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Course Syllabus & Academic Framework

PF201: Object-Oriented Programming 1 — St. Cecilia's College–Cebu, Inc. (AY 2025–2026)

Released2025–2026
Core MottoDoing ordinary things extraordinarily well
CreatorsMichael John A. Bustamante

1. Course Information & Description

PF201 introduces Object-Oriented Programming (OOP) using Java, transitioning from procedural logic to object-centric design and database persistence.
Level Outcome
By completion, students demonstrate a transition from procedural logic to OOP mastery (CMO No. 25, s. 2015), architecting class-based systems in Java with SQLite persistence and professional technical documentation reflecting Cecilian values.

Course Details

Course Code:PF201
Course Title:Object-Oriented Programming 1
Academic Year:2025–2026 (1st Semester)
Total Hours:90 hrs (36 hrs Lecture, 54 hrs Laboratory)
Units:3 Units
Pre-requisite:CC103
Instructor:Michael John A. Bustamante

Course Description

This course introduces the Object-Oriented Programming (OOP) paradigm using Java, transitioning students from procedural logic to object-centric design. Central to the course are the four pillars of OOP: Encapsulation, Inheritance, Polymorphism, and Abstraction. The course progresses from CLI development to functional Data Persistence using SQLite database with JDBC, culminating in a modular, persistent system.

2. Institutional Core Values & Graduate Attributes

Aligned with St. Cecilia's College – Cebu, Inc. vision, mission, and the Lasallian Supervision philosophy.

Cecilian Core Values

Christ-Centeredness
Excellence
Commitment
Integrity
Love for Country
Innovativeness
Arts Lover
Nurturance

BSIT Graduate Attributes

1.
Show innate talents & skills imbued with Christian values.
2.
Demonstrate commitment beyond required tasks.
3.
Apply professionalism and strong leadership.
4.
Innovate pragmatically proactive strategies for social problems.

3. Course Outcomes & Instructional Plan

A term-by-term breakdown from foundational logic review to integrated file and database systems.

PRELIM: Data Abstraction & Logic (20 Hours)

Focus:Functions & Logic Review, User-Defined Types (Structs), Member Access, Memory Allocation, Arrays of Structs.
ILO:Contrast Procedural vs OOP; Execute basic syntax in NetBeans.
Key Outputs:Memory mapping of structs, Lab 1.

MIDTERM: Data Persistence & CSV Handling (21 Hours)

Focus:Volatile vs Non-Volatile Data, File Stream States (fopen, fclose, fprintf), CSV parsing & delimiters, Persistent CRUD Logic.
Key Outputs:Machine Project 1 (File-based Phonebook Management).

PRE-FINAL: Modular Development & Structure (25 Hours)

Focus:Compilation mechanics, Header Files (.h) and Source Files (.c), Preprocessor Header Guards (#ifndef), Function Linkage & Scope.
Key Outputs:Multi-file refactoring and custom module setup.

FINAL: Systems Engineering & SQLite Integration (20 Hours)

Focus:Software Development Life Cycle (SDLC), JDBC with SQLite, Parameterized Queries, Technical Documentation & System Defense.
Key Outputs:Integrated System Build & Technical Defense (Viva Voce).

4. Grading System & Evaluation Rubrics

The course adopts the official 70/30 Cumulative Grading Scheme.

Grading Components (70/30 Rule)

Class Standing (70%):
Hands-on Lab Exercises (40%)
Machine Projects (20%)
Quizzes & Participation (10%)
Major Exam (30%):
Written Logic Test (15%)
Practical Hands-on Coding (15%)

Cumulative Weight Calculations

Prelim Grade = 100% Tentative Prelim
Midterm Grade = (70% Tentative Midterm) + (30% Prelim Grade)
Pre-Final Grade = (70% Tentative Pre-Final) + (30% Midterm Grade)
Final Grade = (70% Tentative Final) + (30% Pre-Final Grade)

Machine Project Rubric

Functionality (40%):Java execution & SQLite integration
Logic & Design (20%):Class Diagram & Object relationships
Code Efficiency (20%):Proper Inheritance & Polymorphism
Syntax & Style (10%):Java Naming standards & Javadoc
User Interface (10%):Intuitive CLI menus

System Defense Rubric

Technical Defense (40%):Explaining Object Instantiation & Connection blocks
Demonstration (40%):Smooth execution showing data persistence
Q&A Response (20%):Confidence during oral evaluation

5. Digital Integrity & AI Policy

Official guidelines regarding Generative AI usage and academic integrity.
Data Privacy & AI Policy Disclaimer
Students are prohibited from uploading sensitive university data, proprietary course modules, or personal identification into AI prompts. The College reserves the right to use logic-matching algorithms to verify code authenticity.

Permitted AI Support

Generative AI (e.g., ChatGPT, Gemini, Claude) may be used as a 'Virtual Tutor' for concept explanation (e.g. 'Explain the difference between interface and abstract class') or pseudocode brainstorming.

Prohibited AI Usage

Students are strictly forbidden from generating source code for Machine Projects or Laboratory Exercises using AI. All submitted code must be defensible in oral reviews.