Structured Algorithm Learning and Exercise Design

• Day: 2023-08-02
• Time: 17:50 to 18:30
• Project: Teaching
• Workspace: WP 1: Strategic / Growth & Development
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Algorithms, Dynamic Programming, Greedy Algorithms, Education, Exercises

Description

Session Goal

The goal of this session was to develop a structured approach to teaching and learning various algorithmic techniques, focusing on dynamic programming and greedy algorithms.

Key Activities

• Recursive Problem Formulation: Developed a recursive algorithm for optimal number selection from a matrix.
• Algorithm Exercises Overview: Planned exercises involving dynamic programming, backtracking, and greedy algorithms.
• Backtracking, Dynamic Programming, and Greedy Algorithms Overview: Reflected on key concepts and practical applications of these techniques.
• Exercise Mapping: Mapped exercises to algorithm concepts to enhance learning.
• Expanded Learning Sessions: Planned detailed educational sessions on dynamic programming and greedy algorithms.
• Session 2 Overview: Focused on dynamic programming with the ‘Terreno’ problem.
• Session 4 Overview: Introduced greedy algorithms with ‘Parejas de Baile’ exercise.
• Session 5 Breakdown: Focused on greedy algorithms and ethical considerations with ‘Escuela en Pandemia’ exercise.

Achievements

• Developed a comprehensive curriculum for algorithmic techniques.
• Created a series of exercises to reinforce learning.
• Mapped exercises to enhance educational outcomes.

Pending Tasks

• Conduct the planned educational sessions and evaluate their effectiveness.
• Develop additional exercises for deeper understanding of algorithmic concepts.

Evidence

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