Table 1 Learning Model Results (Sessions 2 to 4).

Model	Fixed effects	Estimate	SE	z-value	p-value
Mandarin recall	(Intercept)	− 0.544	0.226	− 2.406	0.016*
	Baseline recall score	9.046	0.653	13.843	< 0.001*
	Session	1.520	0.099	15.295	< 0.001*
	Treatment	− 0.116	0.226	− 0.514	0.607
	Session × treatment	− 0.089	0.124	− 0.716	0.474
Arabic recall	(Intercept)	− 1.822	0.252	− 7.226	< 0.001*
	Baseline recall score	14.509	1.052	13.798	< 0.001*
	Session	1.312	0.083	15.875	< 0.001*
	Treatment	0.532	0.238	2.234	0.025*
	Session × treatment	− 0.116	0.096	− 1.202	0.229
Mandarin recognition RT	(Intercept)	7.306	0.060	121.370	< 0.001*
Mandarin recognition RT	Session	− 0.101	0.018	− 5.503	< 0.001*
	Treatment	0.013	0.082	0.163	0.871
	Session × treatment	− 0.028	0.026	− 1.075	0.282
Arabic recognition RT	(Intercept)	7.355	0.052	141.366	< 0.001*
Arabic recognition RT	Session	− 0.106	0.013	− 8.134	< 0.001*
	Treatment	− 0.042	0.071	− 0.597	0.551
	Session × treatment	0.014	0.018	0.783	0.434

Estimates refers to unstandardized regression weights.
Final random effects (all models): (Session | Participant) + (Session + Treatment | Item).
n obs = 12300, n items = 100, n participants = 41 for Mandarin Recall model.
n obs = 10800, n items = 100, n participants = 36 for Arabic Recall model.
n obs = 11021, n items = 100, n participants = 40 for Mandarin Recognition RT model.
n obs = 9232, n items = 100, n participants = 36 for Arabic Recognition RT model.

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