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Article

Comparison of Four Universities on Both Sides of the Taiwan Strait Regarding the Cognitive Differences in the Transition from STEM to STEAM in Design Education

by
Yikang Sun
1,
Chien-Chih Ni
2,* and
Yen-Yu Kang
3,*
1
College of Art & Design, Nanjing Forestry University, Nanjing 210037, China
2
Department of Fashion Design, Hsuan Chuang University, Hsinchu City 30092, Taiwan
3
Department of Industrial Design, National Kaohsiung Normal University, Kaohsiung City 82444, Taiwan
*
Authors to whom correspondence should be addressed.
Educ. Sci. 2023, 13(3), 241; https://doi.org/10.3390/educsci13030241
Submission received: 5 December 2022 / Revised: 4 February 2023 / Accepted: 22 February 2023 / Published: 24 February 2023
(This article belongs to the Special Issue From Hi-Tech to Hi-Touch: A Global Perspective of Design Education and Practice)
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Versions Notes

Abstract

:
There have been many studies on the effectiveness of the STEAM model since its integration into design education, but further investigation is needed to determine whether teachers and students truly understand the meaning of STEAM. The aim of this study is to evaluate people’s perceptions of the STEAM model in design education. Respondents from four universities on both sides of the Taiwan Strait participated in the study. Following expert evaluation and a number of tests, the revised questionnaire was used to survey the attitudes of respondents. The results indicate the following: (1) Respondents were more familiar with universities in their area and therefore rated them relatively highly. While this is reasonable, it suggests that respondents may lack a global perspective. (2) The proportion of arts courses is generally high, but further analysis is required to determine whether they in fact play a role in connecting to STEM. This study concluded that educators and researchers need to have a deep understanding of the essence and connotations of STEAM. Students must also consider how to acquire the knowledge and skills needed for 21st-century design through STEAM courses. Furthermore, the use of STEAM in design education needs to be continuously evaluated and improved.

1. Introduction

From the Bauhaus to the Ulm School of Design, the principles of modern design have been established to have a lasting impact [1,2,3,4,5,6,7,8,9]. The philosophy of modern design emphasizes the importance of benefiting people over products, and human-centered design is prevalent in the design of products. Therefore, for “product”, “design”, and “evaluation”, the focus is always on humans. These principles are also followed when evaluating products or designs [10]. Similarly, the above points apply to the development and application of the model of design education [11,12]. To achieve benign and sustainable development, it is important to continuously adjust the design education model to meet the needs of the times. As far as design education is concerned, the goal is to implement the essence of design, and to adjust how design responds to technological development and social change [13,14,15].
Although the core of design education is still influenced by the Bauhaus [16,17,18], it is worth considering how design education should develop in the future; moreover, the concept and mode of design education also need to be dynamically adjusted, so that the essence and spirit of design can be fully reflected [19]. Additionally, the revision and improvement of the design education model need to answer questions posed by industry. If there is a disconnect between teaching and the practical application of the knowledge and skills, it is difficult for design schools to train students to achieve the competencies they require as designers [20,21,22,23].
Design has changed a significant amount during the 21st century, which means that its educational model also needs to be continuously updated [24,25]. STEAM (science, technology, engineering, arts, and mathematics) was used as the theoretical framework of this study; along with questionnaires and analyses, this framework allowed us to examine the current state of STEAM in design education, as well as to understand the cognitive differences between respondents in terms of the STEAM attributes they valued [26].
Taiwan shares the same cultural background as the Chinese mainland, and its modern design is also influenced by the Bauhaus. Additionally, with the deepening of academic exchanges, Taiwan and the Chinese mainland also learn from each other in the field of design education. Previous research has given us the opportunity to understand the strengths, features, and implications of Taiwan and China’s design education [27,28,29,30,31].
This article is part of a series of studies. A previously completed study, which is undergoing peer review, analyzed Taiwanese respondents’ perceptions of the use of the STEAM model in design education. Thus, this article will conduct research from another angle, analyzing the different views on the same topic among respondents from four universities on both sides of the Taiwan Strait; additionally, it considers the possible reasons for these differences.

2. Theoretical Framework: A Transition from STEM to STEAM with the Support of Art as a Glue

The introduction and research on the basic concept, scope, and core concepts of STEM (science, technology, engineering, and mathematics) and STEAM have attracted much attention from the academic community, and successive published studies have provided strong theoretical support for this research [32,33,34,35,36,37,38,39,40,41,42]. It is unnecessary to rehearse these studies here; we review them only to provide clarification on a central issue, namely, that art has played a huge role in this transformation. If Bauhaus advocated “a new unity, between art and technology”, then STEAM advocated the use of art to further unite the principles and methods of technology and science. The purpose of this research is to provide students, designers, and design educators with a means of creating creative products that are more aligned with the arts and humanities. Art will become a key element connecting the other four dimensions (i.e., S, T, E, and M), which will enhance the artistic and humanistic associations of creative products.
STEM is a broad term used to group together these diverse academic disciplines. This term is typically used to address education policies or curriculum choices. The acronym STEM was suggested by Rita Colwell, Ph.D., a bacteriologist who was the director of the NSF in the 1980s [43]. The framework of STEAM derived from STEM, adding the category of art to the original STEM, emphasizing that future students should develop their humanistic and artistic literacy (Humart = human + art) and interdisciplinary abilities. In short, the STEAM framework integrates art and humanity into “rationality and objectivity” [44], and uses art, culture, and humanity to connect to the rational STEM to form a strategy and mode of thinking (see Figure 1).
In summary, STEM focuses on the technical and methodological aspects, while STEAM is a strategy and concept strongly tied to the formation of an art-centered theoretical framework. Many studies also provide strong evidence [45,46,47,48,49]. Art plays a crucial role in connecting the other four attributes in STE(A)M, and becomes the core of this system. “Art” is a very broad concept, and this study argues that it also has cultural implications [50,51].
As discussed in the above, the STEAM model has been applied to education and training. For example, the formulation and application of STEAM education policies allow STEAM to be quickly promoted in teaching in related fields, and in turn examine the rationality and appropriateness of policies [38,52,53,54]. A large number of specific application examples, as well as critical thinking on the STEAM model, provide a solid foundation for selecting STEAM as the core theoretical framework in this study [28,55,56,57,58,59,60,61,62,63,64].
Another reason for conducting this study as a pilot study is to find out how people differ in their perceptions of STEAM and the relationship between the STEAM model and design education. How is the impact being made? STEAM, which is seen as a new driver, is also essential to ensure that it works as it is intended and can be corrected at any time based on audience feedback [65,66].

3. Materials and Methods

3.1. Hypotheses

Considering that this study aims to examine the application of STEAM in design education, we selected respondents who are either teachers or students at different design schools. Thus, the research hypothesis is focused on the field of design education in universities. Based on the objectives of the study, as well as a literature review, this study proposes the following hypotheses:
Hypothesis 1 (H1).
Respondents who have no study abroad or exchange student experience, may only be familiar with the sample of their country or region, so they will give them a high rating;
Hypothesis 2 (H2).
Two U.S. universities (RISD and MIT Media Lab) in the sample may be relatively unfamiliar to respondents if they have no experience studying abroad. In this case, the respondents’ evaluation will be relatively low;
Hypothesis 3 (H3).
Respondents from Taiwan are more familiar with STEAM, which leads them to rate the use of STEAM in six universities more highly.

3.2. Procedures

This study involved the use of a questionnaire analysis to determine respondents’ views on the use of STEAM in design education. In order to better focus on the sub-topics to be explored, the data obtained from the questionnaire were analyzed from different perspectives. Therefore, the data collected in the questionnaire were used multiple times, and may be cross-compared in different articles.
The study is divided into three parts (see Figure 2). In part I, a literature review is used to elucidate the difference between STEM and STEAM, and the relationship between STEAM and design education is explored. In part II, experts from the field of design were invited to conduct interviews, and design schools/laboratories from six universities were selected as samples. Once the questionnaire was designed, the researchers invited several experts in the field of design to review the questionnaire and tested it on a small scale. The questionnaire was revised based on comments provided by experts and interviewees. In part III, in addition to descriptive statistics, this study focuses on what is attributed to possible cognitive differences between respondents from four universities on both sides of the Taiwan Strait. Meanwhile, respondents’ familiarity with the relevant university is regarded as self-variable, and the differences are analyzed after grouping, to better capture the cognitive differences between different categories of respondents.

3.3. Samples and Their Curriculum

In this study, researchers selected six universities with design colleges or laboratories as samples: (1) the Academy of Art & Design, Tsinghua University, (2) the College of Design and Innovation, Tongji University, (3) the College of Design, National Taiwan University of Arts, (4) the College of Design, National Taiwan University of Science and Technology, (5) the Rhode Island School of Design, and (6) the MIT Media Lab (see Table 1).
Our selection of these six universities for this study is based on the fact that three of them concentrate on the arts and humanities, and the other three focus on the field of science and technology. This division enables this study to better explore the use of the STEAM model and the current situation of design education in art or technical universities.
Additionally, to ensure the reliability of the sample, focus group interviews (FGIs) made up of several experts in the field of art and design identified the above six universities as a sample. These experts are from the National Taiwan University of Arts. The selection of samples generates a number of challenges. For instance, if the sample is too large, the questionnaire may be too complicated. We use university rankings released by both sides of the Taiwan Strait in recent years as a reference indicator; subsequently, experts identified samples from many universities based on their own experience.
The researchers searched the homepages of design schools at four universities and downloaded their course plans. Although curriculum plans may not be complete (e.g., their homepages do not updated curriculum information in a timely manner), this study believes that these curriculum plans still have reference value. The analysis of these data allows us to understand whether the curriculum planning of design schools in these universities refers to the STEAM model.

3.4. Questionnaire Design and Testing

The questionnaire was divided into two parts: the first part pertained to the respondents’ basic information; in the second part, respondents were asked whether they were focused on STEAM at six universities, and then whether the target schools focused on the five dimensions of STEAM. A 5-point Likert scale was used for the responses, with scores ranging from 1 (“Very low”) to 5 (“Very high”) (see Table 2).
Regarding the first question, we hoped that respondents could make judgments based on their intuition, so no more explanation was given for this question. During the small-scale test, the respondents did not dispute it.
This article aimed to find out how views on STEAM differ among respondents from four universities on both sides of the Taiwan Strait. Therefore, two versions of the questionnaire were generated. The first version was filled in by respondents from the Taiwan area and the Chinese mainland who are not students or graduates of those four universities. The second version was available to teachers, students, or graduates from the four universities. We adjusted the options in age and education level to allow those who have not yet graduated from college to answer the questionnaire.
Following pre-testing and revision, the questionnaire was launched on 26 October 2022. Considering that some respondents may not be able to respond immediately, we extended the time for questionnaire collection appropriately. We checked the questionnaires one by one, focusing on whether there were any indiscriminate or incomplete questionnaires. Following checking, all questionnaires were deemed to be valid. SPSS 28.0 was used to further process and analyze the data.

4. Results and Discussion

4.1. Descriptive Statistics

The data related to the respondents are shown in Table 3:
  • Respondents from the Taiwan area and the Chinese mainland (none of whom were teachers, students, or graduates of the four universities) used the first version of the questionnaire. A total of 128 respondents from Taiwan and 222 respondents from the Chinese mainland participated;
  • Teachers, students, and graduates from four universities used the second version of the questionnaire. There were 115 and 60 respondents from the National Taiwan University of Arts (NTUA) and the National Taiwan University of Science and Technology (NTUST), respectively. There were 35 and 64 respondents from Tsinghua University (THU) in Beijing and Tongji University (TJU) in Shanghai, respectively.
Table
Table 3. All respondents in the experiments.
Table 3. All respondents in the experiments.
VariablesTaiwan Area
(n = 128)		NTUA
(n = 115)		NTUST
(n = 60)		Mainland China
(n = 222)		THU
(n = 35)		TJU
(n = 64)
GenderFemale47/36.7%79/68.7%14/23.3%151/68.02%9/25.71%25/39.06%
Male81/63.3%36/31.3%46/76.7%71/31.98%26/74.29%39/60.94%
Age 118–22/29/25.2%11/18.3%85/38.29%13/37.14%21/32.18%
23–35/18/15.7%11/18.3%111/50%7/20%34/53.13%
26–3518/14.1%17/14.8%4/6.7%///
36–4531/24.2%31/27%12/20%17/7.66%11/31.43%7/10.94%
46–5552/40.6%17/14.8%15/25%5/2.25%4/11.43%/
56–6522/17.2%3/2.6%7/11.7%4/1.8%/2/3.13%
>655/3.9%17/14.8%4/6.7%///
Education levelUniversity Student/33/28.7%8/13.3%77/34.68%12/34.29%15/23.44%
Graduated from University9/7%8/7%18/30%7/3.15%4/11.43%5/7.81%
Masters47/36.7%42/36.5%25/41.7%128/57.66%11/31.43%39/60.94%
Ph.D.72/56.3%32/27.8%9/15%10/4.5%8/22.86%5/7.81%
Do you know STEAM?Yes98/78.4%74/64.3%37/61.7%119/53.6%25/71.43%35/54.69%
No27/21.6%41/35.7%23/38.3%103/46.4%10/28.57%29/45.31%
Studying abroad?
(More than 1 year)		Yes40/31.3%26/22.6%8/13.3%13/5.86%9/25.71%7/10.94%
No88/68.8%89/77.4%52/86.7%209/94.14%26/74.29%57/89.06%
The country or region
where you are studying abroad		United States, Canada20/15.6%14/12.2%3/5%2/0.9%3/8.57%/
Europe4/3.1%6/5.2%2/3.3%4/1.8%3/8.57%3/4.69%
Asia12/9.4%5/4.3%2/3.3%5/2.25%3/8.57%3/4.69%
Australia, New Zealand3/2.3%1/0.9%1/1.7%///
None88/68.8%89/77.4%52/86.7%209/94.14%26/74.29%57/89.06%
Other1/0.8%1/0.9%1/1.7%2/0.9%/1/1.56%
1 The age of the respondents varied between versions of the questionnaire. Therefore, regarding the age variable, the options are slightly different.
The familiarity of the respondents of the six universities is shown in Table 4. It is reasonable to assume that the respondents are familiar with universities in their countries or regions. However, even with samples from the respondents’ country or region, a certain percentage of the respondents were unfamiliar with part or all of the sample. This may have affected their in-depth evaluation of the sample.
In the twenty-first century, students can learn about the current situations in renowned universities in other countries or regions by using the internet, and can also use open-source data to study online. However, this may not be sufficient to give students a comprehensive understanding of a university or of a specific department. However, these benefits are still out of reach for students in economically and socially underdeveloped areas. In fact, even in developed countries or regions, there are still many students who are unable to access the educational resources of other countries or regions due to economic constraints (e.g., some families cannot afford to pay for internet communication). Therefore, this study posits that the reasons for the emergence of the above phenomena are more complex than this one explanation allows. However, it is still necessary for students to take advantage of various opportunities and conditions to expand their international perspectives. In recent years, due to the COVID-19 pandemic, international communication has been restricted, but online communication has developed rapidly, and many universities or research institutions have overhauled their homepages and shared numerous resources. This provides great convenience for students, including teachers.
The respondents’ assessments of whether these six universities focus on STEAM are shown in Table 5. The responses reflect the following trends:
  • Respondents from the four universities may have been objective, rather than simply scoring intuitively. For example, they argued that MIT deserves the highest score in some attributes, which is consistent with the actual situation. This may be related to the prestige of MIT;
  • Some of the respondents were not from the four universities mentioned above. However, these people rated the two universities in their home country relatively highly. For example, respondents from the Taiwan area (teachers, students, and graduates who are not from NTUA and NTUST) rated NTUA and NTUST relatively highly. This may be due to the respondent’s intuitive reaction. For example, if respondents have not studied abroad or even used the internet to learn about other universities, they may have given relatively high ratings to universities in their country or region out of patriotic feelings. However, the situation reflected in the above assessment may also be more consistent with the actual situation. Follow-up studies will further analyze whether this phenomenon is real and the reasons for its occurrence.
Table
Table 5. The mean and std. deviation of the respondents’ assessment of the STEAM model.
Table 5. The mean and std. deviation of the respondents’ assessment of the STEAM model.
Taiwan Area (n = 128)THUTJUNTUANTUSTRISDMIT
Science3.23 (1.233)3.14 (1.085)2.88 (0.988)3.88 (0.944)3.26 (0.941)4.44 (0.903)
MIT > NTUST > RISD > THU > TJU > NTUA
Technology3.26 (1.186)3.23 (1.103)3.16 (1.007)4.16 (0.903)3.34 (0.891)4.50 (0.939)
MIT > NTUST > RISD > THU > TJU > NTUA
Engineering3.16 (1.200)3.15 (1.065)2.58 (1.024)3.97 (0.922)3.26 (0.982)4.38 (0.940)
MIT > NTUST > RISD > THU > TJU > NTUA
Arts3.69 (1.266)3.51 (1.190)4.57 (0.928)3.36 (1.070)3.88 (1.047)3.62 (1.080)
NTUA > RISD > THU > MIT > TJU > NTUST
Mathematics2.94 (1.228)2.99 (1.112)2.35 (0.977)3.45 (0.971)2.97 (0.922)4.21 (0.993)
MIT > NTUST > TJU > RISD > THU > NTUA
NTUA (n = 115)THUTJUNTUANTUSTRISDMIT
Science3.27 (1.15)3.01 (1.158)2.79 (1.039)3.65 (0.937)3.13 (0.996)4.21 (1.055)
MIT > NTUST > THU > RISD > TJU > NTUA
Technology3.36 (1.069)3.27 (1.187)3.20 (1.061)4.00 (0.927)3.37 (1.037)4.26 (1.027)
MIT > NTUST > RISD > THU > TJU > NTUA
Engineering3.22 (1.138)3.14 (1.139)2.80 (1.053)3.77 (0.974)3.08 (0.890)4.19 (1.067)
MIT > NTUST > THU > TJU > RISD > NTUA
Arts4.05 (1.083)3.67 (1.212)4.56 (0.797)3.34 (1.075)3.77 (1.071)3.37 (1.151)
NTUA > THU > RISD > TJU > MIT > NTUST
Mathematics3.10 (1.116)3.01 (1.112)2.42 (1.043)3.41 (1.016)3.06 (1.003)4.10 (1.068)
MIT > NTUST > THU > RISD > TJU > NTUA
NTUST (n = 60)THUTJUNTUANTUSTRISDMIT
Science3.28 (1.166)3.20 (1.117)2.73 (1.071)4.08 (0.979)3.17 (0.977)4.02 (1.066)
NTUST > MIT > THU > TJU > RISD > NTUA
Technology3.53 (1.171)3.23 (1.079)3.05 (0.982)4.20 (1.054)3.28 (1.043)4.13 (1.112)
NTUST > MIT > THU > RISD > TJU > NTUA
Engineering3.20 (1.286)3.23 (1.079)2.98 (1.157)4.12 (1.010)3.35 (1.087)4.10 (1.130)
NTUST > MIT > RISD > TJU > THU > NTUA
Arts3.60 (1.153)3.27 (1.133)4.25 (1.068)3.98 (1.033)3.52 (1.112)3.52 (1.097)
NTUA > NTUST > THU > MIT > RISD > TJU
Mathematics3.13 (1.270)3.10 (1.040)2.73 (1.150)3.73 (1.250)3.17 (1.080)3.93 (1.150)
MIT > NTUST > RISD > THU > TJU > NTUA
Mainland China (n = 222)THUTJUNTUANTUSTRISDMIT
Science2.58 (1.355)2.32 (1.262)2.02 (1.149)2.02 (1.218)1.89 (1.142)2.32 (1.444)
THU > MIT = TJU > NTUA = NTUST > RISD
Technology2.62 (1.379)2.38 (1.336)2.01 (1.165)2.06 (1.252)1.93 (1.200)2.36 (1.485)
THU > TJU > MIT > NTUST > NTUA > RISD
Engineering2.49 (1.338)2.41 (1.378)2.00 (1.146)2.02 (1.224)1.94 (1.189)2.31 (1.457)
THU > TJU > MIT > NTUST > NTUA > RISD
Arts3.32 (1.333)2.81 (1.376)2.35 (1.379)2.07 (1.186)2.28 (1.444)2.24 (1.339)
THU > TJU > NTUA > RISD > MIT > NTUST
Mathematics2.36 (1.340)2.22 (1.270)1.93 (1.113)1.94 (1.134)1.84 (1.114)2.29 (1.471)
THU > MIT > TJU > NTUST > NTUA > RISD
THU (n = 35)THUTJUNTUANTUSTRISDMIT
Science3.17 (1.224)3.11 (1.255)2.37 (1.060)2.69 (1.255)2.71 (1.274)3.71 (1.487)
MIT > THU > TJU > RISD > NTUST > NTUA
Technology3.54 (1.291)3.29 (1.274)2.34 (0.998)2.77 (1.308)2.97 (1.317)3.91 (1.483)
MIT > THU > TJU > RISD > NTUST > NTUA
Engineering3.37 (1.215)3.23 (1.308)2.43 (1.037)2.51 (1.147)2.94 (1.282)3.66 (1.414)
MIT > THU > TJU > RISD > NTUST > NTUA
Arts4.20 (0.933)3.54 (1.314)3.20 (1.410)2.74 (1.245)3.80 (1.410)3.40 (1.288)
THU > RISD > TJU > MIT > NTUA > NTUST
Mathematics2.89 (1.132)2.86 (1.216)2.23 (0.973)2.49 (1.197)2.69 (1.207)3.57 (1.441)
MIT > THU > TJU > RISD > NTUST > NTUA
TJU (n = 64)THUTJUNTUANTUSTRISDMIT
Science3.00 (1.272)2.98 (1.327)2.47 (1.284)2.50 (1.392)2.45 (1.272)3.08 (1.546)
MIT > THU > TJU > NTUST > NTUA > RISD
Technology3.11 (1.323)3.12 (1.315)2.42 (1.270)2.48 (1.380)2.56 (1.446)3.08 (1.515)
TJU > THU > MIT > RISD > NTUST > NTUA
Engineering3.00 (1.297)2.98 (1.303)2.53 (1.345)2.45 (1.308)2.41 (1.342)3.03 (1.469)
MIT > THU > TJU > NTUA > NTUST > RISD
Arts3.64 (1.200)3.44 (1.332)2.92 (1.473)2.47 (1.259)2.89 (1.565)2.95 (1.506)
THU > TJU > MIT > NTUA > RISD > NTUST
Mathematics2.91 (1.411)2.72 (1.303)2.28 (1.175)2.42 (1.355)2.36 (1.326)2.95 (1.527)
MIT > THU > TJU > NTUST > RISD > NTUA
Note: samples that receive the highest ratings on different attributes of STEAM are marked in gray shading.

4.2. Differences in Respondents’ Perceptions

One-way ANOVA was used to determine whether there was any cognitive difference among the respondents from the four universities, and the results are shown in Table 6. It can be seen that, with the exception of TJU, there were significant differences in the respondents’ perceptions of the other five universities with different attributes.
Through in-depth analysis and interpretation of the data, the following characteristics can be found:
  • Respondents from NTUA and NTUST rated both the cognitive differences in the attributes that were highly rated;
  • The standard deviation of some attribute scores was large, indicating that perceptions of them varied widely between respondents.

4.3. The Sample’s Curriculum and Its Relevance to STEAM

This study will further analyze the curricula of these four universities, enabling us understand the real situation of the STEAM model in use in these four universities (see Table 7). The following inferences can be drawn from the curricula of these four universities:
  • With the exception of the Department of Architecture at NTUST, art courses have the highest proportion of different departments at these six universities. Typically, the department of architecture or the school of architecture is relatively independent. Although elements of art are also essential to architecture, they may not be prioritized;
  • Some departments do not offer courses related to science or mathematics. Few departments retain a certain proportion of technology-related courses because they require technical support;
  • Due to the different definitions of course categories in each country or region, and the fact that some courses may be interdisciplinary, there is a certain percentage of courses that cannot be included in any category in STEAM, and can only be temporarily replaced by “Other”. The proportion of these courses is not very low.
Table
Table 7. The curriculum of four universities.
Table 7. The curriculum of four universities.
NTUAScienceTechnologyEngineeringArtsMathematicsOtherTotal
1. Department of Visual Communication Design
Curriculum016 (20.50%)4 (5.12%)32 (41.02%)026 (33.33%)78
Arts > Other > Technology > Engineering
2. Department of Crafts and Design
Curriculum1 (1.02%)6 (6.12%)6 (6.12%)53 (54.08%)1(1.02%)31 (31.63%)98
Arts > Other > Engineering > Technology > Mathematics > Sciences
3. Department of Multimedia and Animation Arts
Curriculum042 (56.75%)1 (1.35%)7 (9.45%)024 (32.43%)74
Technology > Other > Arts > Engineering
4. Curriculum in General Education
Curriculum06 (35.29%)06 (35.29%)05 (29.41%)17
Science = Arts > Other
NTUSTScienceTechnologyEngineeringArtsMathematicsOtherTotal
1. Department of Design
Curriculum023 (28.78%)8 (10%)27 (33.75%)022 (27.5%)80
Arts > Other > Technology > Engineering
2. Department of Architecture
Curriculum05 (8.77%)19 (33.33%)14 (24.56%)5 (8.77%)14 (24.56%)57
Engineering > Other > Arts > Technology = Mathematics
THUScienceTechnologyEngineeringArtsMathematicsOtherTotal
1. Department of Visual Communication
Curriculum04(7.69%)1(1.92%)43 (82.69)04 (7.69%)52
Arts > Technology = Other > Engineering
2. Department of Environmental Art Design
Curriculum2 (3.5%)1(1.75%)8(14.03%)36(63.15%)1(1.75%)9(15.78%)57
Arts > Other > Engineering > Science > Technology = Mathematics
3. Department of Industrial Design
Curriculum05(9.43%)3(5.66%)33(62.26%)012(22.64%)53
Arts > Other > Technology > Engineering
TJUScienceTechnologyEngineeringArtsMathematicsOtherTotal
1. Department of Media & Communication Design
Curriculum014(37.84%)014(37.84%)1(2.7%)8 (21.62%)37
Technology = Arts > Other > Mathematics
2. Department of Industrial Design/Product Design
Curriculum08(21.62%)6(16.21%)14(37.83%)1(2.7%)8 (21.62%)37
Arts > Technology = Other > Engineering > Mathematics
3. Department of Environmental Design
Curriculum08(21.62%)6(16.21%)14(37.83%)1(2.7%)8 (21.62%)37
Arts > Technology = Other > Engineering > Mathematics
Source: quoted from the official website of these six universities, and collated by the authors.
Many students are not familiar with the curriculum of the relevant college or department when choosing a university, but will be influenced by the university’s attributes. When they enter university, it is important to ensure that the curriculum is appropriate.
This study indicates that the curriculum arrangement of the design department largely depends on the orientation of the university to which it belongs. In general, it requires not only highlighting the advantages and characteristics of the university, but also flexibly adapting to the actual circumstances and focusing on a particular direction, such as the field of human–computer interaction (HCI). Consequently, the curriculum planning of the design department should find a balance in the STEAM model. It is also critical to note that these courses cannot be designed simply to incorporate the five dimensions of STEAM. Moreover, in order to better grasp the objectives of the curriculum, teachers and students must have a deep understanding of the essence and connotations of STEAM.

5. Conclusions and Recommendations

5.1. Conclusions

Based on the results presented in the questionnaire, as well as the sample curriculum planning of the sample, the three hypotheses proposed in this study are deemed to be valid. If the respondents have no experience studying abroad, their knowledge of schools they have never attended is limited, which may lead to assessments that do not match the actual situation. Although the STEAM model has been widely used, there are still differences in its implementation between different countries or regions. For example, since STEM was introduced to universities in mainland China in 2016 and is still in the development stage (STEAM is also not widely practiced in design education in mainland China), participants from universities in the United States, where STEM and STEAM were developed, are encouraged to support the identification of cognitive difference, thus improving the replicability of the results.
Design educators and researchers need to have a deep understanding of the essence and implications of STEAM. Students must also consider how to acquire the knowledge and skills needed for 21st-century design through STEAM courses. For example, in some countries or regions, the STEAM model has just been applied to design education, and teachers and students lack rich experience. It is necessary to continuously collect feedback from these people. So, the use of STEAM in design education needs to be continuously evaluated and improved.

5.2. Limitations and Follow-Up Research

The limitations of this study, which will be further addressed in subsequent studies, include the fact that all of the respondents in this study are from Chinese-speaking areas, and a large proportion of them have no experience studying abroad, so their assessment of STEAM cannot be discussed more widely for the time being. As part of this research series, we will further cross-compare the results obtained from different perspectives. In the future, we will analyze respondents’ evaluations of two samples from the USA. If possible, we plan to invite teachers and students from these two universities to answer our questionnaire. Their answers can be compared with our findings.
This study posits that science, technology, engineering, and mathematics can be mastered through systematic, scientific, standardized, and continuous training, but artistic and humanistic literacy requires the long-term accumulation of knowledge. In addition, using art to connect science, technology, engineering, and mathematics can also prompt people to think about the humanistic connotations of the four dimensions of STEM from another perspective.
From STEM to STEAM, it is possible that the concept of “arts” can play a major role in connecting the other four attributes. It is expected that future research will focus on what changes “art” brings when it is connected to the other four attributes (science, technology, engineering, and mathematics) as well as what new inspiration and enlightenment these changes can bring to design education. Researchers and educators in the field of design should pay attention to this issue. Although the current research is still ongoing, we would like to reiterate our call for more people to participate in the exploration of the use of STEAM models in design education.

Author Contributions

Conceptualization, Y.S. and Y.-Y.K.; methodology, Y.-Y.K.; writing—original draft preparation, Y.S. and C.-C.N.; writing—review and editing, Y.-Y.K., C.-C.N. and Y.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors would like to thank the experts and participants who took part in the experiments. The authors would also like to thank the teachers and students of the Graduate School of Creative Industry Design, National Taiwan University of Arts for their great assistance.

Conflicts of Interest

The authors declare no conflict of interest.

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Education 13 00241 g001 550
Figure 1. From STEM to STEAM: The fusion of Humart (human + art) and Dechnology (design + technology). (Source: this study).
Figure 1. From STEM to STEAM: The fusion of Humart (human + art) and Dechnology (design + technology). (Source: this study).
Education 13 00241 g001
Education 13 00241 g002 550
Figure 2. The procedures for deriving the effectiveness of the STEAM model that used in design education. (Source: this study).
Figure 2. The procedures for deriving the effectiveness of the STEAM model that used in design education. (Source: this study).
Education 13 00241 g002
Table
Table 1. Samples.
Table 1. Samples.
CategorySix Universities with a College or Laboratory of Design
Arts and HumanitiesAcademy of Art & Design, Tsinghua University (THU)
College of Design, National Taiwan University of Arts (NTUA)
Rhode Island School of Design (RISD)
Science and TechnologyCollege of Design and Innovation, Tongji University (TJU)
College of Design, National Taiwan University of Science and Technology (NTUST)
MIT Media Lab (MIT)
Source: this study.
Table
Table 2. The second part of the questionnaire.
Table 2. The second part of the questionnaire.
Q1: Are you familiar with this university?Very Low 1 2 3 4 5 Very High
Q2: Please assess whether this university attaches great importance to the use of STEAM in their design education?ScienceVery Low 1 2 3 4 5 Very High
TechnologyVery Low 1 2 3 4 5 Very High
EngineeringVery Low 1 2 3 4 5 Very High
ArtsVery Low 1 2 3 4 5 Very High
MathematicsVery Low 1 2 3 4 5 Very High
Source: this study.
Table
Table 4. The mean and std. deviation of the respondents’ familiarity with six universities.
Table 4. The mean and std. deviation of the respondents’ familiarity with six universities.
THUTJUNTUANTUSTRISDMIT
Taiwan Area
(n = 128)		2.18 (1.111)2.27 (1.245)3.95 (1.229)3.43 (1.215)2.34 (1.220)2.91 (1.160)
NTUA > NTUST > MIT > RISD > TJU > THU
NTUA
(n = 115)		2.10 (1.18)1.77 (1.035)3.75 (1.22)2.83 (1.237)1.93 (1.19)2.34 (1.263)
NTUA > NTUST > MIT > THU > RISD > TJU
NTUST
(n = 60)		1.65 (1.039)1.58 (1.062)2.88 (1.474)3.42 (1.476)1.87 (1.255)2.63 (1.507)
NTUST > NTUA > MIT > RISD > THU > TJU
THUTJUNTUANTUSTRISDMIT
Mainland China
(n = 222)		2.75 (1.120)2.45 (1.171)1.93 (1.143)1.78 (1.075)1.85 (1.130)2.01 (1.186)
THU > TJU > MIT > NTUA > RISD > NTUST
THU
(n = 35)		3.89 (1.105)2.74 (1.120)2.00 (1.163)1.77 (0.942)2.49 (1.197)2.51 (1.095)
THU > TJU > MIT > RISD > NTUA > NTUST
TJU
(n = 64)		3.05 (1.188)3.02 (1.188)2.20 (1.311)1.98 (1.105)2.05 (1.188)2.50 (1.321)
THU > TJU > MIT > NTUA > RISD > NTUST
Note: samples that are most familiar to the respondents are marked in gray shading.
Table
Table 6. The differences between respondents from four universities.
Table 6. The differences between respondents from four universities.
SampleAttributeSource of VariationSSdfMSFPost Hoc Tests
THUArtsBetween Groups15.36035.120
1.231		4.158 *1 > 2; 1 > 4; 3 > 2; 3 > 4
Within Groups332.421270
Total347.781273
NTUATechnologyBetween Groups7.53132.510
1.233		2.037 ***1 > 3; 1 > 4; 2 > 3; 2 > 4
Within Groups332.834270
Total340.365273
ArtsBetween Groups10.12233.374
1.318		2.560 ***1 > 3; 1 > 4; 2 > 3; 2 > 4
Within Groups355.892270
Total366.015273
NTUSTScienceBetween Groups104.447334.816
1.230		28.296 ***2 > 1; 1 > 3; 1 > 4; 2 > 3; 2 > 4
Within Groups332.213270
Total436.661273
TechnologyBetween Groups142.449347.483
1.266		37.513 ***1 > 3; 1 > 4; 2 > 3; 2 > 4
Within Groups341.756270
Total484.204273
EngineeringBetween Groups131.618343.873
1.189		36.913 ***2 > 1; 1 > 3; 1 > 4; 2 > 3; 2 > 4
Within Groups320.907270
Total452.526273
ArtsBetween Groups80.579326.860
1.287		20.877 ***2 > 1; 1 > 3; 1 > 4; 2 > 3; 2 > 4
Within Groups347.380270
Total427.960273
MathematicsBetween Groups77.393325.798
1.385		18.630 ***1 > 3; 1 > 4; 2 > 3; 2 > 4
Within Groups373.877270
Total451.270273
RISDScienceBetween Groups24.16138.054
1.209		6.662 ***1 > 4; 2 > 4
Within Groups326.379270
Total350.540273
TechnologyBetween Groups29.15039.717
1.398		6.948 ***1 > 4; 2 > 4
Within Groups377.566270
Total406.715273
EngineeringBetween Groups30.366310.122
1.220		8.300 ***1 > 4; 2 > 4; 3 > 4
Within Groups329.269270
Total359.635273
ArtsBetween Groups34.989311.663
1.576		7.401 ***1 > 4; 2 > 4; 3 > 4
Within Groups425.479270
Total460.467273
MathematicsBetween Groups27.34539.115
1.271		7.171 ***1 > 4; 2 > 3; 2 > 4
Within Groups343.184270
Total370.529273
MITScienceBetween Groups55.207318.402
1.555		11.838 ***1 > 3; 1 > 4; 2 > 4; 3 > 4
Within Groups419.727270
Total474.934273
TechnologyBetween Groups61.438320.479
1.528		13.406 ***1 > 4; 2 > 4; 3 > 4
Within Groups412.459270
Total473.898273
EngineeringBetween Groups61.263320.421
1.515		13.480 ***1 > 3; 1 > 4; 2 > 4; 3 > 4
Within Groups409.015270
Total470.277273
MathematicsBetween Groups57.359319.120
1.574		12.143 ***1 > 3; 1 > 4; 2 > 4; 3 > 4
Within Groups425.112270
Total482.471273
Note: * p < 0.05, *** p < 0.001; respondents from four universities: 1. NTUA, 2. NTUST, 3. THU, 4. TJU.
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Sun, Y.; Ni, C.-C.; Kang, Y.-Y. Comparison of Four Universities on Both Sides of the Taiwan Strait Regarding the Cognitive Differences in the Transition from STEM to STEAM in Design Education. Educ. Sci. 2023, 13, 241. https://doi.org/10.3390/educsci13030241

AMA Style

Sun Y, Ni C-C, Kang Y-Y. Comparison of Four Universities on Both Sides of the Taiwan Strait Regarding the Cognitive Differences in the Transition from STEM to STEAM in Design Education. Education Sciences. 2023; 13(3):241. https://doi.org/10.3390/educsci13030241

Chicago/Turabian Style

Sun, Yikang, Chien-Chih Ni, and Yen-Yu Kang. 2023. "Comparison of Four Universities on Both Sides of the Taiwan Strait Regarding the Cognitive Differences in the Transition from STEM to STEAM in Design Education" Education Sciences 13, no. 3: 241. https://doi.org/10.3390/educsci13030241

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