Course-Work & Reflections
Instructional Design Related Course
IDE 631 Instruct Design-Develop I
Grade: A​
Course Description:
This course provided both a review of, and practice in, design AND an in-depth review of the instructional systems design process. The goals of this course were to explore and experience design—specifically instructional design—and to review the major aspects of instructional systems design in the context of typical instructional design problems and situations, integrating theory with practice.
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Course Artifact:
Reflections and Development in Instructional Design:
IDE 631 marked an important milestone as my first instructional design course within the IDD&E program. IDE 631 effectively bridged my practical experiences with theoretical knowledge, particularly through the introduction and thorough exploration of the ADDIE model. The ADDIE model, consisting of Analysis, Design, Development, Implementation, and Evaluation, quickly became integral to my instructional design practice. Each week, we examined diverse educational case studies. I enjoyed discussing and collaboratively exploring with my classmates how to apply instructional design techniques and learning theories to solve authentic educational issues in those cases. These discussions also helped me further understand how instructional designers should approach real-world educational challenges and apply theory-driven solutions to create impactful learning experiences.
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One of the clearest pieces of evidence of my development in the IDD&E area of specialization was the creation of an original instructional design plan intended to help freshmen at Syracuse University effectively utilize the EBSCO database for scholarly article searching. Working with my two teammates, we identified specific learner performance issues, such as difficulty navigating the SU library website and utilizing EBSCO's search functionalities effectively. Using the ADDIE framework, we meticulously analyzed learner needs, designed targeted instructional objectives, and developed a 105-minute workshop for the targeted learners. In addition to this project, other course assignments allowed me to further hone my instructional design skills. For instance, I created an original Instructional Design Model inspired by the metaphor of hiking up a mountain with friends. In this model, three bears work together to reach the top of a mountain, symbolizing the collaborative and iterative nature of the instructional design process. Just as hikers must plan their route, adjust their strategies when obstacles arise, and rely on tools like telescopes and walking sticks, instructional designers must collaborate with others, design and revise learning interventions and apply various technologies and techniques to support learning. Each bear in the model represents a critical component of the instructional design process—such as analysis, development, and implementation—showing how these elements work together to solve the performance problem. This creative visual model allowed me to explore and express my understanding of instructional design in a meaningful and memorable way.
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In summary, the assignments offered throughout the course provided me with a concrete context to apply theoretical knowledge to practice. Moreover, the regular feedback from my classmates and instructors I received helped me to reflect on my work and improve myself continuously. Ultimately, IDE 631 was transformative in integrating my prior practical experiences while I worked as an instructional designer with the essential theoretical knowledge I learned via this course, enriching my competencies in conducting instructional systems design.
IDD&E Doctoral Level Depth Courses
IDE 850 Doctoral Seminar in Literature Review
Grade: A​
Course Description:
The focus of this course was developing depth of knowledge through literature review, thus there was an equal focus on learning how to conduct a literature review and engaging in a topic of scholarly interest. The purpose of this seminar was to provide a forum to explore current literature and prepare to conduct research in emerging technologies (or other areas) to support learning/performance.
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Course Artifact:
Professor Comments on the Final Paper:
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Reflections:
Taking my second doctoral seminar course, IDE 850: Doctoral Seminar in Literature Review, was a turning point for how I approached academic writing and educational research. When I started the class, I was genuinely curious about how Artificial Intelligence (AI) could improve teaching and learning. I had questions. I had ideas. But I didn’t yet have a structured, research-based way to explore those ideas or turn them into something meaningful. This course changed that.
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The biggest takeaway from the class was learning how to conduct a systematic literature review. Before this course, I had never truly understood the depth and discipline required to write a solid, thorough literature review. Through weekly readings, class discussions, and feedback from Dr. Koszalka, I gradually learned how to narrow down my research scope, develop themes across studies, and most importantly, evaluate research critically rather than just summarizing what I read. That shift—from summarizing to synthesizing—was huge for me.
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During the course, I developed a literature review titled Modeling Pre-service Teachers’ Behavioral Intention to Use Artificial Intelligence Technologies in Daily Teaching Practices. At the time, I was fascinated by the potential of AI to support teachers and enhance learning personalization. I wasn’t satisfied with just reading about the topic—I wanted to do something. So, I went a step further and proposed an intervention: using game-based learning with block-based coding to teach pre-service teachers about AI concepts, specifically AI’s predictive function.
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Writing this paper pushed me to explore the existing literature deeply. I read dozens of articles on AI in education, pre-service teacher professional development, the Unified Theory of Acceptance and Use of Technology (UTAUT) model, and the role of technological knowledge in shaping behavioral intentions. As I delved deeper into those studies, I started to connect the dots—how knowledge leads to perception, and perception shapes intention. That UTAUT theoretical framework became the backbone of my project.
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I also began to see the importance of instructional design in making AI education accessible. Many studies I reviewed mentioned how pre-service teachers lacked confidence or knowledge in AI-related topics. That’s where I saw an opportunity—using interactive tools like coding games to help them learn by doing. Designing this intervention made me feel like I wasn’t just reviewing the literature—I was applying it. And that’s a powerful feeling.
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Throughout the process, I improved not just in my writing and research skills, but also in my understanding of the field. I now feel more confident talking about AI in education—not just the “cool” factor, but the actual research and theories behind it. I’ve come to appreciate that research isn’t just about proving a point; it’s about asking the right questions, building on what others have done, and contributing something new to the conversation.
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In all honesty, this course was challenging. It demanded a lot of reading, critical thinking, and writing. But it was also one of the most rewarding experiences I’ve had in my doctoral journey so far. It gave me both the tools and the mindset to become a more thoughtful researcher. Looking back, I’m grateful I got to take a deep dive into a topic I care about while also leveling up my academic skills.
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Evidence of Development in Research Skills:
Throughout the semester, I read a large number of scholarly articles on AI in education. As a result, I developed a full systematic review titled “How Generative Artificial Intelligence (GAI) is Used in Higher Education: A Systematic Review”, co-authored with another doctoral student. We analyzed 37 empirical studies and applied the Unified Theory of Acceptance and Use of Technology (UTAUT) as our framework to investigate how faculty and students perceive GAI tools like ChatGPT, what concerns they have, and how those perceptions might shape their intention to use such technologies in teaching and learning. The paper was accepted by the 2025 AERA Annual Conference.
IDE 843 Dissertation Research Seminar
Grade: A​
Course Description:
This course was designed to support doctoral students in understanding and developing their dissertation research proposals. Students explored the essential components of a strong proposal, including defining relevant and justifiable research topics, identifying and synthesizing literature using systematic methods, and evaluating appropriate research methodologies. The course also guided students in locating institutional and academic resources, effectively communicating their research ideas through academic writing and presentations, and ultimately crafting a well-justified and feasible research proposal aligned with scholarly standards.
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Course Artifact:
Professor Comments on the Final Paper:
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Peers Comments on the Final Paper:
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Reflections:
IDE 843 was the third doctoral seminar I took, following IDE 850. Looking back, these two courses were like two stepping stones that helped me find the research direction I genuinely want to pursue. While IDE 850 sparked my initial interest in how AI can be used in education, IDE 843 helped me shift gears and go deeper into immersive virtual reality as my new research focus.
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When I came into IDE 843, I still had some leftover ideas from my previous seminar—mostly centered on AI-enhanced learning. My draft topic, which I presented in class, was more about multimedia design principles in immersive learning, but it wasn’t clearly framed yet. During one of our early sessions, I shared this initial version with Dr. Lei and my classmates. The feedback I got, especially from Dr. Lei, was direct and incredibly helpful. She challenged me to think more clearly about the feasibility of my study—what could actually be done, tested, and completed within the scope of a doctoral dissertation.
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Through those weekly seminar discussions, I began to reflect more seriously on what kind of project I could truly commit to. I realized that while AI is still an exciting field, what really fascinated me was the design side of immersive experiences—how virtual reality can simulate real-world environments and how learning can be improved within those experiences. That’s when I made the shift: from AI to immersive VR.
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In this course, I developed a research idea and learned how to build it from the ground up. I designed a theory-driven intervention based on Richard Mayer’s Cognitive Theory of Multimedia Learning and the segmenting principle. I drafted a study that would compare active and passive pauses in an immersive virtual nature trail to examine how they affect cognitive load and learning outcomes. I also discussed how I would collect and analyze data, and how I would recruit participants.
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What made IDE 843 stand out to me wasn’t just the content, but the format. It was a true seminar—we talked, questioned, debated, and supported each other’s ideas every week. This kind of academic dialogue helped me shape a more realistic, theory-informed, and feasible dissertation plan. It made me think not only about what interests me, but what I can actually implement, test, and contribute to the field. This course also taught me to think about research with both integrity and practicality. Designing a study isn’t just about ambition—it’s about aligning theory with methods, working within limitations, and making sure you can actually finish what you start.
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In short, IDE 843 was a course that helped me grow from an exploratory thinker into a more grounded researcher. It gave me the clarity and confidence to pivot my research direction and lay a strong foundation for my future work.
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Evidence of Development in Research Skills:
IDE 843 laid a strong foundation for my continued research in immersive virtual reality (IVR). After the course, I co-authored a systematic literature review with Dr. Huang and other peers that explores how eye-tracking techniques are used to measure cognitive load and anxiety/stress in IVR learning environments. The review shows how eye-tracking provides objective data—such as fixation duration and pupil dilation—to understand learners’ cognitive and emotional responses in immersive settings. This paper was accepted to the 2025 AERA Annual Meeting, marking an important step in my academic development. The knowledge and design experience I gained in IDE 843 also provided a solid foundation for designing the intervention in my Research Apprenticeship Project (RAP), which continues my focus on IVR and its use in education.
Research Methodology Related Courses
EDU 810 Advanced Seminar: Qualitative Research I
Grade: A​
Course Description:
This course was the first part of a two-semester sequence in advanced qualitative methods that was centered around designing a qualitative research project related to student’s specific research interests. As part of this first semester, students reflected together to theoretically complicate important political, ethical, and methodological issues related to qualitative research and developed a research proposal.
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Course Artifact:
Professor Comments on the Final Paper (feedback was delivered verbally after the presentation):
"You’ve developed a strong and relevant proposal with a clear purpose, but there are several areas that need further attention. The sampling section would benefit from more specificity. It’s not clear how you plan to ensure variation among participants or what your plan is if recruitment falls short. The interview questions are generally appropriate, but questions 4 through 6 are overlapping and could be tightened. Consider adding a question that addresses institutional or departmental support, which may give you a broader understanding of the teaching context. In the data analysis section, you mention using both thematic analysis and the TPACK framework, but it's not clear how you plan to integrate the two. Will you begin with an existing codebook based on TPACK, or allow themes to emerge inductively? Also, be sure to include a brief note on ethical considerations, such as how you'll manage consent and data confidentiality. Finally, take time to revise for clarity. There are several small grammar issues and formatting inconsistencies that should be cleaned up."
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--- Dr. Susan Thomas
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Peers Comments on the Paper (at the time the paper was still being developed):
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Comment 1​​​​
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Reflections:
When I first started EDU 810, I honestly struggled a lot. I didn’t have much experience with purely qualitative research, especially not the kind of work this course focused on. Most of the readings were from outside my comfort zone, they weren’t the typical instructional design or educational technology papers I was used to. Instead, they came from fields such as humanities research, gender studies, and cultural research, often focusing on students' experiences in diverse educational contexts and how broader social structures shape learning. These readings were deep, theory-heavy, and often written in unfamiliar academic language. I had to spend several hours each week just trying to understand the content before class. It wasn’t easy.
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But what helped me push through was the weekly in-class discussions. In each session, I talked with my classmates and Dr. Thomas about the assigned readings. We didn’t just talk about the topic or the findings, we focused on the research methods used in each article. For example, if a study used focus groups or narrative inquiry, we’d break down how the method worked, why the author chose it, and what its strengths and limitations were. This was actually the most helpful part for me. Talking through the methods based on real published studies helped me see how qualitative research works in practice, not just in theory. It gave me a better framework for thinking about my own research design.
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The biggest milestone for me in this course was developing my own proposal. At first, I was unsure where to start. However, Dr. Thomas gave me detailed feedback along the way, especially when I was working on designing my interview questions. She encouraged me to think about the logic behind each question, how to align them with my research goals, and how to make sure I was respecting participants’ voices. Her guidance was consistent and clear throughout the semester. Step by step, I revised and improved, and by the end of the course, I had a full proposal that I was satisfied with.
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Looking back, I’m really glad I took this class. Even though I struggled at the beginning, the challenge was worth it. It pushed me to engage with unfamiliar literature, to think more critically about qualitative research design, and to communicate my ideas more clearly. More importantly, it gave me the confidence to do qualitative research in a thoughtful and rigorous way. I now have a better understanding of interview-based research, thematic analysis, and research ethics, skills that will absolutely help me in my RAP and future dissertation work.
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This course reminded me that growth doesn’t happen in your comfort zone. It happens when you’re confused, uncertain, and still show up and figure things out—bit by bit.
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Evidence of Development in Research Skills:
The skills and knowledge I gained from EDU 810 have directly supported the advancement of my current research. After completing my proposal in the course, I submitted an IRB application under the supervision of Dr. Huang based on the project and received approval. I have since conducted my first participant interview and am in the process of collecting more data. Additionally, I submitted a proposal based on this study to the 2025 AECT conference.
EDU 791 Advanced Seminar in Quantitative Research Methods
Grade: A​
Course Description:
The purpose of this seminar was to facilitate SOE graduate students’ integration of theory, research design, and measurement issues with knowledge of statistical procedures needed to plan, accomplish, and evaluate quantitative research projects. The course was built on the foundation provided by EDU 647 and focused on the practical application of quantitative research techniques. Quantitative techniques covered in this seminar included analysis of variance, multiple regression, multiple discriminant analysis, path analysis, and factor analysis. Students completed a statistical portfolio using statistical programs (SPSS/AMOS and/or R) on extent data sets to demonstrate their ability to manipulate and recode data, accomplished several statistical analyses, interpreted the results of the analyses, and presented the findings using both text and data tables.
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Course Artifact:
Professor Comments on the Research Proposal (feedback was delivered verbally after the presentation):
"The use of paired sample t-tests and simultaneous regression is well-justified and aligned with your study's goals. However, one key element missing from your methods section is a power analysis. It’s important to determine whether your planned sample size (80 students) is sufficient to detect meaningful effects, especially for the regression analysis in RQ2. I recommend using G*Power or a similar tool to conduct an a priori power analysis. This would strengthen your methodological justification and help ensure the study is adequately powered. You should report the expected effect size, alpha level, power (typically .80), and the resulting recommended sample size. Including this step would improve the rigor of your design and is expected in projects involving statistical modeling. Otherwise, your statistical choices are solid, and the rationale for each is clearly stated. Consider revising your final report to include this important detail."
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--- Dr. Qiu Wang​​​​​
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Reflections:
EDU 791 was the second quantitative research methods course I took in the IDD&E program, and it turned out to be really helpful—especially at that time when I was exploring how AI could be used in education. I was interested in modeling students’ behavioral intentions to learn AI using the UTAUT framework, and this course gave me the statistical tools to actually test those ideas. In particular, learning about regression analysis helped me understand how to evaluate relationships between different constructs, and whether UTAUT could apply not only to adults or college students, but also to elementary school learners in an AI learning context.
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One thing I really appreciated about this course was the hands-on statistical analysis practices that Dr. Wang designed. Each practice involved working with real datasets and running analyses in SPSS, which was extremely helpful for me. Instead of just learning theory or formulas, I actually got to apply the methods to real data, interpret the output, and make sense of what it meant. It helped me become more confident using SPSS and understanding what the numbers were telling me.
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Another key takeaway from this course was learning how to design an intervention-based study. The final assignment required us to write a full research proposal Through that process, I had to think carefully about every part of the design, from choosing appropriate methods to planning out data collection and analysis. I designed a study that involved using a block-based coding game to teach basic AI concepts to elementary school students. I used pre- and post-tests to measure changes in students’ AI-related perceptions and intentions, and I proposed using both paired t-tests and regression to analyze the results. Writing this proposal helped me put all the pieces together, making design, sampling, instruments, and analysis into a coherent research plan.
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Overall, this course helped me build the technical foundation to analyze data, learn the tools to model complex relationships, and have the experience of designing an educational intervention grounded in a real-world application. Looking back, EDU 791 didn’t just teach me statistics, it helped me grow as a researcher and gave me the confidence to move forward with more advanced research ideas.
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Evidence of Development in Research Skills:
Through EDU 791, I deepened my understanding of statistical analysis and gained the ability to select appropriate methods based on the design of my study. The hands-on SPSS practices helped me move beyond basic familiarity and apply techniques like regression and t-tests with more confidence and accuracy. This course enhanced my ability to align research questions with suitable analytical methods, which has been essential in shaping the way I approach quantitative research in my academic work.