diff --git a/psyneulink/library/compositions/emcomposition.py b/psyneulink/library/compositions/emcomposition.py
index 2cfff700cb..b850621760 100644
--- a/psyneulink/library/compositions/emcomposition.py
+++ b/psyneulink/library/compositions/emcomposition.py
@@ -2736,7 +2736,7 @@ def _identify_target_nodes(self, context)->list:
     def infer_backpropagation_learning_pathways(self, execution_mode, context=None):
         if self.concatenate_queries:
             raise EMCompositionError(f"EMComposition does not support learning with 'concatenate_queries'=True.")
-        super().infer_backpropagation_learning_pathways(execution_mode, context=context)
+        return super().infer_backpropagation_learning_pathways(execution_mode, context=context)
 
     def do_gradient_optimization(self, retain_in_pnl_options, context, optimization_num=None):
         # 7/10/24 - MAKE THIS CONTEXT DEPENDENT:  CALL super() IF BEING EXECUTED ON ITS OWN?
diff --git a/tests/composition/test_emcomposition.py b/tests/composition/test_emcomposition.py
index 1ae497034b..e70a683a7c 100644
--- a/tests/composition/test_emcomposition.py
+++ b/tests/composition/test_emcomposition.py
@@ -340,12 +340,8 @@ def test_field_args_and_map_assignments(self,
 
         # Validate targets for target_fields
         np.testing.assert_allclose(em.target_fields, [True, False, False, True, True])
-        # learning_components = em.infer_backpropagation_learning_pathways(pnl.ExecutionMode.Python)
         learning_components = em.infer_backpropagation_learning_pathways(pnl.ExecutionMode.PyTorch)
-        # FIX:  FOLLOWING LINE SHOULDN'T BE NEEDED
-        learning_components = [node for node in em.nodes if 'TARGET' in node.name]
         assert len(learning_components) == 3
-
         assert 'TARGET for KEY A [RETRIEVED]' in learning_components[0].name
         assert 'TARGET for KEY VALUE [RETRIEVED]' in learning_components[1].name
         assert 'TARGET for VALUE LEARN [RETRIEVED]' in learning_components[2].name