AI for Research Productivity
With Integrity
Program Overview
This professional learning program introduces educators to the essentials of educational research, including its purposes, types, and the use of existing evidence. Participants will build the knowledge and skills needed to design and conduct their own action research projects within their classrooms or schools. Through practical tools, ethical inquiry, collaborative problem-solving, and reflective engagement, the program supports school-based improvement and empowers educators to lead change in context.
Who is this for?
- Educators and researchers across disciplines seeking to integrate AI ethically and responsibly throughout the research process.
- Graduate students and early-career academics developing AI-supported research competencies.
- Education leaders and policy makers interested in evidence-informed decision-making.
Partner With Us
- Schedule a consultation to discuss your organization's needs
- Explore flexible delivery options for your team or institution
- Request a customized program proposal and pricing
Modules at a glance
AI Basics, Prompting, and Planning
Through this module, participants are introduced to the fundamentals of artificial intelligence as they examine AI’s capabilities, limitations, and ethical implications. It covers how AI can be responsibly applied in academic inquiry, with an emphasis on maintaining integrity and transparency. Participants will also explore the principles of prompt design and structured planning, learning how to formulate effective interactions with AI to support research roadmaps aligned with disciplinary standards.
Literature Review, Research Questions, and Hypotheses
This module demonstrates how AI tools can support systematic and comprehensive literature reviews. Tools such as Elicit, consensus, Research Rabbit, and Scite will be introduced to help participants identify, map, and summarize scholarly work. These tools are then connected to the process of refining research questions and hypotheses, showing how AI-generated insights can inform conceptual frameworks while maintaining critical oversight and academic rigor. Participants will learn how to critically assess AI-supported search results, synthesize themes, and map scholarly debates.
Methodology and Data Collection
This module guides participants through the process of designing appropriate research methodologies that are both rigorous and contextually relevant. Tools such as Perplexity, Claude, and Gemini will be introduced with a focus on how they can assist in developing instruments such as surveys, interview protocols, or coding frameworks. Ethical safeguards and the mitigation of bias in data collection will also be addressed. The emphasis will be on aligning methods with research goals while critically addressing potential biases and ensuring participant protection.
AI in Support of Communication and Presentation
This module focuses on how AI can be applied to strengthen the clarity, rigor, and impact of research dissemination. Participants will explore tools such as Napkin AI and Canva for generating data visualizations, and others for refining academic writing, and structuring arguments in ways that enhance accessibility and engagement. Emphasis is placed on ensuring that AI-supported outputs meet scholarly standards, preserve the researcher’s voice, and communicate findings in ways that advance both academic discourse and professional practice.
Our programs are offered on a
business-to-business basis
tailored to meet each organization’s unique needs. We invite institutions and partners to explore our offerings and reach out to discuss customized options. We also design new programs to address specific goals and emerging priorities.
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