This article shares how Design Thinking (DT) can help develop creative thinking skills and how educators can integrate interactivity and AI in their course design. It tells a story of how Design Thinking evolved, what were the new challenges in teaching DT and how they can be addressed with the use of Articulate Rise 360 and free AI agents. The article concludes with some recommendations that educators can implement regardless of the topic of their course.

 

Keywords: Design Thinking (DT), Creative Confidence, Educating Creativity, Collaborating with AI, Interactive Learning

 

Have you ever questioned your creativity or your talents? Many people lack confidence in these aspects, which makes them lean back from many opportunities that appear in their lives because they would require a proactive, creative contribution that they believe they cannot make. Creative professions are commonly believed to be reserved for creative, talented people and unreachable or confusing for others. However, we can question that statement.

 

Since design started to evolve as an academic discipline and a popular profession, there have been attempts to analyze and organize its creative component into a structured process that others can repeat. One of the most well-known methodologies of this kind is called Design Thinking (Fig. 1). The consulting company IDEO popularized it in the 1990s as a methodology to facilitate creativity in a business environment and stimulate creative confidence. The success of DT was due to the customer-friendly terminology developed by IDEO, which made the process more accessible to those who were not educated in design disciplines. As a result, it quickly gained popularity in the business environment thanks to its universality. According to the Design Thinking philosophy, creative confidence is the factor that helps turn ideas into reality. In the business environment, high competition and constantly changing socio-technological and politico-economic environments push companies to innovate, and innovation requires the creative drive that can make the company outstanding in the market. Therefore, the need for creativity evolved, and thanks to DT, many people could nurture their inner creativity and put it into practice.

 

Lately, there has been an intense growth of the design-related methodologies. The interest increased with the world's growing complexity, where simple drawing and model-making techniques were not enough to address wicked problems, and more thinking models started to appear (Jones, 1992 (second edition from the 70s); Buchanan, 1992; Norman, 2010). By 2004, in the work of Dubberly Hugh, "How do you Design? A compendium of Models.", there were over 80 design process models. Today, many Ph.D. dissertations in design disciplines produce new design methodologies, tools, canvases, and more. With the rise of AI, design professionals have started to rethink the workflow and seek opportunities for collaboration with AI, and therefore, they would change the design thinking models again. Educators also adapt the existing methods and develop new ones to fit their teaching needs better. Here at XJTLU, in the Department of Industrial Design, we practice different styles of Design Thinking and project-based learning on a daily basis. 

 

The result of this methodological creativity is that it became common for the same design concept or principle to use different words for its description and naming. Such a plurality of names of the design thinking tools may result in poor memory in learning them, understanding the differences, and the value of use, which often leads to frustration and giving up on the creative process. That is how the idea to create a manual was born to help students understand the main principles and steps behind the creative process in a synthesized manner with tips, useful links to important resources, and images. It started as an individual TDF project, and the first result obtained was a manual in the PDF format (Fig. 2), which contains all the above and uses non-academic plain English to better connect to the audience (students). However, this static format could not encourage students to learn by practicing and needed to be more engaging to stimulate students' interest.

 

On the contrary, an online format can offer more fun and appealing forms of interactivity, facilitate project development, and enable learners to personalize their learning process to fit their learning pace. Moreover, the online format allows the module's content to be delivered to a broader audience – learners with different educational backgrounds and even from other institutions – which complies with the Design Thinking philosophy. Eventually, the online format allows constant updates of the teaching materials and gradual content growth. This idea started to take shape thanks to the collaboration with Learning Mall. In the paragraph below, we will share how we developed this project and which technologies we used to enhance the experience of learning Design Thinking. 

 

 

 

The goal was to create an interactive and engaging environment that supports learners in exploring Design Thinking principles and project development. To achieve that, we started planning on how to adapt the content to the digital environment. 

 

The course was designed for the audience of different educational backgrounds who want to take their first steps in learning Design Thinking principles. The course and the manual are also suitable for UG Industrial Design students as a quick reference for reviewing the project development principles, Design Thinking templates, and useful links.

 

Similarly to the PDF manual, the course structure is organized into two sections: “Thinking and Structuring” and “Narrating and Representing”. “Thinking and Structuring” teaches learners how to think and structure their project development. “Narrating and Representing” section provides additional support to develop visualization and storytelling skills. 

 

The first section is organized into several chapters that represent project development phases, synthesized from different Design Thinking models. Each chapter follows the same structure: an expert video, followed by multiple-choice questions and a series of practical exercises supported with the student examples, methodological templates, tips, useful links, and interactive features. The exercises are organized into five steps to facilitate the progression of the exercise. All the exercises are organized in a way to build upon each other and lead to project completion.

 

The interactive features include interactive case-study boxes (Fig. 3), Drag and Drop exercises (Fig. 4), multiple choice questions, flip cards (Fig. 5). 

 

We utilized Articulate Rise 360 and Storyline 360 to craft customized and dynamic multimedia content and interactions for learners. With the use of these E-learning authoring tools, the learning modules offer several benefits that enhance understanding and engagement.

 

•    Personalized Learning Experiences

Our learning modules are designed to cater to learners' individual needs, preferences, and pace of learning. For example, with the self-paced learning feature, learners can progress through the materials at a speed that suits them, fostering mastery learning. Also, learners are presented with a variety of research topics to choose from at the outset, allowing them to select areas of interest or to meet individual needs. 

 

•    Multimedia Integration

We organized textual information, audio, relevant pictures, videos (e.g., instructor's micro-lessons and student examples), and interactive activities in a coherent structure to help students better understand the concepts and procedures. Multimedia elements can facilitate meaningful learning by drawing learners' attention and focus, providing different modes of representation that align with the dual-coding theory, thus potentially enhancing understanding and retention.

 

•    Interactive Learning

We also selected appropriate types of interactive activities (e.g., Flip Card, Tabs, Process, and Knowledge Check) to present the content while asking learners to click, think, and practice by following the instructions. It makes learning more engaging and promotes active learning strategies. This aligns with the idea that active involvement in the learning process leads to deeper processing and better understanding.

 

•    Assessment and Feedback

Immediate and ongoing feedback is provided through Knowledge Check exercises and assessment, which serve to focus learners' attention on key points and identify their strengths and weaknesses. The targeted feedback promotes a more focused learning approach and facilitates a deeper understanding of the material. By tailoring the learning experience to the individual, we aim to enhance both engagement and educational outcomes.

Because Learning Mall Premium and Core have different technological capabilities, the interactive features developed with the Articulate Rise 360 and Storyline 360 had to be adapted to each platform accordingly. Thus, Learning Mall Core can keep the high degree of interactivity while Learning Mall Premium delivers the same content through a series of videos and PPTs. 

 

 

 

The AI technologies attract more and more interest among the academics, and we also implemented it in the course design.

 

The way we used AI took a mix of the two approaches: co-creation with the AI and optimization of the working processes with the AI. Examples of co-creation with the AI include the use of free GPT-based assistants to brainstorm ideas for structuring the exercises and the use of D-iD  and other specialized assistants in generating videos to deliver content (Fig. 6). Examples of workflow optimization are search (or prompt) refinement within the same chat (which is impossible through web search) and savings in video production time and costs.

 

When working with the free GPT-based assistants to generate texts, it can be helpful to experiment with the different prompts and compare the results of the same prompt using different assistants (e.g., Chat-GPT, Gemini, and others). For example, prompts could be "Write me an exercise using X method," "Write me an exercise in 5 steps using X method," "How to conduct X?" or "What is X?" etc. The results will always be different in detail but similar in principle, and it is the human job to interpret and adjust the AI-generated results. The generated results will neither be as you imagined them nor ready to be directly implemented in your work, yet they are good enough to use as a draft. If you ask GPT for scientific references or links to the web, there will almost always be mistakes in the authorship, or the article's title or the link may be invalid. However, you will find a similar article from different authors in a different title or under another link, and you will have to search for it yourself using any web browser. The free AI assistants do not allow you to train them according to the individual writing style or specific purposes. The free AI assistants generate generic results. Nonetheless, AI assistants are still helpful as they facilitate the first step of creation or research. Thus, after obtaining enough of the generated data, you have to check it for credibility, clean it, adjust it according to your needs, and insert your ideas and visions to make it personalized and meaningful.

 

When working with AI assistants that generate videos, the input processes and the achieved results vary significantly based on the technology being used. For example, when using free assistants such as the D-iD free version, the requested input is a photo and a text, or a photo and a voice recording. You cannot train the assistant to speak any text with your voice. You can either use the voice style from the list to read out your texts or upload your voice recordings for each piece of text separately. Regarding photo animation, it can animate the face but not the whole body. Also, you can ask the assistant to add the "emotions" when animating the portrait. However, a combination of a non-moving body with an unnatural smile makes the video look uncanny (Fig. 6).

 

In this course, we aimed to explore different forms of interactivity and technology integration. A collaboration with Liang Yuan, a former XJTLU member of staff, resulted in producing a tester of the silicon-based digital human. Silicon-based digital humans, as a new type of virtual human technology, have demonstrated potential in the field of teaching video recording. Silicon-based digital humans can provide intelligent services in the education sector. In our case, our experiment allowed us to create an animated digital human who behave in a fluent manner with facial expressions, body movement, and hand gestures (Vid. 1). The whole input process was different: it required a photo, a short video to train the gestures, a short video to train facial expressions, a short voice recording to train the reading. If the videos and/or voice recordings are too short (less than a minute), then the results will be with some glitch, e.g. the mouth articulation. In our case, the fluent reading was not achieved yet.

 

Using video-generating assistants saves the costs of time on video production, it eliminates the need to record the video with the professional camera settings and a camera-man, it eliminates mistakes in speaking and performing of the actor, it saves time on the iterations, it eliminates the need in video editing and editors. In the environment, where the workload is high and the human resources are insufficient, the AI video-assistants can produce results with minimum resources involved. Further potential of such technology that the IT community discusses includes digital humans adjusting teaching strategies according to student feedback, digital humans collecting students' learning data in real-time during teaching and performing analysis and assessment, and more. As technology continues to advance and applications deepen, the role of silicon-based digital humans in the field of teaching video recording may become an important tool for the digital transformation of education, bringing profound impacts on the development of education.

 

More research needs to be done to analyze the effect of AI-generated educational videos on student engagement and educators' satisfaction. Some findings show that pedagogical agents appearance influences learners’ retention and cognitive load, but not attention (Lim, 2024). Some other research states that there is no significant differences in gains in learning from the traditional teaching video methods and generated (Leiker et al., 2023). The findings obtained so far demonstrate that this is an important field of research to be investigated.

 

 

 

 

 

 

 

 

 

The main contribution of Design Thinking lies in making creativity accessible to all. It gained popularity in the business environment thanks to its user-friendly terminology. It evolved due to various external factors, such as the growing complexity of the world and the rise of new tools for creativity, including AI tools. Design Thinking promotes interdisciplinary collaboration through its universal principles and language. It also builds transferrable skills like teamwork, critical thinking, creativity, management, and leadership. Thus, Design Thinking is still a relevant methodology that attracts interest from learners and educators, and influential design schools have their own interpretation of it. This course is a step towards creating the XJTLU Design Thinking school. An online format for learning DT can offer more interactivity, facilitate project development, and enable personalized learning, reaching a broader audience. The idea is to help students achieve results quickly through small steps and build confidence in conducting creative projects. The course will share our faculties' expertise and our students' learning process. Together, this will create a platform for the evolution of Design Thinking methodology, teaching and learning experience, and the promotion of XJTLU Design School as a recognized expert in Design Thinking in China.

 

Regarding the details of using technologies to enhance the learning experience, we highlight Articulate Rise 360 and Storyline 360 for creating multimodal learning experiences and AI assistants for workflow optimization and content co-creation. The basic free AI assistants can create placeholder texts, primitively animated images, etc. More advanced assistants can produce not only the avatars but "natural user interfaces" that can respond to learners' questions live using Chat GPT (general or specifically trained for the subject). The use of AI is to be further researched and tested.

 

According to our experience in developing this course, we would like to share the following tips and recommendations for educators:

 

By leveraging these technologies and recommendations, educators can create a more accessible, interactive, and personalized learning experience for students in different fields of knowledge.

 

The authors express gratitude to XJTLU Teaching Development Fund for supporting the initial idea development, Learning Mall for supporting the online course development, Xinyu Bu, assistant multimedia content developer of Learning Mall, for video production, Liang Yuan for developing a tester of silicon-based human technology, and students of XJTLU Design School for responding to the surveys and contributing to the course development. 

 

 

 

 

 

 

 

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