diff --git a/common/lib/xmodule/xmodule/capa_module.py b/common/lib/xmodule/xmodule/capa_module.py
index ca7e052e7e..e1e023c185 100644
--- a/common/lib/xmodule/xmodule/capa_module.py
+++ b/common/lib/xmodule/xmodule/capa_module.py
@@ -783,7 +783,7 @@ class CapaModule(CapaFields, XModule):
         self.system.track_function('save_problem_check', event_info)
 
         if hasattr(self.system, 'psychometrics_handler'):  # update PsychometricsData using callback
-            self.system.psychometrics_handler(self.get_instance_state())
+            self.system.psychometrics_handler(self.get_state_for_lcp())
 
         # render problem into HTML
         html = self.get_problem_html(encapsulate=False)
diff --git a/lms/djangoapps/psychometrics/psychoanalyze.py b/lms/djangoapps/psychometrics/psychoanalyze.py
index 3e9edcc997..093051a3bd 100644
--- a/lms/djangoapps/psychometrics/psychoanalyze.py
+++ b/lms/djangoapps/psychometrics/psychoanalyze.py
@@ -246,13 +246,16 @@ def generate_plots_for_problem(problem):
         yset['ydat'] = ydat
 
         if len(ydat) > 3:         # try to fit to logistic function if enough data points
-            cfp = curve_fit(func_2pl, xdat, ydat, [1.0, max_attempts / 2.0])
-            yset['fitparam'] = cfp
-            yset['fitpts'] = func_2pl(np.array(xdat), *cfp[0])
-            yset['fiterr'] = [yd - yf for (yd, yf) in zip(ydat, yset['fitpts'])]
-            fitx = np.linspace(xdat[0], xdat[-1], 100)
-            yset['fitx'] = fitx
-            yset['fity'] = func_2pl(np.array(fitx), *cfp[0])
+            try:
+                cfp = curve_fit(func_2pl, xdat, ydat, [1.0, max_attempts / 2.0])
+                yset['fitparam'] = cfp
+                yset['fitpts'] = func_2pl(np.array(xdat), *cfp[0])
+                yset['fiterr'] = [yd - yf for (yd, yf) in zip(ydat, yset['fitpts'])]
+                fitx = np.linspace(xdat[0], xdat[-1], 100)
+                yset['fitx'] = fitx
+                yset['fity'] = func_2pl(np.array(fitx), *cfp[0])
+            except Exception as err:
+                log.debug('Error in psychoanalyze curve fitting: %s' % err)
 
         dataset['grade_%d' % grade] = yset
 
@@ -302,12 +305,12 @@ def make_psychometrics_data_update_handler(course_id, user, module_state_key):
     Construct and return a procedure which may be called to update
     the PsychometricsData instance for the given StudentModule instance.
     """
-    sm = studentmodule.objects.get_or_create(
-        course_id=course_id,
-        student=user,
-        module_state_key=module_state_key,
-        defaults={'state': '{}', 'module_type': 'problem'},
-    )
+    sm, status = StudentModule.objects.get_or_create(
+                       course_id=course_id,
+                       student=user,
+                       module_state_key=module_state_key,
+                       defaults={'state': '{}', 'module_type': 'problem'},
+                 )
 
     try:
         pmd = PsychometricData.objects.using(db).get(studentmodule=sm)
@@ -329,7 +332,11 @@ def make_psychometrics_data_update_handler(course_id, user, module_state_key):
             return
 
         pmd.done = done
-        pmd.attempts = state['attempts']
+        try:
+            pmd.attempts = state.get('attempts',0)
+        except:
+            log.exception("no attempts for %s (state=%s)" % (sm,sm.state))
+
         try:
             checktimes = eval(pmd.checktimes)                   # update log of attempt timestamps
         except: