A novice researcher and an expert researcher will go about finding information for their project and work differently from one another. Understanding the behaviors of novice and expert researchers will help in understanding how to bridge the gap between experienced searchers such as librarians and novice searchers such as undergraduate students. It will also help to identify barriers that novice researchers face.
A novice STEM researcher will focus on problem/solution based research and searching. This means that a novice researcher will try to focus on finding an exact solution to the project or problem they are working on, rather than looking at the wider context of the situation at hand. Librarians play the role of assisting novices in seeing this broader picture, driven by the context of the project or problem.
A novice researcher may also struggle with using databases for their research. As technology has become intertwined with everyday life, students have grown used to resources like Google and their simple user interfaces. Most academic databases rely upon Boolean logic and the search interfaces are designed to leverage that database architecture. These architectures allow for precision searching and limiting.
Search engines like Google and Google Scholar produce an overwhelming number of results, which can lead to a sense of information overload and frustration for the novice researcher. Due to the ease of use, these databases are still the first stop for most novice searchers. Students will increasingly use generative AI in their research for similar reasons. Ease of use and access are paramount for most users, but those researchers may not actually produce relevant information in a timely manner.
Expert researchers, on the other hand, look towards the context of the information need to guide their search for information. An expert researcher will look upon the design criteria or variables of their research question or project to guide their search, before trying to generate a solution. They may ask for relevant information that describes general context or design constraints. For example, the researcher may seek the accessibility requirements they need to follow if they are building a park, maintenance and upkeep projections of similar designs, or demographic data that describes the community. These contexts or design constraints inform the research project or design project.
Additionally, an expert researcher will understand that they are likely to revisit the research process throughout the duration of the project, where a novice researcher will treat the research process as something only needed once. It is important for novices to understand that as the project continues and new things about it are revealed from stakeholders and solutions, the research process will be revisited.
Contextual information will help flesh out details around a design project, and help engineers understand the user's needs. Conversations with clients can help generate context concerns that engineers should look out for. Key context concerns that engineers should make note of are as follows:
A design team will consider which of the contextual information may apply to their project before starting to search during the specification design phase. Searching for relevant information will also be an iterative process throughout the design lifecycle. Additionally, information gathered will have to be reviewed and assessed by the team. It may be helpful to present the information gathered to fellow designers outside the team to help with identifying gaps.
In order to apply contextual information a persona, or an archetype meant to stand in for a typical stakeholder, is often created. These personas are built off of the information about the users and stakeholder gathered by the researcher to be used as a fictional stand in for them. They are often used in one of two methodologies, scenarios and stakeholders.
Scenarios are created to synthesize the information collected about the larger context of the design project to compliment the persona created by the engineer. Scenarios are the short stories that frame the persona interacting with the design based in the contextual information gathered the the researcher. Scenarios are useful to remind designers of factors to be taken into account, and typically take a narrative form.
Storyboards provide a visual summary of the larger context of the design. This method is useful for depicting a visual step-by-step process of events for the usage of a design. Similarly to scenarios, storyboards are narrative, but unlike a scenario they are depicted visually.
Both of these methodologies are used to apply the contextual information within a format to help designers understand the scope of what work is to be done within the context of their project. From the information gathered through scenarios and storyboards, they can then start to create criteria, the things the designers would like the design to be able or not able to do, and the constraints, the criteria to be met in order for the design to work within the context. Good criteria should be clear, measurable, and distinguishable between feasibility and desirability.
An important part of retrieving information is to know how to retrieve it, and strategies to make retrieving the information more precise and accurate. The goal for searching is to pull up resources that are relevant to your research and within the scope of the search.
Begin by planning your search and clarify the aims and scope of the search.
One foundational skill needed to search with accuracy and precision is Boolean Operators. The Boolean Operators can help widen or limit your search by using the operators (AND, OR, NOT) with your keywords.
Parentheses are another way to focus on retrieving accurate information during a search. Databases read searches left to right, and parentheses can help searchers group terms together when correctly formated with Boolean Operators.