Bebras Tasks in the Curriculum

Promoting Computational Thinking in Schools

Valentina Dagiene and Sue Sentance (2016)

Introduction to Bebras

• International informatics challenge running since 2004
• Over 50 countries participate worldwide
• More than 1.3 million participants in 2015
• Short tasks designed to be solved within three minutes
• Focuses on core concepts without requiring prior programming experience

What is Computational Thinking?

• Conceptualized by Seymour Papert (1996) and popularized by Jeannette Wing (2006)
• Solving problems, designing systems, and understanding human behavior via computer science principles
• An essential foundational literacy for all students across K-12
• Embedded into national curricula worldwide (such as England and Poland)

Five Core Computational Thinking Skills

• Abstraction: Reducing complexity by focusing on essential features
• Algorithmic Thinking: Designing step-by-step procedures to reach a solution
• Decomposition: Breaking down a complex problem into smaller parts
• Evaluation: Testing and assessing correctness, efficiency, and resource constraints
• Generalisation: Transferring problem-solving techniques to new situations

Five Informatics Subject Areas

• Algorithms and programming
• Data, data structures, and representations
• Computer architecture and processes
• Communications and networking
• Interactions, systems, and society

Analysis of 2015 Bebras Tasks

• Analysis of 52 tasks used across Lithuania and the United Kingdom
• Algorithmic thinking: 22 tasks (42%)
• Evaluation: 11 tasks (21%)
• Abstraction: 8 tasks (15%)
• Decomposition: 6 tasks (12%)
• Generalisation: 5 tasks (10%)
• Algorithmic tasks dominate because they fit the three-minute format well

Detailed Example 1: Biber Hotel

• Topic: Data structures (Binary Trees and Search)
• CT Skill: Algorithmic thinking
• Task context: A beaver den has rooms arranged in a branching tunnel system, with numbered doors
• Goal: Navigate through the den to locate room number 1337
• Computer science connection:
  • Each room is a node with up to two child branches (binary search tree)
  • With n comparisons, one can distinguish between 2^n - 1 entries
  • A depth of 20 comparisons can search through over one million records
• Source Link: Springer LNCS 9973

Detailed Example 2: Dream Dress

• Topic: Logical operations and Boolean conditions
• CT Skill: Algorithmic thinking and evaluation
• Task context: Kate searches four shops for a specific dress that meets three rules:
  • Short sleeves
  • More than 3 buttons
  • Stars on the sleeves
• Goal: Identify which shop sells the dress satisfying all conditions
• Computer science connection:
  • Evaluates compound Boolean expressions using the AND operator
  • Teaches how programs evaluate multiple conditions to filter data
• Source Link: Springer LNCS 9973

Detailed Example 3: Spies

• Topic: Communication networks and protocols
• CT Skill: Generalisation and algorithmic thinking
• Task context:
  • Six spies meet in pairs to share secrets
  • Each spy starts with one piece of information
  • It takes three rounds of pairwise meetings for all six spies to learn every secret
• Goal: Determine the minimum number of rounds needed if one spy stops attending (five spies remain)
• Computer science connection:
  • Models information dissemination and gossiping algorithms in distributed networks
  • Demonstrates protocol efficiency, parity constraints, and network scaling
• Source Link: Springer LNCS 9973

How Teachers Can Use Bebras in Class

• Starter tasks: Quick warm-up exercises to introduce a new computing concept
• Formative assessment: Automated scoring and checks for student understanding
• Year-round curriculum: Using past task archives continuously beyond contest week
• Teacher professional development: Solutions include clear concept explanations for non-specialist teachers

Summary and Recommendations

• Bebras tasks bridge non-formal challenges and formal school curricula
• Tasks make abstract computing principles accessible without technical overhead
• A two-dimensional categorization (skills and concepts) supports curriculum alignment
• Countries can build localized task repositories for teachers and students