Week 3

DoctoralConceptsFinal111.docx

Writer's Journal: Doctoral Concepts

Reflection on My Role as a Doctoral Scholar

Stepping into the role of a doctoral scholar marks a new chapter in my academic journey, one that will require me to elevate both my writing and research practices. Unlike previous levels of study, the doctoral role emphasizes original contributions to knowledge, which means I must approach writing not only to communicate ideas but also to shape and advance scholarly conversations. This role will require me to think critically, analyze more deeply, and synthesize information across multiple perspectives. Moving forward, my writing must demonstrate precision, clarity, and a strong evidence-based foundation. My research, in turn, must go beyond summarizing existing knowledge to identify gaps, applying rigorous methods, and drawing meaningful conclusions that add value to my field.

Comfort and Discomfort with the Academic Writing Genre

I feel comfortable with the structured and formal aspects of academic writing, particularly the reliance on evidence, logical organization, and citation practices that hold writers accountable. I also find that outlining and revising multiple drafts helps me express my ideas clearly. However, I sometimes find the density of academic language and the expectation for highly technical precision to be challenging. Writing at this level often requires striking a balance between accessibility and sophistication, a skill I know I need to develop further. Additionally, I would benefit from more practice in synthesizing complex sources and integrating multiple perspectives seamlessly into my own argument, rather than allowing my work to feel like a summary of others’ ideas.

Essential Resources and Tools for My Writer’s Journal

As I progress in my doctoral studies, I want to include resources and tools that support both the technical and conceptual aspects of my writing. Organizing these materials into a centralized journal will help ensure consistency, efficiency, and clarity in my scholarly work.

APA Style Resources

· APA Style Official Website – Offers authoritative guidelines for formatting, citations, and style.

· Purdue OWL APA Guide – Provides practical examples and explanations to support proper application of APA rules.

Research Tools

· Google Scholar and Library Databases – Useful for locating peer-reviewed articles and current research in my field.

· Citation Management Tools (Zotero or Mendeley) – Assist in efficiently organizing references and generating accurate citations.

Writing Aids

· Grammarly – Supports grammar, clarity, and readability improvements.

· Templates and Notes – Especially for literature reviews, research methods, and academic vocabulary development.

Personal Notes

· Key Definitions and Terminology – Ensures consistent understanding and application of disciplinary concepts.

· Outlines and Checklists – Provide structured guidance for critical research processes, including problem statements and source evaluation.

These resources will allow me to remain consistent, organized, and focused on producing high-quality scholarly writing. By curating them in one place, I am creating a living journal that supports my coursework while also serving as a valuable, evolving reference throughout my doctoral program and beyond.

Writer's Journal: Research Sources

Reflection on Building My Research Plan

Developing my research plan has been an enlightening experience that has demonstrated the tremendous significance of structured organization in doctoral-level research. The best note-taking approach I have found is the double-taking of source descriptive notes and field descriptive notes, described in the research plan template. Having detailed templates for individual sources, consisting of one-sentence summaries, basic research parameters (focus, rationale, scholarly context, method, findings, implications), and connections to my specific research project, helps me better engage with each text rather than passively assimilating information. Additionally, organizing these notes into a spreadsheet has been a helpful way to read horizontally for insights specific to a source and vertically for trends and gaps in the literature. The most valuable sources I am finding are peer-reviewed scholarly articles from established databases, as they provide the rigorous methodology and evidence base needed to conduct doctoral-level work, while also giving clear examples of how scholars position their work within existing conversations.

Essential Resources and Tools for Research Excellence

As I develop my research skills, I am hoping to add a few database-specific resources to my journal to increase my chances of doing in-depth searches. I have found academic databases for my discipline, including Academic Search Complete, JSTOR, and ProQuest Dissertations & Theses Global, to be especially helpful, as they provide a variety of sources useful for different purposes in my research (Droog, 2021). I also want to incorporate the Learning Commons Search Strategy Worksheet mentioned in the research plan template because it gives a systematic approach to keyword development and database selection. These resources are important because they ensure that I am not restricting myself to surface-level or easily accessible sources, but instead engaging the depth and breadth of scholarship necessary for doctoral work. Additionally, using these specialized databases quickly will allow me to find the most recent research and not rely on outdated information that would be detrimental to my scholarly contributions.

Moreover, I would like to include advanced citation management and collaborative tools in my research tools. In addition to simple Zotero functionality, I will use Zotero's group library function to share sources with advisors and colleagues, and the templates of Zotero notes that correspond to the format of the source descriptive note that I have established (Behera & Meher, 2022). Additionally, I would like to include links to discipline-specific style guides and materials that address the finer requirements of my discipline beyond general APA formatting. We need such tools as they are instrumental to the technical side of the research and in the collaborative and iterative nature of doctoral scholarship. When I prepare my research materials in an organized, shareable, and professional manner, I will be better able to serve my scholarly community. It will also help me make my work as scholarly as possible. This resource management plan is designed to facilitate the completion of original and high-quality research in my doctoral studies.

Writer's Journal: Growth and Feedback

Reflection on Growth as a Writer

After reading my initial posts of the Writer’s Journal, I realize I have come quite far in understanding the requirements of writing at the doctoral level. Initially, when I wrote about my role as a doctoral scholar, I did so in an abstract manner because I understood that I needed to provide specific details. I needed to write in an evidence-based manner, and my specificity and evidence had to be rigorous, but I was not yet operating at that level of rigor. Previously, I did not think much about the writing task. However, I have learned that writing is more reproducible and recursive than I initially thought. Writing is not simply a task of expressing ideas clearly. It is about thinking through and getting ideas down on the page. Each draft points to gaps in my logic, weaknesses in my evidence, or opportunities to strengthen my argument. I am also becoming more comfortable with the discomfort of academic writing. I have learned that struggling, revising, and not getting it right on the first try does not make me a bad scholar. The most important thing I knew was that writing and research are inseparable. My writing refines my research and vice versa.

Reflection on Giving and Receiving Feedback

Providing and receiving feedback on doctoral-level deliverable items has been transformative for me as a scholar and a writer. Receiving feedback taught me to consider my work in various ways. A well-researched idea is not useless just because it is not fully clear, properly organized, or has the wrong word used. At first, I found it tough separating who I was from what I made and got offended by feedback. Now, I see it as a chance to grow. My change in mindset has enabled me to accept suggestions more openly and to revise my work more meaningfully. Having provided feedback to peers has also substantially sharpened my ability to read critically. In particular, it has made me aware of various types of weaknesses in critical academic writing that commonly appear in texts, including unclear thesis statements, lack of evidence and supporting arguments, and poor transitions, among several others. Through this process, I have improved my editorial eye for my own work and gained a better appreciation for the collaborative nature of academic writing. Receiving feedback has made me a more deliberate, thoughtful, and self-aware writer.

Essential Resources and Tools

As I develop my doctoral writing skills, I aim to incorporate resources that specifically examine the writing process itself and the quality assurance aspects of academic work. I intend to include the book They Say / I Say: The Moves That Matter in Academic Writing by Gerald Graff and Cathy Birkenstein. The book provides templates to help us enter the conversation that occurs in academia, aiming to find a balance between integrating sources and our own argument. In my first journal entry, I stated that I want to develop this area of my writing. Additionally, I would like to include Paul Silvia's " How to Write a Lot: A Practical Guide to Productive Academic Writing," which discusses ways to establish consistent writing habits and addresses the productivity challenges that can arise when pursuing a doctoral degree. Additionally, I will draw on the University's Writing Center, including links to their online materials for developing a thesis statement, constructing paragraphs, and revising drafts, as well as consultations for high-stakes assignments. I value these tools because they inform me on what to write and how to approach writing systematically and sustainably, so that writing does not become an overwhelming task, but instead develops into one that is sustainable.

Another critical area I would like to strengthen in my journal is resources that support peer review, collaboration, and the refinement of ideas through dialogue. I plan to add links to peer review guidelines and rubrics that will help me provide a more structured and constructive response to colleagues, while anticipating how my own work will be evaluated against these criteria. Additionally, I would like to incorporate collaborative writing tools. Specifically, I want to use Google Docs to collaborate in real time with my peers and advisors during the writing process. Additionally, I plan to utilize tools like Miro or Notion for visual brainstorming and concept mapping. This will help me better organize complex ideas before writing them in formal prose. In addition, I will incorporate materials on academic discourse communities and writing for publication. This will include guidelines from major journals in my field, as well as examples of successful article structures. As a result, I will gain a deeper understanding of the scholarly conversations within my discipline. To be meaningful, doctoral writing must engage with the work of others. It benefits from critical dialogue and ultimately seeks to contribute to meaningful conversations. This is why tools like the Writing Pad and Thesis Writing Guide are vitally important. I position myself as a developing scholar, utilizing resources for collaboration, feedback, and professional development, rather than merely fulfilling assignments as a student. In addition to using resources in my assignment, I plan to use them to engage with the academic community and share my work.

Literature Review Analysis

Votto, A. M., Rohit Valecha, Peyman Najafirad, & Rao, H. R. (2021). Artificial Intelligence in Tactical Human Resource Management: A Systematic Literature Review. International Journal of Information Management Data Insights, 1(2), 100047–100047. https://doi.org/10.1016/j.jjimei.2021.100047

Purpose

Votto et al. (2021) present a systematic literature review with two clear research questions: which tactical HRIS elements are presented in the literature, and how those components are methodologically reflected. Instead of offering a general description of AI in HR, in general, the authors explicitly focus on the tactical (operational) but not strategic functions, and they break down HRIS into six specific components in both managerial and technical arenas. To achieve their intended aim, they subjected 315,053 articles to a rigorous methodology, narrowing down the selection to 33 primary studies. However, the limited focus of my results would require me to look elsewhere if I want strategic-level AI-HR integration or more recent information.

Genre and Structure

A systematic literature review is a two-step systematic method that employs transparent inclusion/exclusion criteria, search strings, and a statement of analysis. It is logically organized into background and definitions (Sections 2.1-2.6), a more detailed methodology (Section 3), and findings by HRIS component type (Section 4), which creates an impression of predictability and reproducibility. The disposition of the genre towards exhaustive categorization, at the expense of synthesis, results in the review enumerating what exists, rather than fundamentally critiquing theoretical contradictions or dissonances in the literature. The structure, however, does a good job of indicating where research focus is; yet, I need to put in more effort to comprehend why some aspects of it are under-researched or what theoretical insights the patterns provide.

Context in the Field

Votto et al. locate their contribution clearly in opposition to three previous systematic reviews (Di Vaio et al., 2020; Vrontis et al., 2021; Qamar et al., 2021), asserting that the reviews lacked analysis of how AI applications differ in technical (data-driven) versus managerial (human-centric) HRIS functions. They define their own contribution in Table 3. I will observe that such positioning can be more robust, as the authors admit that they complement prior work, but do not delve into the reasons why prior reviews did not employ this technical-managerial division or whether that division was methodologically warranted. Their review of the existing literature is superficial; they outline previous literature but do not thoroughly examine its theoretical premises or methodological advantages and disadvantages.

Thematic Coherence and Integration

The review structures findings based on the technical-managerial HRIS spectrum, which structures the literature but limits my analysis as a reader. The authors create a fundamental organizational distinction by distinguishing between Employee Performance and Satisfaction (managerial) and Best Practices (technical); however, this organizing principle is sometimes imposed by the literature rather than being derived from it. The results indicate that technical elements prevail in the empirical research (19 of 33 articles deal with resource-based activities). However, the review does not thoroughly address whether it is an actual research gap or a methodological bias in quantifiable, automatable functions. Cross-component integration is limited- every category of HRIS is treated separately, and I can learn little about how these functions interrelate or how a deficiency in one area influences another.

Implications and Contributions

The review identifies a concrete research gap: managerial HRIS components lack empirical studies, machine vision has not been utilized in HR settings, and compensation/benefits systems have not received direct attention in the 33 articles. The results lead to uncharted territory and direct future research. The review, however, does not question whether the gaps are actual opportunities or structural issues that pre-empt some AI applications from reacting to empirical testing. As an illustration, a research gap on compensation and benefits might reflect both actual negligence and the realization that algorithmic fairness in compensation decisions needs irreducible human judgment. Its practical contribution to my personal work is minimal, as the review provides a landscape audit, but has little information on how AI systems can be applied or work efficiently.

Comparison with My Research Area Primer

According to my analysis, the context in which AI-HR tools are implemented significantly influences their effectiveness. Trust in those tools varies between cultures, and well-being depends on organizational support. Furthermore, the ROI can only be ascertained from extensive measurement. Conversely, Votto et al. merely take stock of what exists without constructing a unifying theoretical argument. In my primer, I highlight the dynamics of implementation and point to tensions worthy of investigation (such as how organizational support may promote or harm well-being). Votto et al. identify research absences but do not clarify their theoretical significance. My primer draws on abstract concepts based on case studies (Microsoft); Votto et al. interpret articles as data points in a distribution. One point of difference I observe: I read the literature to see patterns and contradictions that raise deeper questions, whereas Votto et al. reads the literature to find out what components are repeated how many times. My primer is placed in the context of larger organizational discourse; Votto et al. is placed in the context of the systematic review literature. When developing my own literature review, the Votto et al. models meets all criteria of methodological rigor, but it also cautions me to avoid letting categorical organization take the place of critical synthesis.

Madanchian, M., Taherdoost, H., & Mohamed, N. (2023). AI-based human resource management tools and techniques; a systematic literature review. Procedia Computer Science, 229, 367-377. https://doi.org/10.1016/j.procs.2023.12.039

Purpose

Madanchian et al. (2023) perform a systematic literature review based on three clear research questions: what AI tools are popular in HRM, how accessible are these tools, and what is the connection between AI and the HRM case? The authors commit to “critically synthesizing diverse scholarly perspectives” and providing “evidence-based insight.” However, the purpose of the review is somewhat clouded for me, due to what I perceive as scope creep. It aims to catalogue tools, measure impact, synthesize theory, and offer statistical trends all at once. The implication is that the authors wish to do all things at once instead of respecting their priorities. I believe that the review is a success in certain areas (tool identification) and a failure in others (theoretical synthesis, statistical rigor).

Genre and Structure

The systematic literature review is classically constructed: the introduction determines the importance, the methodology includes inclusion/exclusion criteria and the search strategy, the results provide the list of findings, which is divided into themes, and the discussion ties the results to the research questions. But I could see that the execution is unequal. This methodology is too brief. It only has 15 lines of code. The authors narrowed the 117 papers to 17 (a 15% retention rate) and they do not specify why they rejected any at each phase, which I consider acceptable. The results section switches between the various organizational patterns: by AI application (recruitment, training); adoption drivers and challenges. I find it difficult to follow their argument because of its organizational inconsistency. The genre promises systematic rigour but provides what looks like a systematic overview.

Context in the Field

Madanchian et al. do not position themselves against earlier AI-HRM reviews as Votto et al. did. They cite other literature reviews as a passing referral (Votto et al., Vrontis et al., Di Vaio et al.) but fail to explain why their work is distinct or constructed on this basis. It is a great weakness--I know not whether they are adding anything new to the landscape, or whether they are repeating past analyses. Their engagement with the readings is mostly descriptive. When they discuss Agarwal on preparedness in organizations, or Qahtani and Alsmarait on trust, I find myself reading abstracts. This makes the review more of a catalog than of a scholarly discussion with the present work.

Thematic Coherence and Integration

The review identifies themes, including AI adoption and impact (8 articles), AI uses in HRM (5 articles), and ethical considerations (1 article), which do not work well together. The authors distinguish between adoption and applications and ethics and suggest that the two are parallel tracks and are not connected. As a case in point, in one of the studies, ethical considerations seem to be a side matter, not a thread that runs through the text of adoption and implementation. Those themes do not resonate as strongly when I read about adoption drivers (organizational preparedness, perceived benefits, trust) as we discuss the issues of dehumanization or team-level human-AI interaction. It would be clearer in the review how these themes build or layer one another—in what ways, e.g., trust is an adoption driver as well as a problematic issue challenged by the issue of algorithmic bias.

Implications and Contributions

The review observes that 60% of the articles mention the positive AI impacts on HR effectiveness, and 70% the drivers and challenges of adoption. These percentages sound interesting to me, but not studied- what are the percentages that most articles discuss adoption drivers, not actual impact? The authors conclude by a list of implications: organizations should be prepared to, trust is essential, ethics are crucial, and human-AI collaboration is complex. They are rational considerations, yet they do not extend further than what the literature informs us of. The review does not generate an original thesis of what underlies these trends, or what the trends tell us about the maturity of the field. In my example, the most meaningful addition is to discover whether the emphasis on adoption drivers portrays real failures in our ability to measure impact, or whether it reveals optimism among authors regarding AI in the absence of that optimism. This is not the question the review tries to answer.

Comparison with My Research Area Primer

There are significant variations in my synthesis approach compared to that of Madanchian et al. My primer highlights the following tensions that require investigation: organizational support may either strengthen or undermine well-being; the cultural context may have a profound influence on trust mechanisms; and the methodological basis of ROI measurement remains weak. Madanchian et al. reveal trends, including trust issues, ethical concerns, and the need for adoption preparation. I employ cross-cutting themes (cultural context, implementation dynamics, measurement) in my primer to support the thesis that context dictates outcomes. Madanchian et al. classify by function (recruitment, training, performance management). My primer bases its arguments on real-life examples (the gradual strategy of Microsoft, the Microsoft case with 40% adoption growth). Madanchian et al. cite the research more abstractly. My primer ends with methodological implications for my future inquiry (must be longitudinal, quasi-experimental methodologies). Madanchian et al. conclude with concrete suggestions for organizations. The contrast reveals a significant point: I am developing a research agenda based on what the literature tells us about complexity and constraints, whereas Madanchian et al. are developing a practitioner guide based on what the literature indicates works. They are both legitimate, yet they differ radically as intellectual undertakings. In relation to developing my literature review, Madanchian et al. advise me not to be satisfied with trend identification when I might be developing theoretical tension that warrants exploration.

References

American Psychological Association. (n.d.). APA style. https://apastyle.apa.org/

Behera, M., & Meher, D. (2022). Zotero: An overview of an open-source citation management tool for researchers. Indian Journal of Information, Library & Society, 35(1-2), 74-82. https://www.researchgate.net/publication/362066740

Droog, A. A. (2021). ProQuest dissertations & theses global. The Charleston Advisor, 23(2), 30-33. https://orcid.org/0000-0003-2868-8495

Graff, G., & Birkenstein, C. (2014). They say, I say: The moves that matter in academic writing (p. 245). New York: WW Norton & Company. https://www.researchgate.net/publication/281562720

Grammarly. (n.d.). Grammarly: AI writing assistance. https://www.grammarly.com/

Mendeley. (n.d.). Reference management software. Elsevier. https://www.mendeley.com/

Purdue Online Writing Lab. (n.d.). APA style introduction. Purdue University. https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_style_introduction.html

Silvia, P. J. (2018). How to write a lot: A practical guide to productive academic writing. American Psychological Association. https://psycnet.apa.org/doi/10.1037/0000109-000

Zotero. (n.d.). Your personal research assistant. https://www.zotero.org/