T Level Digital: Computational Thinking and Algorithms

Problem solving opens the content of every Pearson digital T Level core, whichever occupational route a student is on: Digital Software Development, Digital Support and Security or Digital Data Analytics. The core is assessed through two written papers and an employer-set project, and on the software development route the employer-set project asks for what this topic trains: breaking a brief down, designing a solution with flowcharts or code, and finding and fixing defects in code that someone else wrote.

The quiz has twelve questions set in invented workplaces. Three ask you to tell the four components of computational thinking apart when they are applied rather than defined: a library splitting a reservation system into parts, a cinema reusing a booking design it has built before, and a car park deciding which values vary and which stay constant. Three ask you to trace short Python programs and give their exact output, including a loop that counts digits with integer division and a dictionary of café prices. Three show code that does not meet its requirement: a free-delivery rule that fails at exactly £50, a password check that never counts attempts, and an average that comes out as 3.0 instead of 12.0. The last three cover flowcharts and constructs: the sub-process symbol, a flowchart translated into code that prints two tickets for an adult, and choosing a condition-controlled loop. Every explanation walks through the trace or the rule and says why the tempting wrong option fails.

The flashcards cover the four components, the questions to ask when abstracting, the flowchart symbols, the three ways of controlling the order of steps and the common off-by-one and accumulator errors.

The written work has eight tasks to answer on paper. Two ask you to build a trace table and to check code against a requirement; three ask you to decompose a lunch pre-order app, abstract a bus departure program and write an algorithm for loyalty points. Three are longer, evaluative answers of the kind the papers use for their higher-mark questions: flowchart against code for a client, count-controlled against condition-controlled loops, and whether computational thinking is worth the time on every support ticket. Each task has a model answer and the points a marker would look for.

There is also a short oral practice with an examiner, who describes flowcharts and code in words, asks one question at a time and gives brief feedback at the end. Code is Python, the language the software development specification names; students on the other two routes can treat the code questions as algorithm tracing.

• Tell decomposition, pattern recognition, abstraction and algorithmic design apart in a workplace scenario
• Use abstraction to list inputs, outputs, what varies and what stays constant
• Trace a short algorithm and state its exact output for a given input
• Find an error in an algorithm, including off-by-one comparisons, loops that never end and misplaced accumulators, and correct it
• Read and use flowchart symbols, including sub-processes and decisions
• Choose between sequence, selection, count-controlled and condition-controlled iteration
• Evaluate ways of expressing an algorithm for a given audience

Practice material written by Zestly, based on the core content of the Pearson T Level Technical Qualifications in Digital Software Development, Digital Support and Security and Digital Data Analytics (first teaching September 2025), content area 1: problem solving (computational thinking and algorithmic design).