Design Intricacies

Photo by Declan Sun on Unsplash

Backward Design

Planning with end goals in mind is an excellent way to narrow down the scope of the plan. A plan without end goals to guide it can become too cloudy at one point or another and can make the people involved lose the motivation and the discipline required to stick with it. In my first year at UVic, I took an introductory programming course where I memorized Python syntax to pass quizzes, which is a classic case of surface learning. The assessments didn’t require me to apply or connect ideas, so I forgot most of the content after the exam. In contrast, my recent software engineering internship was a game-changer. The outcome was to develop a full-stack web application using agile methodologies. Weekly sprints, peer reviews, and a final demo aligned perfectly with this goal which encouraged me to connect concepts like front-end frameworks, database design, and user authentication. This hands-on approach fostered deep learning as I could see how each component contributed to a real-world product. This objective-oriented planning helped me be accountable at every turn of the project and the knowledge stuck with me at the end as well, and I still use those skills in personal projects. This experience taught me that well-designed learning, like well-structured code, requires alignment and purpose to create lasting impact. Someone who does a way better job at articulating this is one of my favorite educators: Grant Wiggins. In the video attached below, he expounds these concepts beautifully.

Design Thinking

Design Thinking, with its emphasis on empathy, iteration and problem solving, has profoundly changed how I think about designing and experiencing learning. In the tech industry, empathy is critical when building user-facing applications as you need to understand the user’s needs to create something valuable. Design Thinking applies this to education and encourages educators to empathize with learners, prototype solutions, and iterate based on feedback. This approach makes learning more focused on the students itself as it shifts the focus from the process of making content to solving real problems for learners. A standout example from my time at my very first internship emphasizes this. I was tasked with designing a user interface for a project management tool. Our initial design was visually appealing but, after testing, we learned it was inaccessible to visually impaired users due to poor screen-reader compatibility. Using Design Thinking, we empathized with these users by interviewing them and understanding their challenges. We prototyped new designs with non-blending colors and keyboard navigation using a tool called Figma. The initial results seemed promising but required more iterations and amendments based on the feedback we got from the target users. This process not only improved the product but also taught me the value of empathy in problem-solving. In an academic context, I experienced design thinking during a human-computer interaction course which I had taken last semester. Our group project involved designing an app for campus navigation. We started by interviewing students to understand their pain points. Prototyping multiple wireframes and testing them with peers led to a more intuitive design and this consolidated the idea for me that iteration augments solutions. Essentially, design thinking encourages me to approach learning design like software development:

• Start with the user as their opinion and interaction with your application is sacrosanct
• Test any tangible outcome from these ideas early and get feedback from these users
• Refine and amend as much as it takes before the finished product seems to align with the user’s expectations.

Bloom’s/ SOLO Taxonomies

Learning outcomes are the foundation of effective design, and Bloom’s and SOLO Taxonomies provide tools to craft and evaluate them. I find SOLO Taxonomy more helpful because it emphasizes the progression of understanding which is something that mirrors my growth in Computer Science as a student. In my first co-op term, I could list components of a web framework but by my third term, I was actually designing systems and evaluating the trade-offs based on scalability and user needs. This ability to have a certain level of confidence to take charge of this process was only because of development in the learning. SOLO’s focus on depth helps me set goals for deeper learning. For instance, in CSC 370 (which is a course about databases), a weak outcome like “understand SQL” led to memorizing queries for exams which I did till the mid-term. A stronger outcome like “write SQL queries for retrieving from a multi-table join in a database,” would have pushed me to analyze and apply concepts prompting deeper engagement. SOLO’s gamut helps me track my journey from surface level to noteworthy understanding. More examples of this can be:

Solve this algorithmic problem	Solve this algorithmic problem optimally using a technique that results in an acceptable time complexity
Understand the front-end framework React	Be able to write code blocks in React that can power a real-time web page which is hosted somewhere
Play guitar	Be able to play the basic guitar chords like E, D, C, G from muscle memory and not spend time resting each individual finger in a particular chord shape

Better Learning Design

Learning by doing, surface vs. deep learning, and constructive alignment are different facets of purposeful design. Surface learning involves minimal effort while deep learning connects ideas and applies them to new contexts. Constructive alignment ensures outcomes and the activities involved work together to support deep learning. In my second year at UVic, I took an algorithmic course where I memorized different algorithms and their advantages and disadvantages. The time complexities and other convoluted properties of these algorithms and techniques was also on the purview. I was unable to cram all of this material due to a lack of desire in grasping this knowledge and passed with a B. In contrast, when I had to interview for various companies in my third year and onwards, I found out the different algorithmic problems asked and why they mattered. The interview process laid stress on the efficiency of these algorithms in different situations and how a specific technique applied in a certain situation would prove optimal and the same one used in a different situation would create the ineffective scenario. All of this intrigued me and now I was filled with the needed desire. I started studying up algorithms and applying them to problems and seeing firsthand why different algorithms were needed and after studying them, I was able to crush these interviews and that knowledge has still stayed with me. This process started with empathy as I had to acknowledge that I was struggling initially. The next step was prototyping a plan to get me from being unskilled to someone more proficient and lastly, I employed iteration. Iteration was needed as the plan needed to be changed sporadically until I got in the groove.

Inquiry and Project-based learning

Inquiry and project-based learning deeply connect to my studies and professional interests in software development. In fact, inquiry learning mirrors the problem-solving process in coding. For example, tackling an algorithmic problem that entails finding the shortest path in a graph requires you to explore multiple approaches, much like an inquiry question encourages creative experimentation. In my studies, courses based on artificial intelligence often pose open-ended problems. In addition to that, encapsulating an open-ended question with the process of design can prove to be difficult as the objectives will be somewhat ambiguous. The objectives can be interpreted differently by individuals which poses certain deterrents towards the progress with open-ended questions. On the other hand, this can also result is outcomes where the objectives, being subjective, deviate into a whole different dimension of the question and the defined objectives lead to a certain nuance in that spectrum and lead you to a desirable but an unforeseen or impertinent product