Journals

Personal Learning Goals for the Course:

1. Develop a deeper understanding of the learning design choices behind an ongoing project or learning product, and how they relate to the learning theories and current academic findings of learning sciences.

2. Build technical proficiency in working with AI tools and technologies.

3. Gain hands-on experience collaborating on a team-based design project, and learn to develop the rapport for project meetings.

4. Experiment with innovative ideas related to learning design.

5. Cultivate my identity as a learning designer by developing a portfolio of work.

Initial Considerations for the Project:

• Understand the level of flexibility and personal involvement expected from each team member.

• Explore effective strategies for team communication and collaboration to ensure the successful completion of the project.

There is more than one way to learn how to drive.

As instructional designers, it is crucial to understand the predominant learning theories and recognize how they manifest in the design of various curricula and learning experiences. In Week 2, the class designed driving curricula based on different learning theories, which in itself was a constructionist approach to understanding these theories.

Through readings and class activities, I became more aware of how one’s theoretical assumptions about learning shape one’s design choices, and how each approach has its own strengths and limitations.

Behaviorism

Behaviorism emphasizes observable changes in behavior, using a stimulus-response mechanism to help learners build associations. Conditioning and reinforcement are key tools in enhancing learning outcomes. For many veteran drivers, driving maneuvers become muscle memory—actions performed effortlessly but often without conscious explanation. These skills are acquired through years of conditioning and reinforcement on the road, interacting with other drivers and passengers.

As someone who just learned how to drive and got my license, I don’t feel that I know how to drive yet—what I have is an understanding of how driving is accomplished. To truly know how to drive requires many more hours of practice through trial and error. This process will involve repetitive training every time I’m behind the wheel. Feedback is immediate and clear—other drivers might yell at me, or I could receive a ticket. In this sense, behaviorism has its merit, as driving skills are honed through repeated practice on the road.

Cognitivism

Cognitivists emphasize the mental organization of information. Instructional designers following this approach focus on building knowledge schemata to facilitate learning. To become a skilled driver who truly understands the craft, one must not only know what to do in different situations but also develop a mental model of how each movement affects the car. This deeper understanding might even extend to the ability to repair or adjust the car to improve its function, going beyond simple muscle memory. In this case, the learner develops a robust mental representation of the car and traffic systems.

Constructivism and Constructionism

Constructivism emphasizes learning through experience, while constructionism involves learning through making. My learning experience aligned with the constructivist approach, as my instructor placed me behind the wheel, allowing me to learn through experimentation. Learning in a real-world context and collaborating with peers helped me build a strong mental framework. The visceral experience of exploration made the memory more robust.

In contrast, constructionism posed a challenge during our class activity. My group struggled to connect the concept of “making” with the skill of driving, leading to the realization that this approach might not be ideal for learning how to drive.

It’s important to note that effective curricula often blend multiple approaches. No single theory is perfect for all contexts, and driving instruction, like many skills, can benefit from a combination of behaviorism, cognitivism, and constructivism.

"Hi Adam, I think you're right in that not all learning situations are best suited to all approaches, and we need to tailor  our approach based on the learner, the goals, and the context. But I wonder how the goals of that lesson would change if we decided that a constructionist approach was best suited to engage a specific set of learners. Perhaps we want to inspire motivation or spark creativity or just add an element of play into what would otherwise be a dry, cognitivist lesson. The goal of our constructionist interlude may not be "to drive a car" but instead perhaps "to get from point A to point B" or something more directly relevant to our learners, like getting to after school job. Students may be inspired to think about transportation and mobility in new ways that will make the eventual lesson on how to drive a car more meaningful for them. "

- Prof. Bill

In class, we discussed the importance of designing for equity and access, focusing on putting learners at the center of the design process and giving them more power and voice in shaping their own learning experiences. This approach is highly valued as a means to promote equitable learning opportunities, and I fully understand the principles behind it. However, one aspect that made me think more critically is the idea that some designers may have more authority over learners, not out of ego, but because they possess a deeper understanding of the subject matter and the learners’ needs. In some cases, designers may be more aware of what learners require for effective learning than the learners themselves.

For instance, in class, we talked about brands that resonate with us, and I chose Apple. My relationship with Apple made me reflect on the question of what learners really know about their needs versus what designers know about their users. When I first used Apple products, I thought they weren’t what I needed. I was drawn to fancy features and new functionalities that I believed would enhance my experience. However, after dealing with poor performance from Android and Windows devices, I tried Apple. Over time, I realized that what I actually needed was not all the flashy features, but a stable system that didn’t crash, had long battery life, and didn’t become sluggish over time. This was far more cost-effective for me as a student, and in retrospect, it was what I should have prioritized when choosing a product.

Relating this back to education, many learners are limited by their own lived experiences and narrow perspectives. They often gravitate towards familiar or comfortable knowledge without critically questioning the essence of learning or what they need to truly grow. This is where effective designers come in, using their understanding to guide learners towards what’s best for their development. This is a form of visionary leadership, where designers have a broader perspective than learners, who may be unaware of innovations and possibilities beyond their current knowledge.

This idea ties into Vygotsky’s theory of the Zone of Proximal Development, where learners need guidance from experts—in this case, designers—to reach levels of understanding they wouldn’t be able to achieve on their own. While giving learners a voice is important, placing too much emphasis on every learner’s opinion can hinder the learning process, as learners may not always be aware of what they truly need to grow.

Ultimately, the debate comes down to balancing empathy and authority in design. Designers must temper their authority with empathy to avoid a one-size-fits-all approach and to develop learning experiences that are flexible and customized. At the same time, designers should be confident in guiding learners towards the most effective learning outcomes, even if that means sometimes seeing beyond what learners themselves think they need. This balance of empathy and authority is essential for creating impactful and meaningful learning experiences.

"I appreciate your concern that the novice or learner may not know what they are lacking, or may not be able to articulate it in a way that meets their needs. We know that the role of the expert is required in designing and delivering a learning experience. And I can see how the idea of “ceding power” can sound like the expert does not guide the process. I think there’s a way to maintain the expertise of the instructor and designer but still center the learner. One criticism of design thinking is that the designer gathers information from the learner and then returns with a product to test and improve with feedback. An equity-centered approach would include the learner in the design work. Give them an equal role in ideating and prototyping, and not just testing. They are not just the clients, they’re partners."

- Prof. Bill

In this week’s project development phase, my focus was on the evolving landscape of AI, a field that deeply resonates with my interests and project. This exploration aligns with one of our session’s core discussions and readings, highlighting AI’s potential and implications. My study journey here has been shaped by a continuous drive to explore the possibilities of AI, but I hold mixed feelings about this new era. Initially, I was captivated by AI’s capabilities and functionalities, but my enthusiasm soon turned to apprehension over the potential impact on the workplace and labor market. These mixed emotions shaped my approach to the project, which draws on my professional interests and work experience.

One transformative experience has been using AI as a guide to teach myself web development—a field in which I had no prior experience. As I worked through building a website from scratch, navigating APIs and web development fundamentals, I began to see a clearer picture of the relationship between AI and humans. I resonated with Chris Dede’s perspective on IA, or augmented intelligence. In this developmental stage of AI and large language models, I believe what we need most is IA—a synergy where AI augments human intelligence rather than attempting to replace it. My daily interactions with AI have illuminated what this means, and I’d like to break it down.

Firstly, even the most advanced models today, such as O1, are not omnipotent. Without human guidance, even the best model struggles to accomplish precisely what designers envision. Creating a project from the ground up, especially in instructional design, requires human insight to guide AI effectively. There’s an essential balance in knowing what tasks AI handles well versus those better suited to human judgment. For example, when developing an AI-powered tutoring website, delegating the entire project to AI with minimal instructions would likely lead to a fragmented outcome. The project’s complexity spans various domains, and even a highly knowledgeable language model can struggle to piece everything together coherently. Therefore, understanding the roles and responsibilities between humans and AI is foundational to effective IA.

Interestingly, this journey has shown me that extensive technical expertise is not always necessary. Despite starting with zero knowledge of web development, I managed to build a fully functional website within a week. I went from learning basic code to deploying a full-fledged website online. Five years ago, achieving something like this would have seemed impossible. This is the “augmented” part of intelligence—AI serves as an empowering teammate, allowing individuals to pursue ambitious projects. However, it’s crucial to remember that, like a car, AI requires us to steer; even small decisions can lead to significant outcomes.

As designers, our role is not only to craft aesthetically pleasing and functional tools but also to consider the learner’s perspective and intended learning outcomes. This is an area where human expertise remains irreplaceable. For instance, we can’t simply tell a language model to create an appealing design—AI lacks the intrinsic understanding of what visually resonates with people. Thus, our responsibility extends beyond the technical to ethical judgment, vision, and user-centered planning. The AI can help bring our blueprints to life, but the direction must come from us.

Another key skill I developed is negotiating effectively with the language model. Sometimes, it doesn’t produce what I intended, not due to a lack of capability, but rather from the way instructions are phrased or the iterative process of refining its output. I’ve noticed that too many interruptions can make the model “lazy,” akin to managing a team member. Developing a familiarity with the model’s tendencies helps me guide it more efficiently and avoid unexpected results.

Finally, as learning designers, we must remain cautious of over-reliance on AI’s capabilities. Trusting AI to deliver is essential, yet it’s also important to recognize its limitations. AI isn’t simply copying existing knowledge; it can synthesize new insights and make educated predictions based on limited data. I liken AI to a knowledgeable person with a Ph.D.—extremely adept in knowledge processing but lacking human judgment and empathy. It’s powerful in many ways, but we should stay mindful of its limitations, neither blindly trusting nor dismissing its abilities.

As AI continues to advance, the design landscape will transform rapidly. This will empower small teams and individual creators to achieve what once required large organizations. Ultimately, success in this evolving field will come down to our ideas and design choices, as augmented intelligence opens a new era for AI-driven innovation.

In this module of the T-127 Teaching and Learning Lab Practicum, we engaged in a gallery walk, which we had prepared for during one of our final synchronous sessions as a group. The decision to design the gallery walk as the last synchronous session aligns closely with the course’s enduring understandings and learning outcomes. 

One of the key learning outcomes for this course is to learn how to listen well, develop rapport in project meetings, and begin to cultivate a professional persona grounded in experience. The gallery walk provided a unique opportunity to embody these outcomes in a practical, real-world setting.

Gallery Walk and Learning Design Principles

The gallery walk mirrored the course’s emphasis on making deliberate design choices and designing for specific audiences. By presenting our projects in a conference-style display, we were tasked with communicating our ideas effectively to peers. This required us to make strategic choices about how to present our projects visually and verbally, ensuring that our pitches were engaging and clear. Unlike traditional presentations, the gallery walk offered a less formal and more flexible environment. This flexibility tested our ability to adapt our communication strategies based on the audience’s interest and engagement. For instance, some attendees may not have been attracted to certain ideas, leading them to bypass our stations, while others engaged deeply, sparking meaningful conversations. This experience highlighted the importance of audience analysis and outcome mapping, core components of effective learning design.

Professional Persona and Portfolio Development

Participating in the gallery walk also contributed to developing a professional persona, another enduring understanding of the course. Presenting our projects in a semi-organized conference setting required us to adopt a professional demeanor, enhancing our ability to communicate learning designs in professional environments. Additionally, the act of taking photos during the event serves as a tangible addition to our electronic portfolios, showcasing our ability to present and engage in professional settings. This aligns with the course’s objective of creating a professionally relevant portfolio that highlights the application of research-based principles to learning experiences.

Valuable Feedback and Real-World Insights

One of the significant benefits of the gallery walk was the opportunity to receive valuable feedback from peers and guests, including industry professionals. Engaging in conversations with individuals working on similar AI tutor bots provided insights into the latest trends and best practices. For example, a discussion with a developer from Bok Center introduced the concept of using chains of AI agents to boost project accuracy, a consideration I had not previously explored. This aligns with the course’s goal of conducting needs analyses and contributing to course planning meetings by integrating external feedback into our design processes.

Team-Based Approach and Collaboration

Reflecting on the team-based approach of this project, I recognize its alignment with the course’s emphasis on collaborative learning and the development of teamwork skills. Working in a diverse group brought multiple perspectives and minimized personal biases, enriching the learning experience. My teammates were particularly supportive, influencing my design decisions and enhancing my ability to collaborate effectively. This experience underscored the importance of active participation and responsibility within a team, echoing the course’s focus on professional collaboration and collective project development.

Although I typically find teamwork inefficient, this project taught me valuable lessons about team dynamics and the importance of taking initiative. Initially, our team faced setbacks due to access issues and lack of direction. However, by voicing my opinions and guiding the team, I helped push the project forward. Leading and chairing meetings provided me with insights into managing team dynamics and ensuring productive collaboration. This experience aligns with the course’s objective of developing strategies to apply appropriate theoretical models and enhancing our ability to work effectively within professional teams.

In short, the gallery walk was a pivotal experience that reinforced the course’s enduring understandings and learning outcomes. It provided a platform to apply instructional design principles, develop a professional persona, and engage in meaningful collaboration. The feedback and insights gained during the gallery walk not only enhanced my capstone project but also contributed to my growth as a learning designer. The team-based approach, while initially challenging, proved to be invaluable in developing essential teamwork skills and fostering a collaborative environment. This aligns with the course’s primary aim of developing the learning experience of a real learning designer through practical application of theoretical models. Therefore, the gallery walk and the team-based approach were integral in achieving the course’s objectives, preparing us for professional roles in learning design.

(NB: The language is improved by AI.)

Designing SpiderAsasks, an ESL writing platform, has been a transformative journey for me. Throughout this process, I kept coming back to the core principles in our course, which acted as guiding stars shaping my approach and decisions. Reflecting on these enduring understandings—I can see how deeply they influenced the development of SpiderAsasks.

Learning Design is All About Making Choices

Every design decision involves making choices that balance various factors to create an effective learning environment. While developing SpiderAsasks, I faced numerous decisions, from selecting the technological stack to determining the types of feedback mechanisms to implement. For example, choosing Python Flask for the backend was a deliberate decision to ensure rapid development and flexibility, aligning with the need for a scalable and responsive platform. Additionally, opting for AI-driven feedback over traditional methods was a strategic choice to provide immediate, actionable critiques without the high costs associated with one-on-one tutoring. Each decision was carefully weighed against the platform’s goals, ensuring that every feature meaningfully contributed to enhancing students’ writing skills.

If You Do Not Design for Someone, Then You Are Designing for No One

Understanding and empathizing with the target audience was crucial in the design process. SpiderAsasks is specifically tailored for high school to college-level students in China, many of whom come from low- to middle-income families. This focus guided the platform’s accessibility features, ensuring it was user-friendly across various devices and didn’t require expensive hardware or software. Moreover, recognizing that these students often lack access to expert feedback, I prioritized integrating AI-driven critiques that mimic the insights of native English speakers and experienced educators. This user-centered approach ensured that the platform addressed real needs, fostering an inclusive and supportive learning environment.

Constraints Are Good, Up to a Point

Constraints often spark creativity and innovation. In designing SpiderAsasks, budgetary limitations and technological constraints required efficient use of resources. For instance, opting for SQLite as the database solution provided a lightweight and easily maintainable option suitable for initial development stages without incurring high costs. Additionally, the need to cater to a diverse user base with varying technological proficiencies imposed constraints that shaped the platform’s simplicity and intuitive design. These limitations, rather than hindering progress, inspired solutions that enhanced the platform’s functionality and accessibility, demonstrating that constraints, when managed effectively, can lead to robust and innovative designs.

Designers Are Human, Designing for Humans

At the heart of SpiderAsasks lies the recognition that learning is a deeply human experience. This principle was reflected in the platform’s design elements aimed at reducing anxiety and fostering a positive emotional climate. The inclusion of a cartoonish spider character was a thoughtful choice to create a friendly and non-intimidating interface, encouraging students to engage confidently with writing tasks. Additionally, integrating empathetic feedback strategies addressed the emotional needs of learners, validating their efforts and providing motivational support. Acknowledging that designers bring their own perspectives and biases, I remained committed to creating a platform that respects and responds to the diverse emotional and cognitive needs of its users. My analysis of the HPL Tutorbot further enriched the design process. Learning from its strengths and weaknesses, I enhanced SpiderAsasks’ feedback mechanisms to include detailed, example-driven critiques and model revisions. This not only provided actionable suggestions but also served as tangible models for students to emulate, fostering deeper understanding and skill development. Additionally, addressing the gaps in emotional responsiveness observed in HPL Tutorbot, I incorporated empathetic feedback strategies to create a more supportive and engaging learning environment.

Growth

Throughout the course, my personal learning goals were centered around developing a deeper understanding of learning design choices, building technical proficiency with AI tools, gaining hands-on experience in team-based projects, experimenting with innovative design ideas, and cultivating my identity as a learning designer through portfolio development. Reflecting on my journey, I can see significant growth in each of these areas. Initially, my understanding of learning theories was purely theoretical, but through practical application in designing SpiderAsasks, I gained a nuanced appreciation of how theories like Cognitive Apprenticeship inform design choices. Building technical proficiency with AI tools was challenging yet rewarding, enabling me to implement sophisticated feedback mechanisms that enhance user experience. Collaborating on a team-based project honed my communication and leadership skills, essential for professional practice. Experimenting with innovative ideas, such as integrating a cartoonish spider character, demonstrated the importance of human-centered design in creating engaging learning environments.

By making informed choices, centering the design around the user, leveraging constraints creatively, and embracing the human aspect of design, I developed a platform that not only addresses the technical aspects of writing improvement but also supports the emotional and motivational needs of its users.

NB: The writing has been improved by AI for language accuracy and clarity.