The integration of digital technologies is revolutionizing the
instructional and research landscapes.
We have unprecedented opportunities for collaboration and
intellectual inquiry.
Generative AI offers an additional tool to help with instruction,
research, collaboration, and inquiry, especially with respect to an
understudied area of science and scholarship:
problem-finding (especially for ill-defined
problems)
Motivation
Why is a focus on problem-finding important?
Whole disciplines are dedicated to problem-solving but part
of getting an education and part of being a great researcher is being
able to ask good questions.
The role of outstanding scientists in influencing younger associates
is repeatedly emphasized in the interviews with [Nobel] laureates.
Almost invariably they lay great emphasis on the importance of
problem-finding, not only problem-solving (Merton, 1968/1973,
p. 453).
Merton, Robert K. (1968/1973). The Matthew Effect in Science. In N.
W. Storer (Ed.), The Sociology of Science: Theoretical and Empirical
Investigations (pp. 439–459). University of Chicago Press.
Motivation
Why is a focus on problem-finding important?
The formulation of a problem is often more essential than its
solution, which may be merely a matter of mathematical or experimental
skill (Einstein & Infeld, 1938, p. 92, as cited in Abdulla &
Cramond, 2018, p. 198).
And:
Despite its theoretical and practical importance, it is surprising
that PF [problem-finding] has received little attention … (Abdull &
Cramond, 2018, p. 200).
Abdulla, A. M., & Cramond, B. (2018). The creative problem
finding hierarchy: A suggested model for understanding problem finding.
creativity. Theories – Research - Applications, 5(2), 197–229.
https://doi.org/10.1515/ctra-2018-0019
Einstein, A., & Infeld, L. (1938). The evolution of
physics. New York: Simon & Schuster.
Discursive
Generative AI, as a chat bot, offers a way to
develop problem-finding methodologies using discursive reasoning.
I define and use the term discursive in two ways:
In education: types of teaching methods that involve
dialogue, discussion, or other forms of discourse to
facilitate learning
In philosophy: a type of reasoning that proceeds
through argumentation and debate
e.g., Socratic method
Socratic method: Problem-finding
For example, through dialogue, discussion, argumentation, and debate,
the Socratic method can be used to:
Identify assumptions
Raise question
Explore alternatives
Refine a problem
Expose contradictions
Engage in collective inquiry
Reach a conclusion or identify further questions
Motivation
But what’s the problem I am responding to?
Instructor: Ask ChatGPT how to think about X problem.
Student asks one question and then stops.
Discursive, Learning, and Problem-Finding
Why discursive?
To promote independent learning and exploration. To learn how to ask
good questions through dialogue, discussion,
argumentation, and debate.
Generative AI chat bots are chat (conversation)
centered.
Discursive, Learning, and Problem-Finding
Why discursive?
Student led discursive practices may foster independent, critical
thinkers
To the extent that knowledge acquisition and academic performance are
the goals, teacher-controlled methods of students’ active learning are
superior–especially for younger students and in well-structured subject
domains. In contrast, if the goal is to help students to “learn to
become independent thinkers and learners rather than
simply become able to perform basic computations and retrieve simple
knowledge and facts” […], then methods in which students have
opportunities to learn more independently, to identify, define, and
solve problems in different ways, and to use acquired insights
to overcome other tasks are more likely to be successful (Weinert &
Helmke, 1995, p. 141).
Weinert, F., & Helmke, A. (1995). Learning from wise Mother
Nature or Big Brother Instructor: The wrong choice as seen from an
educational perspective. Educational Psychologist, 30. doi: https://doi.org/10.1207/S15326985EP3003_4
Problem-Finding
Because problem-finding is important to learning and to
science,
Because discursive practices help us problem-find,
Because generative AI can be used as a discursive agent (i.e., chat
bot),
Then we have the opportunity to develop methodologies to using
generative AI as a problem-finding tool.
As an example, I used ChatGPT to problem-find a framework for
problem-finding.
Let’s begin.
ChatGPT: Articulating a Problem
Interactions with ChatGPT have been abbreviated.
I asked: What are some approaches to articulating a problem that can
be applied in instruction and research?
Curiosity-driven research
Gap in existing knowledge
Applied needs
Interdisciplinary approaches
Funding and resources
Social and ethical concerns
Technological advances
Peer and mentor suggestions
Policy and regulation
Competitive edge
Personal interest or experience
ChatGPT: Narrowing to a Research Question
I followed up with: What are some approaches to refining a research
question?
Consultation and feedback
PICO(T) framework
The ‘So what?’ test
The FINER Criteria
The ‘Vice’ criteria
The ‘Smart’ criteria
Iterative refinement
Gap analysis
Interdisciplinary collaboration
Hypothesis-driven
Data driven
Ethical considerations
Real-world applicability
Pilot studies
ChatGPT: Consultation and Feedback Approach
I focused on one answer: How might consultation and
feedback help refine a research question?
Feedback from experts
Mentorship and advising
Interdisciplinary collaboration
Workshops and seminars
Pilot testing
Iterative process
Ethical review
Public or stakeholder input
Online forums and social media
ChatGPT: Engagement
I asked for more refinement: What are methods and strategies to
maximize the effectiveness of a conversation or brainstorming session to
refine a research question?
Preparation
Background research
Agenda
Structure
Time management
Moderator
Inclusivity
Diverse perspectives
Equal participation
Techniques
SWOT analysis
Mind mapping
Probing questions
ChatGPT: Engagement (cont.)
Documentation
Real-time notes
Whiteboard or digital tools
Critical thinking
Devil’s advocate
Ranking and voting
Ethical and practical considerations
Ethical review
Feasibility check
Follow-up
Action items
Feedback loop
Reflection
Meeting Summary
ChatGPT: Develop a Framework Based on Prior Response
Based on the prior responses, I asked ChatGPT to develop a framework
and to present it in tabular form.
ChatGPT: Develop a Framework Based on Prior Response
Phase
Strategy
How to Engage Generative AI (e.g., ChatGPT)
Preparation
Background Research Agenda
Feed the AI summaries or key points from existing literature to set
the context.
Clearly state your objectives for the AI session.
Structure
Time Management Moderator
Decide in advance how long you’ll engage with the AI and what topics
you’ll cover.
You’ll act as the moderator, guiding the AI through the discussion
topics you’ve outlined.
Inclusivity
Diverse Perspectives Equal Participation
While AI doesn’t offer diverse “personal” perspectives, it can
generate a range of ideas based on its training data.
Ensure that all generated ideas are considered.
Techniques
SWOT Analysis Mind Mapping Probing Questions
Ask the AI to list potential Strengths, Weaknesses, Opportunities,
and Threats for your initial research question.
Use the AI to generate related terms or questions, which you can
then organize into a mind map.
Use the AI to generate probing questions that could help refine your
research question further.
Documentation
Real-time Notes Whiteboard or Digital Tools
Keep a record of the AI’s suggestions and your own thoughts as you
go along.
Copy and paste the AI’s suggestions into a digital whiteboard or
note-taking app.
Critical Thinking
Devil’s Advocate Ranking and Voting
Ask the AI to generate counterarguments or criticisms of your
initial research question.
Ask the AI to generate a list of refined questions, which you can
then rank or vote on yourself or with your team.
Ethical and Practical Considerations
Ethical Review Feasibility Check
While the AI may not provide ethical guidance, it can generate a
list of ethical considerations you should be aware of.
Ask the AI for potential challenges or limitations related to your
research question.
Follow-up
Action Items Feedback Loop
Use the AI to help list next steps based on the discussion.
Return to the AI for additional sessions as you refine your question
further.
Reflection
Meeting Summary
After the session, review the AI-generated content and your own
notes to create a summary.
ChatGPT: Create the Study
I asked ChatGPT to write up a description of a study that could test
how the framework works as a problem-finding strategy.
Study Title
“AI-Enabled Discursive Exchanges and Their Influence on Research
Conceptualization, Methodology, and Epistemic Limitations in
Undergraduate STEM Research”
Objectives
To investigate how AI-enabled discursive exchanges influence the
conceptualization and elaboration of research topics.
To identify patterns in these discussions that can be harnessed to
refine research methodologies.
To explore the limitations and challenges posed by such
interactions, especially concerning the epistemic nature of AI.
ChatGPT: Create the Study
Participants
Undergraduate students enrolled in STEM programs.
Methodology
Phase 1: Preparation
Background Research: Students will be provided with
literature on AI-enabled research methodologies and discursive
exchanges.
Agenda: An introductory workshop will set the
objectives and agenda for the study.
Phase 2: Structure
Time Management: The study will span one semester,
with bi-weekly check-ins.
Moderator: A research assistant will guide the AI
sessions and discussions.
ChatGPT: Create the Study
Phase 3: Inclusivity
Diverse Perspectives: Students from various STEM
disciplines will be included.
Equal Participation: All students will be
encouraged to engage equally with the AI and in group discussions.
Phase 4: Techniques
SWOT Analysis: Students will perform a SWOT
analysis on their initial research questions using AI.
Mind Mapping: AI will assist in generating mind
maps for each research topic.
Probing Questions: AI will generate probing
questions to help students refine their research questions.
ChatGPT: Create the Study
Phase 5: Documentation
Real-time Notes: A research assistant will document
all AI sessions and discussions.
Whiteboard or Digital Tools: Students will use
digital tools to jot down AI-generated ideas.
Phase 6: Critical Thinking
Devil’s Advocate: AI will generate counterarguments
to challenge the students’ research questions.
Ranking and Voting: Students will rank AI-generated
refined questions to identify the most promising ones.
ChatGPT: Create the Study
Phase 7: Ethical
and Practical Considerations
Ethical Review: An ethics board will review the
study design.
Feasibility Check: Students will assess the
feasibility of their refined research questions.
Phase 8: Follow-up
Action Items: Students will list next steps based
on their discussions with AI.
Feedback Loop: Students will have the option for
additional AI sessions to refine their questions further.
Phase 9: Reflection
Meeting Summary: Students will submit a summary
report of their experience and findings.
ChatGPT: Create the Study
Data Collection and Analysis
Transcripts of AI sessions
Student reports and mind maps
Bi-weekly check-in notes
Final summary reports
Expected Outcomes
A better understanding of how AI can influence research
conceptualization and methodology.
Identification of patterns that can be harnessed for research
refinement.
Insight into the limitations and challenges posed by AI-enabled
discursive exchanges.
ChatGPT: Conclusion
Finally, I asked ChatGPT to summarize and provide some key takeaways
from our session:
Key Takeaways
Interdisciplinary Approach: Combining human
expertise with AI can lead to more refined and impactful research
questions.
Methodological Innovation: AI can be a valuable
tool in modern research methodology, aiding in everything from idea
generation to feasibility checks.
Ethical and Epistemic Considerations: While AI
offers many advantages, it’s crucial to consider its limitations,
especially concerning ethical and epistemic aspects.
Conclusion: Problem-Finding
Because problem-finding is important to learning and to
science,
Because discursive practices help us problem-find,
Because generative AI can be used as a discursive agent (i.e., chat
bot),
Then we have the opportunity to develop methodologies to using
generative AI as a problem-finding tool.