I appreciated how you connected your example of studying to the principles of backward design. It shows so clearly how defining a clear end objective, such as mastering DFA and NFA. I have had the same experience myself where studying without an end outcome lost hours, so I could appreciate your experience. It’s a pleasant reminder that learning design, whether for a friend or an entire class, is most effective when it is deliberate.
My favorite section was your design thinking section too. I liked how you set up empathy to be the basis of innovation, especially in your co-op experience where you created a training app. That indicates that design isn’t always about being efficient but also about people, which I think is so easy to forget in technical fields.
I also agree with your interpretation of SOLO taxonomy. Bloom’s is helpful, but SOLO’s emphasis on progression is more representative of the way learning actually occurs. Your example of reinforcing the DFA/NFA result showed how minor wording changes can lead learners toward deeper understanding.
Your post does a great job connecting learning design theories to real-world experiences in programming and software development. I especially related to your example about surface learning in the Python course compared to deep learning during your internship. Iâve had similar experiences where the assessment style determined how much of the knowledge stayed with me after the course. Like you, I found that when activities and outcomes were tied to authentic applications, the learning became much more meaningful and lasting.
I also appreciated your emphasis on empathy in Design Thinking. The example you gave about redesigning a UI for accessibility highlighted how feedback and iteration are crucial, not only in tech but also in education. It made me think about how often courses fail to âtestâ their design with learners in mind. Your insights on SOLO Taxonomy stood out as well; the progression from surface to deep understanding feels especially relevant in computer science, where growth is often about moving from memorization to problem-solving.
Starting with the end goals in mind is especially valuable in the sciences. In microbiology, most lab courses begin with specific outcomes such as âstudents will be able to isolate and characterize a bacterial strainâ. Knowing this at the start makes it clear why we need to learn each technique along the wayâplating, staining, PCR, or microscopy. When my third-year molecular microbiology lab used this backward design approach, I found the learning much more meaningful because I could see how every step contributed to demonstrating the final outcome. Instead of treating each lab as a separate task, I understood the overall purpose and how my skills built toward that final demonstration.
Design Thinking
Design thinking is a model for solving problems centered on empathy, iteration, and prototyping. It focuses on creating solutions that meet actual learner or user needs.
Prototyping / Problem Solving involves testing practical solutions that still generate meaningful results, even if simplified. Our final setup was less complex but still valid.
Empathy means understanding othersâ perspectives, challenges, and limitations. In my lab, this meant recognizing time and resource constraints when designing experiments.
Iteration is the process of refining ideas through feedback and testing. For us, piloting an antibiotic resistance experiment and revising it based on our TAâs input improved the design.
Aspect of Design Thinking
Connection to Microbiology Learning
Example from Lab Work
Empathy
Considering the needs of learners and the limits of lab resources
Realized the original antibiotic resistance experiment was too complex for the time and equipment available
Iteration
Revising and refining ideas based on testing and feedback
Piloted the experiment, gathered feedback from the TA, and adjusted the design
Problem Solving / Prototyping
Finding workable solutions that still achieve meaningful results
Simplified the experimental setup while still collecting valid and useful data
Learning Outcomes and Bloomâs/ SOLO Taxonomies
I find Bloomâs taxonomy particularly useful for describing different levels of learning in microbiology. It is a hierarchical framework that classifies learning objectives by their complexity, moving from remembering to creating (Simplylearn, 2021). For example, the lowest level, remember, focuses on recalling factsâsuch as listing the steps of Gram staining. The next level, understand, might involve summarizing those steps in oneâs own words to show comprehension. At the apply level, students could use their knowledge of Gram staining to predict how a new bacterial isolate might appear under the microscope. The analyze stage would require breaking down results to investigate whether Gram staining provides reliable evidence for bacterial classification. At the evaluate level, students might defend or critique the effectiveness of Gram staining compared with molecular methods. Finally, at the create stage, learners could design an improved protocol or project that builds on the traditional technique.
A weak outcome in microbiology might be: âStudents will know the steps of Gram staining.â A stronger one, aligned with Bloomâs higher levels, would be: âStudents will be able to evaluate the effectiveness of Gram staining in differentiating bacterial species.â This stronger outcome goes beyond memorization to analysis and application. SOLO taxonomy also resonates with lab-based science because it highlights depth. Moving from surface responses to integrated responses.
Better Learning Design: Surface vs. Deep Learning
Looking back, I can see how surface learning and deep learning played out differently in my microbiology studies.
Surface Learning Example:
In my introductory courses, I often memorized metabolic pathways without really understanding how they connected.
This approach helped me pass tests, but I quickly forgot much of the material afterward.
The design of those courses emphasized recall rather than application, which made it easy to stay at a surface level.
Deep Learning Example:
In my fourth-year labs, I was required to apply those same pathways when interpreting experimental data.
For instance, understanding glycolysis wasnât just about listing enzymes anymoreâit became about explaining why a yeast strain failed to grow under certain conditions.
These tasks pushed me into problem-solving and analysis, which deepened my understanding and made the knowledge stick.
The contrast shows how course design shapes the type of learning. When activities and assessments only test recall, surface learning tends to dominate. When the design emphasizes application, problem-solving, and explanation, students are guided toward deep learning that lasts beyond the exam.
Inquiry and Project-Based Learning
Inquiry and project-based learning are deeply connected to microbiology research. In upper-level labs, my group once designed an experiment to test how environmental stresses affect microbial growth. There was no single ârightâ answer. We had to plan methods, troubleshoot, and interpret messy results, much like real research.
SĂĄnchez-GarcĂa and Reyes-de-CĂłzar (2025) emphasize that strong PBL includes elements such as a driving question, authenticity, inquiry, and public products. However, their review also shows that reflection and student voice are often underused, which I noticed in my own projects. While our inquiry was authentic, structured opportunities for reflection were limited. Still, the experience reflects how PBL fosters not just scientific skills but also collaboration, problem-solving, and adaptability. Key competencies for addressing real-world challenges.
References
SĂĄnchez-GarcĂa, R., & Reyes-de-CĂłzar, S. (2025). Enhancing project-based learning: A framework for optimizing structural design and implementationâA systematic review with a sustainable focus. Sustainability, 17(11), 4978. https://doi.org/10.3390/su17114978
Hi Amy, thank you so much for sharing such a thoughtful and motivational post! I particularly loved how you connected your own ADHD and growth mindset experiences to your learning trajectory. It made your observations seem very real and relatable. I also enjoyed your description of behaviourism, cognitivism, and constructivism. Especially how you showed how your professor employed all three theories collectively was a good example of how they can work together in the real world. I enjoyed the way you then applied the theories themselves to actual study habits. Your lists make it very easy to adopt the ideas. Your explanation of the ARCS Model was also a really nice thing about your post, and I liked how you wove in relevance and confidence in your own motivation as a student. It was wonderful at illustrating how theory applies in real life. Finally, I loved your conversation about prior knowledge, specifically your comment on not merely adding to what we have in mind but unlearning when necessary. Overall, your blog was nicely structured, engaging, and chock full of information that I can utilize for myself within my own education.
Hi Alexandra. Thank you so much for sharing! I thoroughly enjoyed reading about your educational journey and how it took you from Calgary to UVic. It added such a personal touch to your introduction and made your account interesting. I also appreciated how you described your learning style so elegantly. Your point that you learn things more easily when you are able to see them and discuss them resonate strongly with me, since collaborative work tends to foster understanding. Your observation about how your own working definition of learning evolved over time was also useful. I liked the contrast between the way you used to think about “street smarts vs. book smarts” and the way you now value both formal education and life skills. All in all, your entry was reflective, intimate, and inspiring to read, and it helped me have new perspectives on my own learning experiences.
Hello Fiona! Thanks so much for the great post! I enjoyed how you transitioned your love of childhood books into your life of learning today; it made your concept of learning so personal and meaningful. The example of the sewing class and wood shop was one that I found particularly enjoyable, since it showed so well how creating new information connect back to something you are already passionate about ensures that it sticks with you. I also appreciated your discussion of behaviorism and cognitivism. It is interesting to see how you balance memorization with attempts to do the heavy lifting of making connections at the deeper level in what you’re learning. The motivation section was also what caught my attention, and how you differentiated the different ARCS categories according to whether you are learning for school or for yourself. Finally, I enjoyed the format of your post by use of pictures and diagrams and it made it appealing and easy to follow. Overall, your entry was understandable, well-organized, and motivating, and it caused me to think differently about my own methods of learning.
Hello, my name is Larissa Baloran, and Iâm a fourth year student studying microbiology. I was always fascinated by the subject because I had passionate science teachers that boosted my interest about how microorganisms shape the world around us. They made learning captivating by connecting everyday life to the unseen microbial processes that go on around us at all times. Their love for science motivated me to pursue microbiology, and hopefully apply what I learn in the medical field someday.
