Enhancing Sustainable Design Thinking Education Efficiency: A Comparative Study of Synchronous Online and Offline Classes

Abstract

As online education advances, there is a growing interest in conducting various online courses. However, design thinking education, which heavily relies on active interactions and discussions among team members, has predominantly taken place in offline environments. This raises the question of whether online design thinking education can be equally as effective as offline education. To address this, our study conducted comparative research between offline and synchronous online design thinking classes to investigate how these different environments contribute to developing design thinking mindsets. The acquisition levels of seven design thinking mindsets—ambiguity, curiosity, empathy, experimental spirit, integrative thinking, open mind, and teamwork—were used to measure the efficiency of the design thinking classes. The research involved a 15-week project-based course provided to 126 engineering students at a university, examining the differences in design thinking mindsets before and after the completion of the process. The study’s findings demonstrated that synchronous online classes favorably influence the cultivation of design thinking mindsets, exhibiting efficiency comparable to that observed in traditional offline courses. Specifically, synchronous online classes were found to be more effective in cultivating empathy, integrative thinking, and open mind, while experimental spirit showed more significant development in offline courses. These findings contribute to a better understanding of the potential of synchronous online design thinking education and contribute the development of sustainable and effective online learning environments.

1. Introduction

Design thinking is human-centered and iterative process used to create innovative solutions for complex challenges. Design thinking mindset is a positive belief that fosters creative confidence to solve uncertain problems in challenging environments [1]. Design thinking has been widely adopted by universities over the past decades. Practicing design thinking helps to improve problem-solving skills, communication skills, and mindsets of creativity and teamwork [2,3,4]. In this respect, design thinking is regarded as a core factor of convergence that can develop the necessary competencies to survive in the fourth industrial era [2].

There has been increasing demand for design thinking in the job market. Professional jobs requiring design thinking skills exceed over 30,000 requirements in various positions such as industrial engineers, software developers, general managers, marketing managers, graphic designers, management analysts, computer and information systems managers, etc. [5]. This observed outcome reflects the increasing demand for design thinking education in universities. Limited initially to extracurricular programs like startups and creativity development, design thinking education has expanded into credit courses spanning engineering, management, design, medicine, and even compulsory liberal arts subjects [6].

During COVID-19, most universities turned classes into online education environments, and after the ‘With CORONA’ era, experts expect that online education will co-exist with offline education [7,8]. With the shift to online education, the effectiveness of online design thinking learning experiences compared to physical learning environments remains in debate. While there are studies showcasing successful online learning experiences in design thinking [9,10,11,12,13,14], most of the literature focuses on analysis within either asynchronous online education, offering theoretical knowledge, or synchronous online education, providing individual projects to learners. It was required to examine the efficiency of design thinking education online, where proactive team exercises and group projects are included. Some studies conducted synchronous online education where team projects and real-time education are available. Still, the conclusions were mostly based on the satisfaction levels of process knowledge, design thinking skills, overall feedback, and overall mindset [15,16,17]. It was difficult to find papers that measured the effectiveness of design thinking education in achieving its intended objectives.

This study aims to investigate the increasing level of design thinking mindsets among students in offline and synchronous online classes. The level of mindset acquisition serves as a critical indicator for evaluating the effectiveness of design thinking education. Design thinking is regarded as a mindset and process for problem-solving and innovation anchored around human-centered design [5]. Participants develop the necessary mindsets by experiencing the design thinking process [18]. Developing the required mindsets can help achieve creative confidence, which is the goal of design thinking education [18]. Therefore, the degree of acquisition of these relevant mindsets can serve as a reliable metric for assessing the effectiveness of design thinking education.

This study started by identifying evaluation questionnaires to gauge design thinking mindsets. Subsequently, the enhancement level of each mindset was assessed in both offline and synchronous online classes through a comprehensive survey of students. The survey was conducted both before and after a 15-week course. The final analysis is presented in the last section. The detailed research process is provided in Figure 1.

The later sections of the paper are structured as follows. Section 2 provides an overview of the relevant literature on the study’s topic. Section 3 explains materials and methods with the hypothesis, research tool, participants, and analysis. Section 4 represents the primary research examining mindset acquisition degrees in offline and synchronous online courses. Subsequently, Section 5 presents an extensive discussion of these results, followed by the drawing of conclusions. It is our aspiration that the outcomes of this study serve as a valuable reference for the advancement of online design thinking education in the future.

2. Literature Review

2.1. Design Thinking Process

The design thinking process is characterized by its non-prescriptive sequence of steps, allowing for fluid movement and iterative progression across stages. This inherent flexibility empowers practitioners to reframe problems and adapt the process to suit the evolving demands of solution development [18]. The essence of the design thinking process lies not in following a linear and sequential set of steps but in a complex and iterative process where multiple stages between the starting point and the destination overlap and allow for backtracking. Moreover, it is designed to enable a team to refine ideas and explore new directions, facilitating the repetition of a single process more than once.

Since the 2000s, design thinking has been significantly adopted into the business field. Curedale explicitly stated that the meaning of design thinking has evolved and, since the 2000s, it has expanded into the mindsets of business [19]. Many companies, including Apple, Samsung, Hyundai, Coca-Cola, and Microsoft, have integrated design thinking into their new product development and business strategy. This has led to a diversification of the design thinking process.

However, the interpretation of the education field’s design thinking process differs from that in the business context. In businesses where generating results is crucial, the implementation stage is emphasized and specified to include an action road map and market launch. In contrast, implementation is relatively less emphasized in the education sector. In the process proposed by IDEO and SAP, the final stage is the implementation phase, designed as an experimentation stage for business execution. IDEO emphasizes business model, pilot, and storytelling through the deep dive methodology in the implementation phase [20]. Similarly, SAP divides the process into explore, discover, design, and deliver stages, emphasizing business innovation and execution during the deliver stage [21].

In contrast, the representative design thinking process in the education field follows Stanford d. School’s design thinking process [20]. It emphasizes a human-centered approach rather than prioritizing business factors. This process is divided into five main stages. The first stage is “empathize” to comprehend the user’s experience for whom you are creating the design. It grasps the emotions that influence user behavior and identifies needs and problems that users may not be aware of. This stage forms the foundation of the human-centered design process, which profoundly engages with people. The second stage is “define,” where the insights gained from empathy are unpacked and synthesized into concrete and meaningful problem statements. This stage includes analyzing and integrating the discoveries derived from your empathy work to establish a user-centric perspective, which will be the focal point for addressing your design solutions. The third stage is “ideate”, where alternative solutions to the problems found in the define stage are generated. This phase focuses on extensively exploring diverse solutions by developing a substantial volume of varied possibilities. This approach will enable you to transcend conventional thinking and venture into a wide range of innovative ideas. The fourth stage is “prototype”. This process converts conceptual ideas into tangible prototypes, facilitating immersive experiences and interactions. Through this iterative process, participants can gain deeper insights and understanding of users, further fostering empathy and enhancing the development of solutions. The final stage is the “test”. Participants conduct trials with high-resolution prototypes, carefully analyzing observations and feedback to refine the designs iteratively. This iterative process not only helps gain valuable insights into user behavior but also allows for continuous improvement and refinement of the initial user perspective.

2.2. Online Learning and Design Thinking Education

The categorization of online learning is contingent upon several factors, including the mode of communication between educators and learners, the level of learner participation, and the potential for adapting educational content. Online learning modalities, such as video conferences, facilitate real-time interaction and simultaneous access for educators and learners. It fosters active engagement and enables students to collaborate towards shared learning objectives through group discussions. In line with Bonwell and Eison’s classification [22], synchronous online classes fall under the category of active online learning, characterized by student involvement and participation in class discussions and activities. Wingfield and Black emphasize that active learning encompasses a range of various practices, such as incorporating moments of reflection during lectures, integrating brief writing exercises, facilitating small-group discussions within larger class settings, employing survey instruments, quizzes, and self-assessment exercises, conducting laboratory experiments, organizing field trips, and incorporating debates, games, and role play into the learning process [23].

In contrast, in an asynchronous online class, there is a restriction on immediate interaction between educators and learners. The learning process takes place independently at each individual’s preferred time. The educational content remains consistent without alterations. As per Wingfield and Black’s classification [23], asynchronous online education, such as massive open online courses (MOOCs), falls under the category of passive online learning. In this mode, professors predominantly deliver lectures, while opportunities for active student participation, discussions, and experiential exercises are limited in the class [24,25]. Thirty five design thinking courses are available on twelve prominent online education platforms, including Coursera and edX [24]. Wrigley highlighted that only two programs are offered at the expert level within this selection of MOOC-based design thinking courses [24]. Most courses tend to focus on introductory content, covering basic knowledge and design thinking principles [24]. For design thinking that require team activities, asynchronous education of MOOC has a limitation of real time communication. Without the inclusion of learner collaboration and the establishment of a potential community of practice, the interactive aspect necessary for effective design thinking engagement is lacking within MOOC environments.

The rapid online expansion since COVID-19 has fueled the development of advanced technologies in education. Integrating digital technologies into online learning is evolving to enhance the quality of the classroom environment through real-time feedback and interactive engagement [26]. This trend encourages students’ active participation and endeavors to achieve better educational outcomes. Schmucker et al. conducted research to train machine learning models that predict the academic performance of future students by utilizing various types of log data from previous students [27]. This approach involves multiple specialized student performance models trained for different aspects of the curriculum and then combined to predict student performance collectively [27]. Chen and Ciu introduced a comprehensive framework to predict learners’ outcomes and latent factors in online education [28]. This framework employs deep learning-based collaborative filtering to capture learner–item interactions and enable personalized learning and cognitive diagnosis for individual students. It evaluates past performance and recommends personalized learning content [28].

The evolving trend in online education demands that students fully comprehend and efficiently use online education systems. To achieve this, students will require guidance in learning and independently utilizing the system, along with an understanding of the competencies needed for self-directed learning. Yilmaz et al. proposed the integration of artificial intelligence (AI) into an online learning system to provide personalized guidance and support, particularly during problem-solving [29]. This includes adaptive mastery tests (AMT) to assess competency and intelligent tutoring systems (ITS) for dynamic assessment and adaptive feedback [29]. These AI-driven enhancements can improve the learning experience and outcomes in LMSs and MOOCs, offering students a more tailored and supportive approach [29]. Sanusi et al. investigate the competencies needed for AI education among students [30]. The study emphasizes the importance of students’ cognitive, teamwork, self-learning, and human–tool collaboration competencies in enhancing their understanding of AI through course content. Teamwork and human–tool collaboration are required elements of AI-based online education, fostering creativity, innovation, and motivation among students [30].

However, the development of online education systems and the integration with advanced technology continue to progress. In this regard, the effectiveness of active online learning, particularly synchronous online classes such as Zoom, in the context of design thinking have been a topic of debate. According to Forbes, students’ participation in Zoom classes are more active than in offline classes due to a decreased sensitivity to mutual evaluation [10]. In addition, Kern’s research revealed that in synchronous group discussions, students produced two to four times more sentences than face-to-face discussions, enhancing their language communication skills [8]. Lim demonstrated positive evaluations regarding learning satisfaction, cooperative learning understanding, knowledge acquisition and application, practical experience, and improvement of problem-solving skills in online design thinking classes [11]. Vallis and Redmond found that online and remote delivery modes can contribute to developing novice design thinking skills, process knowledge, and mindsets among students [12]. Lau explored how virtual simulation, game-based learning, and role-playing practices enhance the learning experiences of design students in online design thinking classes [13]. Other researchers have introduced diverse methodologies to facilitate design thinking experiences in online settings. Xie’s study highlighted the benefits of using collaborative online tools rooted in design thinking, as they deepen the understanding of group collaborative design and provide valuable inspiration for teachers [17].

While numerous studies have demonstrated the positive outcomes of online classes, there are still concerns about online education methodology. Kim and Kam emphasized that interactive teaching and learning strategies, employing diverse digital platforms and content, significantly impact empathy, relationship formation, and active communication among learners in non-face-to-face settings [14]. These factors serve as crucial determinants of class quality. Park further explained that, in online-oriented classes, the absence of interaction between instructors and learners compared to face-to-face courses and the limitations in effectively utilizing digital devices and content raise concerns about potential declines in class quality [31]. A study by Sørum et al. discovered that students prefer live lectures while simultaneously desiring access to recorded video lectures [32]. Moreover, the recording of lectures is regarded as a positive aspect by students, and those who seldom or never turn on their cameras during classes did not expect others to show their faces either [32,33].

2.3. Design Thinking and Mindsets

In the past two decades, the expansion of design thinking to the business and education fields has viewed design thinking as a mindset that fosters creativity, innovation, and problem-solving. Curedale described design thinking as the mindset of business during the 2000s, as shown in Figure 2 [1,19]. Rather than merely following a linear set of steps, design thinking embraces a set of attitudes, beliefs, and cognitive frameworks that guide individuals and teams toward innovative solutions. Martin emphasized abductive thinking, highlighting the harmonious integration of analytical and intuitive thinking in design thinking [34]. The more cognitive approach using both parts of the brain was highlighted to utilize design thinking and synthesize logic. Brenner et al. categorized design thinking into the fusion of divergent and convergent thinking [35]. Carlgren et al. defined design thinking as a process for developing long-term innovation capability involving the dimension of mindset [36].

Various scholars have emphasized the significance of mindset in design thinking with the evolution of its perspectives. According to Kimbell, the absence of the mindset during design thinking practice can hinder the achieving of desired outcomes [37]. In design thinking, the fundamental approach involves forming interdisciplinary teams composed of members with diverse backgrounds. However, Schweitzer pointed out that having a collaborative mindset in team members is more important than forming such interdisciplinary teams [38]. Tim Brown also highlighted the requirement for T-shaped talents in design thinking, illustrating the necessity of empathy and integrative thinking [39]. A T-shaped expert is described as someone who is an outstanding specialist in their own field and, at the same time, possesses the ability to understand other domains and interact with experts in those fields [39]. Stanford University provided insights into the significance of acquiring the design thinking mindset. At Stanford d. School, design thinking is not seen as a set of tools or techniques but as a mindset that fosters a human-centered, creative, and empathetic approach to innovation and problem-solving [40].

A central objective of design thinking education is to nurture creative confidence [18]. Creative confidence entails the self-belief to embrace risks, learn from failure, and creatively address challenges to yield innovative solutions. Kelley and Kelley emphasized that design thinking education should foster resilient and optimistic creative confidence [41]. As shown in Figure 3, Rauth et al. stressed that creative confidence is cultivated by experiencing the design thinking process and developing the required mindsets [18]. This nurturing of creative mindsets occurs through exposure to processes and the development of behavioral patterns in specific situations. Consequently, these mindsets lead to a preference for creative behavior in uncertain and chaotic situations.

In the action-oriented stage above, establishing the necessary mindset in design thinking is essential for fostering creative confidence. Dweck explained that the mindset, which influences creativity, can be developed and cultivated through training [42]. Kelly indicates that creative confidence is a skill developed through practice, not merely an innate talent [33]. While the process may initially feel uncomfortable, discomfort diminishes over time and is replaced with creative confidence and abilities [33].

Design thinking is perceived as a mindset rather than mere tools and techniques. The objective of design thinking education, fostering creative confidence, is achieved through cultivating requisite mindsets via experiential learning. Assessing the level of mindset acquisition and variations therein can serve as a valuable metric for evaluating the effectiveness of design thinking education.

2.4. Design Thinking Characteristics

There is no predetermined list of design thinking mindsets, as researchers have approached their definitions and applications in diverse manners. Their interpretations have led to different criteria and ranges for these attributes. The design thinking mindset is sometimes viewed as an element within attributes or characteristics, while in other cases, it is considered an integral part of the overall design thinking process.

To understand what design thinking mindsets are, gathering and summarizing all the characteristics related to design thinking is necessary. As the first step, the list of the 17 design thinking characteristics was compiled in

Table 1. Description of design thinking characteristics.

Characteristics	Description
Ambiguity	The capacity to accept unclear situations or multiple possible interpretations
Collaboration	Act of working together from diverse backgrounds to draw out meaningful insights and solutions
Creative Confidence	One’s capacity to generate inventive solutions and the willingness to take creative risks to address challenges
Curiosity	Eagerness to learn about new things; being motivated to ask questions, even when one knows the answers
Empathy	Guess the users’ mind and thought by closely observing user’s words and actions
Experimental Spirit	Ask questions, explore constraints, and try new things that propose entirely different directions
Holistic View	Comprehensive perspective of a particular subject, problem, or situation that involves considering the entire system or context
Human Centered	Understanding and empathizing with the end-users to create solutions that are tailored to their specific requirements and preferences
Integrative Thinking	A cognitive process that involves synthesizing and reconciling seemingly opposing or conflicting ideas
Intellect	The capacity for rational thinking, critical reasoning, and cognitive abilities, enabling individuals to understand and solve complex problems
Open Mind	A non-judgmental attitude that is willing to consider new ideas, perspectives, or information without being constrained by preconceived notions or biases
Optimism	A positive viewpoint on situation, believing that things will generally work out for the best
Process Watchfulness	Cautious monitoring of ongoing activities or procedures to ensure they are executed accurately and efficiently
Teamwork	The effort of a group of individuals working together towards a common goal, utilizing their complementary skills and contributions to achieve success
Tolerance	The capacity to accept and respect differences in opinions, beliefs, cultures, or behaviors without judgment or prejudice
Trust	A firm belief in the reliability, honesty, and integrity of someone or something, leading to a willingness to rely on and confide in them
Visualization	The process of creating tangible images or representations of information or concepts to enhance understanding, analysis, and communication

by studying the works of 20 researchers from 2000 to the present [33,36,38,39,41,42,43,44,45]. The description of characteristics is gathered based on Schweitzer [38], Brown [39], Martin [34], Lor [46], and Howard [47].

3. Materials and Methods

3.1. Research Hypothesis

This study employed a comparative research to investigate the effectiveness of acquiring design thinking mindsets in offline and synchronous online courses. Two surveys were administered to students before and after participating in a design thinking course, enabling the analysis of the observed changes over time. The survey consisted of 23 questions aligned with the seven mindsets derived from the preceding section.

The effectiveness of online learning compared to traditional offline education has been a subject of debate. Some scholars, such as Park and Sørum et al., claim that online learning is less effective for learning [31,32]. Despite this, there is no denying the ongoing increase in online learning methods. Design thinking has been widely applied in various educational domains due to its value in developing the necessary competencies to survive in the fourth industrial era. Therefore, based on these premises, the present study formulated the following research hypothesis to investigate whether the cultivation level of design thinking mindsets differs based on the educational methods.

Hypothesis 1 (H1).

The cultivation level of “ambiguity” in design thinking education differs between offline classes and synchronous online classes.

Hypothesis 2 (H2).

The cultivation level of “curiosity” in design thinking education differs between offline classes and synchronous online classes.

Hypothesis 3 (H3).

The cultivation level of “empathy” in design thinking education differs between offline classes and synchronous online classes.

Hypothesis 4 (H4).

The cultivation level of “experimentation” in design thinking education differs between offline classes and synchronous online classes.

Hypothesis 5 (H5).

The cultivation level of “integrative thinking” in design thinking education differs between offline classes and synchronous online classes.

Hypothesis 6 (H6).

The cultivation level of “open mind” in design thinking education differs between offline classes and synchronous online classes.

Hypothesis 7 (H7).

The cultivation level of “teamwork” in design thinking education differs between offline classes and synchronous online classes.

3.2. Research Tool

In order to select the right evaluation questions for design thinking mindsets, two expert surveys were conducted: first, to identify the design thinking mindset necessary for university students and second, to develop the questions for evaluation.

The first survey was conducted with 62 professionals who have taught design thinking for more than ten years at the university level. The survey was conducted over a period from 2–23 July 2022. The participants were provided with a list of 17 design thinking characteristics with corresponding descriptions. Subsequently, the professionals identified and categorized characteristics. The findings demonstrate the classification of design thinking attributes into seven distinct mindsets: ambiguity, curiosity, empathy, experimental spirit, integrative thinking, open mind, and teamwork.

The second survey was executed with the same experts from 1–15 August 2022. Before the survey, a total of 53 initial evaluation questions related to seven mindsets were derived based on Dorsi et al.’s questionnaires [45] of design thinking mindset measurement, empathy evaluation guideline provided by Spreng et al. [48], ambiguity measurement by MacDonald [49], membership characteristics of collaboration by Mattessich et al. [50], and Song and Jiang’s integrative thinking measurement questionnaires [51]. The survey with the experts went through online via email. The 53 initial evaluation sentences were provided, the evaluation sentences for seven mindsets were checked on a subjective basis, and the number of selected items was not limited. If the individual expert thought there was a necessary sentence, they would add questions to each mindset.

Table 2. Evaluation questionnaires for design thinking mindsets.

Mindsets		Questions
Ambiguity	q1.1	Do I adapt my strategies and approaches when faced with unpredictable situations?
	q1.2	Am I not repulsed when facing with things that are not accustomed to?
	q1.3	Do I feel at ease when dealing with uncertain or unclear situations wheter they can be successfully resolved or not?
Curiosity	q2.1	Do I actively seek out information or knowledge beyond what is?
	q2.2	Am I naturally curious and eager to explore new ideas and concepts.
	q2.3	Do I demonstrate resilience and a lack of boredom when encountering new situations?
Empathy	q3.1	Do I find it easy to understand and relate to the emotions and feelings of others?
	q3.2	Do I believe that understanding and showing empathy towards others are essential for the source of inspiration in deciding the direction of problem-solving?
	q3.3	Do I habitually consider the user’s perspective when thinking or making decisions?
	q3.4	Do I find it easy to empathize with other people’s feelings and emotions about a particular phenomenon?
Experimental Spirit	q4.1	Do I pursue numerous opportunities despite the possibility of making mistakes?
	q4.2	Do I view problems or difficult situations as opportunities for learning?
	q4.3	Do I challenge the status quo and suggest improvements to existing processes or practices?
Integrative Thinking	q5.1	Do I enjoy exploring multiple perspectives and incorporating different ideas to solve complex problems?
	q5.2	Do I actively seek out diverse viewpoints before making a decision when faced with a challenging situation?
	q5.3	Do I understand the impact of related parts interacting with each other and on the results?
	q5.4	Do I feel comfortable incorporating elements from a broader vision into the ultimate solution?
Open Mind	q6.1	Am I willing to reconsider my opinions and adapt my views, when presented with new information?
	q6.2	Am I receptive to new ideas and perspectives, even if they challenge my existing beliefs?
	q6.3	Do I enjoy engaging in discussions that involve diverse viewpoints, even if they differ from my own?
Teamwork	q7.1	Do I actively contribute my skills and expertise to support the success of the team?
	q7.2	Do I feel comfortable developing new knowledge with other team members?
	q7.3	Am I receptive to feedback from teammates and use it to improve our collective performance?

summarizes the final evaluation questionnaires of design thinking mindsets.

Cronbach’s alpha test analysis was performed to assess whether the variables demonstrate reliable internal consistency [52]. In the Cronbach’s α test, the result value of 0.933 shows high internal consistency, indicating strong reliability. Furthermore, Cronbach’s α for each mindset also exhibited high reliability, ranging from 0.820 to 0.937. In order to evaluate the internal consistency of the measurement instrument, a split-half reliability test was administered. The Guttmann half reliability coefficient for the 23 questions yielded a high-reliability value of 0.814. The reliability coefficients for the seven specific mindset areas ranged from 0.702 to 0.884, indicating high internal consistency.

An exploratory factor analysis was conducted to ascertain the validity of the research instrument. Principal component analysis was employed to extract component factors from all the measured variables and to remove items with eigenvalues greater than or equal to 1.0, serving as the selection criterion. Furthermore, a loading value threshold of 0.40 was set for each factor. As a result of the factor analysis in

Table 3. Factor analysis result.

Factors	Item	Factor Loading
		1	2	3	4	5	6	7
Ambiguity	1	0.753	0.176	−0.033	0.083	0.095	0.095	0.088
	3	0.727	0.174	0.079	0.125	0.13	0.031	0.040
	2	0.715	0.160	0.011	0.062	0.015	0.042	0.001
Curiosity	21	0.314	0.768	0.047	0.082	0.173	0.088	0.023
	23	0.298	0.751	0.013	0.051	0.181	0.040	0.170
	22	0.296	0.739	0.008	0.011	0.231	0.002	0.167
Empathy	17	0.098	−0.069	0.911	−0.024	−0.078	0.096	0.131
	18	0.054	−0.068	0.883	−0.024	−0.046	−0.101	−0.095
	19	0.079	−0.059	0.864	−0.038	−0.05	−0.078	−0.100
	20	0.065	−0.52	0.795	−0.034	−0.41	−0.069	−0.091
Experimental Spirit	6	0.051	0.021	0.422	0.681	−0.237	−0.395	−0.077
	5	0.223	0.145	−0.049	0.632	0.233	0.262	0.040
	4	0.209	0.292	0.066	0.622	0.169	0.289	0.263
Integrative Thinking	12	0.197	0.226	−0.04	0.452	0.748	0.048	0.290
	11	0.239	0.126	−0.154	0.094	0.765	0.085	0.049
	10	0.189	0.089	−0.02	0.133	0.738	0.063	0.042
	13	0.177	0.078	−0.01	0.127	0.698	0.061	0.039
Open Mind	9	0.148	0.223	0.101	0.16	0.673	0.620	0.086
	8	0.134	0.139	0.004	0.644	0.57	0.619	0.064
	7	0.023	−0.011	0.16	−0.069	−0.026	0.567	0.121
Teamwork	14	0.085	−0.223	0.152	−0.2	0.003	0.669	0.718
	15	−0.11	−0.040	0.095	0.12	0.127	0.674	0.696
	16	0.001	0.002	0.001	−0.002	0.001	0.001	0.510
Eigenvalue		9.315	2.815	1.982	1.729	1.374	1.199	1.174
Proportion (%)		28.258	9.014	6.239	5.382	4.291	3.753	4.181
Cumulative (%)		26.269	38.363	44.549	16.912	54.109	57.335	54.301

KMO = 0.938. Bartlett’s test of Sphericity x² = 22375 df = 496 p = 0.000.

, all 23 questions exhibited loading values of 0.40 or higher, indicating satisfactory validity.

3.3. Rsearch Participants

Although this study meets all the experimental design criteria, it is quasi-experimental in that the subjects were selected rather than randomly assigned. The general characteristics of the survey participants were examined through frequency analysis, and the results are presented in

Table 4. General characteristics of survey subjects.

Characteristics		No.	%
Gender	Male	90	73.8
	Female	36	26.2
Grade	Junior	50	37.7
	Senior	76	62.3
Education Environment	Offline	60	47.6
	Synchronous Online	66	52.4

. All students participating in the study had prior experience with teamwork, having engaged in collaborative activities on at least three separate occasions, and were new to the concept of the design thinking.

Furthermore, to create an original synchronous online educational environment, all face-to-face meetings between students were excluded from this experiment. To ensure equal treatment between the synchronous online and offline environments, developing prototypes was limited to using the software development method. With this reason, engineering students are selected as the sample for this study.

3.4. Course Content

The study comprised a sample of 126 students majoring in Information and Communication Engineering. Among them, 66 students engaged in a synchronous online class for the duration of 15 weeks of the fall semester during the year 2022, while the remaining 60 students participated in an offline class for 15 weeks of the spring semester in 2023. At the outset of the classes, students were organized into teams of four members. Both courses aimed to develop creative solutions to subjects that each team chose based on pain points from daily life. Each course was structured to be 3 h long and conducted continuously for 15 weeks, once a week.

The introductory session presented a comprehensive overview of design thinking, including its purpose, methodology, and team composition. The detailed class structure is shown in

Table 5. Class structure.

Process	Time Spent (h/week)	Class Material
		Offline	Synchronous Online
Introduction	3 h/1 week	Pen, Papers	Laptop
Empathize	12 h/4 weeks	Pen, Papers, Camera	Laptop, Camera
Define	6 h/2 weeks	Pen, Papers	Laptop
Ideate	6 h/2 weeks	Pen, Papers	Laptop
Prototype	9 h/3 weeks	Laptop	Laptop
Test	9 h/3 weeks	Laptop	Laptop

. The rest of the classes followed Stanford d. School’s five steps of design thinking [20].

The first process is “empathize”, where students, both in the offline and synchronous online classes, observe the user’s behavior to identify needs and problems that may not be readily recognized. In the synchronous online course, while one representative student directly observes the user, the remaining team members watch the same user behavior via video conference. In the offline online course, students as a team executed and observed users on site. Both offline and online students have the option to record user behavior and spend additional time on observation after the class. In the second process of “define”, offline and synchronous online teams gather and synthesize all the insights and information obtained during the “empathize” stage. They work towards creating problem statements and developing user personas by the end of the stage. In the third process, “ideate”, offline and synchronous online teams generate a wide range of creative ideas to address the problems or challenges identified during the “define” stage. The focus is on expanding and diverging the volume of ideas to explore diversity [45]. Brainstorming and brain-writing techniques are used in both classes to increase the volume and quality of ideas. The fourth process, “prototype”, involves converting ideas into a visualized format, aiming to resolve inconsistencies between ideas and visualization and create a final solution. In the offline class, students work together as a team, using computer programming languages to build prototypes. In the synchronous online course, students follow the same procedure but meet only via synchronous online platforms. In the final step of “test”, both offline and synchronous online teams receive user feedback and iteratively refine and improve the solutions after building prototypes. Synchronous online teams receive feedback from users only via online channels, while offline teams received user feedbacks on site.

To ensure consistency in the experimental environment, both the offline and synchronous online classes were taught by the same lecturer, covering identical course objectives and using the same instructional process. A distinction between the two environments was the variance in class materials utilized. In the synchronous online class, students employed screen-shared memo applications on their laptops for decision-making, progress tracking, and idea visualization. In contrast, the offline course used traditional tools such as Post-it notes, blank paper, and pens for the same purposes.

In the synchronous online classes, the participants were deliberately not allowed to meet offline. This was done to reduce the potential impact of offline interactions. Such interactions can enhance related mindsets in design thinking activities. Including offline meetings among participants in online course could introduce confounding factors and potentially obscure the experimental outcomes of the synchronous online class. The inexperience or errors in machine operation did not affect our experiment. We conducted a preliminary test for Zoom to prevent mechanical problems that might have affected the research. Students are familiar with Zoom classes, as they experienced online lectures during the COVID period from 2020 to 2022.

3.5. Research Analysis

The results of examining design thinking mindsets were analyzed using SPSS 21.0 software. The study compared two teaching methods: offline and synchronous online courses. The research examined cultivation levels of seven mindsets: ambiguity, curiosity, empathy, experimental spirit, integrative thinking, open mind, and teamwork, as dependent variables. These variables were analyzed to assess the impact of different instructional modalities on developing design thinking mindsets. The study utilized a student survey with questions based on a 5-point Likert scale [53]. In this scale, the ratings were interpreted such that “1” indicated strongly disagree, “2” represented disagree, “3” denoted a neutral, “4” indicated agree, and “5” signified strongly agree.

4. Research Result

The paired sample t-test was employed to examine the overall differences between the pre-measurement and post-measurement of the mindset cultivation levels. As shown in

Table 6. Paired t-test result in pre- and post-measurement.

Mindset	Pre-Measurement vs. Post-Measurement
	Paired t-Test	Average Difference pre and Post Measurement
Ambiguity	t(126) = −8.811	0.464
Curiosity	t(126) = −10.429	0.464
Empathy	t(126) = −12.568	0.734
Experimental spirit	t(126) = −7.858	0.536
Integrative thinking	t(126) = −8.524 ***	0.453
Open mind	t(126) = −15.115	0.738
Teamwork	t(126) = −8.279	0.439

Note. ***. The correlation coefficient is significant at level 0.001.

, there has been a noticeable increase in the mean value of mindset cultivation across all variables, both in offline and synchronous. Among the variables examined, empathy and open mind exhibited the most substantial transformations following the implementation of design thinking education, demonstrating an increase of 0.73 or more on the 5 Likert Scale.

In the synchronous online course, the result of the paired t-test indicates all the variables show a statistically significant increase. The design thinking class mindset exhibited an average increase of 0.569 after the course. Notably, empathy demonstrated a considerable rise of 0.812 on the 5-point Likert scale. The following most substantial change was observed in the open mind, with an increase of 0.893. However, the experimental spirit showed a minor increase of 0.304 compared to the overall average. The remaining mindsets (ambiguity, curiosity, integrative thinking, and teamwork) maintained increases around the average value. Furthermore, the effect size of the synchronous online class was assessed using Cohen’s d value [54], which was calculated to be −0.898. According to Cohen’s d interpretation standards (where values of 0.2 or less indicate no effect size, 0.2~0.5 represent medium effect size, 0.5~0.8 signify large effect size, and 0.8~ indicates very large effect size), the result suggests that the difference between pre- and post-measurements is highly significant and has a considerable practical impact. The detailed values of mindset cultivation levels are shown in

Table 7. Research results from the synchronous online class survey.

Mindset	Pre		Post		Paired t-Test
	Mean	SD	Mean	SD	t-Test	p
Ambiguity	3.381	0.846	3.848	0.631	−4.45	0.000
Curiosity	3.36	0.688	3.833	0.78	−6.826	0.000
Empathy	3.022	0.633	3.942	0.661	−8.974	0.000
Experimental spirit	3.323	0.786	3.627	0.518	−3.257	0.002
Integrative thinking	3.314	0.672	3.846	0.523	−6.125	0.000
Open mind	3.295	0.647	4.188	0.522	−12.506	0.000
Teamwork	3.612	0.533	4.079	0.592	−7.889	0.000

.

Within the offline course, the design thinking mindsets experienced an average enhancement of 0.530 after the course completion. The paired t-test result indicates that all the variables show a statistically significant increase. Empathy and experimental spirit significantly improved, with increased levels of 0.656 and 0.768, respectively. In contrast, integrative thinking demonstrated a more modest increase of 0.374, which was lower than the average value. The remaining mindsets, ambiguity, curiosity, open mind, and teamwork, exhibited increases approximately in line with the average increased value, as shown in

Table 8. Research Results from the Offline Class Survey.

Mindset	Pre		Post		Paired t-Test
	Mean	SD	Mean	SD	t-Test	p
Ambiguity	3.358	0.575	3.819	0.667	−8.284	0.000
Curiosity	3.434	0.721	3.889	0.579	−7.974	0.000
Empathy	3.007	0.682	3.571	0.752	−8.761	0.000
Experimental Spirit	3.314	0.755	4.082	0.737	−8.885	0.000
Integrative Thinking	3.334	0.871	3.708	0.648	−6.288	0.000
Open Mind	3.273	0.894	3.856	0.635	−9.574	0.000
Teamwork	3.634	0.642	4.048	0.593	−4.347	0.000

. Cohen’s d value of −0.741 in the offline setting indicates a large effect size, suggesting that the difference between pre and post measurements is substantial.

Figure 4 shows the differences in mindset measurement values before and after the classes. The empathy cultivation level was higher in both courses. Moreover, empathy in the synchronous online course increased by 0.812 on the 5 Likert Scale, which was 0.156 higher than in the offline course. In the synchronous online class, students were allowed to record their observations outside of class and subsequently share these recorded videos with their peers. The shared videos underwent iterative review by team members until they were satisfied with their observations. In the offline class, students were also given the option to record videos of their observations. Nevertheless, the majority, except for one team, opted not to do so and relied on their memory, photographs, and notes taken during the observation process.

The experimental spirit exhibited a higher increase of 0.768 in the offline course than in the synchronous online course, with 0.304 growth. Given that prototyping requires a strong experimental spirit among the five stages of design thinking [37], analysis of experimental spirit mainly focused on the prototyping process. In the offline class, students actively discussed and developed prototypes, leading to multiple modifications. On the other hand, in the synchronous online course, students held meetings via video conference by prearranged appointments, and discussions mainly occurred after individual tasks were completed. As a result, the opportunity for immediate discussions and prototype modifications was limited in the synchronous online class.

The integrative thinking growth in the synchronous online course was comparable to an average increment of 0.532. However, the offline course showed a lower increase than the average. Students in the synchronous online class effectively utilize internet searches and share information with team members simultaneously. The mandatory use of the internet for Zoom access facilitated convenient exploration and exchange of information among team members. In contrast, students in the offline class had mobile phones and occasionally brought laptops, but most of the students relied on their individual ideas and pre-existing knowledge during discussions and ideation.

The synchronous online class strongly impacted fostering an open mind, with an above-average increase of 0.893. In contrast, the below-average increase was observed in the offline course. During the post-interview, students clearly preferred sharing their opinions within the synchronous online class setting. Some students felt less apprehensive about expressing dissenting ideas in this virtual environment, as peers in a classroom did not physically surround them. Conversely, others reported feeling more confident when sharing their opinions in a virtual communication setting where personal contact was absent. Students perceived synchronous online interactions as more convenient and less emotionally charged than offline interactions.

5. Conclusions

Given the rising need for design thinking skills in job markets and the continuous evolution of online education following the onset of the COVID-19 pandemic, deign thinking requires the development of comprehensive online education programs. However, as design thinking traditionally relies on active communication and interaction among team members, a cautious approach is necessary for devising online design thinking education initiatives. Thus, it becomes crucial to thoroughly understand the impacts and constraints related to online design thinking education before embarking on future development.

The objective of this study was to examine the development of design thinking mindsets in the synchronous online course compared to the traditional offline design thinking course. The effectiveness of design thinking education was evaluated by assessing the cultivation level of seven key design thinking mindsets; ambiguity, curiosity, empathy, experimental spirit, integrative thinking, open mind and teamwork. These mindsets served as parameters to gauge the efficacy of design thinking education in online and offline learning environments. Our study has demonstrated the potential for synchronous online education to be more effective than offline education in the context of design thinking education.

This research findings support the claims made by Vallis and Redmond [12], as well as those made by Lim [11], that the online learning enhances knowledge and mindset related to design thinking. Our study observed an increase in the seven representative mindsets of design thinking in synchronous online course, with students gaining a deeper understanding of each process. Furthermore, our study reconfirmed the beneficial impact of employing collaborative online tools, as explained by Lim and Ahn, in promoting enhanced group teamwork [4]. Teamwork cultivation increased a 0.464 in the synchronous online course, a higher effect size compared to 0.414 increases in the offline course. In addition, Lim and Ahn’s claim can be indirectly supported by the increase in the rate of open mind. In order to foster teamwork, cultivating an open mindset is a prerequisite. In that context, the fostering of an open mindset in the synchronous online course was found to be more effective than offline, leading to increased confidence among students in sharing diverse opinions within their teams.

Kim and Kam emphasized the impact of interactive education employing diverse digital devices and platforms, which particularly reinforced the effects on empathy and relationship formation [14]. In the synchronous online class, students utilizing devices, such as Zoom and video recordings, influenced empathy cultivation through verbal and visual communication. Students in the synchronous online class benefit from the ability to record and share observations, facilitating iterative review and meticulous analysis. The prevalence of using class recordings for later reference enables teams to extract valuable user insights and enhance their understanding of the subject matter.

Our study results support those of Wrigley et al. and Sørum et al. that students in Zoom classes are more active in communication [25,32]. Students demonstrated utilization of computer and internet connectivity resources to the fullest extent in the synchronous online course, not only for communication but also for simultaneous information searching, connecting, and integrating. In the integrative thinking phase, a synchronous online environment proves to be a more effective platform for students easily to analyze, evaluate, and synthesize information.

Park mentioned that the limitations of digital device usage can diminish the quality of online classes [31]. In our study, cultivating the experimental spirit in the synchronous online environment was less effective than in the offline environment. It was primarily due to the limitations of digital devices, as students in the synchronous online environment tended to work individually first and then meet online to review afterward. As a result, modifications or changes were not executed promptly, leading to delays. In contrast, in the offline environment, students worked on partial prototyping while simultaneously merging, modifying, and revising, resulting in faster completion. It influenced the effectiveness of the trial and error process in the synchronous online class.

This study aimed to evaluate the effectiveness of synchronous online education in design thinking through the evaluation of mindset cultivation levels. Limitations of this study are that the findings are confined to a specific engineering topic, where students use computer programming to develop prototypes, making it challenging to generalize the results. Hence, future research should encompass a broader range of subjects to effectively explore the development of design thinking mindsets in synchronous online environments.

Our study highlights the potential to develop and enhance synchronous online education for sustainability in design thinking. By utilizing the benefits of online platforms, such as accessibility, resource efficiency, and global reach, we can create more inclusive and environmentally responsible educational practices. Emphasizing the collaborative nature of design thinking in the synchronous online environment further strengthens its potential for sustainable education. As we continue to explore and innovate, we can pave the way for a more sustainable future where design thinking education transcends physical boundaries and empowers learners from diverse backgrounds to drive positive change in the world.