Understanding Search in the Smithsonian Learning Lab

Client Overview

The Smithsonian Learning Lab is a free platform for discovering millions of digital resources (objects, artwork, photographs, text, audio, video, and more) from across the Smithsonian, creating personalized interactive learning experiences (“collections”), and sharing in the Smithsonian’s expansive community of knowledge and learning. It is designed for PreK–12 teachers and students but is available for anyone to use. 

The team behind the Lab, the Smithsonian Office of Educational Technology (OET), leads the Smithsonian in increasing digital access to museum resources for PreK–12 education.

Goals

Faced with the increasing number of users and user-created interactive experiences on the platform, OET wants to understand how users interact with the Lab’s primary feature: search. 

Our research focuses on two guiding questions: 

Answering these guiding questions will help OET better understand what users are looking for, how to improve the Lab’s search interface, how to support Smithsonian educators in building new educational content to fill gaps, and how to improve user supports for creating and publishing collections that are easily discoverable by others.

Our Team

In addition to my role as a Pratt student, I have worked with the Smithsonian Learning Lab since 2015 and am currently a Digital Content Producer at OET. My analytics research for this project focuses on understanding patterns in search terms, how users are using Refine Search filters, how users search for specific museums, and how software improvements and Smithsonian-created educational content can fill existing gaps and meet user needs.

Our Process

1. Client Meeting: This opportunity enabled our team to have a conversation with the client to hear their platform goals, ask questions, and gain data access.
2. Data Analysis: In this phase, the team developed guiding questions for research and began assessing the provided data. This phase included the initial development of a Google Data Studio dashboard to track quarterly search analytics, later finalized in Phase 03.
3. Development of Findings and Recommendations: This phase included multiple team meetings to discuss findings and recommendations, the development of the final report, and the completion of the Google Data Studio dashboard.
4. Client Presentation: This opportunity included a 20-minute presentation to the client of our findings and recommendations with time after for a larger discussion. We also turned over control of the Google Data Studio dashboard to support OET’s future work.

Methodology

Metrics studied include:

Limitations of our research are as follows:

• Lack of event tracking for search on Google Analytics.
• Lack of search filter tracking, outside of Subject Filters, as search terms on Google Analytics.
• Lack of insight into user motivations through lack of qualitative data; dividing users into those who are exploratory and those who are results-driven is an assumption made based on search behavior. 
• Lack of insight into end-use of content through lack of qualitative data; we do not have insight into whether sessions with search are based on independent use or teaching in the classroom. 

Findings and Recommendations

View the full findings and recommendations in our final evaluation report and presentation linked above. The following is a summary of the key findings and recommendations I developed as a team researcher.

Findings

Finding 1: Searches related to heritage months, followed closely by subject areas, are the most popular. Searches related to heritage months include “black history,” “hispanic heritage,” “asian pacific american history,” “american indian heritage,” and “women’s history.” Searches for subject areas are highly varied and include both broad subjects (ie. science) and more specific subjects (ie. chemistry).

Recommendations

Recommendation 1: Build a controlled vocabulary into the Keywords tool based on the most common search terms. This tool is currently an unrestricted text input field, and this change will increase the recall and precision rates of collection searches by regulating the terms used to tag collections, ensuring that collections are tagged with the most common words users search with, prevent tagging typos, and provide collection-creators with a starting place to brainstorm keywords. 

Recommendation 2: Develop a call for content from Smithsonian educators based on findings on search result accuracy and top search terms, categories, words, and filters to enable the creation of new educational resources based on user needs. A preview of preliminary focus areas, based on findings from this report’s analysis, are displayed above, while a full table is included in the evaluation report.

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Conclusion

We met with OET leadership in a final meeting to present our key recommendations and findings, deliver the full analytics report, and share the final Google Data Studio dashboard we developed to continuously track search analytics data on a quarterly basis.

Client feedback

After our presentation, we met with our client to discuss our findings in detail. Overall, OET leadership was very pleased with the report and greatly appreciated the actionable nature of our recommendations. As a member of OET, I can say that we are seriously reflecting on findings and considering recommendation implementation, and we plan to have our first internal presentation of the report and discussion of next steps in late May.

key takeaways