Table 4 Summary of prediction parameters and predictive power.

Construct prediction summary	PLS Model
Construct prediction summary	RMSE	MAE	Q²_predict
ICT	0.946	0.730	0.180
SI	0.970	0.739	0.151
OMNIC	0.956	0.754	0.166
VCC	0.962	0.708	0.153

Indicator prediction summary	PLS Model			LM		[PLS-LM]
Indicator prediction summary	RMSE	MAE	Q²_predict	RMSE	MAE	ΔRMSE	ΔMAE
ICT_1	1.189	0.935	0.113	1.259	0.994	−0.070	−0.059
ICT_2	1.685	1.375	0.049	1.737	1.406	−0.052	−0.030
ICT_3	1.746	1.462	0.104	1.857	1.530	−0.111	−0.068
ICT_4	1.426	1.134	0.041	1.495	1.190	−0.069	−0.056
ICT_5	1.371	1.111	0.226	1.461	1.130	−0.090	−0.019
SI_1	1.253	0.916	0.070	1.296	0.947	−0.043	−0.031
SI_2	1.044	0.784	0.100	1.103	0.845	−0.059	−0.062
SI_3	1.286	0.994	0.139	1.323	1.033	−0.037	−0.038
SI_4	1.161	0.917	0.117	1.218	0.973	−0.057	−0.056
OC_1	1.304	0.858	0.088	1.370	0.896	−0.067	−0.038
OC_3	1.711	1.394	0.092	1.753	1.413	−0.042	−0.019
OC_4	1.900	1.552	0.065	1.907	1.580	−0.007	−0.028
OC_5	1.512	1.262	0.126	1.573	1.322	−0.061	−0.060
OC_6	1.685	1.290	0.082	1.770	1.375	−0.085	−0.086
OC_7	1.614	1.232	0.146	1.672	1.270	−0.058	−0.037
OC_8	1.206	0.947	0.099	1.280	0.997	−0.074	−0.051
Engagement	0.966	0.701	0.088	1.006	0.734	−0.039	−0.033
Learning	0.943	0.746	0.135	0.979	0.763	−0.037	−0.017
Participation	0.931	0.729	0.151	0.954	0.760	−0.023	−0.031
Reciprocity	0.938	0.736	0.135	0.984	0.784	−0.046	−0.048

	Skewness	Error used	Δ[PLS-LM]	Predictive power
ICT_1	−1.022	MAE	−0.059	YES
ICT_2	−0.740	RMSE	−0.052	YES
ICT_3	−0.588	RMSE	−0.111	YES
ICT_4	−0.659	RMSE	−0.069	YES
ICT_5	−0.759	RMSE	−0.090	YES
SI_1	−1.411	MAE	−0.031	YES
SI_2	−0.961	RMSE	−0.059	YES
SI_3	−1.004	MAE	−0.038	YES
SI_4	−0.814	RMSE	−0.057	YES
OC_1	−2.267	MAE	−0.038	YES
OC_3	−0.690	RMSE	−0.042	YES
OC_4	−0.635	RMSE	−0.007	YES
OC_5	−0.728	RMSE	−0.061	YES
OC_6	−1.145	MAE	−0.086	YES
OC_7	−0.996	RMSE	−0.058	YES
OC_8	−0.968	RMSE	−0.074	YES
Engagement	−1.291	MAE	−0.033	YES
Learning	−0.943	RMSE	−0.037	YES
Participation	−1.001	MAE	−0.031	YES
Reciprocity	−0.816	RMSE	−0.046	YES

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