Training Course on Advanced E-resource Assessment and Usage Analytics

Training Course on Advanced E-resource Assessment and Usage Analytics

Introduction

In today's dynamic information landscape, libraries and information centers are increasingly reliant on electronic resources (e-resources) to meet the evolving needs of their users. Effectively assessing the value and impact of these digital assets is paramount for informed decision-making, strategic resource allocation, and demonstrating return on investment. Training Course on Advanced E-resource Assessment and Usage Analytics equips professionals with the essential knowledge and practical skills to navigate the complexities of e-resource evaluation. Participants will delve into sophisticated methodologies for collecting, analyzing, and interpreting usage data, ultimately enabling them to make data-driven decisions that optimize resource collections, enhance user experience, and demonstrate the library's vital contribution to their institution's goals. Mastering data-driven librarianship through a deep understanding of usage patterns and assessment techniques is no longer a luxury but a necessity for thriving in the digital age.

This intensive program goes beyond basic statistics, exploring advanced analytical tools and techniques to uncover actionable insights from e-resource usage. By focusing on practical application and real-world case studies, participants will gain hands-on experience in applying various assessment methods and visualizing data to communicate findings effectively. The course emphasizes the importance of aligning e-resource assessment with institutional objectives, demonstrating the library's value proposition through evidence-based decision-making. Participants will learn to identify key performance indicators (KPIs), conduct in-depth analysis of vendor-supplied data, and implement strategies for continuous improvement of their e-resource collections. This training fosters a culture of data literacy within the library, empowering staff to become strategic partners in resource management and institutional success.

Course Duration

5 days

Course Objectives

Upon completion of this training course, participants will be able to:

1. Master advanced techniques for e-resource usage data collection and management.
2. Apply sophisticated statistical methods for in-depth usage analysis and interpretation.
3. Utilize various data visualization tools to effectively communicate assessment findings.
4. Evaluate the strengths and limitations of different e-resource assessment methodologies.
5. Identify and track key performance indicators (KPIs) relevant to e-resource performance.
6. Conduct comparative analysis of usage data across different platforms and resources.
7. Integrate qualitative and quantitative data for a holistic understanding of e-resource impact.
8. Develop strategies for demonstrating the return on investment (ROI) of e-resource collections.
9. Align e-resource assessment practices with institutional goals and strategic priorities.
10. Utilize vendor-supplied usage reports effectively and identify potential data inconsistencies.
11. Implement user surveys and feedback mechanisms to inform e-resource assessment.
12. Apply ethical considerations and best practices in the collection and use of usage data.
13. Create actionable reports and presentations to communicate e-resource value to stakeholders.

Organizational Benefits

• Data-driven insights enable informed decisions about subscription renewals, cancellations, and new acquisitions, optimizing budget utilization.
• Understanding usage patterns helps tailor collections to user needs, leading to increased satisfaction and engagement.
• Robust assessment data provides evidence of the library's contribution to institutional goals, strengthening its position within the organization.
• Streamlined assessment processes and effective use of analytics tools save staff time and resources.
• A thorough understanding of usage data empowers libraries to negotiate more effectively with e-resource providers.
• Usage analytics informs strategic planning for collection development and service delivery.
• Evidence-based reports support advocacy efforts for library resources and funding.
• Ongoing assessment fosters a culture of continuous improvement in e-resource management.

Target Audience

1. Collection Development Librarians
2. Electronic Resources Librarians
3. Reference Librarians
4. Library Directors and Administrators
5. Assessment Librarians
6. Data Services Librarians
7. Information Specialists
8. Library and Information Science Educators

Course Outline

Module 1: Foundations of E-resource Assessment

• Understanding the e-resource landscape and its evolution.
• Identifying key stakeholders and their information needs.
• Exploring different types of e-resources and their unique assessment considerations.
• Defining the purpose and scope of e-resource assessment within the organizational context.
• Case Study: Analyzing the impact of a journal cancellation based on initial usage data at a university library.

Module 2: Data Collection and Management for Usage Analytics

• Navigating vendor-supplied usage statistics (COUNTER, SUSHI).
• Implementing local data collection methods (e.g., access logs, authentication data).
• Understanding data privacy and ethical considerations in data collection.
• Utilizing tools and techniques for data cleaning and preparation.
• Case Study: Identifying and resolving inconsistencies in COUNTER reports from different vendors at a consortium.

Module 3: Advanced Techniques for Usage Data Analysis

• Applying descriptive statistics to summarize usage patterns.
• Exploring inferential statistics for drawing conclusions from usage data.
• Conducting trend analysis and forecasting future usage.
• Implementing cohort analysis to understand user behavior over time.
• Case Study: Using regression analysis to identify factors influencing database usage in a public library.

Module 4: Data Visualization and Reporting

• Selecting appropriate visualization techniques for different types of data.
• Using tools for creating effective charts, graphs, and dashboards.
• Developing compelling reports for various stakeholders (administrators, faculty, users).
• Communicating assessment findings clearly and concisely.
• Case Study: Creating an infographic to showcase the impact of e-resources on research output at a special library.

Module 5: Qualitative Assessment Methods

• Designing and conducting user surveys and focus groups.
• Analyzing qualitative data to understand user perceptions and needs.
• Integrating qualitative findings with quantitative usage data.
• Using usability testing to evaluate e-resource interfaces.
• Case Study: Conducting a user survey to understand satisfaction with a new e-book platform at a college library.

Module 6: Return on Investment (ROI) and Impact Evaluation

• Identifying relevant metrics for demonstrating ROI.
• Calculating the cost-effectiveness of e-resource subscriptions.
• Measuring the impact of e-resources on research, teaching, and learning outcomes.
• Developing strategies for articulating the library's value proposition.
• Case Study: Calculating the ROI of a key database subscription based on its contribution to faculty publications and student research.

Module 7: Aligning Assessment with Institutional Goals

• Understanding the strategic priorities of the parent organization.
• Identifying how e-resource assessment can support institutional objectives.
• Developing assessment plans that align with institutional reporting requirements.
• Collaborating with other departments to demonstrate the library's impact.
• Case Study: Aligning e-resource assessment with a university's strategic goal of enhancing research productivity.

Module 8: The Future of E-resource Assessment and Usage Analytics

• Exploring emerging trends in usage data and analytics.
• Understanding the role of artificial intelligence and machine learning in assessment.
• Adapting assessment strategies to new types of digital resources.
• Building a culture of continuous assessment and improvement.
• Case Study: Discussing the potential application of AI-powered tools for predictive analytics in e-resource management.

Training Methodology

This training course will employ a blended learning approach, incorporating:

• Interactive lectures and presentations
• Hands-on exercises and practical application of tools
• Group discussions and collaborative problem-solving
• Real-world case studies and examples
• Individual and group assignments
• Access to online resources and materials

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.