India · 2026-27 syllabus
CISCE (ICSE / ISC)
16 lab practicals for the ICSE / ISC syllabus.
The 2026-27 CISCE syllabus: Computer Applications at ICSE and Computer Science at ISC, both in Java. Every lesson is stepped, compiled and checked by a real toolchain on your own machine — the model reviews your code afterwards, it does not decide whether you passed.
Updated
Semester by semester
Programme: Computer Applications (ICSE IX-X) and Computer Science (ISC XI-XII). Scheme: 2026-27 syllabus. Open a course to see its practical units and the lab lesson GroutCode ships for each.
Class 9
1 course4 lab lessonsJava- ICSEIXJava
Computer Applications
4
lessons
- Primitive Data Types and Operators
- Electricity Bill Calculator with Conditional Constructs
- 1Primitive Data Types and OperatorsUnit 1 · Values, data types and operators
- 2Electricity Bill Calculator with Conditional ConstructsUnit 2 · Conditional constructs
- 3Pattern Printing with Nested LoopsUnit 3 · Iterative constructs
- 4Creating a Student Class with Grade ManagementUnit 4 · Classes, objects and methods
Class 10
1 course5 lab lessonsJava- ICSEXJava
Computer Applications
5
lessons
- Wrapper Classes and Character Methods
- Java Constructors
- 1Wrapper Classes and Character MethodsUnit 1 · Library classes and wrapper classes
- 2Java ConstructorsUnit 2 · Constructors
- 3Java Method ImplementationUnit 3 · User defined methods
- 4Selection Sort ImplementationUnit 4 · Arrays: sorting and searching
- 5String Reversal with Built-in MethodsUnit 5 · String handling
Class 11
1 course3 lab lessonsJava- ISCXIJava
Computer Science
3
lessons
- Binary to Decimal Converter
- Creating a Student Grade Tracker
- 1Binary to Decimal ConverterUnit 1 · Number systems and binary arithmetic
- 2Creating a Student Grade TrackerUnit 2 · Objects, classes and encapsulation in Java
- 3Bubble Sort ImplementationUnit 3 · Arrays, strings and recursion
Class 12
1 course4 lab lessonsJava- ISCXIIJava
Computer Science
4
lessons
- Polymorphic Animal Sounds
- Stack Implementation Using Arrays
- 1Polymorphic Animal SoundsUnit 1 · Inheritance and polymorphism
- 2Stack Implementation Using ArraysUnit 2 · Stacks and queues
- 3Singly Linked List ImplementationUnit 3 · Linked lists
- 4Safe File Reader with Custom ExceptionUnit 4 · Exception handling and file I/O
The full 4-course syllabus is transcribed in the app, including the theory courses. Lessons are authored against the course codes that have practical work, and the list grows with each release.
GroutCode is not affiliated with or endorsed by CISCE (ICSE / ISC). Course codes and titles are transcribed from the institution’s published scheme documents.
How a practical runs
The same five steps for every lesson, in every language.
- 1
Pick your syllabus
Choose your university or board and the semester or class you are in. The course list is the transcribed official scheme, not an approximation.
- 2
Open a lab lesson
Each lesson is a stepped practical for a specific course, with a starter file you edit and a test file you do not.
- 3
Write the code yourself
The starter has the signatures and the TODOs. You implement them in the editor, in the language your course actually uses.
- 4
Run the checks
The toolchain compiles and runs the tests — 8 to 15 of them across the lesson, one per step, so you find out which change broke what.
- 5
Get the review
Once the tests pass, the model reads your implementation and tells you the input that breaks it. It never reports the pass or fail itself.
Why the compiler grades, not the model
The obvious way to build an AI lab tool is to let the model read the student’s code and say whether it is correct. It is also the way that produces a tool nobody can trust. A model will tell you your code works when the compiler says otherwise, and it will fail you for a style it happens to dislike.
So the two jobs are split:
- The model designs the lesson, writes the starter and the tests, and — after the tests pass — reads what you actually wrote and tells you the input that breaks it.
- The toolchain decides whether it compiles and whether each step passes. That verdict is not negotiable and the model never issues it.
And why steps instead of one big task
A 40-to-60 minute practical with a single Run at the end gives a beginner one bit of feedback an hour, and it arrives after every decision has already been made. Each lesson here is 8 to 15 steps, each with its own instruction and its own check, so you find out which change broke what while you still remember making it.
Frequently asked questions
Does GroutCode cover the ICSE / ISC 2026-27 syllabus?
Yes. GroutCode ships the transcribed ICSE / ISC 2026-27 syllabus for Computer Applications (ICSE IX-X) and Computer Science (ISC XI-XII) — 4 courses — with 16 authored lab lessons mapped to specific course codes. The syllabus was transcribed from the official documents, and the source and checksum of each one is recorded in the app.
Which languages do the ICSE / ISC practicals use?
Java (16 lessons). The language is set per course code rather than guessed from the title, because the same subject is taught in different languages at different institutions.
Does the AI just write the practical for me?
No. The starter file has the signatures and the TODOs; you implement them. The toolchain — not the model — decides whether your code compiles and whether each step passes, so the AI cannot tell you your code works when the compiler disagrees. What it does afterwards is read your implementation and point out the input that breaks it.
Do the practicals work offline?
The lessons, the syllabus and the test runner are bundled in the app and run locally, so the compile-and-check loop works with no connection. The review step at the end uses a model, which can be a local one or a cloud one with your own key.
What do I need installed?
GroutCode detects which toolchains are present on your machine and tells you what is missing and what would fix it. You need the compiler or interpreter for the language your course uses — a C compiler, a JDK, Python, Node or SQLite.
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