METHODOLOGY This section describes the research design, the study’s participants, data sources, instruments, and data-gathering procedures. It also presents research methods and statistical analysis. Research Design This study utilizes a Developmental Research Design to engineer and deploy the SPACE (Smart Productivity and Academic Companion for Education) web application. Within this developmental framework, the researchers will employ a mixed-methods approach, gathering both quantitative and qualitative data to ensure a comprehensive evaluation of the system. This methodology is directly justified by the study's specific research questions and objectives. The quantitative aspect is utilized to fulfill Research Objective 4 and address Research Question 2. By deploying the System Usability Scale (SUS) to PLT College students and recording technical performance metrics, the researchers can generate objective, numerical data to evaluate the system's usability, efficiency, and reliability (such as data persistence via PHP and MySQL). On the other hand, the qualitative aspect is essential to answer Research Questions 1 and 3, which deal with subjective user experiences. Understanding how the Neumorphic UI successfully reduces cognitive load, or how the unified dashboard (Pomodoro, Task Manager, and Note-Taker) practically impacts student productivity, requires nuanced human feedback. Through open-ended survey responses and user observations, the researchers can capture the tactile, stress-reducing benefits that numbers alone cannot explain. Ultimately, this mixed-methods approach ensures SPACE is both technically robust and genuinely valuable to its users. System/Software Architecture The technical foundation of SPACE (Smart Productivity and Academic Companion for Education) relies on standard Three-Tier Architecture. This approach was chosen to maintain a clear separation between what the user sees (presentation layer), how the application processes information (business logic), and where the information is stored (data persistence). By structuring the system this way, SPACE can smoothly run its responsive Neumorphic interface while securely managing complex AI-assisted features in the background. To fully illustrate how these components interact, the system's design is documented using four key visual models: a System Architecture Diagram, a Data Flow Diagram (DFD), an Entity-Relationship Diagram (ERD), and a Use Case Diagram. 027876500 Figure 3 System Architecture right1605700 Figure 4 Data Flow Diagram Lvl.0 left21526500 Figure 5 Data Flow Diagram Lvl. 1 00 Figure 6 Entity Relationship Diagram right000 Figure 7 Use Case Diagram Module Description Key Technologies Task Management Module A central hub for tracking assignments and deadlines. Students can easily prioritize workloads, break big projects into manageable checklists, and visualize their schedule using interactive Kanban boards or calendar views, complete with alerts for overdue work. PHP, MySQL, JavaScript (Drag-Drop API), Tailwind CSS Note-Taker Module A built-in digital notebook that keeps lecture insights organized and secure. It offers a smooth writing experience with helpful features like auto-save, folder organization, quick search, version history, and the ability to export notes directly to PDF. PHP, MySQL, Quill.js (WYSIWYG), TCPDF Pomodoro Module A customizable focus timer designed to beat procrastination. It guides students through structured study and break cycles, complete with ambient background sounds (like rain or cafe noise), progress-tracking charts, and a "Focus Mode" to block out distractions. JavaScript, SVG, Chart.js, Web Push API, PHP, MySQL AI Assistant Module The "smart" study partner. Students simply upload their reading materials, and the system securely leverages AI to instantly generate bite-sized summaries and interactive flashcards. This drastically cuts down on manual study prep time and helps students review faster. PHP, External AI API, MySQL, JavaScript Table 1: Module Table Data Collection This details the instruments and procedures employed to gather primary data for the evaluation of the SPACE web application. Given the developmental nature of this research, data collection relies exclusively on primary sources obtained directly from system interactions and the target end-users. To rigorously assess system acceptability and user satisfaction, the researchers will utilize the System Usability Scale (SUS) as the primary quantitative survey instrument. Following a structured User Acceptance Testing (UAT) phase involving a sample of 30 to 50 students at PLT College of Guinobatan Inc., the validated 10-item SUS questionnaire will be administered to capture direct feedback on the application's Neumorphic interface, overall navigability, and the perceived utility of the integrated productivity modules. In conjunction with user surveys, quantitative technical data will be gathered through rigorous Benchmark Testing. This involves controlled system evaluations to measure critical performance metrics, specifically the response latency of the external AI API during document processing, the execution speed of PHP-driven database transactions, and the real-time accuracy of the JavaScript Pomodoro timer. Finally, supplementary qualitative data will be collected through direct Observation during the UAT sessions. By monitoring participants as they interact with the centralized dashboard in a naturalistic academic setting, the researchers can effectively identify navigational friction points and assess how intuitively students utilize the toolset without prior technical training. Development Methodology The software development life cycle (SDLC) model adopted for the creation of the SPACE web application is the Agile methodology. This iterative and flexible approach was chosen over traditional sequential models because it allows for continuous user feedback, which is critical when integrating external Artif