VALCRI is short for "Visual Analytics for Sense-making in Criminal Intelligence Analysis". A system that helps police in the analysis of large datasets for intelligence and investigative purposes. VALCRI is an Integrating Project funded through the European Commission’s 7TH Framework Programme, Contract Number FP7-IP-608142, awarded to Middlesex University and Partners.
Website: http://valcri.org/
Project Overview:
Research Question: How do crime analysts think, reason, make decisions, and do sense-making with the help of the software VALCRI and how can we improve its effectiveness?
Methods: Semi-Structured Interviews, Critical Decision-Making Method, Cognitive Task Analysis, Emergent themes analysis, Think Aloud Protocol, Heuristic Evaluation
Skills: Interviewing, Transcribing, Synthesizing, Facilitating, Design critique
Deliverables: An academic report
Tools: Transcribe, Post-its, Google Suite
My Roles and Responsibilities:
As a visiting researcher, I was responsible for evaluating the effectiveness of this data-driven tool developed by the team at Middlesex University, to help investigators analyze crime databases. With the intention to build improvements into their product, the team was looking to better understand the users, their environments, and challenges faced in the use of the product.
Challenges:
Context simulation: VALCRI was supposed to be used by the crime analysts while analyzing the crime data which involved critical thinking so to test out the prototypes in the usability lab required the simulation of the situation while avoiding unnaturalness.
Language Barrier: Doing the research in different geography altogether involved a little more comprehension time for me as a researcher because of varied accents in the English language.
Unfamiliar & complex field: the crime databases involved complicated and countless terminologies and intricate relationships .
Outcome:
Identified the challenges in the usage while analyzing the crime data.
Identified features that are not working and the reasons behind their ineffectiveness.
Recommended modifications required for crime analysts to think, reason, make decisions, and do sense-making effectively.
Process:
I conducted an intensive usability study to understand the challenges faced while using the tool. While also observing patterns in thinking, reasoning, decision making, and sense-making of crime analysts which can further be used to develop the system. Technology as a medium of learning was not familiar to many users and hence this factor was studied in-depth.
Collecting Data > Transcribing Data > Analysing Data
1. Collecting Data We had 3 participates from the criminology/law background. They were given the task of analyzing the crime in the town Torrington. We used a think-aloud protocol for these. We also recorded the screen and used camera recording as a back. After the participant performed to the task we conducted a semi-structured interview in order to identify key decision points using the Critical Decision Method.
2. Transcribing Data
The task and the interviews were word to word transcribed using the software Transcribe.
3. Analyzing Data
For the analysis of the data, first, a coding scheme was developed in order to make the decision charts. After the decision charts were made they were analyzed using the Emergent Themes Analysis:
* Explicit information has been hidden to comply with the NDAHere are some of the things the team at MDX has to say about the work:
...I have found her to be a highly independent learner, with a strong ability to understand and make connections between various human factors concepts. She is amongst the most self-motivated students I have had the opportunity to engaged with, a team player driven by her strong desire to persevere and complete a task well, and to make sure that the outcomes are useful...
Professor B.L. William Wong
Head Interaction Design Centre
Middlesex University London, UK
...The study carried out clearly shows her ability to deliver a clear, concise, and well-thought piece of research at an undergraduate student level. I have supervised many students at the undergraduate level, however, Vidushi stands out as she is a great person to collaborate with also who is self-driven and motivated. Overall, Vidushi is intelligent, has good analytical skills, outstanding commitment, and strong research interest...
Dr. Neesha Kodagoda
Operations Manager VALCRI/ Researcher Visual Analytics
Middlesex University London, UK
If you would like me to conduct such a study for your product or team or would just like to know how to conduct such then do hit me up!