Collaq
Mining Knowledge Together
UX Research
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UX-UI Design
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Interaction Design
Information Architecture
Product Design
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Highlights.
Collaq is a theoretical research assistance platform designed to connect researchers from academic institutions and corporations to foster meaningful collaborations.
The platform integrates three key components:
- A collection of quality academic and industry research resources.
- An intuitive workspace for organizing research, managing tasks, and capturing insights.
- A vibrant community hub for finding cross-sector partners and sharing knowledge.
Collaq’s Home Page
User Research.
Collaq was born from a deep understanding of the need to support the entire research lifecycle, beyond simple content access.
I conducted a qualitative study in order to define users’ needs and characteristics. The study was carried out by surveys with 15 students, pursuing various professional fields and degrees.
Core challenges:
A. Finding quality sources and extracting valuable insights is time-consuming and frustrating
B. Data research quickly becomes chaotic and disorganized, makes reusing material difficult
C. Lack of access to researchers from other institutions makes collaboration difficult
Personas.
Project Goals.
B. Design a smart content management system for quick usage, e.g., entering highlights, quoting, and citing
C. Establish a research hub for the global research community, for sharing ideas and collaborating
Usability Testing.
Iterative design process
The design process was characterized by numerous iterations, encompassing continuous research, usability testing, and refinement cycles. Below, I’ll briefly outline the usability testing methodology, followed by a detailed look at each key feature, its design iterations, and their impact.
Usability testing: Overview
Objective: To assess the usability, efficiency, and logical coherence of the information organization and navigation within the platform.
Research questions:
A. Is the information organized logically, optimizing workflows?
B. How easy is it for users to navigate the system and locate resources/actions?
C. Does the information architecture and navigation align with users’ mental models?
D. How easy is it to retrieve and utilize materials?
E. Are there specific areas of confusion or difficulty during usage?
Task Success Rate: Percentage of users successfully completing defined tasks related to information organization and navigation.
Time on Task: Average time taken for key information organization and retrieval tasks.
Methodology:
I conducted a moderated usability test with 4 potential users (researchers and students) on a Figma prototype. Participants were asked to navigate the system and perform core actions, while thinking aloud (Think Aloud Protocol), observations and pain points were documented.
Key Discoveries:
I identified difficulties related to information organization, search actions, and general navigation, all impacting workflow efficiency and overall satisfaction. Specific insights, including unexpected discoveries and their impact on the design will be detailed under the relevant feature descriptions.
Search experience.
Many users, especially first-degree students, felt overwhelmed by the search engine’s vast data. My mission was to design a seamless and effective search experience combined with AI data extraction, to alleviate this cognitive load.
Early stages wireframes
Key iterations & insights
Key improvements made during iterations, were driven by research, user feedback and best practices:
Progressive disclosure for filters & advanced search: Simplified the interface by revealing complex options only as needed, easing cognitive load.
Enhanced filtering UI: Refined filter presentation and interaction for more intuitive and efficient application.
Saved search functionality: Enabled saving searches with filters for quick re-access, improving workflow continuity.
Smart auto-complete suggestions: Reduced typing effort and guided users to relevant queries faster.
Comparative analysis of leading search engines
To design a seamless and effective search experience, I conducted a comparative analysis of leading search engines—Google, PubMed, and Harvard University’s library platform. The research focused on understanding their search processes, user flows, and key features, aiming to identify best practices and solutions for Collaq’s search engine.
Below is a visual comparison outlining the different features each platform uses:
Final search flow
Time on task – The average time users take to complete the following task: From initiating a search query to saving material. Measured through usability tests.
Search Success Rate: The percentage of users who successfully complete a goal-oriented action after a search query (e.g., entering/saving a source, or extracting information). Measured via usability tests and product analytics.
Potential impact
The implemented improvements are expected to deliver a more fluid and intuitive search experience, significantly reducing cognitive load throughout the process. This will lead to higher success rates in applying filters, and improved task completion times.
Architecture (IA) & Content Management.
The user research indicated that users require more than simple access to sources. They want features that help organize their data effectively. By using functions like project creation, researchers can group related information, move smoothly between studies, manage brainstorming sessions, and complete their tasks more efficiently.
Early stages wireframes
Key iterations & insights
Key improvements made during iterations, were driven by research, user feedback and best practices:
Refined navigation bars: Implemented a three-tiered navigation system – a global menu on top, a local menu underneath it, and a persistent left sidebar for quick access to favorites and common actions.
Unified concepts & features: Integrated elements like “highlights” across the platform, allowing consistent access directly from source page and project view.
Optimized layout: Enhanced screen scannability and strategically placed quick action buttons near relevant items.
Intuitive iconography: Introduced clear iconography to aid internal navigation.
Site map
Challenges in search engine design
Challenges in search engine design
Initially, I believed a single, unified search would be simplest for users.
However, moderated usability test, revealed a significant misalignment with users’ mental models: they struggled to understand what they should search for where, and what results to expect (e.g., distinguishing between an academic database search and a task database search).
This insight, in addition to revealing technical constraints, led to a redesign of the search scope, now tailored to different databases within varying platform areas.
I implemented micro-text labels and clear visual cues in search fields to explicitly indicate the contextual search scope.
This key learning underscored the crucial importance of aligning interfaces with user mental models and leveraging expert technical insights to build trust and clarity.
Final screens
Three-tiered navigation system
Global menu, local menu, persistent left sidebar
The Workspace
Divided by project, tasks, assisting tools and teams
Project system
Local menu for resources, tasks, highlights and more
Reading mode
Search, save highlights, mark, copy and more
Task Success Rate – A measure of the percentage of users who successfully complete goal-oriented tasks involving navigating, locating, grouping, or reorganizing information. measured through moderated usability tests.
System usability scale – A measure of the overall perceived usability of the platform, with a focus on data organization. Measured through a moderated usability test followed up by a survey.
Potential impact
By prioritizing a logical site structure and clear navigation, the implemented improvements are expected to significantly reduce user confusion and enhance their ability to effectively organize and retrieve data.
Community Hub.
The community hub enables establishing connections with peers from diverse sectors and geographical locations, and creating events such as academic conferences, professional webinars, and more.
At the heart of this section lies the Discoveries area, where users encounter content curated to match their research interests and preferences.
Discoveries
Network management
Community hub active user ratio: The percentage of registered users who actively engage with the community hub on a weekly basis, indicating the overall adoption and utilization of the feature. Measured through product analytics.
Content Contribution Rate: The percentage of active users within the community hub who contribute content (e.g., posting, commenting, creating events). Measured through product analytics.
Future validation & optimization:
This section was designed in a later phase, after the usability tests. Therefore, I didn’t have the opportunity to evaluate its effectiveness and relevance through direct user testing. To gain insights into the defined KPIs, the next step would be to conduct analytical research for quantitative data collection. Should there be a need to improve these metrics, subsequent usability tests, surveys, or interviews would be essential to identify specific pain points.
Conclusion.
Key learnings
Throughout the Collaq project, key design principles emerged, directly shaping the product’s evolution and offering valuable insights for future challenges:
Progressive disclosure: Gradually introducing complexity reduces cognitive load, allowing users to focus.
Clarity in search scope: Unambiguous search functionality is vital for user confidence and task success.
Contextual navigation: Accessible, relevant navigation options boost user efficiency and productivity.
Workflow efficiency & continuity: Designs should enable smooth task transitions for a continuous user journey.
Unified experiences: Integrating related features across the platform creates a cohesive, intuitive user flow.
Project limitations & next steps
As a theoretical endeavor, Collaq’s solutions weren’t live, meaning no real-world user data was collected for defined KPIs. This led to several key limitations:
Research limitations:
- Limited research scope: usability tests involved a small, homogenous sample (4 Israeli participants), lacking diverse representation.
- Early-stage usability tests: tests were conducted in initial design phases, without comprehensive tasks or deep evaluation of all internal features.
Should this project be implemented, quantitative data collection and analytical research would be crucial to validate feature necessity. Subsequent usability tests and additional qualitative methodologies would then be required to further identify pain points and drive ongoing optimization.
Next project
