Computer Application Form Four - 100 Homework Questions & 25-Question Model Exam

This master workbook delivers an authoritative, hands-on pedagogical capstone tailored specifically for Form Four Ordinary Secondary Education across Tanzania. Fully synchronized with the Tanzania Institute of Education (TIE) Information and Computer Studies (ICS) Form 4 Syllabus, Dadisi ICT Grade 4 notes, and VETA Vocational Computer Application standards, this workbook covers modern digital technology across four structured thematic modules:
• Module 1: Digital Marketing, Content Strategy & CRM Systems (Q001 – Q025): Concepts of Digital Marketing vs. traditional marketing; core digital channels (SEO, SEM, SMM, Email, Content); customer journeys & the AIDA model (Awareness, Interest, Desire, Action); inbound vs. outbound strategies; On-Page SEO (title tags, meta descriptions, heading hierarchy, image alt text); Off-Page SEO & backlinks; Technical SEO (robots.txt, XML sitemaps, mobile-first indexing, HTTPS); Search Engine Marketing (SEM), Google Ads auction, Quality Score; online advertising models (CPC, CPM, CPA, CTR & conversion math); display ad formats & programmatic RTB; pixel-based retargeting & frequency capping; social media marketing (LinkedIn, Instagram, TikTok); organic reach vs. paid ads & engagement metrics; content marketing lifecycle; blog platforms & CMS; email marketing (double opt-in, anti-spam CAN-SPAM laws, drip automations, hard vs. soft bounces); influencer & affiliate marketing tracking; web analytics (GA4 telemetry, users, sessions, events); website KPIs; A/B split testing; and Customer Relationship Management (CRM) architecture, lead scoring, and customer retention.
• Module 2: Artificial Intelligence & Machine Learning Fundamentals (Q026 – Q050): Artificial Intelligence definition, Alan Turing's Turing Test (1950) & Dartmouth Conference (1956); Narrow AI (ANI) vs. General AI (AGI) vs. Superintelligence (ASI); rule-based expert systems vs. machine learning; core AI subfields (ML, Deep Learning, NLP, Computer Vision, Robotics); machine learning paradigms (Supervised, Unsupervised, Reinforcement Learning); supervised classification vs. regression with Tanzanian applications; unsupervised clustering (K-Means) & anomaly detection; reinforcement learning (agent, environment, states, actions, rewards, policy); the end-to-end ML pipeline; data preprocessing (missing value imputation, one-hot encoding, normalization); dataset splitting (training, validation, test sets); model evaluation (Accuracy formula & confusion matrix analysis); overfitting vs. underfitting; artificial neural networks (ANNs: inputs, hidden layers, weights, biases, activation functions); CNNs, RNNs & Transformers; Computer Vision (classification, object detection, segmentation); Natural Language Processing (tokenization, stop-words, lemmatization, sentiment analysis); Generative AI & Large Language Models (LLMs: next-token prediction); prompt engineering (zero-shot, few-shot, role-prompting, chain-of-thought); AI hallucinations & Retrieval-Augmented Generation (RAG); AI in African agriculture & healthcare diagnostics; algorithmic bias; data privacy; and ethical AI governance frameworks.
• Module 3: Web Authoring, HTML5, CSS & Web Development (Q051 – Q075): World Wide Web client-server architecture, web browsers, web servers, HTTP vs. HTTPS; domain names, DNS resolution, web hosting, URL anatomy; standard HTML5 skeleton (DOCTYPE, html, head, meta, title, body); structural text tags (headings h1–h6, paragraphs, strong, em, pre); ordered, unordered, and description lists; hyperlinks (absolute vs. relative URLs, target='_blank' security); intra-page bookmark navigation (#id); image embedding, alt text, and aspect ratios; HTML5 native audio & video players; tables (table, tr, th, td, colspan, rowspan); forms architecture, form action, and HTTP GET vs. POST transmission security; form controls (text, password, email, number, submit); radio buttons vs. checkboxes; dropdown select menus; semantic form accessibility (, textarea); Cascading Style Sheets (CSS) and Separation of Concerns; three methods of applying CSS (inline, internal, external) and the cascade; CSS selectors (element, class, ID); the CSS Box Model (margin, border, padding, content); typography & font stacks; color systems (Hex, RGB, RGBA); CSS layout positioning (static, relative, absolute, fixed); semantic HTML5 tags (header, nav, main, article, section, footer); Responsive Web Design (viewport meta tag, media queries); and W3C web standards & WCAG accessibility guidelines.
• Module 4: Information Systems, E-Commerce & Systems Development (SDLC) (Q076 – Q100): Information Systems definition & DIKW hierarchy (Data, Information, Knowledge, Wisdom); six fundamental IS components (hardware, software, data, people, procedures, networks); Transaction Processing Systems (TPS), ACID properties, batch vs. real-time OLTP; Management Information Systems (MIS) tactical reports; Decision Support Systems (DSS), model bases, What-If & Goal-Seeking analyses; Executive Support Systems (ESS/EIS) dashboards & drill-down features; Expert Systems (knowledge base, inference engine, explanation facility); Electronic Commerce (E-Commerce) vs. E-Business; E-Commerce business models (B2B, B2C, C2C, G2C); digital payment systems & East African mobile money (M-Pesa, Airtel Money, TIPS interoperability, GePG gateway); e-commerce security (SSL/TLS, payment tokenization, 3D Secure, PCI-DSS); e-commerce architecture (catalogs, carts, payment gateways, inventory sync); System Development Life Cycle (SDLC) methodologies (Waterfall vs. Agile Scrum); SDLC Phase 1: Feasibility Study (TELOS framework); SDLC Phase 2: Systems Analysis & fact-finding techniques (interviews, questionnaires, observation, document inspection); Data Flow Diagrams (DFDs) & context diagrams; Entity-Relationship Diagrams (ERDs) & cardinality (1:1, 1:N, M:N); Software Requirements Specifications (SRS: functional vs. non-functional); SDLC Phase 3: Systems Design (logical vs. physical, UI wireframing); SDLC Phase 4: Implementation & data migration; SDLC Phase 5: Testing hierarchy (unit, integration, system, alpha & beta UAT); SDLC Phase 6: System changeover strategies (direct, parallel, phased, pilot); system documentation (user manuals vs. technical manuals); and SDLC Phase 7: System maintenance (corrective, adaptive, perfective, preventive) and post-implementation review.