About us | GAMSAT- Sameer Khan

Vision

Our vision

“Good healthcare accepts doctors from all walks of life”

We break down S3 (section 3) questions so they are easy to understand for students who don’t have a strong background in science. We use an evidence based teaching philosophy, Bloom’s taxonomy, to progressively master skills in the scientific method. Our vision is to help you achieve your dream of entering medical or dental school, irrespective of your educational background.

Focus on problem-solving skills
Supportive teaching, enjoyable learning
Favourable student results
Flexible and affordable

Our Gallery

Teaching Philosophy

Teaching Philosophy

We help students master essential problem-solving skills needed to excel in the GAMSAT.

We teach our students:

01

Systematic approach

Learn to identify rules and formulate diagrams to help answer questions.

02

Problem solving domains

Learn high yield skill clusters: Spatial geometry, Systems Equilibrium and Data interpretation.

03

Deductive and Inductive reasoning

Solve long question stems that combine multiple skill clusters and topics.

Bloom’s taxonomy

Our mission is to help students ascend Bloom’s ladder so they can think laterally across Biology, Chemistry and Physics to solve the toughest S3 problems!

Create: Formulate informed hypotheses

Investigate, formulate, develop, suggest, outline, propose, question, test

Evaluate: Compare available options and justify selected choice

Appraise, compare, defend, weigh, judge

Analyze: Navigate and interpret the rules outlined in the stem

Examine, organise, interpret, relate

Apply: Test rules in new scenarios

Implement, solve, suggest, operate, demonstrate

Understand: Comprehend fundamental rules and ideas

Describe, explain, identify, select, classify

Remember: Recall fundamental concepts

Recognize, define, list

Our Journey

2020

Scored 80 overall (100th percentile) in the September GAMSAT

92 raw in S3 and 76 raw in S2

2021

Authored a Section 2 writing guide

Many students scoring in the low 70s and high 80s for S2

2022

Officially began S3 tutoring

Heavily influenced by learning models taught in MD

2023

S3 tutoring compiled
into a 10-week program

Bloom’s hierarchy of learning central to program philosophy

2024

S3 skill clusters conceptualised

Increased emphasis on data interpretation and cognitive loading

2025

Sameer’s GAMSAT
website launches online

LMS: Bloom’s S3 Mastery Program

Achievements

46+

S3 scores of 75+

69

S3 score median National S3 median: 58

13

marks in S3 improved on average

34%

MD and DMD admissions, vs 8% national average

1

9, 75+ S3 GAMSAT

16 total admissions for 2023: 4 USYD MD and 12 GEMSAS

2022

2

14, 75+ S3 GAMSAT

21 total admissions for 2024: 6 USYD MD and 15 GEMSAS

2023

3

23, 75+ S3 GAMSAT

28 total admissions for 2025: 7 USYD MD and 21 GEMSAS

2024

4

Awaiting results

Awaiting results

2025

Sameer’s GAMSAT

Why Choose
Sameer’s GAMSAT?

Evidenced based education

Based on Bloom’s taxonomy, our Section 3 program encourages critical thinking and rewards reflective practice.

Build problem solving skills

We emphasise logical reasoning abilities in high yield skill clusters instead of background knowledge.

Highly successful results

This program has been taught to hundreds of students and boasts a high S3 median of 69 (vs national median of 58) and MD/DMD admissions rate of 34% (vs national average of 8%).

Testimonial

Hear from our students

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MD 2025

Lin Aung

University of Sydney

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MD 2025

Ahmed Kamal

University of Sydney

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MD 2025

Meghna Nagarajan

University of Melbourne

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MD 2025

Yashasvi Logan

University of Notre Dame

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MD 2024

Apuroop Chunduri

University of Sydney

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MD 2025

Adithya Manoj

University of Notre Dame

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MD 2024

Diyana Wijayawansha

University of Notre Dame

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MD 2023

Eileen Ho

Griffith University

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MD 2024

Grace Scantlebury

University of Queensland

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MD 2024

Hayley Favelle

University of Melbourne

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MD 2025

Jenna Boschen

University of Melbourne

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MD 2024

Rohan Bhatia

University of Sydney

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MD 2025

Stella Vesovski

University of Queensland

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MD 2023

Kieran Elley

University of Sydney

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MD 2025

Thirani Munasinghe

University of Melbourne

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MD 2025

Tasnia Malek

University of Queensland

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MD 2024

Prashant Jhala

University of Sydney

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MD 2023

Lara Miller

University of Queensland

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DMD 2025

Ibrahim Syed

University of Sydney

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MD 2025

Ejaz Nijadi

Flinders University

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MD 2023

Shruti Vekaria

University of Notre Dame

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MD 2024

Stefany George

University of Sydney

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MD 2023

Reece Don

University of Notre Dame

Got more questions? Have a chat with us!