Optimization Research on Interactive Methods of Ideological and Political Education in Colleges and Universities under Intelligent Teaching Environment

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Different methods are compared in the Emo-DB data concentration accuracy

Experimental group	Data set	Processing method	Accuracy rate
A	Emo-DB	3D-CRNN	82.2%
B	Emo-DB	Improved speech processing+2-DCNN	83.9%
C	Emo-DB	DCNN_LSTM	81.1%
D	Emo-DB	DCNN_DTPM	83.9%
E	Emo-DB	ML ELM_AE	81.4%
F	Emo-DB	Ours	87.2%

Video class case basic information statistics

Class	Province	Teacher Number	The Total Number Of Actions (N)	Serial Behavior Number (G)	Behavioral Conversion Rate (G-1)/N	Teaching Model
Class 1	Guizhou	A1	79	26	0.32	Interactive type
	Jiangsu	A2	78	35	0.44	Dialog type
	Shanghai	A3	72	26	0.35	Interactive type
	Ningxia	A4	74	24	0.31	Interactive type
	Shaanxi	A5	80	35	0.43	Dialog type
	Sichuan	A6	76	29	0.37	Interactive type
	Xinjiang	A7	72	25	0.33	Interactive type
Class 2	Anhui	B1	82	37	0.44	Dialog type
	Beijing	B2	84	22	0.25	Interactive type
	Hupei	B3	80	21	0.25	Interactive type
	Jilin	B4	87	23	0.25	Interactive type
	Jiangxi	B5	77	39	0.49	Dialog type
	Liaoning	B6	83	29	0.34	Interactive type
	Qinghai	B7	82	29	0.34	Interactive type
Class 3	Beijing	C1	79	32	0.39	Interactive type
	Guangxi	C2	66	34	0.50	Dialog type
	Hainan	C3	71	23	0.31	Practice type
	Heilongjiang	C4	82	19	0.22	Interactive type
	Inner Mongolia	C5	83	29	0.34	Interactive type
	Yunnan	C6	83	23	0.27	Interactive type
	Chongqing	C7	78	27	0.33	Interactive type
Class 4	Fujian	D1	71	26	0.35	Interactive type
	Guangdong	D2	80	31	0.38	Interactive type
	Hebei	D3	86	31	0.35	Interactive type
	Henan	D4	78	18	0.22	Practice type
	Hunan	D5	75	26	0.33	Interactive type
	Tianjin	D6	81	38	0.46	Dialog type
	Zhejiang	D7	77	27	0.34	Interactive type

The residual difference of the interaction behavior of teachers and students

	1	2	3	4	5	6	7	8	9	10	11	12	13	14
1	3.89	1.27	-0.82	-1.88	-0.61	5.87	0.89	0.14	0.43	-0.96	0.57	-1.9	-0.66	1.38
2	1.28	1	0.3	-0.63	3.35	4.5	-1.25	1.15	-1.52	1.4	-0.98	-1.54	4.6	1.99
3	1.08	-0.72	-0.74	0.26	-0.36	-0.68	1.53	0.42	0.49	1.11	1.46	0.91	-1.69	0.18
4	4.52	-1.17	4.85	11.87	0.06	2	-1.74	0.73	-1.82	-1.55	-0.99	-0.4	-0.14	0.75
5	-0.68	1.98	1.06	-1.03	21.21	-0.71	-0.33	-1.91	0.33	1.49	-0.41	0.2	-0.53	-1.66
6	-0.36	1.59	1.19	-0.68	1.75	4.47	-1.4	0.08	0.55	-1.31	0.19	-0.82	1.84	-1.28
7	0.01	0.91	-0.8	1.21	1.18	-1.35	22.84	-0.51	-0.38	-1.78	-0.71	3.25	-1.42	1.13
8	0.26	1.2	0.25	3.5	1.16	-0.7	0.04	-0.85	-0.08	-1.38	0.85	1.3	0.86	1.38
9	0.83	0.72	-1.98	1.63	0.34	1.56	1.79	-1.51	8.45	4.55	0.45	-1.91	-1.09	1.77
10	1.32	-0.76	0.42	-1.94	1.79	-1.13	-1.88	-1.61	3.6	12.84	-0.64	0.58	0.12	0.91
11	-0.74	-0.55	-1.25	0.45	-1.53	0.9	1.66	-0.89	-1.2	1.27	16.54	-0.45	-0.6	0.07
12	5.64	0.16	-0.17	-1.97	-1.16	-1.95	0.58	-0.44	1.09	-1.88	-1.95	4.87	-0.29	-1.56
13	1.45	0.87	-1.75	1.6	-0.68	3.28	-0.06	0.53	-1.91	-1.87	0.29	-0.02	5.21	-1.86
14	-1.87	0.79	1.05	0.99	-0.17	0.02	-1.67	0.24	-0.7	1.77	0.56	3.64	4.05	0.57

Different methods are compared in the casia data concentration accuracy

Experimental group	Data set	Processing method	Accuracy rate
A	CASIA	3D-DCNN	52.6%
B	CASIA	RestNet	83.4%
C	CASIA	Data enhancement+DCNN+LSTM	75.1%
D	CASIA	CNN+BLSTM	70.2%
E	CASIA	Ours	89.8%