NEW: Module Series for Early Career Researchers

The ASIS&T Research Engagement Committee (REC) has developed a multi-part module series titled "Sharpening your Research Skills (SRS) Modules Series: Translating Research for Practice". This series provides actionable research knowledge, particularly aimed at practitioners, students, early career professionals, and those from developing countries. It aims to address a range of research training needs - from foundational skills to communicating with impact. Specifically, each module will address one or more the following:

Foundational Data Skills for Applied Research
Engaging Communities through Innovative Methods
Using AI Responsibly in Information Work
Navigating Ethics and Policy in Data-Driven Work
Communicating for Impact: From Data to Story

This series, which will be spread out over several session between September 2026 through April 2027, has the following pricing:

Single Module
- Members: $25/Module
- Non-members: $40/Module

All-Access Pass
- Members: $100
- Non-members: $175

These Modules can be viewed live or asynchronously at your own pace.
Click the button below to register for a single module or the All-Access Pass! Read more about each module below.

Module 1: Beyond Partnerships: Understanding Community Engagement as Learning, Inquiry, and Action

Date & Time: September 22 - 11 AM ET

Community engagement is often described through the language of partnerships, collaboration, and reciprocal relationships. While these concepts are essential, they do not fully explain how community-engaged research (CER) and community-engaged learning (CEL) create meaningful change. This module proposes an alternative perspective. Community engagement is fundamentally a democratic learning environment in which students, institutions, and communities collectively investigate complex problems, create knowledge, and translate learning into action.

Drawing on community-engaged research, participatory action research, knowledge democracy, and Black Studies, the module introduces a practical conceptual framework organized around three recurring dimensions of community-engaged practice: pedagogy, social investigation, and action. Participants will explore how this praxis operates across three interconnected learning spaces - student, institutional, and community learning - and why these forms of learning are central to community knowledge creation, democratic participation, and transformative action.

The module concludes by introducing knowledge infrastructure as a practical lens for understanding community-engaged practice. Community-engaged practice is both relational and infrastructural. Relationships create the conditions for trust, reciprocity, and shared inquiry. Knowledge infrastructures create the conditions for continuity, collective memory, learning, and coordinated action. Participants will explore how everyday artifacts, including meeting agendas, facilitation processes, community archives, documentation systems, AI tools, and evaluation frameworks, shape what communities can collectively learn, remember, and act upon.

Module 2: Using AI Responsibly in Information and Data Driven Work: Ethical Guidelines for Information Professionals or Responsible AI in Information Studies: Addressing Bias, Governance, and Trust in Data Systems

Date & Time: October

This module will equip Information researchers and practitioners with frameworks and practical tools to evaluate, design, and use AI Systems responsibly across the information lifecycle with attention to ethical guidelines, community impacts, and institutional accountability. Participants will examine the following:

The algorithmic and information bias in AI driven systems used for discovery, classification, analysis, and decision-making.
The implication of AI for data quality, access, representation and trust.
Ethical considerations for working with sensitive, personal, Indigenous, and culturally protected information.

Depending on the speakers, participants may consider discussions around Readiness Assessment Methodology (RAM) which includes a range of quantitative and qualitative questions designed to gather information about different dimensions related to AI information ecosystems, including the legal and regulatory, social and cultural, economic, scientific and educational, and technological and infrastructural dimensions or other assessment methodologies.

Module 3: From Data to Story: Communicating Societal Impact in Information and Library Research using Google NotebookLM

Date & Time: December 15 - 10 AM ET

This module will situate NotebookLM and similar tools within information workflow, emphasizing curation, context, provenance, and ethics. will guide Information Studies researchers and practitioners through the use of NotebookLM and comparable AI-supported tools to transform curated data, documents, and evidence into clear, ethical, and audience-appropriate impact narratives. Participants will learn how to structure information inputs, craft effective prompts, and critically evaluate AI-generated outputs to communicate societal impact while maintaining information integrity, transparency, and context. The session will also address ethical considerations, including data selection, source transparency, bias in AI-generated narratives, and the responsibilities of information professionals when using generative tools for public communication. Other data storytelling tools can be Columns, Tableau, MAXQDA or ATLAS.ti.

Module 4: Beyond Citations: Making Research Matter by Capturing Societal Impact

Date & Time: January TBD

Societal impact is a broad term that describes the impact of research outside academia. This module has been planned to enhance researchers’ understanding of the societal impact of research and its role in advancing communities, institutions, and public policy. By the end of the session, participants will be able to distinguish between academic and societal impact, identify pathways through which LIS research influences society, and apply practical strategies to design, measure, and communicate impact beyond publications and citations. Participants will gain the skills needed to integrate impact planning into research projects and effectively demonstrate the value of LIS research to stakeholders, funders, and the wider public.

Module 5: Mapping Scholarly Connections: Social Network Analysis of Academic Social Networking Sites

Date & Time: February TBD

Academic Social Networks generate rich data about research output, collaboration, and impact. This webinar will introduce data analysis techniques for exploring scholarly platforms such as ResearchGate, Academia.edu., and others. Participants will learn how Academic Social Networks data can be collected, analysed, and visualized to uncover collaboration patterns, research trends, and visibility indicators.

Module 6: From Opinions to Patterns: Application of Q Methodology in Library and Information Science Research

Date & Time: March 16 - 8 AM ET

This webinar aims to equip researchers with a practical and conceptual understanding of Q Methodology for studying subjectivity in information environments. By the end of the session, participants will be able to understand the philosophical foundations of Q methodology, design a Q study relevant to LIS problems, develop a concourse and Q-set, administer Q-sorting, and interpret factor analysis results meaningfully. The webinar will also demonstrate how Q methodology can be applied to explore users’ perceptions, professional attitudes, and policy issues in libraries. Participants will gain confidence in integrating Q methodology into their own research projects, enhancing both the depth and rigor of LIS inquiry.

Module 7: Critical Data Storytelling

Back to Inside ASIS&T, August 2026