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This book showcases new interdisciplinary academic research on the relationship between information literacy and learning.It combines findings with new understandings drawn from theoretical and empirical research conducted in primary and secondary schools, higher education, workplaces, and community contexts.

The long-awaited 2nd edition of this best-selling research methods handbook is fully updated and includes brand new coverage of online research methods and techniques, mixed methodology and qualitative analysis.

The last 46 years have witnessed a deep and continued interest in information literacy. This interest has resulted in an extensive range of research being undertaken and a burgeoning corpus of literature created by academic researchers, library practitioners and other researchers who explore information literacy through their own disciplinary lens. The Qualitative Landscape of Information Literacy Research is a landmark publication that will develop and support readers' understanding of how information literacy research and teaching is framed, developed and produced. Written by a leading expert in the field, it introduces and describes the key approaches taken by qualitative researchers, identifying core and specialist methods, techniques and theories. In each chapter, examples will illustrate how theory, types of pedagogical frameworks, methods and tools have been used. Coverage includes: theory and key concepts of information literacy social theory framework and their application to information literacy research exploration of the pedagogical frameworks that inform information literacy a range of qualitative methods that shape information literacy research data collection techniques research design. This book will be valuable to researchers in information literacy, students who are developing or undertaking research or simply interested in identifying approaches to information literacy and practitioners who want to investigate the practice of information literacy to create an evidence base to support information literacy in their workplaces or institutions.

Research is such an important subject for information professionals that there will always be a need for effective guides to it.Research skills are a prerequisite for those who want to work successfully in information environments, an essential set of tools which enable information workers to become information professionals.

Visual Research Methods: An Introduction for Library and Information Studies is the first book to focus on visual methods in LIS, providing a comprehensive primer for students, educators, researchers and practitioners in the field. Contributed chapters in the book showcase examples of VRM in action and offer the insights, inspirations, and experiences of researchers and practitioners working with visual methods.

Learning and teaching to program is an arduous task. It requires a lot of commitment, dedication, and passion from everyone involved. Programming courses have high dropout and failure rates. Throughout time, several educational research works have been carried out to study the different learning processes and characteristics of students. With this work, we present and describe our vision and model of teaching and learning of initial programming to minimize the problems. We present a technological tool, called HTProgramming (Help To Programming), which complements the teaching and learning process. This allows students to practice a wide variety of activities with immediate feedback, directly related to content and themes for learning programming. It allows the teacher to follow the whole process and students’ results. Using a machine-learning (neural network) predictive model of student failure, it will allow the teacher to anticipate possible student failure and act quickly. In this paper, we apply the Design Scientific Research Methodology to tackle teaching and learning difficulties to initial programming. We also include the results and evaluation of the application. Students consider the application an important tool for their learning process. The student failure prediction model presents very realistic values.

PurposeThe purpose of this research is to provide a framework in which new data quality dimensions are defined. The new dimensions provide new metrics for the assessment of lecture video indexing. As lecture video indexing involves various steps, the proposed framework containing new dimensions, introduces new integrated approach for evaluating an indexing method or algorithm from the beginning to the end.Design/methodology/approachThe emphasis in this study is on the fifth step of design science research methodology (DSRM), known as evaluation. That is, the methods that are developed in the field of lecture video indexing as an artifact, should be evaluated from different aspects. In this research, nine dimensions of data quality including accuracy, value-added, relevancy, completeness, appropriate amount of data, concise, consistency, interpretability and accessibility have been redefined based on previous studies and nominal group technique (NGT).FindingsThe proposed dimensions are implemented as new metrics to evaluate a newly developed lecture video indexing algorithm, LVTIA and numerical values have been obtained based on the proposed definitions for each dimension. In addition, the new dimensions are compared with each other in terms of various aspects. The comparison shows that each dimension that is used for assessing lecture video indexing, is able to reflect a different weakness or strength of an indexing method or algorithm.Originality/valueDespite development of different methods for indexing lecture videos, the issue of data quality and its various dimensions have not been studied. Since data with low quality can affect the process of scientific lecture video indexing, the issue of data quality in this process requires special attention.

The research in this paper adds to the discussion linked to the challenge of capturing and modeling tacit knowledge throughout software development projects. The issue emerged when modeling functional requirements during a project for a client. However, using the design science research methodology at a particular point in the project helped to create an artifact, a functional requirements modeling technique, that resolved the issue with tacit knowledge. Accordingly, this paper includes research based upon the stages of the design science research methodology to design and test the artifact in an observable situation, empirically grounding the research undertaken. An integral component of the design science research methodology, the knowledge base, assimilated structuration and semiotic theories so that other researchers can test the validity of the artifact created. First, structuration theory helped to identify how tacit knowledge is communicated and can be understood when modeling functional requirements for new software. Second, structuration theory prescribed the application of semiotics which facilitated the development of the artifact. Additionally, following the stages of the design science research methodology and associated tasks allows the research to be reproduced in other software development contexts. As a positive outcome, using the functional requirements modeling technique created, specifically for obtaining tacit knowledge on the software development project, indicates that using such knowledge increases the likelihood of deploying software successfully.

The importance of gaining insights into informal organizational structures for management purposes is acknowledged by both research and practice. However, “traditional” approaches to analyzing informal organizational social networks involve significant manual effort and do not scale for larger datasets. Enterprise Social Networks (ESN) have emerged as important tools for informal employee interactions, such as for problem-solving and information sharing. While the analysis of ESN back end data might provide insights into the informal fabric of organizations, and in particular employees’ roles in such networks, there is a lack of systematic approaches for carrying out ESN analytics, such as for user role identification. Following a design science research process, a process-based method to identify user roles from ESN data was developed and evaluated. The method’s efficacy is demonstrated through an in-depth application in a case study of Australian professional services firm Deloitte. In doing so the paper shows how ESN data can be utilized to derive metrics that characterize participation behavior, message content, and structural network positions of ESN users.

This paper presents the system architecture of a collaborative virtual environment in which distributed multidisciplinary teams involved in space exploration activities come together and explore areas of scientific interest of a planet for future missions. The aim is to reduce the current challenges of distributed scientific and engineering meetings that prevent the exploitation of their collaborative potential, as, at present, expertise, tools and datasets are fragmented. This paper investigates the functional characteristics of a software framework that addresses these challenges following the design science research methodology in the context of the space industry and research. An implementation of the proposed architecture and a validation process with end users, based on the execution of different use cases, are described. These use cases cover relevant aspects of real science analysis and operation, including planetary data visualization, as the system aims at being used in future European missions. This validation suggests that the system has the potential to enhance the way space scientists will conduct space science research in the future.