diff --git a/reasoning_gym/algorithmic/word_sorting.py b/reasoning_gym/algorithmic/word_sorting.py
index bc20177c..34951c0c 100644
--- a/reasoning_gym/algorithmic/word_sorting.py
+++ b/reasoning_gym/algorithmic/word_sorting.py
@@ -19,6 +19,23 @@ class TextTransformation(StrEnum):
     RANDOMCASE = "randomcase"
 
 
+QUESTION_TEMPLATE = """Your task is to sort words in ascending or descending order using ASCII/Unicode ordering.
+
+Example:
+- Input: Sort these words in ascending order (using ASCII/Unicode ordering) and return them as a comma-separated list: freely, idea, indemnify, last, END, solving
+- Output: END, freely, idea, indemnify, last, solving
+- Explanation:
+    - Uppercase letters come before lowercase letters, hence why "END" comes first.
+    - "freely" comes before "idea" because "f" comes before "i".
+    - "idea" comes before "indemnify" because even though they both start with "i", "d" comes before "n".
+    - "indemnify" comes before "last" because "i" comes before "l".
+    - "last" comes before "solving" because "l" comes before "s".
+    - Finally, the output is provided as a comma separated list of the sorted words.
+
+Now, sort these words in {direction} order (using ASCII/Unicode ordering) and return them as a comma-separated list: {words}
+"""
+
+
 @dataclass
 class WordSortingConfig:
     """Configuration for word sorting task generation"""
@@ -94,7 +111,7 @@ class WordSortingDataset(ProceduralDataset):
         answer = asc_words if is_ascending else desc_words
 
         return {
-            "question": f"Sort these words in {direction} order (using ASCII/Unicode ordering) and return them as a comma-separated list:\n{', '.join(transformed_words)}",
+            "question": QUESTION_TEMPLATE.format(direction=direction, words=", ".join(transformed_words)),
             "answer": ", ".join(answer),
             "metadata": {
                 "original_words": original_words,
@@ -106,26 +123,17 @@ class WordSortingDataset(ProceduralDataset):
         }
 
     def score_answer(self, answer: Optional[str], entry: Dict[str, any]) -> float:
-        """Determine if the solution provided solves this task.
+        oracle_answer = entry["metadata"]["sorted_words"]
+        if answer is not None and len(answer) > 0:
+            parsed_answer = [word.strip() for word in re.split(r",\s*", answer)]
+            if parsed_answer == oracle_answer:
+                return 1.0
+            elif sorted(parsed_answer) == oracle_answer:
+                return 0.2
+            else:
+                return 0.01
 
-        The function awards 1.0 for a correct answer.
-
-        Args:
-            answer (Optional[str]): The user's answer.
-            entry (Dict[str, any]): The original dataset entry containing the correct answer.
-
-        Returns:
-            float: The computed score between 0.0 and 1.0.
-        """
-
-        if answer == None:
-            return 0.0
-
-        s_answer = answer.strip().replace(" ", "")
-        if not s_answer == entry["answer"].strip().replace(" ", ""):
-            return 0.01
-        else:
-            return 1.0
+        return 0.0
 
 
 register_dataset("word_sorting", WordSortingDataset, WordSortingConfig)
diff --git a/tests/test_word_sorting.py b/tests/test_word_sorting.py
index ea66b86f..8920e814 100644
--- a/tests/test_word_sorting.py
+++ b/tests/test_word_sorting.py
@@ -116,3 +116,35 @@ def test_word_sorting_dataset_iteration():
 
     # Test multiple iterations yield same items
     assert items == list(dataset)
+
+
+def test_word_sorting_scoring():
+    """Test scoring function"""
+    config = WordSortingConfig(size=1, seed=42)
+    dataset = WordSortingDataset(config)
+
+    item = {
+        "metadata": {
+            "sorted_words": ["apple", "banana", "cherry"],
+        }
+    }
+
+    # Correct answer
+    answer = "apple, banana, cherry"
+    assert dataset.score_answer(answer, item) == 1.0
+
+    # Correct answer, with incorrect spaces
+    answer = "apple,banana,        cherry"
+    assert dataset.score_answer(answer, item) == 1.0
+
+    # All words present, but not sorted
+    answer = "banana, cherry, apple"
+    assert dataset.score_answer(answer, item) == 0.2
+
+    # Garbage
+    answer = "gibberish"
+    assert dataset.score_answer(answer, item) == 0.01
+
+    # Empty answer
+    answer = None
+    assert dataset.score_answer(answer, item) == 0.0