How to Draft a Problem Statement with AI

In this blog, learn how to craft effective problem statements using AI tools. Explore the essential components—context, knowledge gap, and significance—with insights from Moxie’s Research Article Summarizer and Literature Review Matrix Analyzer. 

The problem statement is the heartbeat of a well-written dissertation. A well-written problem statement acts as the “North Star” of a dissertation – outlining the logic of the research and helping researchers stay true to their research agenda. A problem statement is a tightly woven argument that lays out three main aspects of a research problem (Merriam & Tisdell (2016). 

A good research problem statement commonly contains the following three  elements: 

  1. Context
  2. Gap in knowledge
  3. Significance

Problem statement elements as outlined by Merriam and Tisdell (2016). 

Each problem statement component rests upon a researcher’s knowledge of the current literature about their research topic. In each area, a researcher must move beyond citing sources piecemeal and describe the current discourse around their research problem. 

Moxie’s Research Article Summarizer is engineered to summarize the salient points a researcher needs to vet an article for relevancy. Researchers can view summaries and categorize articles based upon which part of the problem statement to which they apply. Some articles will provide context, others will show what researchers have discovered about a problem. Still others will show why addressing a specific problem is necessary (significance). Of course, articles may contain material that address all three facets of a problem statement. No problem. 

The power of AI to find patterns in language comes into play when researchers use our Literature Review Matrix Analyzer to analyze a literature matrix of relevant research. A literature matrix charts key study elements such as methodology, purpose, and findings. Moxie’s tool helps researchers rapidly identify patterns, trends, and gaps in the literature. Researchers can compare their own manual analysis with Moxie’s output. Doing so often corroborates themes that a researcher has found. Conversely, Moxie may identify a potential new theme or gap that a researcher hasn’t considered.

Once themes about context, knowledge gap, and significance have been identified, researchers can draft to each element. The benefit of this approach is that AI has provided an assist for the heavy lift of sorting and synthesizing research — augmenting the process but ultimately handing the reins back to the researcher. In addition to saving time, this use case helps researchers draft a problem statement that is very organized and contains each problem statement element. This use case also helps researchers overcome problem statement researchers block because during any portion of the process they can ask our tools to:

  • Clarify terms (“How is context different from setting?”)
  • Vet an article for relevancy (“Does this article help establish the need for my study?)
  • Clarify an output (“I see a different trend in these studies. Do you? Why or why not?”)
  • Review their problem statement (e.g. “Does this statement clearly articulate the gap in knowledge? Please give me feedback).

 

Finally, this use case helps research writers focus their problem framing efforts so that valuable time is not lost plucking citations and piece-mealing together a problem statement. Researchers can trust that their problem statement conforms to the norms of the form and begin shaping other aspects of their study that naturally follow from problem framing (e.g. purpose, research questions, and hypotheses). Finally, as architects of studies, researchers efficiently vet several research problems during the early phases of their study design, knowing that they are engaging with the process with fidelity. Instead of being tempted to cut corners in problem framing, this use case encourages researchers to expand and more fully consider researching problems — vetting them both for viability and feasibility based upon the current state of the research. Now that is true scholarship.

Reference

Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation (4th ed.). Jossey Bass.

 

Drs. Kimberly Becker and Desi Richter

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