions involved teachers, district leaders and technical specialists who considered usability, usage data and alignment with student learning and interoperability, respectively. While in some cases there were plans to collect data on student learning outcomes, districts did not uniformly emphasize that in their decision-making processes. Instead, the type of educational technology tool that was purchased influenced whether or not districts planned to seek out student-level outcome data as evidence of the product's efficacy. For the purchases associated with access to content, school leaders considered usage or log data generated by the program itself as sufficient indication that the program is “working.” Where the software's functionality encompassed skill development, leaders stated future plans to look at student-level outcomes as a means for judging if the program “worked.”

Few accounts of district decision-making about the adoption of educational technology innovations are present in the literature. These five cases provide insight into the role evidence plays in decisions to adopt educational technology.