Developing Quality Dissertations Review

Developing Quality Dissertations Review

Table of Contents

Why is it that crafting a dissertation in the humanities often feels like navigating an intricate maze? Where do we begin, and most importantly, how do we sustain our sanity while aiming for excellence? Enter “Developing Quality Dissertations in the Humanities: A Graduate Student’s Guide to Achieving Excellence Paperback – 31 December 2008,” a beacon of hope for those of us dipping our toes (or perhaps drowning) in the treacherous waters of academic publishing.

Get your own Developing Quality Dissertations in the Humanities: A Graduate Students Guide to Achieving Excellence     Paperback – 31 December 2008 today.

The Magic of Clear Guidance

How many times have we sat down with a cup of coffee, ready to tackle our dissertation, only to find ourselves overwhelmed? This guide, thankfully, breaks things down in a seamless way, holding our hand (figuratively, of course) through the monumental process. It’s as if someone poured a soothing balm over our frayed nerves.

The Breakdown of the Beast

One of the beauties of this book is the way it divides the daunting dissertation process into digestible segments. Let’s break down the main components here:

Section Description
Conceptualizing This involves the initial stages of brainstorming and refining our topic.
Researching Tackles methodologies and strategies for gathering and analyzing data.
Writing Offers tips and structures for the writing process itself.
Revising Guides us through the critical process of revision, making sure nothing is overlooked.

Each section feels like a mini-victory; we can easily see our progress as we move from one to the next, a motivating factor unparalleled in other guides.

Developing Quality Dissertations in the Humanities: A Graduate Student's Guide to Achieving Excellence Paperback – 31 December 2008

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Solid Strategies for Success

Sure, it’s nice to have someone say, “Just start writing!” But what about when we hit a wall? This guide doesn’t leave us hanging. It dives deep into specific strategies, from developing a solid thesis statement to dealing with the inevitable writer’s block.

Step-By-Step Instructions

What’s even more compelling is the step-by-step nature of the advice. Instead of vague platitudes about “doing your best,” the book lays out clear, actionable steps. We’re talking about detailed outlines, sample timelines, and even suggested reading lists that are heaven-sent when we’re knee-deep in primary sources.

Using Real Examples

The guide also uses examples from actual dissertations. Seeing real-world applications of what we’re trying to achieve? That’s pure gold. It demystifies the process and provides tangible milestones we can aim for.

Developing Quality Dissertations in the Humanities: A Graduate Students Guide to Achieving Excellence     Paperback – 31 December 2008

Find your new Developing Quality Dissertations in the Humanities: A Graduate Students Guide to Achieving Excellence     Paperback – 31 December 2008 on this page.

Let’s Talk About Feedback

Revisiting our work is like looking back through the window of time; it’s rarely pleasant, often cringe-worthy, but utterly essential. “Developing Quality Dissertations in the Humanities” elevates this process, emphasizing structured feedback loops that can turn our rough drafts into polished gems.

Feedback That Works

The book makes it clear: not all feedback is created equal. It teaches us how to seek out and digest constructive criticism, and more importantly, how to implement it effectively. Think of it as a guide on turning noise into a harmonious symphony that readers (and our advisors) will appreciate.

Peer Reviews and Beyond

Another gem is the inclusion of strategies for peer reviews. Getting feedback from friends or colleagues can be a minefield, but this guide offers ways to navigate it gracefully and productively. By the end, we’ll be pros at both giving and receiving critical feedback.

Time Management Tips for the Eternally Overwhelmed

When it comes to dissertations, the sheer volume of work can be paralyzing. However, this book doesn’t just give tips; it offers a systematic approach to time management.

Creating a Timetable

We get a lot of advice about making schedules, but this book goes a step further by offering templates and suggestions. With these tools, it’s much easier to create a realistic timetable. Finally, we can see an endpoint in sight!

Juggling Commitments

Balancing a dissertation with other commitments – like teaching, part-time jobs, and personal lives – can feel like juggling flaming swords. Luckily, the guide provides strategies for multitasking and prioritization, helping us to keep everything afloat without losing our minds.

Developing Quality Dissertations in the Humanities: A Graduate Students Guide to Achieving Excellence     Paperback – 31 December 2008

Emotional Support (Yes, We Need It)

Working on a dissertation often feels like a solitary journey, but it doesn’t have to be. The book touches on the importance of emotional and psychological well-being.

Coping Mechanisms

The emotional ups and downs of dissertation work are addressed thoughtfully, and the guide offers practical coping mechanisms. We learn how to deal with the isolation, burnout, and anxiety that often accompany such major projects.

Finding Support Networks

It also stresses the importance of support networks. Whether through academic advisors, writing groups, or even family and friends, it encourages fostering a network of people who can provide moral support. Knowing someone has our back makes a world of difference.

The Art of the Rewrite

Perhaps one of the most practical sections of the book is the one on revisions. And let’s be honest, very little emerges perfect on the first try. Understanding this is crucial for our sanity.

Structural Revisions

The guide advises breaking down the revision process into manageable pieces, focusing initially on larger structural issues before zooming in on finer details. This approach prevents us from getting overwhelmed and allows for more effective revisions.

Polishing the Final Draft

Once the heavy lifting is done, the book guides us through the final polish – fixing typos, refining language, and ensuring our argument flows seamlessly. It’s like giving our dissertation a final buff to make it truly shine.

The Finish Line: Submission and Beyond

Just when we think we’re done, the final submission process rears its head. Luckily, the book doesn’t abandon us here.

Preparing for Submission

From formatting guidelines to double-checking footnotes and citations, the guide covers all the nitty-gritty details. Last-minute errors can be the difference between acceptance and rejection, and this section ensures we don’t overlook anything.

Defense Strategies

Even post-submission, we’re not out of the woods. The dissertation defense looms large, but fear not. “Developing Quality Dissertations in the Humanities” offers strategies to prepare us for this academic rite of passage. We’re talking about mock defenses, potential questions, and ways to articulate our ideas clearly and confidently.

Final Thoughts and Ruminations

Reflecting on the whole process, it feels less like a dreaded chore and more like an achievable journey, thanks in large part to this guide. We’ve gone through conceptualizing, researching, writing, revising, and even defending our work with a clear map in hand.

The All-in-One Resource

In a sea of vague and overwhelming advice books, “Developing Quality Dissertations in the Humanities” stands out for its practical, step-by-step guidance. It provides not just a roadmap but also the emotional and tactical support that many of us desperately need.

Room for Improvement

No guide is perfect. If there’s one area for improvement, it might be the inclusion of even more diverse case studies and examples. Every dissertation is unique, and seeing a wider variety of approaches could benefit readers from different subfields within the humanities.

A Must-Have for Grad Students

In sum, whether we’re just starting or already deep into the dissertation process, this guide is an invaluable resource. It offers a reassuring voice and clear, actionable advice that can transform a daunting project into a more manageable and even enjoyable endeavor. So, should we get cracking on our dissertations? Absolutely. But let’s make sure this guide is right by our side.

Through its well-organized sections, practical strategies, and supportive tone, “Developing Quality Dissertations in the Humanities” truly is a graduate student’s guide to achieving excellence. Who knew that writing a dissertation could be this… manageable?

And with that, let’s dive—scratch that—let’s just gently wade into our dissertations, equipped with both confidence and a solid plan.

Find your new Developing Quality Dissertations in the Humanities: A Graduate Students Guide to Achieving Excellence     Paperback – 31 December 2008 on this page.

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University Student Essentials
University Student Essentials

About Me

With 25 years of experience in healthcare IT implementation, Emmanuel began his career at the University of Pittsburgh Medical Center, working as an assistant manager for a billing system implementation. Over the years, he has explored various aspects of the healthcare IT domain, successfully implementing several laboratory information systems and electronic medical record (EMR) systems, such as Cerner Millennium and Epic EMR.

In 2005, Emmanuel shifted his focus to public health, working on bio-surveillance implementation for the Centers for Disease Control and Prevention (CDC). He contributed to the BioSense Data Provisioning Project and performed extensive analysis of HL7 messages in hospitals and healthcare facilities. Additionally, Emmanuel requirements analysis for the CDC BioSense Analysis, Visualization and Reporting (AVR) project and played a key role in publishing the Situational Awareness updates to the BioSense System Requirements Specification (SRS).

Over the past 11 years, Emmanuel has worked in the Middle East, implementing the Epic EMR system at Cleveland Clinic Abu Dhabi. As a multidisciplinary team member, he has taken on various roles, including SCRUM Master, Project Manager, Integration Engineer, and Platform Engineer. Concurrently working as an adjunct university faculty member, teaching graduate-level courses in Systems Life Cycle and undergraduate courses in Health Information Systems

From a technological standpoint, Emmanuel has designed, installed, and implemented complete hospital integration systems using Rhapsody Integration Engine, MS SQL Server, and Public Health Information Networks Messaging System (PHINMS). He has also developed over 10,000 interfaces some of which coded in Java and JavaScript.

In 2019, Emmanuel expanded his skill set and entered the field of digital marketing, quickly becoming a proficient Digital Marketing Strategist. He has since helped numerous clients develop robust digital marketing strategies for their businesses. His expertise encompasses Social Media Marketing, On-page and Off-page SEO, Google Ads, and Google Analytics. Additionally, he and a team have managed clients’ website development projects, ensuring that each site is optimized for SEO, further enhancing their online presence and performance.

Alongside their digital marketing expertise, Emmanuel has delved into the world of Affiliate Marketing, where Emmanuel and his team successfully managed and executed campaigns for a variety of clients. By identifying the right products and services to promote, Emmanuel and his team helped clients generate passive income streams and increase their overall revenue.

Their approach to Affiliate Marketing involves creating valuable content that educates and engages the target audience, while strategically incorporating affiliate links. Emmanuel and his team have experience working with multiple affiliate networks and platforms, ensuring optimal tracking and reporting of performance metrics. By staying up to date with the latest trends and best practices, Emmanuel and his team have been able to optimize affiliate campaigns for maximum results, fostering long-term partnerships and sustainable growth for their clients.

As an accomplished professional, Emmanuel holds dual Bachelor of Arts degrees in Linguistics and English, a Master of Science in Health Information Systems from the University of Pittsburgh, and a Ph.D. in Information Systems from Nova Southeastern University.

My Teaching History

Professor Bazile is a dedicated technology instructor and Adjunct Faculty professor, who began his teaching career in April 2000 at the Business Career Institute in Las Vegas, Nevada.

In 2001, he expanded his expertise by training nurses in the use of Electronic Medical Records (EMR) systems. His experience in both technology and healthcare led to his appointment as an Adjunct Faculty professor at the University of Phoenix in May 2008, where he has taught several graduate-level information technology and healthcare information systems courses.

Dr. Bazile has also developed an HL7 course, which he has taught at various healthcare facilities, drawing from his own book, “HL7: Introductory and Advanced Concepts,” currently available on Amazon. With a passion for teaching and a commitment to ensuring students get the most out of each course he teaches, Dr. Bazile is a valuable asset to both his students and the institutions he serves.

My Teaching Philosophy

My teaching philosophy as an Information Systems professor in healthcare is built on the concept that education should equip students to be confident and capable problem solvers who are prepared to traverse the complicated and ever-changing landscape of Healthcare IT.

In order to accomplish this, I prioritize the creation of a dynamic and engaging learning environment that encourages students to engage with course material and with one another. This involves employing a range of teaching approaches, such as lectures, seminars, and hands-on activities, to ensure that students learn in the manner that best matches their learning style.

I believe the reason we have Information Systems as a discipline is to allow students to apply technology to solve real world problems. If that is the case, both undergraduate and graduate students have to be challenged to incorporate their core academic courses with their matriculated subjects. As such, it is important that students enter their Junior and Senior years with a strong command of the core courses such as Programming, databases, networks, hardware and software, as they serve as the foundation upon which real-world solutions will be built.

I also believe in the importance of incorporating real-world examples and case studies into my courses, as this helps to connect abstract concepts to practical applications. Additionally, I encourage students to apply what they are learning to their own personal and professional goals, as this helps to make the material more meaningful and relevant to their lives.

I strive to foster a positive and supportive learning environment where all students feel comfortable asking questions and participating in class discussions. I believe that this is key to fostering a sense of community and ensuring that all students have the opportunity to succeed.

I have also taught online courses. I have found in an asynchronous learning environment it can be difficult to apply the Peer Teaching or Experiential Learning Pedagogical Approaches. However, I have found the Discovery Learning approach to works quite well. Along with a boost to students’ self-confidence, Discovery Learning in an online environment allows students to synthesize information, expand on existing concepts on their own, while experiencing a positive outcome through trial and error.

Ultimately, my mission as an educator, and a Healthcare IT Information Systems professor is to provide students with the knowledge, skills, and confidence they need to thrive and succeed in their careers and to be technological leaders. By creating a positive and supportive learning environment, incorporating real-world examples and case studies, and encouraging students to apply what they are learning to their own objectives; my hope is to inspire and empower all students to achieve their full potential.

Population Size:

A total of 310 responses were originally received. Any response containing missing data due to unclicked radio buttons or unchecked checkboxes were first reviewed, and, if justified, were omitted from analysis. For surveys with missing data, a total of 18 responses were removed. In order to address any issues with response-set, the data was downloaded into Microsoft Access and queries ran to identify responses that contained the same values for each question. A total of 16 responses were found to be qualified for removal. Another 18 were identified as outliers and removed leaving a total of 258 responses for the study analysis.

In order to assess multivariate outliers, the Mahalanobis distances were calculated and plotted against their corresponding Chi-Square distribution percentiles (Schmidt & Hunter, 2003). The resulting scatterplot is similar to a univariate normal Q-Q plot, where deviations from a straight line show evidence of non-normality. The data showed indications of moderate deviations from multivariate normality, as indicated by the concavity of the data points. There were no additional multivariate outliers or missing values in the data after the removal of 52 responses.

Descriptive Statistics

Frequencies and percentages were conducted for the demographics indicators, while means and standard deviations were calculated for the continuous indicators. For gender, there were 151 females (59%) and 107 males (41%) in the sample. For ethnicity, most participants were Caucasian (119, 46%), followed by African American (56, 22%). The two most populous education levels were Bachelor’s (90, 35%) and Master’s (62, 22%). The biggest proportion of the sample by age group was the 35-44 age group (101, 39%) followed by the 45-54 age group (59, 23%).

Analysis:

Confirmatory Factor Analysis and Composite Reliability

A CFA was conducted along with a reliability analysis to assess construct validity. Examination of modification indices and factor loadings indicated that CSE1, CSE5, CSE7, PC5, ATE1, ATE6, ATE8, PP5, and PP6 were all causing significant problems with the model parameters. The results of the last iteration of the CFA performed in R showed significantly improved fit, although still poor overall (χ2(545) = 2125.61, p < .001, CFI = 0.82, TLI = 0.81, RMSEA = 0.11). The high degrees of freedom indicate that a very large number of parameters are being estimated in this model.

Composite Reliability

For the full model, each construct had excellent reliability. The ATE latent construct had a composite reliability value of 0.89. The ORC construct had a composite reliability value of 0.94. The CSE latent construct had a composite reliability value of 0.85 and PC had a composite reliability value of 0.95. For PP and RES, the composite reliability scores were 0.80 and 0.96 respectively. These values indicate that the loadings for each construct were all directionally similar, and that the items in each construct show a high degree of consistency.

Cronbach’s Alpha

Cronbach’s alpha values were calculated for the items in each construct. The alphas for PC (α = 0.90), AXY (α = 0.94), and RES (α = 0.94) indicated excellent reliability. The alphas for CSE (α = 0.80), ATE (α = 0.88), and PP (α = 0.83) all showed good reliability. These values confirm the results of the composite reliability tests, and reiterate the high degree of reliability within each latent construct.

Partial Least Squares – Structural Equation Modeling

A partial least squares- structural equation modeling (PLS-SEM) was conducted to determine how well the data fit the proposed model, and discern whether significant relationships existed between the independent and dependent constructs. The full model showed AVE values of 0.53 for ATE, 0.69 for AXY, 0.44 for CSE, .72 for PC, .35 for PP, and 0.81 for RES. The high values for AXY, PC, and RES indicate that the amount of variance accounted for in the manifest variables is sufficiently high. The values for ATE, CSE, and PP indicate that some of the variance in the manifest variables is left unexplained.

Structural Model

Once the measurement model had been tested for model specification, the structural model was tested to determine if ATE, AXY, CSE, PC, and PP had a significant effect on RES. A path weighted model was calculated using 10,000 bootstrap samples in R. The results showed a pseudo R-squared value of 0.78. This indicates that approximately 78% of the variance in RES is explainable by the collective effects of CSE, PC, ATE, PP, and AXY.

Further examination of the effects indicated that AXY had a highly significant effect on RES (= 0.87, < .001). This indicates that a standard deviation increase in AXY increases the expected value of RES by 0.87 standard deviations. CSE did not have a significant effect on RES (= 0.02, = .423). Additionally, CSE (= 0.02, = .423), PC (= 0.05, = .334), ATE (= 0.00, = .983), and PP (= 0.03, = .407) did not have significant effects on RES. Table 11 outlines the results of the path estimates.

Correlation Analyses

Both Pearson and Spearman correlations were calculated on the composite scores. The results of the Pearson correlations indicated that CSE was significantly correlated AXY (= 0.22, < .001) and RES (= 0.21, < .001). The results also indicated that PC was significantly correlated with ATE (= -0.79, < .001), AXY (= 0.18, < .001), and RES (= 0.20, < .001). ATE was significantly correlated with AXY (= -0.19, < .001) and RES (= -0.19, < .001). AXY was significantly correlated with RES (= 0.85, < .001).

ANCOVA Analyses

An analysis of covariance (ANCOVA) was conducted to determine if a significant relationship existed between the AXY, PP, CSE, PC, ATE scores and RES controlling for Gender, Age, Ethnicity, Education, and Specialty. The overall model was found to be significant (F(63,194) = 53.39, < .001), with an R2 value of .95, indicating that 95% of the variance in RES was explained by the collective effect of the independent variables and covariates.

Since the overall model was found to be significant, the model’s covariates were assessed. The AXY (F(10,194) = 262.20, < .001), ATE (F(7,194) = 2.20, = .036), Years computers (F(1,194) = 5.71, = .018), and PC (F(12,194) = 2.00, = .026) scores were found to be significant, indicating that a significant amount of variance in RES is explained by AXY, ATE, and PC.

A path diagram depicting the results of the structural model.

Results

This research investigated Computer Self-Efficacy (CSE), Perceived Complexity (PC), Attitudes toward EMR Systems (ATE), Peer Pressure (PP), and Anxiety (AXY) to determine whether these constructs as individuals, or as a group, or coupled together with some other factors could significantly explain resistance to EMR systems. Quantitative examination of self-reported survey results was performed to understand the strength and significance of the relationships, while these relationships were investigated to test the strength of model fit.

the regression paths of the structural model were examined to test the hypotheses. Significance was determined using an alpha level of .05. The model had an overall R2 value of 0.78. This indicates that approximately 78% of the variability in RES can be accounted for by CSE, PC, ATE, PP, and AXY. Since the overall model was significant, the individual coefficients can be interpreted. Some of the hypotheses were supported by the results of this study, and some were rejected. The construction of a data model of the relationships in this study could not meet thresholds that would be evidence of a good fit of the relationships identified in the study.

The fifth hypotheses tested the influence of AXY on resistance to EMR systems. AXY was expressed to be significantly related to resistance (r=.87, p<.001). This finding supports the hypothesis that anxiety with the EMR system will lead to medical care professionals rejecting use of the system. Unlike the findings of the first four hypotheses, the findings of the current study support previous research. Angst and Agarwal (2009) indicated that AXY is a factor which is significantly related to the problem of EMR system resistance. Based on the empirical findings of previous research, the present research and conceptual propositions and conclusions in previously written scholarly articles, there is a great deal of support for the finding that AXY is significantly influenced by EMR resistance.

The findings of this research do not support all findings by previous researchers, and there are multiple relationships which had been established as being significant that were identified as being insignificant in the current research. Generally, because of the inconsistency of previous findings and the current study there may be elements related to the sample examined or other contextual factors which may contribute to the inconsistency that exists. Ultimately, it is suggested that there be further research done on the problem of resistance to EMR system use.

Ultimately the findings support a new take on the problem of EMR system resistance that may contribute to the ways in which scholars investigate the problem of EMR resistance in general. This may also help with the way practitioners approach EMR systems, and articulate value of the systems to medical professionals investing record-keeping systems in the workplace.