A Framework for Evaluating Digital Library Services

Choudhury, Sayeed; Hobbs, Benjamin; Lorie, Mark; Flores, Nicholas E.

doi:10.1045/july2002-choudhury

Cited by 32 publications

(26 citation statements)

References 16 publications

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“…This is to allow the evaluator the flexibility to decide on this according to their needs and research constraints. There are a variety of frameworks for digital library evaluation [19,[20][21][22][23][24][25][26], but all fall short of impact evaluation such as that presented by the model proposed. The key emphasis of most of these frameworks and their measures is on statistical measures e.g.…”

Section: Discussionmentioning

confidence: 99%

Impact-ED - A New Model of Digital Library Impact Evaluation

Madle

Kostkova

Roudsari

2008

Research and Advanced Technology for Digital Libraries

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Section: Discussionmentioning

confidence: 99%

Impact-ED - A New Model of Digital Library Impact Evaluation

Madle

Kostkova

Roudsari

2008

Research and Advanced Technology for Digital Libraries

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“…Previous considerations about possible connections between CAPM and LibQUAL+ TM , a methodology developed by the Association of Research Libraries (ARL) and Texas A&M University Libraries (Choudhury et al, 2002;Heath et al, 2003), also led to further contacts with ARL and other interested partners. As a result of these contacts a working plan was established to adapt the ProSeBiCA framework for U.S. libraries.…”

Section: Aims and Procedures Of The Prosebica Projectmentioning

confidence: 99%

ProSeBiCA: development of new library services by means of conjoint analysis

Hermelbracht¹,

Koeper

2006

Library Hi Tech

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Purpose: Description of the project ProSeBiCA, carried out in order to adapt the marketing research tool Conjoint Analysis for the development of future library services. The paper describes the methodical approach, and provides an overview of the results gained by several user surveys. Design/methodology/approach: The methodical approach includes the use of Adaptive Conjoint Analysis (ACA) and Choice-Based Conjoint Analysis (CBC). Findings: Conjoint Analysis is an appropriate tool for the strategic development of library services. It provides detailed results by identifying users' preferences towards concrete services, and allows to deduce general statements about future trends for library services. Research limitations/implications:Future plans include cooperation with the Sheridan Libraries at Johns Hopkins University (Baltimore, Maryland), the Association of Research Libraries (ARL), and other interested partners in order to adapt the ProSeBiCA framework for U.S. libraries and to integrate techniques used by the partners (CAPM, LibQUAL+ TM ). The extension of Conjoint Analysis to the evaluation of services for a fee will be an additional area of research. Practical implications: Service orientation in libraries can be based on a systematic approach. Depending on local circumstances, interested libraries can improve their service orientation in different ways, either by discussing the results of the analysis made in this project or by using the Conjoint Analysis questionnaire for a survey in their institutions. Originality/value: The paper describes the current status and provides the latest results of ProSeBiCA. It is of interest to library managers and marketing researchers. Keywords: Information services, Market research, Surveys, Academic libraries, Germany Paper type: Research paper In the context of changing educational environments, current discussions about the strategic development of German academic libraries clearly show the need for a basic change in the way they see themselves. They need to evolve from mere academic institutions into service providers which actively design and offer services that fit users' needs and preferences. More and more customer take-up of library services is becoming a new quality standard that will have a significant effect on the status of libraries within universities, particularly in times of small budgets and growing autonomy in academia. In order to achieve this take-up, libraries need to establish and improve their customer relations, and above all they have to develop a profound knowledge of their users and their needs. But how can we get this knowledge in a systematic way? How can we get a clear idea of user preferences in order to shape future library services?The project ProSeBiCA, funded by the German Research Foundation (DFG) and carried out jointly by the Chair of Marketing at Bielefeld University and

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“…Big Data is described as a framework to predict future problems, future performance outcomes and prescribe solutions about academic programs, teaching, learning and research [8,20,21]. The growing research into Big Data in higher education has led to renewed interests in the use of analytics, virtual reality, augmented reality and other related fields [22][23][24][25].…”

Section: Big Data and Analytics In Educational Researchmentioning

confidence: 99%

Data Science Approach for Simulating Educational Data: Towards the Development of Teaching Outcome Model (TOM)

Ndukwe

Daniel

Butson

2018

BDCC

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Abstract:The increasing availability of educational data provides the educational researcher with numerous opportunities to use analytics to extract useful knowledge to enhance teaching and learning. While learning analytics focuses on the collection and analysis of data about students and their learning contexts, teaching analytics focuses on the analysis of the design of the teaching environment and the quality of learning activities provided to students. In this article, we propose a data science approach that incorporates the analysis and delivery of data-driven solution to explore the role of teaching analytics, without compromising issues of privacy, by creating pseudocode that simulates data to help develop test cases of teaching activities. The outcome of this approach is intended to inform the development of a teaching outcome model (TOM), that can be used to inspire and inspect quality of teaching. The simulated approach reported in the research was accomplished through Splunk. Splunk is a Big Data platform designed to collect and analyse high volumes of machine-generated data and render results on a dashboard in real-time. We present the results as a series of visual dashboards illustrating patterns, trends and results in teaching performance. Our research aims to contribute to the development of an educational data science approach to support the culture of data-informed decision making in higher education.

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A Framework for Evaluating Digital Library Services

Cited by 32 publications

References 16 publications

Impact-ED - A New Model of Digital Library Impact Evaluation

Impact-ED - A New Model of Digital Library Impact Evaluation

ProSeBiCA: development of new library services by means of conjoint analysis

Data Science Approach for Simulating Educational Data: Towards the Development of Teaching Outcome Model (TOM)

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