A comparative study of pre-service teachers&#39; perceptions on STEAM education in UK and China

Jingwen He; Shirley Simon; Feng-Kuang Chiang

doi:10.3934/steme.2022020

Article Contents

2022, Volume 2, Issue 4: 318-344. Doi: 10.3934/steme.2022020 open access

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Research article

A comparative study of pre-service teachers' perceptions on STEAM education in UK and China

1.
The Ohio State University, Columbus, OH, USA
2.
Institute of Education, University College London, London, UK
3.
School of Education, Shanghai Jiao Tong University, Shanghai, China

Author Bio: Jingwen He is a PhD student in the Learning Technology program at the Ohio State University, US. She is specialized in quantitative research. Her research interests include motivation, student-teacher relationships, self-regulated learning, and engagement in the virtual learning context; Dr. Shirley Simon is an emeritus professor of science education at University College London Institute of Education, UK. She is specialized in scientific inquiry, cognitive acceleration, teacher learning and professional development. Her current research focuses on argumentation in science, attitudes to science and participation in science; Dr. Feng-Kuang Chiang is a professor at School of Education and the founding director of the Center for Future Education at Shanghai Jiao Tong University, China. He specializes in the innovative use of technology for teaching and learning purposes. His research interests include STEAM education, learning space, ICT in innovative instruction, robotics in education, some cross-disciplinary topics
Email: fkchiang@sjtu.edu.cn; Tel: +86 21 342048851
Email: fkchiang@sjtu.edu.cn; Tel: +86 21 342048851

Academic Editor: William Guo

Received: September 2022

Accepted: December 2022

Published: December 2022

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Abstract

As more countries emphasize the development of science, technology, engineering, art, and mathematics (STEAM) education, the training of professional pre-service teachers has received considerable attention. To explore Chinese and UK preservice teachers' understanding of STEAM education, their willingness to engage in STEAM-related occupations, and their attitudes toward various STEAM disciplines, this study designed a questionnaire to investigate the perceptions of 109 and 379 preservice teachers from the United Kingdom and China, respectively. A quantitative analysis revealed the following: (1) Preservice teachers lacked the understanding of STEAM education in general. (2) Chinese and UK preservice teachers had different overall understandings of STEAM education. (3) Both Chinese and UK preservice teachers had different opinions about the role of art in STEAM. (4) The scores of Chinese preservice teachers in the semantic questionnaire in each discipline were significantly higher than those of the UK teachers, and significant differences in gender and profession were observed. (5) No significant differences were observed between the total scores of the UK and Chinese participants on the career interest questionnaire. Finally, we combined the experiences of the Chinese and UK preservice teachers to provide recommendations for teacher training.

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Figure 1. The perceptions, attitudes, future career interest, and reflected teaching ability in STEAM education of Chinese and UK preservice teachers

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Table 1. Description of participants' demographic information

	Descriptions	UK	China
Gender	Male	42 (38.5%)	108 (28.5%)
	Female	65 (59.6%)	269 (71.0%)
	Missing	2 (1.8%)	2 (0.5%)
Age	under 20	0	266 (70.2%)
	21-25	71 (65.1%)	106 (28.0%)
	26-30	17 (15.6%)	1 (0.3%)
	over30	21 (19.3%)	1 (0.3%)
	Missing	0	5 (1.3%)
Education	Math	20 (18.3%)	64 (16.9%)
Background	Science (physics,	34 (31.2%)	190 (50.1%)
	chemistry, geography,
	biology)
	Humanities (English,	28 (25.7%)	22 (5.8%)
	History, Music,
	Anthropology)
	Education Technology	0	45 (11.9%)
	Computer science	0	52 (13.7%)
	Others	8 (7.3%)	6 (1.6%)
	Missing	19 (17.4%)	0
Teaching	Yes	58 (53.2%)	144 (38.0%)
experiences	No	50 (45.9%)	231 (60.9%)
	Missing	1 (0.9%)	4 (1.1%)
The willingness to be a teacher	Yes	97 (89.0%)	179 (47.2%)
	No	12 (11.0%)	42 (11.1%)
	Haven't decided	0	150 (39.6%)
	Missing	0	8 (2.1%)
The grade you will	Primary school	2 (1.8%)	38 (10.0%)
teach	Secondary school	98 (89.9%)	161 (85.2%)
	Tertiary Education	9 (8.3%)	180 (47.5%)
The subject you	Math	59 (54.1%)	61 (16.1%)
will teach	Science	35 (32.1%)	104 (27.4%)
	Others	15 (13.8%)	214 (56.5%)

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Table 2. STEAM visualizations and explanations (modified from [31])

Type	Visualization	Explanation
(1) Nested		Nested visualizations conveyed that STEAM was an overarching discipline comprising five disciplines.
(2) Interconnected		Interconnected visualizations conveyed that there were connections between each of the five disciplines.
(3) Overlapping		Overlapping visualizations used a Venn diagram to convey that the disciplines were overlapping.
(4) Sequential		Sequential visualizations conceived of STEAM as disciplines in a sequence.
(5) Art independent		Art independent visualizations conveyed that there were connections among STEM's four disciplines, but that art was independent.
(6) Siloed		Siloed visualizations portrayed the manner in which STEM has been historically taught in schools—in isolation of each other.
(7) Transdisciplinary		Transdisciplinary visualizations suggested a focus on the real-world, application-based nature of STEM.
(8) Pot		Pot visualizations compared STEAM education to vapor from a pot.
(9) Other		Responses cannot be classified in the above categories.

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Table 3. Perceived connectedness of STEAM disciplines

Scale^a	# (UK)	%	# (China)	%
9	9	8.3	16	4.2
8	14	12.8	63	16.6
7	29	26.6	132	34.8
6	24	22.0	45	11.9
5	13	11.9	90	23.7
4	7	6.4	14	3.7
3	4	3.7	13	3.4
2	2	1.8	2	.5
1	1	.9	2	.5
Missing	6	5.5	2	.5
Total	109		379
^a Scale 1-9;choosing 9 indicates the view that STEAM disciplines are completely connected

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Table 4. Conceptual understanding of STEAM connectedness

Theme	Coding frequency	#(UK)	%	#(CHINA)	%
Specialized	Negate art	13	20.3	13	4.5
Specialized	Process	12	18.8	12	4.1
Specialized	Approve art	5	7.8	3	1.0
Specialized	Dependent	2	3.1	9	3.1
Specialized	Ranked	0	0	9	3.1
General	Related	8	12.5	101	34.8
General	Related, but unique	7	10.9	66	22.8
General	Related, process	3	4.7	21	7.2
General	Related, negate art	3	4.7	20	6.9
General	Related, dependent	2	3.1	18	6.2
General	Related, ranked	0	0	15	5.2
General	Unrelated	2	3.1	0	0
Other	Vague	7	10.9	15	5.2
	Total	64		290

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Table 5. STEAM visualizations, explanations, frequency, and percentages

Type	#(UK)	%	#(CHINA)	%
(1) Nested	11	16.2	44	22.2
(2) Interconnected	6	8.8	61	30.8
(3) Overlapping	1	1.5	48	24.2
(4) Sequential	1	1.5	12	6.1
(5) Art independent	7	10.3	21	10.6
(6) Siloed	15	22.1	0	0
(7) Transdisciplinary	11	16.2	0	0
(8) Pot	8	11.8	0	0
(9) Other	8	11.8	12	6.1
Total	68		198

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Table 6. Preservice teacher rationale of visual representations

Code	#(UK)	%	#(CHINA)	%
Application	2	4.0	0	0
Art independent	2	4.0	31	11.0
Dependent	2	4.0	96	34.2
Independent	4	8.0	3	1.1
Related	14	28.0	71	25.3
Related, dependent, ranked	7	14.0	75	26.7
Related ranked	6	12.0	0	0
Vague	7	14.0	0	0
None	6	12.0	5	1.8

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Table 7. Characteristics of STEAM

UK			China
Characteristics	#	%	Characteristics	#	%
Creative	16	22.5	Integrated	126	29.8
Real life	9	12.7	Practical	59	13.9
Inspiring	6	8.5	Fun	40	9.5
Science	6	8.5	Creative	37	8.7
Art	5	7.0	Professional	37	8.7
Technology	4	5.6	Logical	34	8.0
Engineering	4	5.6	popularize	32	7.6
Math	4	5.6	Scientific	26	6.1
Logical	4	5.6	contemporary	10	2.4
Academic	4	5.6	Knowledgeable	8	1.9
Necessary	3	4.2	Project-based learning	5	1.2
Making	3	4.2	Effective	3	0.7
Other	3	4.2	Other	6	1.4
Total	71 words		Total	423 words

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Table 8. Career Interest Questionnaire scales and STEAM semantic survey scales

		N	Mean	Std. dev.	Sig.
Career Interest Questionnaire scales
Career interest-total scale score	UK	91	3.46	.75	.985
	China	379	3.46	.72
Career interest – education	UK	99	3.17	1.06	.013^*
	China	379	3.44	.92
Career interest – support	UK	95	3.43	.79	.076
	China	379	3.27	.79
Career interest – career	UK	97	3.81	.82	.165
	China	379	3.68	.83
STEAM semantic survey scales
Science average	UK	92	3.73	.54	.000^***
	China	379	5.58	1.07
Math average	UK	94	4.01	.82	.000^***
	China	379	5.10	1.38
Engineer average	UK	93	4.00	.73	.000^***
	China	379	4.62	1.27
Technology average	UK	90	3.89	.75	.000^***
	China	379	5.09	1.26
Art average	UK	91	3.94	.76	.000^***
	China	379	5.80	1.25
Career average	UK	92	4.08	.80	.000^***
	China	379	5.07	1.16
Note. ^p < .05; ^p < .01; ^**p < .001, same below.

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Table 9. Analysis by gender for career interest and semantic survey in United Kingdom and China

		UK				China
		N	Mean	SD	Sig.	N	Mean	SD	Sig.
Career Interest Questionnaire scales
Career interest-total scale score	Male	34	3.43	.90	.686	108	3.51	.74	.273
	Female	55	3.49	.65	.686	269	3.45	.71
Career interest – education	Male	39	3.21	1.12	.842	108	3.52	.97	.645
	Female	58	3.16	1.03	.842	269	3.41	.90
Career interest – supports	Male	36	3.36	.90	.467	108	3.30	.77	.794
	Female	57	3.49	.73	.467	269	3.26	.80
Career interest – career	Male	36	3.83	.99	.835	108	3.70	.84	.462
	Female	59	3.80	.71	.835	269	3.67	.82
STEAM semantic survey scales
Science average	Male	35	3.59	.45	.070	108	5.67	1.11	.292
	Female	55	3.80	.56	.070	269	5.54	1.05	.292
Math average	Male	35	4.17	.96	.152	108	5.24	1.32	.226
	Female	57	3.92	.73	.152	269	5.05	1.40	.226
Engineer average	Male	35	3.83	.69	.086	108	5.15	1.42	.524
	Female	56	4.11	.75	.086	269	5.06	1.18	.524
Technology average	Male	34	3.69	.59	.044^*	108	4.74	1.41	.241
	Female	54	4.02	.82	.044^*	269	4.57	1.21	.241
Art average	Male	35	3.89	.78	.783	108	5.26	1.54	.000^***
	Female	54	3.94	.74	.783	269	6.02	1.04	.000^***
Career average	Male	34	4.16	1.01	.497	108	4.99	1.31	.356

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Table 10. Analysis by major for semantic survey in the United Kingdom

		N	Mean	Std. dev.	Sig.
Career interest-total scale score	Math	15	3.34	.52	.003^**
	Science	30	3.81	.69
	Humanity and Arts	25	3.16	.86
	Other	8	2.97	.50
Career interest – education	Math	18	3.11	1.00	.002^**
	Science	31	3.69	.93
	Humanity and Arts	26	2.82	1.03
	Other	8	2.42	1.15
Career interest – support	Math	17	3.33	.59	.011^*
	Science	30	3.72	.69
	Humanity and Arts	25	3.27	.93
	Other	8	2.75	.79
Career interest – career	Math	17	3.80	.59	.129
	Science	31	3.99	.76
	Humanity and Arts	26	3.46	1.04
	Other	8	3.75	.66
STEAM semantic survey scales
Science average	Math	16	3.76	.46	< .001^***
	Science	27	3.52	.35
	Humanity and Arts	27	3.84	.49
	Other	7	4.37	.78
Math average	Math	16	4.36	1.31	.165
	Science	28	3.81	.52
	Humanity and Arts	27	3.99	.58
	Other	8	4.02	.69
Technology average	Math	15	3.96	.84	.035^*
	Science	27	3.70	.56
	Humanity and Arts	27	3.92	.65
	Other	7	4.43	1.49
Engineering average	Math	15	4.29	.82	.169
	Science	28	3.75	.61
	Humanity and Arts	27	4.02	.70
	Other	8	4.50	1.10
Art average	Math	14	4.41	1.00	.043^*
	Science	28	3.99	.73
	Humanity and Arts	27	3.73	.73
	Other	7	3.63	.56
Career average	Math	15	4.65	1.19	.002^**
	Science	27	3.75	.61
	Humanity and Arts	27	3.86	.64
	Other	8	4.28	.58

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Table 11. Analysis by major for career interest and semantic survey in China

		N	Mean	Std. dev.	Sig.
Career interest-total scale score	Biology	68	3.29	.67	.008^**
	Physics	36	3.60	.77
	Chemistry	31	3.49	.70
	Math	63	3.60	.76
	Computer science	52	3.52	.70
	Science and Technology Education	20	3.90	.53
	Astronomy	17	3.48	.97
	Geography	38	3.30	.58
	Education Technology	25	3.38	.60
	Other	29	3.18	.76
Career interest – education	Biology	68	3.23	.81	< .001^***
	Physics	36	3.67	.95
	Chemistry	31	3.46	.90
	Math	63	3.72	.96
	Computer science	52	3.54	.95
	Science and Technology Education	20	3.90	.76
	Astronomy	17	3.51	1.19
	Geography	38	3.17	.65
	Education Technology	25	3.31	.63
	Other	29	2.89	1.07
Career interest – support	Biology	68	3.10	.78	.132
	Physics	36	3.30	.84
	Chemistry	31	3.20	.88
	Math	63	3.42	.78
	Computer science	52	3.33	.76
	Science and Technology Education	20	3.67	.67
	Astronomy	17	3.25	.80
	Geography	38	3.24	.69
	Education Technology	25	3.24	.75
	Other	29	3.03	.91
Career interest – career	Biology	68	3.55	.78	.243
	Physics	36	3.85	.87
	Chemistry	31	3.81	.73
	Math	63	3.66	.87
	Computer science	52	3.69	.82
	Science and Technology Education	20	4.12	.66
	Astronomy	17	3.67	1.12
	Geography	38	3.51	.74
	Education Technology	25	3.60	.67
	Other	29	3.62	.96
STEAM semantic survey scales
Science average	Biology	68	5.69	.98	< .001^***
	Physics	36	6.06	1.03
	Chemistry	31	5.63	1.05
	Math	63	5.51	.98
	Computer science	52	5.28	1.08
	Science and Technology Education	20	5.87	.82
	Astronomy	17	6.31	.83
	Geography	38	5.41	.84
	Education Technology	25	5.30	1.40
	Other
Math average	Biology	68	5.10	1.21	< .001^***
	Physics	36	5.36	1.36
	Chemistry	31	4.64	1.52
	Math	63	5.86	1.02
	Computer science	52	4.99	1.47
	Science and Technology Education	20	5.42	1.09
	Astronomy	17	4.94	1.04
	Geography	38	4.87	1.32
	Education Technology	25	4.89	1.42
	Other	29	4.16	1.73
Technology average	Biology	68	5.09	1.20	.027^*
	Physics	36	5.48	1.20
	Chemistry	31	5.14	1.06
	Math	63	4.99	1.36
	Computer science	52	5.11	1.19
	Science and Technology Education	20	5.63	.93
	Astronomy	17	4.96	1.41
	Geography	38	5.26	.89
	Education Technology	25	4.85	1.55
	Other	29	4.39	1.53
Engineering average	Biology	68	4.46	1.20	.024^*
	Physics	36	4.95	1.33
	Chemistry	31	4.49	1.28
	Math	63	4.64	1.29
	Computer science	52	4.50	1.16
	Science and Technology Education	20	5.13	.75
	Astronomy	17	4.98	1.38
	Geography	38	4.68	1.20
	Education Technology	25	4.93	1.27
	Other	29	3.93	1.54
Art average	Biology	68	5.83	1.24	.888
	Physics	36	5.54	1.45
	Chemistry	31	5.85	1.23
	Math	63	5.87	1.24
	Computer science	52	5.78	1.21
	Science and Technology Education	20	5.76	1.05
	Astronomy	17	5.74	1.65
	Geography	38	6.05	.80
	Education Technology	25	5.85	1.33
	Other	29	5.57	1.43
Career average	Biology	68	4.83	1.19	.001^***
	Physics	36	5.48	1.19
	Chemistry	31	5.26	.88
	Math	63	5.32	1.12
	Computer science	52	4.84	1.10
	Science and Technology Education	20	5.62	.68
	Astronomy	17	5.25	1.48
	Geography	38	5.10	.91
	Education Technology	25	4.90	1.42
	Other	29	4.46	1.30

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Table 12. Model significance for STEAM semantic disposition measures predicting career interest (China)

	Unstandardized Coefficients		Standardized Coefficients	t	Sig.
	B	Std. Error	Beta	t	Sig.
Constant	1.676	.209		8.002	< .001
Science	.033	.035	.048	.939	.348
Math	-.007	.024	-.013	-.271	.787
Technology	-.044	.034	-.077	-1.308	.192
Engineering	.044	.031	.077	1.407	.160
Art	-.024	.026	-.042	-.930	.353
Career	.354	.032	.574	11.026	< .001

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Table 13. Preservice Teachers' Reporting on STEAM Teachers' Abilities

Codes	#(UK)	%	#(China)	%
1. Have comprehensive knowledge	17	15.6	92	24.3
2. Professional knowledge	8	7.3	42	11.1
3. Integrate interdisciplinary knowledge	2	1.8	29	7.7
4. Innovation ability	23	21.1	28	7.4
5. Be an interesting teacher	1	0.9	19	5.0
6. Logic thinking ability	10	9.2	17	4.5
7. Communication ability	5	4.6	14	3.7
8. Teaching skills	2	1.8	9	2.4
9. Practical ability	0	0.0	8	2.1
10. Make connections between knowledge and real life	2	1.8	2	0.5
11. Problem solving skills	6	5.5	1	0.3
12. Determined	4	3.7	0	0
13. Patience	3	2.8	0	0
14. Open attitude	2	1.8	0	0
15. No idea	1	0.9	35	9.2
16. Missing	23	21.1	83	21.9
17. Total	109		379

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