Reflexive Journaling

I. Redefining the Purpose of Research

Entering this week, I brought a foundation from previous research design coursework, where I had exporsure to several qualitative research design methodologies. However, returning to the "big picture" of qualitative inquiry has been instrumental in distinguishing it from the quantitative tradition. While quantitative research is often driven by hypothesis testing and the pursuit of objective generalizations, qualitative research has different objectives.

According to Peshkin (1993), the outcomes of qualitative research can be distilled into four primary categories: description, interpretation, verification, and evaluation. I found his nuance on "theory" particularly enlightening. In qualitative work, interpretation involves developing theory rather than confirming it. Furthermore, the concept of "verification" here includes a unique form of generalization. Unlike the statistical generalizations of quantitative studies, qualitative research relies on the consumer to perform the generalization, deciding which aspects of a specific case study are transferable to their own unique contexts. As Peshkin implies, we are not trying to verify a universal law; we are looking for the possibility of generalization within complexity.

II. Subjectivity as an Active Participant

Our class discussion and the reading of "In Search of Subjectivity" (Peshkin, 1988) challenged the traditional notion that subjectivity is a "bias" to be eliminated. Instead, Peshkin argues that subjectivity is both inevitable and invaluable. He posits that we should actively seek out our "Subjective-I’s" throughout the entire research process.

The "Who Am I?" exercise we did in class, listing 20 aspects of our identity, vividly illustrated the multiple lenses through which I view the world. In my professional life as an instructional designer, I view accessibility as a core requirement that must be integrated from day one, not a "fix" applied at the end. I now see subjectivity in research through that same lens: it is not an afterthought or a section to be added to a final paper; it is an active consideration at every stage of a research project. Peshkin’s terminology of "warm and cool spots" (the positive or negative feelings triggered by our subjects) and "situational subjectivity" provides a framework for this enhanced self-awareness. If the self and the subject are intertwined, then being "attuned" to that connection is a hallmark of "good" qualitative work.

III. Identity and Power in Scholar Development

The final reading by Choi et al. (2021) felt particularly relevant to my current journey as a PhD student at TAMU-CC. Their collaborative autoethnography explored the power dynamics inherent in higher education and how these forces shape our identity development as emerging scholars.

Transitioning from a consumer of knowledge to a creator of knowledge is a fraught process. This article served as an excellent practical example of a qualitative study in action. It utilized a collaborative autoethnography design, which I noted shared certain characteristics with cross-case analysis due to its rigorous coding and thematic analysis. The authors clearly articulated their theoretical frameworks and research questions, providing a transparent look at how methodology (data collection and analysis) leads directly to findings and implications.

Final Reflection

This week has reinforced that "reality is a slippery notion." If every method of data collection is only an "approximation of knowledge," then the goal of the researcher is to remain cyclical by using the answers we find to refine the questions we ask. By acknowledging my own subjectivity and understanding the specific descriptive and interpretive goals of my work, I can move toward a more "authentic" scholarly identity.

I. Mapping the Philosophical Terrain

This week, our exploration shifted from the broad purposes of qualitative inquiry to the specific philosophical "spaces" researchers inhabit. The reading by Sipe and Constable (1996) provided a vital "philosophical map," illustrating that a researcher’s choice of paradigm is far more than a technical preference. It is a reflection of one’s ontology (beliefs about the nature of reality) and epistemology (beliefs about the nature of knowledge).

Sipe and Constable’s use of visual tables and metaphors to describe the four paradigms (Positivist, Interpretivist, Critical Theory, and Deconstructivist) made these complex concepts highly approachable. For a visual learner, these representations served as an effective entry point, moving beyond a simple qualitative/quantitative binary to show the unique nuances of how different researchers "word the world." This mapping is essential for situating my own work and understanding the "why" behind my methodological choices. To take this a step further, I used Google's Gemini and Nano Banana to examine the article and create the infographic below based on the four paradigms. 

II. The Researcher as the Primary Instrument

Building on this philosophical foundation, Johnny Saldaña (2011) describes qualitative research as an "umbrella term" for studying social life through primarily non-quantitative data. The theme of the researcher as the primary instrument reappeared this week; Saldaña emphasizes that because we are the ones collecting and analyzing data, our backgrounds, biases, and personalities inevitably shape the findings. We are not detached observers; we are participants immersed in the world we study. Saldaña’s distinction between description and interpretation is particularly useful for my own writing: if I emphasize description, the reader sees what I saw; if I emphasize interpretation, the reader understands what I think. This reminds me that my voice as a researcher is the vehicle for the research itself.

III. The Art of Translation and Practical Foundations

Glesne (2016) further bridges the gap between theory and practice by describing qualitative research as the act of "translating life into text." Her alignment with the interpretive tradition resonates with the idea that reality is a socially constructed, complex, and subjective phenomenon. Glesne’s focus on pre-study tasks, such as reflexivity (such as maintained through this journal) and pilot study, underscores the importance of preparation for research questions, ensuring they make sense to participants before the full study begins. These practical steps ensure that the translation from life to text is as informed and rigorous as possible.

IV. Connections to the Field: Sharon Merriam

In our discussion board activity, I reflected on the work of Sharon Merriam, a methodologist whose perspective has been foundational to my understanding of case analysis. Merriam’s definition of qualitative research aligns closely with this week’s themes of interpretivism and induction. She posits that the researcher’s goal is to capture the participants' perspectives and how they view and make meaning of their own experiences. Like Saldaña and Glesne, Merriam views the human researcher as the primary instrument for data collection and analysis. Her work reinforces the idea that there is no single, universal truth or generalizable law; instead, there are multiple interpretations of a single event. In this view, reality is a localized, social construct, making the researcher’s role one of uncovering these varied "meanings" within their specific social contexts.

Final Reflection

This learning has has deepened my appreciation for the complexity of the qualitative landscape. I’ve come to understand that research demands a constant awareness of my own perspective, acknowledging my subjectivity. This awareness is crucial for producing work that is both academically rigorous and genuinely human.

Part I: Anchors and Assets

This week’s readings from Negotiating the Complexities of Qualitative Research emphasized that a study must be "anchored" in a compelling interest, i.e. a pressing "why" that drives the inquiry. As a doctoral student in educational technology and instructional design, I feel the tension described in the text: the "shadow" of quantitative research. My field often relies on data analytics from technology platforms, which are inherently quantitative. However, I am increasingly aware that user experience contains qualitative depths that numbers cannot capture.

The text argues that a researcher’s worldview must align with their methodology. Identifying as a constructivist, I realize I cannot adopt positivist methods without creating a fundamental misalignment. This requires constant ethical reflexivity to ensure my questions, methods, and analysis remain consistent with my belief that reality is socially constructed.

I was particularly struck by the discussion of Community Cultural Wealth and asset-based frameworks. In my work with accessibility, the default approach is often to address "deficits" or gaps related to disabilities. However, looking through an asset-based lens shifts the narrative entirely. For example, while a learner with dyslexia may face challenges with text, they often possess superior visual-spatial reasoning and creative problem-solving skills. This week’s reading validated my belief that accessible design should not just "fix" barriers but also leverage these inherent strengths, moving from a deficit model to one of empowerment.

Part II: Reflection on Subjectivity – The Instructional Designer as Instrument

Reflecting on my own subjectivity this week, I recognize that my professional background is both a lens and a potential blinder. With 18 years of experience, transitioning from a high school physics teacher to a university instructional designer, I view my research topic (OER and AI) through the eyes of a practitioner who wants to solve real-world problems. I am driven by a desire to see instructors move beyond "adoption" of OER to active "adaptation" using Generative AI.

However, my expertise creates a specific "positionality" I must manage. As a technology enthusiast, I carry the assumption that these tools will transform learning. This optimism risks blinding me to the valid hesitations or struggles of instructors who lack my technical background. I must be careful not to judge participants based on what I think they "should" know. To mitigate this, I need to "check my expertise at the door," avoiding jargon and creating a safe, anonymous space where participants feel free to share their challenges without fear of judgement. My goal is to use my subjectivity not to dictate the answer, but to empathize with the early stage of AI adoption that my participants are navigating.

This week, our focus shifted from the "why", i.e. the compelling interests and theoretical frameworks, to the "how," or the actual work of conducting qualitative research. I was particularly struck by Saldaña’s (2011) assertion that "good research is not about good methods as much as it is about good thinking." This resonates with me because it reframes data collection not as a passive act of "finding things," but as an active, creative process of asking the right questions.

Understanding that analysis is cyclical rather than linear is a crucial takeaway. The concept that I will need to collect, analyze, find gaps, and then collect again relieves the pressure to get everything “perfect” in the first sweep. Moving from specific data points to broader themes through coding and recoding supports this approach.

My research interest in the intersection of Open Educational Resources (OER) and Generative AI is driven by a desire to improve both the availability of materials and the workflows behind them. I see a professional tension where technology is often viewed merely as a burden or a shortcut. However, I argue that AI can be a "collaborative partner," handling the heavy lifting of curriculum mapping and accessibility remediation so that faculty can focus on pedagogy.

In terms of methodological approach, Creswell and Poth (2024) helped clarify my direction. While Grounded Theory is intriguing (specifically because I may need to build a model for AI-assisted OER adaptation where none currently exists) I believe my research interest is best served by a Case Study design. Since my work is technology-oriented, seeking an in-depth understanding of a specific "bounded system" (or comparing several cases of instructors using these workflows) aligns best with my goals.

The Theoretical Framework 

This week, we examined specific hermeneutical phenomenology and narrative inquiry, which are methodological frameworks designed to understand lived experiences in education. We focused on two articles by Jeong-Hee Kim, both of which utilize storytelling to challenge the "deficit models" often prevalent in education. Kim argues that we must look beyond identified problems or labels to understand the complex lived experiences of students.

Methodologically, these articles demonstrate how hermeneutics (the art of interpreting) and narrative construction allow researchers to see the "big picture" and uncover the humanity of marginalized students. These methodologies directly challenge the positivistic idea that knowledge is objective and definite; instead, they position research as the act of assigning meaning to phenomena.

The Practical Application 

This theoretical understanding directly applies to our current work in the course: designing interview protocols. As emerging researchers, we are learning that qualitative interviewing is more than simply asking questions; it is a social and theoretical process where the researcher helps the participant tell their story. The quality of the data is inextricably linked to the quality of the researcher-participant relationship.

The reading Qualitative Interview Studies by deMarrais provides the practical tools to achieve the depth that Kim describes. To get the detailed results found in Kim’s student cases, we must use the "mechanics" deMarrais outlines:

• Open-endedness: Asking broad questions that allow the participant to illustrate their experience.

• "How" vs. "Why": We should prioritize asking "how" and "what" rather than "why." Asking "why" can give the appearance of a value judgment on the participant's actions, potentially making them defensive.

• The Participant as Expert: We must avoid judgment and acknowledge that we are not the experts; the participant is the expert in their own story.

Ultimately, while Kim provides the goal (humanizing the student through deep interpretation), deMarrais provides the method (avoiding judgment, building rapport, and asking descriptive questions). By mastering these interview mechanics, I hope to capture the rich, non-objective descriptions necessary to understand the lived experience of my own future participants.

Finally, this week’s annotated bibliography on qualitative research regarding doctoral student identity reinforced why these deep interviewing techniques are so vital. In reviewing research on international doctoral students, I was struck by how systemic barriers such as language differences or non-traditional academic trajectories are often dismissed as mere logistical inconveniences when they actually pose profound threats to a student's professional identity. This insight directly informs my own research interests in curriculum mapping and accessibility. When I eventually study how instructors interact with OER and AI, I cannot view "accessibility" as just a technical checklist. I must use the social justice lens highlighted in my bibliography to see if current educational systems hold inherent biases against those with different linguistic or cultural backgrounds. 

Looking at the readings this week on Critical Race Theory (CRT), I made some connections with the recent activities we've done in class, specifically the peer interview exercise and the exercise where we devised purpose statements for our research across the five different qualitative approaches (case study, narrative inquiry, ethnography, grounded theory, and phenomenological study). The readings and these exercises have made me reflect on my role as a researcher and how I am required to act as an "auditor" of power structures.

I. Counter-Storytelling

In one of the articles I referred to about doctoral identity by Tucker and Adams, the authors analyze students' identity construction through Dialogical Self Theory (by Hermans and Hermans-Konopka). The parallel I see here is giving voice to marginalized or non-traditional experiences to challenge dominant academic narratives. Ladson-Billings emphasizes the use of storytelling and counter-narratives in CRT to challenge the discourse of the demographic majority. The experiential knowledge of individuals is considered a vital source of data, and an interview is one way to get that experiential knowledge.

With the classmate that I interviewed, using the framework of the theory of the dialogical self, we explored her multiple identities as a parent, an elementary school teacher, and a doctoral student. Via storytelling, she told me about her imposter syndrome and the conflict between her "expert teacher" side and her "novice researcher" identity, which act as counter-narratives. Academias has this idea of what a scholar should look like and how they should behave; we see the systemic issues that a non-traditional scholar-practitioner faces when they are entering spaces that were not historically designed for them. This interview really helped me uncover the human toll of navigating institutional power dynamics beyond the investigations in the literature.

II. Curriculum as Intellectual Property vs. Open Educational Resources

Ladson-Billings and Tate state that U.S. society is based on the idea of property rights. Historically, something like high-quality curriculum would be treated as intellectual property available to the privileged. They point out that education quality is tied to the property values of the community, which is a form of gatekeeping of knowledge.

Open Educational Resources (OER) or zero-textbook-cost courses run counter to the concept of curriculum as property. OER can serve as a way to dismantle those financial barriers that keep high-quality educational materials out of the hands of marginalized students. This makes education something that is treated as a human right, rather than a commodity that can be purchased by the privileged.

III. Exposing Systemic Barriers

Aviles de Bradley talked about policies that might look helpful on the surface but fail because they are implemented within a biased or inequitable structure. A policy might exist, but systemic barriers prevent its outcomes from being realized.

Connecting this to what I'm doing with OER and looking at accessibility standards, it's not enough for these resources just to be available or just be free, as it is a very superficial fix. If they are not really usable because they lack UDL and accessibility for students, it becomes exclusionary rather than an inclusive resource. My inquiry into how AI workflows can ensure alignment and accessibility shows my underlying belief that true equity requires examining the hidden barriers built into the curriculum.

Our reading this week, Sarah J. Tracy’s (2010) article, "Qualitative Quality: Eight 'Big-Tent' Criteria for Excellent Qualitative Research," gives qualitative researchers a concrete rubric to defend their work against people who only think in quantitative terms like "validity" and "reliability." I would identify myself as one of those people because of my background and experiences. Trained in the objective, measurable world of STEM and IT analytics, and living in a household fluent in the rigorous statistics of clinical research while pursuing a doctorate in a deeply human social science, I am sitting at the exact intersection of competing paradigms. This tension between the quantitative default of my past and the qualitative demands of my current C&I program has led me to reflect on several of Tracy’s criteria.

I. The "Bilingual" Researcher and the Demand for Sincerity

My transition from STEM/EdTech into qualitative C&I is like learning a new language. Tracy identifies sincerity (self-reflexivity and vulnerability) as one of her criteria and argues that excellent qualitative research requires the researcher to be honest about their biases and background. Stepping out of the comfortable, positivist, "objective" world of learning analytics and clinical data—where truth is a number—into a space where truth is interpreted exposes a vulnerability. However, acknowledging deep-seated quantitative roots isn't a weakness in qualitative research; according to Tracy, naming that lens is a hallmark of sincerity.

II. Redefining "Rigor" in an EdTech World

In IT and learning analytics, quality and rigor are indicated by large sample sizes, click-rates, and statistically significant usage data. It is tempting to look at my research interest (AI and OER) through that familiar lens. However, Tracy redefines rigor as "thick description," time in the field, and the care taken in analysis. I will need an internal paradigm shift to stop looking for the usage statistic, and instead seek the rich rigor and credibility that comes from deeply understanding a single instructor's experience with instructional design.

III. Meaningful Coherence at the Border of Tech and Social Science

Tracy states a study is coherent when its methods align perfectly with its overarching paradigm. Because technology naturally invites quantitative measurement (how fast, how many, how efficient), there is a constant risk of methodological misalignment. I know that it will take a conscious effort to ensure my study of AI and OER retains meaningful coherence by remaining a social science inquiry focusing on human decision-making and systemic equity (accessibility), rather than slipping back into an IT usability report.

This week, our coursework shifted from the philosophical frameworks of qualitative research into the practical, grounded work of the ethnographer. The reading by Spradley (1980) detailed observational methods introduced the metaphor of the researcher as a "map-maker" approaching an uncharted island. We were tasked with relying on "grand tour" questions, asking simply "What is going on here?" to make descriptive observations without testing any hypotheses.

I. Leaving the Dashboard Behind

As I have noted, my background in STEM, IT, and learning analytics has conditioned me to look for predefined variables. I am used to logging into a system to read a dashboard of usage statistics. Stepping into the Old Braeswood Neighborhood Park to conduct a one-hour, non-participant observation forced me to leave that quantitative dashboard behind. I had to become the instrument of measurement myself. It is a surprisingly vulnerable feeling to just sit on a bench with a notebook, resisting the urge to categorize things, making assumptions about relationships and motivations immediately and instead forcing myself to just absorb the "waves of activity" as they unfolded.

II. Becoming the Instrument

This exercise taught me a critical lesson about the nature of qualitative inquiry. Before we can ask targeted "mini-tour" questions, we have to understand the landscape. This ethnographic exercise demonstrated that if you sit quietly and observe a space on its own terms, the environment will show you what is actually important. Learning to trust my own senses to map these unspoken social realities is a vital step in my development as a qualitative researcher.

III. Mapping the Unspoken Boundaries

By sticking to the grand tour question and observing the mundane, the invisible map of the park began to reveal itself. I noticed strict, though entirely unspoken, demographic and spatial segregations: women and young children dominated the shaded playground, while men with dogs occupied the open grass. There was also a highly synchronized temporal pattern, with a mass exodus that occurred before 5 PM as families timed their departure for the evening routine. I discovered that the organizing principle of the setting was spatial and temporal risk-management.

Our activity this week was to analyze an interview qualitatively. In this case, it was an excerpt from a TV interview with Myles Horton. Horton was an educator, a social activist, and an influential figure in adult education for social change. As an intellectual force behind democratic education movements, he emphasized "education" versus "schooling" and believed in people's own abilities to change their lives based on their own experiences. He viewed education as a political, ethical, and foundational practice based on respect for the learner's experience and the aim of social transformation. His approach to learning is known for its emphasis on dialogue, questioning, reflection on lived experience, and the belief that education should balance authority with freedom and inquiry.

When I was performing descriptive coding, I tended to default to the rhetorical function of the sentence rather than the topic of the data. Once I analyzed it further, I realized that I needed to summarize what was actually being discussed when I created a descriptive code. For example, on my first attempt, I coded data as "value" and "mission statement," but I later realized that a better descriptive code would be "trusted people" and "teaching and learning mission." I also found that during process coding, I needed to capture the action being described by Horton in the interview, as opposed to just describing the content of the sentence. For example, I changed "positioning statement" to "stating beliefs."

Upon analyzing this data, I found strong clusters associating the descriptive code of "trust in people" with the process code of "stating beliefs." He used phrases like "we believe in people" and "our loyalty is to people," which showed his philosophy of establishing a belief in the inherent value of the community before teaching or facilitating. I also observed clusters linking the descriptive code "teaching and learning mission" with the process code "valuing experiences and empowering." This showed how his mission isn't passive; it actively uses these adults' past experiences to build agency.

All in all, this relates directly to my understanding of my own role in training and helping adult professionals, whether they are university faculty or teachers at a professional development session, or staff being trained on a process. My role these audiences is not to be a traditional transmitter of knowledge, but to facilitate their empowerment as professional adults.

I actually implemented these ideas  at a workshop I presented this week at the TxDLA Digital Learning Conference, where I decentralized my own authority and gave adult learners the opportunity to interact in a two-cycle learning model. The first stage I describe as individuation, which is independent, choice-based discovery where each person in the group picks a different mastery path to explore. This is followed by pluralization, a collaborative knowledge-building phase where they synthesize their knowledge together. This design moves participants from active listeners of a presentation to active creators. The goal was to move away from traditional professional development where there is a distinct theory-practice gap and presenters lecture to educators about active learning without actually modeling it. Instead of simply being exposed to pedagogical theories, the instructors get to experience the theory and actively implement it within the session. In this way, educators get to relate the material to their own experiences and take more control of the learning process.

This week, we further explored literature related to our research interests, focusing entirely on empirical studies based on qualitative approaches. I had the chance to be exposed to many theoretical and conceptual frameworks along with different qualitative approaches.

Exploring this literature helped me reframe my interest in instructor evaluation of OER. It informed my understanding of the topic, prompting me to think of it as a multidimensional challenge involving technology, pedagogy, and social context, rather than just focusing on compliance measures. Because I am interested in educators using OER, I looked at a lot of sources where educators are implementing OER strategies. I also reviewed literature on the AI literacy of people developing OERs and of educators in general, as well as the theory and practice gaps in educator training.

I did this so I could further synthesize my understanding of my core research topic: educators using AI to evaluate and improve OERs. The literature makes it clear that the adoption of OERs is not only a technical upgrade, but a sociotechnical intervention. It requires very clear guidelines in terms of security, ethics, accessibility, and pedagogical and curricular standards. For educators to be able to shift their labor burden using AI, they really do have to have a strong foundation in its use.

Furthermore, the theory-practice gap in educator training can be improved with a participatory, continuous feedback paradigm driven by a strong social justice lens to ensure AI literacy and equitable OER design. OERs present a huge opportunity to challenge the educational normativity that comes from standard sources of instructional material. However, to realize this opportunity, educators need the ability to evaluate these resources for their curricular and instructional purposes in a way that actively promotes equity and social justice.

Now that I have completed the CITI training, I considered how it would apply to my specific research interest regarding educational faculty using AI to evaluate and adapt OERs. In a social science setting, the risk in research is usually psychological, social, or professional; in my context, I believe the risk to participants would be mostly professional.

There is a given stigma around AI use in curricular activities and to generate content for instruction. Additionally, given the increased legal compliance required for accessibility, educators talking about not knowing how to make their courses accessible might face professional repercussions. Because the researcher is very embedded in data collection, a qualitative study can never truly be anonymous. Therefore, confidentiality is the key aspect. In this case, not only do names need to be de-identified, but other aspects such as courses, institutions, and specific materials must be masked to fully protect participants' identities.

Given that we are in an age where most of our data is collected digitally, this brings a lot of data security questions to the forefront, specifically regarding data storage. The ethical standard is to use institutional accounts where data is protected by the agreements between the institution and the vendor, as opposed to using personal, free accounts which do not have those protections or the same level of enterprise security.

Finally, being an expert in the topics I am asking about, such as accessibility and instructional design, I must be aware of how I am perceived. Being in the education field, I might be viewed by participants as an evaluator rather than a researcher. The principles of the CITI training will help me design an informed consent process that explicitly separates my research from any administrative oversight, allowing participants to speak freely and safely.

As I conclude this course, this final entry serves as both a reflection on my Qualitative Research Design Proposal and a synthesis of my evolution throughout the course. What began as an exploration of qualitative research methods has culminated in a rigorous proposal that views technology through a deeply human, sociotechnical lens. The experience of assembling this proposal was one of profound synthesis. It required connecting the components built piece by piece—the Research Purpose, the Annotated Bibliographies, and the Methodological Framework—into a coherent product.

My final project, titled "Navigating the Workflows of Open Educational Resources: A Cross-Case Analysis of AI-Assisted Evaluation and Adoption in Higher Education," is a realization of my semester’s work. My topic focuses on the instructional and support ecosystems around evaluating and adapting OER using AI. By designing a qualitative Cross-Case Analysis (CCA), I am creating a framework to examine different instructors as distinct "cases" and determine whether AI can act as a "collaborative partner" in their instructional workflows, ensuring curriculum mapping and inclusive design are prioritized. 

Choosing CCA was a deliberate, strategic decision; it is an inherently robust methodology that provides a comparative lens, enabling the identification of patterns and variations across different institutional or disciplinary contexts. It moves beyond the uniqueness of a single case to build higher-level concepts and broader explanations. Furthermore, the flexibility of CCA is particularly significant for a researcher operating at the intersection of social science and technology. It provides a methodological framework that can comfortably accommodate mixed-methods in the future. 

While this proposal is rooted in qualitative inquiry, the "Big Tent" of CCA allows for the eventual layering of quantitative data, such as learning analytics or system usage metrics, over the deep narratives of the participants. This ability to integrate the objective "dashboards" of my professional background with the interpretative "thick descriptions" of qualitative research is essential for a comprehensive study of the sociotechnical landscape. This proposal is not just a class assignment; it is a doctoral blueprint and a commitment to ensuring that my future research doesn't just describe the world of educational technology, but actively works to transform it.