diff --git a/gymnasium_robotics/envs/franka_kitchen/kitchen_env.py b/gymnasium_robotics/envs/franka_kitchen/kitchen_env.py
index 47e57548..beba0af9 100644
--- a/gymnasium_robotics/envs/franka_kitchen/kitchen_env.py
+++ b/gymnasium_robotics/envs/franka_kitchen/kitchen_env.py
@@ -355,6 +355,7 @@ def compute_reward(
         desired_goal: "dict[str, np.ndarray]",
         info: "dict[str, Any]",
     ):
+        self.step_task_completions.clear()
         for task in self.tasks_to_complete:
             distance = np.linalg.norm(achieved_goal[task] - desired_goal[task])
             complete = distance < BONUS_THRESH
@@ -394,7 +395,7 @@ def _get_obs(self, robot_obs):
     def step(self, action):
         robot_obs, _, terminated, truncated, info = self.robot_env.step(action)
         obs = self._get_obs(robot_obs)
-        
+
         reward = self.compute_reward(obs["achieved_goal"], self.goal, info)
 
         if self.remove_task_when_completed:
@@ -411,7 +412,6 @@ def step(self, action):
             if task not in self.episode_task_completions:
                 self.episode_task_completions.append(task)
         info["episode_task_completions"] = self.episode_task_completions
-        self.step_task_completions.clear()
         if self.terminate_on_tasks_completed:
             # terminate if there are no more tasks to complete
             terminated = len(self.episode_task_completions) == len(self.goal.keys())
@@ -425,7 +425,7 @@ def reset(self, *, seed: Optional[int] = None, **kwargs):
         obs = self._get_obs(robot_obs)
         self.tasks_to_complete = set(self.goal.keys())
         info = {
-            "tasks_to_complete": self.tasks_to_complete,
+            "tasks_to_complete": list(self.tasks_to_complete),
             "episode_task_completions": [],
             "step_task_completions": [],
         }
diff --git a/tests/envs/franka_kitchen/test_kitchen_env.py b/tests/envs/franka_kitchen/test_kitchen_env.py
index 23dca2c6..e6616cf6 100644
--- a/tests/envs/franka_kitchen/test_kitchen_env.py
+++ b/tests/envs/franka_kitchen/test_kitchen_env.py
@@ -16,8 +16,7 @@
     [[True, True], [False, False]],
 )
 def test_task_completion(remove_task_when_completed, terminate_on_tasks_completed):
-    """
-    This test checks the different task completion configurations for the FrankaKitchen-v1 environment.
+    """This test checks the different task completion configurations for the FrankaKitchen-v1 environment.
 
     The test checks if the info items returned in each step (`tasks_to_complete`, `step_task_completions`, `episode_task_completions`) are correct and correspond
     to the behavior of the environment configured at initialization with the arguments: `remove_task_when_completed` and `terminate_on_tasks_completed`.
@@ -52,9 +51,6 @@ def test_task_completion(remove_task_when_completed, terminate_on_tasks_complete
             _, _, terminated, _, info = env.step(env.action_space.sample())
             completed_tasks.add(task)
 
-            assert set(info["step_task_completions"]) == {
-                task
-            }, f"The key `step_task_completions` returned by info: {set(info['step_task_completions'])}, must be equal to the tasks completed after the current step: {task}."
             assert (
                 set(info["episode_task_completions"]) == completed_tasks
             ), f"The key `episode_task_completions` returned by info: {set(info['episode_task_completions'])}, must be equal to the tasks along the current episode: {completed_tasks}."
@@ -63,11 +59,17 @@ def test_task_completion(remove_task_when_completed, terminate_on_tasks_complete
                 assert set(info["tasks_to_complete"]) == set(
                     tasks_to_complete
                 ), f"If environment is initialized with `remove_task_when_completed=True` the item `tasks_to_complete` returned by info: {set(info['tasks_to_complete'])}, must be equal to the tasks that haven't been completed yet: {tasks_to_complete}."
+                assert set(info["step_task_completions"]) == {
+                    task
+                }, f"The key `step_task_completions` returned by info: {set(info['step_task_completions'])}, must be equal to the tasks completed after the current step: {task}."
 
             else:
                 assert set(info["tasks_to_complete"]) == set(
                     tasks_to_complete
                 ), f"If environment is initialized with `remove_task_when_completed=False` the item `tasks_to_complete` returned by info: {set(info['tasks_to_complete'])}, must be equal to the set of tasks the environment was initialized with: {tasks_to_complete}."
+                assert (
+                    set(info["step_task_completions"]) == completed_tasks
+                ), f"The key `step_task_completions` returned by info: {set(info['step_task_completions'])}, must be equal to the tasks completed after the current step: {completed_tasks}."
 
         if terminate_on_tasks_completed:
             assert (
@@ -79,43 +81,43 @@ def test_task_completion(remove_task_when_completed, terminate_on_tasks_complete
             ), "If the environment is initialized with `terminate_on_tasks_complete=False`, the episode must not terminate after all tasks are completed."
 
     # Complete a task during the same environment step
-    # for _ in range(3):
-    #     tasks_to_complete = deepcopy(TASKS)
-    #     completed_tasks = set()
-    #     _, info = env.reset()
-
-    #     terminated = False
-
-    #     # Complete a task sequentially for each environment step
-    #     for task in TASKS:
-    #         # Force task to be achieved
-    #         env.data.qpos[OBS_ELEMENT_INDICES[task]] = OBS_ELEMENT_GOALS[task]
-    #         _, _, terminated, _, info = env.step(env.action_space.sample())
-    #         completed_tasks.add(task)
-
-    #     assert (
-    #         set(info["step_task_completions"]) == completed_tasks
-    #     ), f"The key `step_task_completions` returned by info: {set(info['step_task_completions'])}, must be equal to the tasks completed after the current step: {completed_tasks}."
-    #     assert (
-    #         set(info["episode_task_completions"]) == completed_tasks
-    #     ), f"The key `episode_task_completions` returned by info: {set(info['episode_task_completions'])}, must be equal to the tasks along the current episode: {completed_tasks}."
-    #     if remove_task_when_completed:
-    #         assert (
-    #             len(info["tasks_to_complete"]) == 0
-    #         ), f"If environment is initialized with `remove_task_when_completed=True` and all tasks were completed the item `tasks_to_complete` returned by info: {set(info['tasks_to_complete'])}, must be empty."
-
-    #     else:
-    #         assert set(info["tasks_to_complete"]) == set(
-    #             tasks_to_complete
-    #         ), f"If environment is initialized with `remove_task_when_completed=False` the item `tasks_to_complete` returned by info: {set(info['tasks_to_complete'])}, must be equal to the set of tasks the environment was initialized with: {tasks_to_complete}."
-
-    #     if terminate_on_tasks_completed:
-    #         assert (
-    #             terminated
-    #         ), "If the environment is initialized with `terminate_on_tasks_complete=True`, the episode must terminate after all tasks are completed."
-    #     else:
-    #         assert (
-    #             not terminated
-    #         ), "If the environment is initialized with `terminate_on_tasks_complete=False`, the episode must not terminate after all tasks are completed."
+    for _ in range(3):
+        tasks_to_complete = deepcopy(TASKS)
+        completed_tasks = set()
+        _, info = env.reset()
+
+        terminated = False
+
+        # Complete a task sequentially for each environment step
+        for task in TASKS:
+            # Force task to be achieved
+            env.data.qpos[OBS_ELEMENT_INDICES[task]] = OBS_ELEMENT_GOALS[task]
+            completed_tasks.add(task)
+
+        _, _, terminated, _, info = env.step(env.action_space.sample())
+        assert (
+            set(info["step_task_completions"]) == completed_tasks
+        ), f"The key `step_task_completions` returned by info: {set(info['step_task_completions'])}, must be equal to the tasks completed after the current step: {completed_tasks}."
+        assert (
+            set(info["episode_task_completions"]) == completed_tasks
+        ), f"The key `episode_task_completions` returned by info: {set(info['episode_task_completions'])}, must be equal to the tasks along the current episode: {completed_tasks}."
+        if remove_task_when_completed:
+            assert (
+                len(info["tasks_to_complete"]) == 0
+            ), f"If environment is initialized with `remove_task_when_completed=True` and all tasks were completed the item `tasks_to_complete` returned by info: {set(info['tasks_to_complete'])}, must be empty."
+
+        else:
+            assert set(info["tasks_to_complete"]) == set(
+                tasks_to_complete
+            ), f"If environment is initialized with `remove_task_when_completed=False` the item `tasks_to_complete` returned by info: {set(info['tasks_to_complete'])}, must be equal to the set of tasks the environment was initialized with: {tasks_to_complete}."
+
+        if terminate_on_tasks_completed:
+            assert (
+                terminated
+            ), "If the environment is initialized with `terminate_on_tasks_complete=True`, the episode must terminate after all tasks are completed."
+        else:
+            assert (
+                not terminated
+            ), "If the environment is initialized with `terminate_on_tasks_complete=False`, the episode must not terminate after all tasks are completed."
 
     env.close()