diff --git a/src/components/HealthBar.tsx b/src/components/Quiz/HealthBar.tsx
similarity index 100%
rename from src/components/HealthBar.tsx
rename to src/components/Quiz/HealthBar.tsx
diff --git a/src/components/Quiz/index.tsx b/src/components/Quiz/index.tsx
index 8048397..93abcad 100644
--- a/src/components/Quiz/index.tsx
+++ b/src/components/Quiz/index.tsx
@@ -21,7 +21,7 @@ import {
   TooltipProvider,
   TooltipTrigger,
 } from '@/components/ui/tooltip';
-import HealthBar from '@/components/HealthBar';
+import HealthBar from '@/components/Quiz/HealthBar';
 import useSoundEffects from '@/hooks/useSoundEffects';
 import type { ParsedQuestion } from '@/lib/markdownParser.ts';
 import { loadAllQuestions } from '@/lib/markdownParser.ts';
diff --git a/src/questions/example-question-two.md b/src/questions/example-question-two.md
new file mode 100644
index 0000000..156c7fe
--- /dev/null
+++ b/src/questions/example-question-two.md
@@ -0,0 +1,141 @@
+---
+title: The Ultimate Coding Challenge
+description: Test your programming skills across various languages and concepts!
+level: 2 # Questions will be sorted by level
+correctAnswer: 2
+difficulty: "Expert" # Beginner, Intermediate, or Expert (optional)
+---
+
+## Context
+
+### Introduction
+
+Welcome to the Ultimate Coding Challenge! This quest will test your knowledge of **programming concepts, algorithms, and problem-solving skills**. Are you ready to prove your coding prowess?
+
+Test of code highlighting:
+
+inline code: `console.log('Hello, Alice!');`
+
+```python
+def decorator(func):
+  def wrapper(*args, **kwargs):
+    print("Before function call")
+    result = func(*args, **kwargs)
+    print("After function call")
+    return result
+  return wrapper
+```
+
+### Question
+
+You're tasked with implementing a function to find the most frequent element in an array. The function should work efficiently for large arrays. Consider the following requirements:
+
+1. The function should handle arrays of integers.
+2. If there are multiple elements with the same highest frequency, return any one of them.
+3. The function should have a time complexity better than O(n^2).
+
+```go
+func mostFrequent(arr []int) int {
+    maxCount := 0
+    result := arr[0]
+    for i := range arr {
+        count := 0
+        for j := range arr {
+            if arr[i] == arr[j] {
+                count++
+            }
+        }
+        if count > maxCount {
+            maxCount = count
+            result = arr[i]
+        }
+    }
+    return result
+}
+```
+
+How would you implement this function?
+
+### Outro
+
+__Efficient__ array manipulation and understanding of data structures are crucial skills for any programmer. This problem tests your ability to balance time complexity with code readability.
+
+## Answers
+
+- Use nested loops to count occurrences of each element:
+
+```python
+def most_frequent(arr):
+    max_count = 0
+    result = arr[0]
+    for i in range(len(arr)):
+        count = 0
+        for j in range(len(arr)):
+            if arr[i] == arr[j]:
+                count += 1
+        if count > max_count:
+            max_count = count
+            result = arr[i]
+    return result
+```
+
+- Use a hash map to count occurrences in a single pass:
+
+```python
+from collections import defaultdict
+
+def most_frequent(arr):
+    count = defaultdict(int)
+    for num in arr:
+        count[num] += 1
+    return max(count, key=count.get)
+```
+
+- Sort the array and count consecutive elements:
+
+```python
+def most_frequent(arr):
+    arr.sort()
+    max_count = 1
+    res = arr[0]
+    curr_count = 1
+    for i in range(1, len(arr)):
+        if arr[i] == arr[i-1]:
+            curr_count += 1
+        else:
+            if curr_count > max_count:
+                max_count = curr_count
+                res = arr[i-1]
+            curr_count = 1
+    return res
+```
+
+- Use a set to eliminate duplicates, then count occurrences:
+
+```python
+def most_frequent(arr):
+    return max(set(arr), key=arr.count)
+```
+
+## Explanation
+
+The correct answer is option 2: Using a hash map to count occurrences in a single pass.
+
+This solution is optimal because:
+
+1. It has a time complexity of O(n), where n is the length of the array.
+2. It only requires a single pass through the array.
+3. The space complexity is O(k), where k is the number of unique elements in the array.
+
+Here's a breakdown of how the function works:
+
+1. `defaultdict(int)` creates a dictionary where any new key is automatically initialized with a value of 0.
+2. The loop `for num in arr:` iterates through each element in the array.
+3. `count[num] += 1` increments the count for each number.
+4. `max(count, key=count.get)` returns the key (number) with the highest count.
+
+This solution efficiently handles large arrays and meets all the specified requirements.
+
+## Hint
+
+Think about data structures that allow for fast lookups and updates. How can you keep track of counts while only passing through the array once?