PracticeVideosBlogFlashcardsEspañol
All Practice Exams

Free Practice Questions for ASSEB Class 10 AI & Robotics

Exam-style questions and explanations by OpenExamPrep.

✓ No registration✓ No credit card
Exam pass rate: ~85%
100+ Questions
100% Free

Loading practice questions...

Same family resources

Explore More Assam ASSEB HSLC Elective Subjects

Continue into nearby exams from the same family. Each card keeps practice questions, study guides, flashcards, videos, and articles in one place.

Assam ASSEB HSLC Advanced Mathematics — Elective

Practice Questions

Assam ASSEB HSLC Arabic — Elective

Practice Questions

Assam ASSEB HSLC Assamese — Elective

Practice Questions

Assam ASSEB HSLC Commerce — Elective

Practice Questions

Assam ASSEB HSLC Computer Science — Elective

Practice Questions

Assam ASSEB HSLC Dance — Elective

Practice Questions
Exam Review

Key Facts: ASSEB Class 10 AI & Robotics Exam

100

Total Marks

ASSEB HSLC Curriculum

70 / 30

Theory / Practical Split

ASSEB Board Regulations

3 Hours

Exam Duration

ASSEB Board Timetable

7 Units

Syllabus Modules

ASSEB Class 10 Syllabus

Python 3

Programming Language

ASSEB AI Practical Guide

The ASSEB Class 10 AI & Robotics exam evaluates students on 7 key units: Introduction to AI, Machine Learning, Computer Vision, Natural Language Processing, Ethics in AI, Basics of Robotics, and Python Programming. Master these topics with 100 targeted practice questions covering theoretical definitions, hardware mechanisms, and Python code snippets.

Sample ASSEB Class 10 AI & Robotics Practice Questions

Try these sample questions to review concepts for the ASSEB Class 10 AI & Robotics exam. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1Who is widely recognized as the 'Father of Artificial Intelligence' for coining the term and organizing the famous 1956 Dartmouth Conference?
A.Alan Turing
B.John McCarthy
C.Marvin Minsky
D.Geoffrey Hinton
Explanation: John McCarthy coined the term 'Artificial Intelligence' in 1955 and organized the 1956 Dartmouth Conference, which officially established AI as a field of computer science research.
2Which benchmark test proposed by Alan Turing in 1950 evaluates whether a machine can exhibit intelligent behavior indistinguishable from a human?
A.Voight-Kampff Test
B.Turing Test
C.McCarthy Intelligence Exam
D.CAPTCHA Test
Explanation: The Turing Test, originally named the 'Imitation Game' by Alan Turing in 1950, tests if an evaluator cannot reliably tell a machine apart from a human during text conversation.
3Artificial Narrow Intelligence (ANI), also known as Weak AI, is best described as AI that:
A.Possesses self-awareness and conscious emotional reasoning
B.Is designed to perform a specific dedicated task with high proficiency
C.Can learn and execute any intellectual task a human can perform
D.Surpasses human intelligence across all cognitive fields simultaneously
Explanation: Artificial Narrow Intelligence (ANI) is specialized AI focused on doing one single task extremely well, such as playing chess, detecting spam, or recognizing faces.
4Which of the following highlights a key advantage of Artificial Intelligence over Human Intelligence?
A.AI possesses innate emotional empathy and moral consciousness
B.AI can process vast datasets at high speeds without physical fatigue
C.AI easily adapts to completely unfamiliar out-of-domain situations without retraining
D.AI inherently possesses creative commonsense intuition
Explanation: AI excels at high-speed data processing, pattern recognition, and operating 24/7 without experiencing fatigue, emotional burnout, or physical strain.
5Which AI domain enables computers to interpret, process, and analyze visual information from digital images or video streams?
A.Natural Language Processing
B.Computer Vision
C.Robotic Kinematics
D.Expert Systems
Explanation: Computer Vision (CV) is the domain of AI that enables software to analyze and derive meaningful information from visual inputs such as photos and live camera feeds.
6Artificial General Intelligence (AGI) refers to a theoretical stage of AI development where a machine:
A.Can only play board games following fixed programmed rules
B.Can perform any intellectual task that a human being can do across diverse domains
C.Operates purely using mechanical switches without software algorithms
D.Is limited strictly to speech recognition applications
Explanation: Artificial General Intelligence (AGI), or Strong AI, refers to hypothetical AI systems that match human cognitive abilities across all general reasoning, problem-solving, and learning domains.
7Which domain of AI allows machines to read, understand, translate, and generate human written or spoken language?
A.Computer Vision
B.Natural Language Processing (NLP)
C.Reinforcement Learning
D.Artificial Super Intelligence
Explanation: Natural Language Processing (NLP) is the branch of AI focused on bridging the communication gap between human natural language and computer systems.
8What is 'Algorithmic Bias' in AI systems?
A.A hardware malfunction in a microchip processor
B.Unfair or discriminatory outputs produced because the training dataset reflects historical human prejudice or skewed data
C.The tendency of an AI model to run faster on modern graphics processing units
D.A requirement to encrypt all stored data
Explanation: Algorithmic bias occurs when an AI system produces systematically prejudiced or unfair results because the data used to train the system contained historical or sampling biases.
9Synthetic media created using deep generative models to replace a person's face or voice in a video with convincing accuracy is called a:
A.Deepfake
B.Watermark
C.Phishing scam
D.Microcontroller flash
Explanation: Deepfakes are synthetic media in which a person's likeness, face, or voice is realistically swapped using deep neural networks, raising serious ethical concerns regarding disinformation.
10Which principle of Responsible AI emphasizes that users and developers must understand how an AI system reaches its decisions?
A.Transparency and Explainability
B.Maximum Speed
C.Data Compression
D.Exclusive Access
Explanation: Explainability (or Transparency) ensures that AI decision-making processes are understandable to human domain experts rather than remaining an unexplainable 'black box'.

About the ASSEB Class 10 AI & Robotics Exam

The Assam ASSEB Class 10 HSLC Elective Artificial Intelligence and Robotics course introduces secondary students in Assam to modern technology domains. It covers core AI concepts, Machine Learning paradigms, Computer Vision fundamentals, Natural Language Processing pipelines, ethical implications of AI, hardware components of Robotics (sensors, actuators, controllers), and introductory Python programming.

Exam sponsor: Assam State School Education Board (ASSEB). The requirements and fees below concern the certification or admission exam, separate from our free practice resources.

Assessment

100 multiple-choice practice questions (Theory Board Exam: 70 marks theory + 30 marks practical)

Time Limit

3 hours

Passing Score

30% aggregate

Exam / Certification Fees

Included in HSLC Board Fee

Exam sponsor website

Reported exam pass rate: ~85%. Average pass percentage across Assam state schools for elective subjects This describes exam candidates, not OpenExamPrep users or results from using our resources. Exam sponsor website

Fees, eligibility, and exam policies can change. Confirm them with the exam sponsor before applying or paying.

Our practice resources: topics covered

We aim to reflect publicly available exam outlines and topic information in our study resources. Coverage, format, and difficulty may differ from the actual exam, and we cannot guarantee that every detail is accurate or current. Confirm exam requirements, fees, and policies with the official exam sponsor.

15%

Introduction to AI

Definition of AI, history, AI vs Human Intelligence, Narrow vs General vs Super AI, real-world applications in healthcare, smart homes, and transportation.

15%

Machine Learning Concepts

Supervised, Unsupervised, and Reinforcement Learning, Classification vs Regression, Clustering, Training vs Testing datasets, Overfitting and Underfitting.

15%

Computer Vision

Basics of Computer Vision, pixel representation, RGB color model, feature extraction, object detection, face recognition, and autonomous navigation.

15%

Natural Language Processing (NLP)

NLP workflow, text preprocessing (tokenization, stop words removal, stemming, lemmatization), Bag of Words model, sentiment analysis, and chatbots.

10%

Ethics in AI

Data bias, algorithmic fairness, privacy concerns, copyright, job displacement, deepfakes, transparency, and responsible AI principles.

15%

Basics of Robotics

Definition and anatomy of robots, Isaac Asimov's Laws of Robotics, sensors (ultrasonic, IR, gyro, touch), actuators (DC motors, servo motors, stepper motors), and microcontrollers.

15%

Python Programming Basics for AI

Python data types, lists, dictionaries, conditionals, loops, functions, and key AI libraries like NumPy, Pandas, and Matplotlib.

Preparing for the ASSEB Class 10 AI & Robotics Exam

What You Need to Know

  • Passing score: 30% aggregate
  • Assessment: 100 multiple-choice practice questions (Theory Board Exam: 70 marks theory + 30 marks practical)
  • Time limit: 3 hours
  • Exam / certification fees: Included in HSLC Board Fee Official sources

Using Our Practice Resources

  • Work through all 100 available questions
  • Review every answer and explanation
  • Track weak areas and revisit them
  • Use our AI tutor for tough concepts

ASSEB Class 10 AI & Robotics: Suggested Study Strategy

1Understand the conceptual difference between Supervised, Unsupervised, and Reinforcement Learning with real-life examples
2Memorize Isaac Asimov's Three Laws of Robotics and their significance in robot safety
3Practice step-by-step NLP text preprocessing: Tokenization -> Stop Words Removal -> Stemming/Lemmatization
4Learn the function of common robotics sensors: Ultrasonic (distance), IR (line follower/obstacle detection), LDR (light)
5Master Python data structures (lists vs tuples vs dictionaries) and loop operations
6Understand how images are represented as 2D/3D matrix arrays of RGB pixel values in Computer Vision
7Review ethical issues in AI such as algorithmic bias in dataset selection and data privacy

Frequently Asked Questions

What is the ASSEB Class 10 Elective AI & Robotics subject?

It is an elective subject introduced by the Assam State School Education Board (ASSEB, formerly SEBA) for Class 10 students to build early technical competency in Artificial Intelligence, Machine Learning, Robotics hardware, and Python programming.

What is the marking scheme for the HSLC AI & Robotics board exam?

The subject carries 100 marks in total, typically divided into 70 marks for the written board theory examination and 30 marks for internal practical assessment and lab projects.

What Python programming topics are required for Class 10 AI & Robotics?

Students need to understand basic Python syntax including variables, data types (integers, strings, lists, dictionaries), conditional statements (if-else), loops (for, while), functions, and introduction to libraries like NumPy and Pandas.

What robotics hardware components are tested in the exam?

The exam covers basic sensors (Ultrasonic distance sensors, IR proximity sensors, Gyroscopes, Touch sensors), actuators (DC motors, Servo motors, Stepper motors), and microcontrollers (such as Arduino and Raspberry Pi).

Are there practical coding questions in the exam?

Yes, theory exams include output prediction questions, code snippet completion, and syntax error identification, while practical exams require writing and executing simple Python scripts.