University of the Cumberlands Online PhD in Information Technology

I dont know about NVivo but students do get free Grammarly Premium.

 

"E no da same."

Nvivo: "NVivo is a qualitative data analysis computer software package produced by Lumivero. NVivo is used across a diverse range of fields, including social sciences such as anthropology, psychology, communication, sociology, as well as fields such as forensics, tourism, criminology and marketing. Wikipedia"

Grammarly Premium here. https://www.grammarly.com/premium Hay una gran diferencia.

Good to have both, at such exalted writing levels.

 

I completed my DNP utilizing a combination of JASP for statistical analysis, SPSS for complex quantitative data crunching, Excel for data organization and visualization, and Word for writing. That entire manual process was enormously taxing. I'll never do that again. I highly recommend software-driven efficiency. Explore these tools to make your academic and research journey a bit smoother!

1. Literature Review:
   • EndNote: It's an excellent tool for managing your references and citations in your academic work.
   • Mendeley: This one not only helps you organize your references but also lets you connect with others in your field and discover new research.
2. Data Collection Surveys:
   • Qualtrics: If you need to create complex surveys with all sorts of fancy features like branching questions, Qualtrics is your go-to.
   • SurveyMonkey: It's super user-friendly and perfect for making and sharing surveys with various question types.
3. Data Analysis (Quantitative and Qualitative):
   • Qualitative Data Analysis:
     • NVivo: When you're dealing with lots of different types of data in qualitative research, NVivo is a lifesaver for coding and finding patterns.
     • Atlas.ti: Another user-friendly option for qualitative analysis, especially if you're working with big datasets.
   • Quantitative Data Analysis:
     • SPSS (Statistical Package for the Social Sciences): It's a powerhouse for crunching numbers and doing complex statistical analyses in various fields.
     • STATA: Especially great for economics and political science, it offers a wide range of statistical tools and data manipulation options.
4. Data Visualization:
   • Tableau: If you want to create cool, interactive dashboards to make your data pop, Tableau is your friend.
   • Microsoft Excel: It might be basic, but it's still a handy tool for creating different types of data visualizations.
5. Writing and Document Management:
   • Microsoft Word: The good ol' standard for writing and formatting academic papers – it's got all the features you need.
   • Google Docs: If you want real-time collaboration and cloud-based storage, Google Docs is a convenient choice.
6. Plagiarism Checks:
   • Turnitin: Widely used in academia, it has a vast database and provides detailed similarity reports.
   • Grammarly: Not just for checking plagiarism, it also helps with grammar, punctuation, and style – a useful all-in-one tool.

Note - These are some examples of each category not my recommendations

 

Submitted my final papers for ITS 833 and ITS 835. Regarding the SafeAssign incorrectly flagging the duplication of Milestone 2 in 833 as plagiarism (and the subsequent duplication of Milestone 3 since it includes 1 and 2), the Professor asked me to run the paper through Grammarly Pro (free to students) and report back the results (which showed limited plagiarism because it only checks the web and not past papers.) I did, and she said that she was satisfied no plagiarism occurred.

I've got a short week 8 (some discussion board posts) and then the term ends December 15. The next courses start Monday, January 8, 2024. Hoping to use the intervening time to complete CLEP Biology on Modern States and then I'll see about CLEP Chemistry in January. If I can pass both of those with good grades (not that CLEP does grades but their scaled score of 70 is roughly a 90% in a traditional course), I'll look into enrolling into Doane for real coursework.

 

It looks like the University of the Cumberlands just added another specialization to the Ph.D. in Information Technology.

Artificial Intelligence Specialization:

• MSAI 511 Introduction to Artificial Intelligence
• MSAI 532 Neural Networks and Deep Learning
• MSAI 532 Natural Language Processing
• MSAI 544 Application of AI in Healthcare
• MSAI 578 Data Visualization
• MSAI 630 Generative AI with Large Language Models
• MSAI 631 Artificial Intelligence for Human-Computer Interaction
• MSAI 632 Application of AI in Risk Management (originally listed as BADM 566)
• MSAI 599 Transforming Business with Artificial Intelligence

 

There were four content specialty areas available in the UCumberlands PhD in IT as of their 2021-22 catalog: Blockchain, Digital Forensics, Information Systems Security, and Information Technology.

The program has added not only Artificial Intelligence but also two other new content specialty areas since then: Cyber Engineering, and Data Science.

 

Oh, I don't see Data Science. But Cyber Engineering was there last year. I started with Information Security, but I switched to Blockchain. I am more interested in AI and Data Science.

 

In 736, I wrote this summary of tips and observations.

Also, in 736, I wrote Chapter 3 and then wrote Chapter 1.

I took 839 in the Fall of 2023:

• My chair strongly recommended just taking the comprehensive exam without studying. Then, if I failed any part of the exam, I could retake just that part. She was concerned I would waste a lot of time studying. I passed the first try, albeit with the lowest possible score. The exam is pass/fail, so it doesn't matter about the score.
  ---
• I spent the first few weeks creating my IRB application as broken into assignments in 839. I gained IRB approval on the first attempt.
  ---
• In 736, I already picked my survey instrument to gather the data required to answer the draft research questions I created. The theory helped explain the hypotheses I drafted. All of the foregoing made creating the IRB materials easier.
  ---
• We already knew my data was likely to be non-parametric, meaning the data was unlikely to follow a normal distribution. I wanted to do a mediation analysis, and given the scenario of non-normal data, that locked me into a statistical analysis called PLS-SEM. While waiting on IRB approval, I spent about 40 hours learning PLS-SEM, an advanced statistical analysis technique. Then I reinforced what I learned in SmartPLS, which is software used for PLS-SEM analysis. I found the topic challenging but relatively straightforward when learning one component at a time.
  ---
• I also began writing Chapter 3 while waiting on IRB approval. We were supposed to write it a little at a time over the whole course, but I worked ahead. Once I understood PLS-SEM, I felt the chapter naturally flowed.
  ---
• With IRB approval already gained four weeks into the semester, my chair recommended I pay a research firm called SurveyMonkey to gather the data. I knew what she was trying to say. Don't be one of "those students" who collect data for 3, 4, or 6 months, begging people on LinkedIn to take their survey. SurveyMonkey completed the data collection in a day or two.
  ---
• My chair said that Chapter 3 was good enough to pass 839, so why not start on Chapter 4? Why wait, she asked, when the only thing that now matters is dissertation completion. She noted Chapter 3 would evolve as I wrote Chapter 4.
  ---
• With 6 weeks left in the semester, I then wrote Chapter 4. I did spend a lot of time revisiting Chapter 3 based on what I actually did in Chapter 4. In fact, I made countless revisions to Chapter 3 (which explains what/how you will do in Chapter 4). Since Chapter 3 describes the what and how of what you will do (or did) in Chapter 4, it needs to match. It's your methodology. It was somewhat annoying to constantly update Chapter 3 as my research into PLS-SEM unfolded in Chapter 4.
  ---
• With 2 weeks left in the semester, I then started Chapter 5 and finished a week after the semester ended. I then made several passes back over all the chapters during the holiday break.
  • My editing style is I start reading and then find things wrong. If it's a recurring problem, I note where I am (so I can return there) and fix all other instances of the problem.
  • Making multiple passes through the document took a few weeks, a perfect fit for the holiday break.
  • Chapter 4 is ripe for APA formatting issues with statistical reporting, tables, and figures. There are many nuanced rules impacting the presentation of numeric data.
    ---
• Writing Chapter 5 was more difficult than I expected. The idea of Chapter 5 is to explain the significance of your results, especially how they fit with existing scholarly research, and close the research gap(s).
  • Thus, Chapter 5 is a mini-literature review analysis where you re-open selected areas of the literature review to show how your research agrees with, contradicts, or how your findings align or fit within the existing research.
  • Then, you will have ideas about why something worked, didn't work, agreed with, or didn't agree with existing research, which flows naturally into the limitations of the research and future research implications.
  • There were plenty of comparisons to make between the findings for my five research questions and the literature review.
    ---
• Near the end of 839, I reached out to my two potential committee members to front-run the idea of them being a committee member. They agreed. I'll seat them in 930.

Reflections and Thoughts:

• With a complete draft of the entire dissertation, I'm waiting for 930 to begin. Chapter 5 is the only chapter my chair has not yet seen. I think 930 does a QC (quality control) review over Chapters 1-4, then later over Chapters 1-5. I guess I'll spend the next two semesters playing the hurry-up-and-wait game, with little else to do other than minor revisions. Hopefully, I can defend early in 931 (maybe May), which begins in late April 2024.
  ---
• I haven't found the dissertation to be exceptionally difficult. Unnecessarily tedious? Yes. Could the whole be said in a more compact form like a journal article does? Of course. This is why no one outside of a committee reads dissertations. They're a rite of passage designed to complicate and punish research changes. If you change something, you probably have to update multiple chapters.
  ---

• The failure rate remains as high for DSRT 839 as it was for 736, where I believe maybe 5 or 6 students from our original 736 are still with me in 930!
  • I tried to help several students who approached me privately through the Blackboard messaging system. They generally had little to no theory to guide the research. Or, their survey instruments didn't gather the data needed to answer their research questions. Or the research questions made no sense given their literature gap. Or, they were trying to create their own survey instrument without using any theory, which makes no sense. Or, the writing was horrific--like, I thought WTF is this paragraph even saying here? How do these paragraphs connect? Why does this page even exist? I was stunned that they made it that far. Or, some combination of the previous.
    ---
  • Sadly, no amount of time is really going to make this work until they dismantle the whole thing and start over with everything in alignment.
    ---
  • I also saw a student with an absolute mess of a qualitative dissertation. There seems to be this belief that qualitative is easier. It's a TON of iterative work with interviews, coding the interviews, matching patterns, etc. In my view, qualitative wasn't even appropriate for this student's topic. Qualitative makes sense when we don't know much about a phenomenon and need qualitative research to determine variables or themes for future quantitative research.
    ---
  • Statistical analysis isn't that difficult. It's just basic logic. It's a test of whether you can reason and think about data. However, I think some students' innate fear of statistics forces them into bad dissertation decisions, like qualitative, because they think it's easy when it's not.
    ---
• From what I've seen, two common problems doom students in the dissertation process:

1. They just can't write. They bumbled, fumbled, cheated, or bull-crapped their way through the coursework. They don't understand how paragraphs should connect with one another--or how to even properly write a paragraph. They randomly sprinkle citations like it's pepper over soup, but they do not support critical statements. They lack the analytical and critical thinking skills to assemble #2 below.
   ---
   
2. UC doesn't make students configure a proper roadmap in 736. Students need to verify a path forward then, not later. The path forward or roadmap: a proper research gap, alignment of research questions with that research gap, testable hypotheses, survey instrument(s) (or some other data collection methodology) that provides the needed data to answer those research questions, real theoretical frameworks (not conceptual models, process models, etc. ) that justify the survey instrument (or whatever data collection is being used) guide how and why of hypotheses creation, etc.
   ---
   For qualitative, someone should ask: Is this really going to happen with interviews? What theory guides this research? Who says qualitative research is even needed here? Why is it needed here? If the student can't or won't learn statistics, are they really willing to do the enormous amount of work for a qualitative dissertation? That work starts with a small number of interviews, coding, etc, for a field test. Qualitative has its own special set of pitfalls too!
   ---
   Regardless of methodology, if you don't have the puzzle pieces together by the end of 736, they shouldn't let you out of 736. Nothing good will happen later. You're just wasting time because you don't have the proper pieces on the board.
   ---

​

If you do what I said in my post here and this post, there's no reason why this shouldn't be a straightforward process.! Consider how quality journal articles in your research area introduce the topic, explain theory, generate research questions and hypotheses using theory, explain their methodology, report their results, and then explain the significance. You're doing the same thing with more detail. That's all this is! It's a glorified journal article with much more background information and detail.

 

I'm in 931 at the moment. Looking through the grade book:
Week 2 - Apply for graduation
Week 3 - Chapters 1-4 Revisions
Week 7 - Chapter 5 draft
Week 9 - Dissertation file due (all components)
Week 15 - Dissertation Submission

Within the dissertation portal, I now have access to the IRB Closeout form. It states you can complete it once "approved human subject research is CONCLUDED."
It has a series of questions:
IRB Approval Number
Date of IRB Approval
Study Title
Reason for Closure
Total Number of participants
Total Number of participants who withdrew
Reason for participant withdrawal
PII Collected? (yes/no)
Informed Consent? (yes/no)
Analysis of PII? (yes/no)
Research Status? (yes/no)
Agree to maintain records? (yes/no)
Student/Investigator telephone #
Student/Investigator address

Now, here's what is interesting to me. In 931, the submissions clearly show it is graded by your Chair. No mention at all requiring YOU submit it to the Graduate school. Nothing about submitting it to your Committee either. Moreover, on the IRB portal, the Chair is supposed to submit your dissertation up to that point to the Graduate school for review. I can tell you for a fact that did not happen with our class. Thus, it would appear you just give everything to your Chair and if he/she blesses off on it, you're golden. I am inclined to believe this a bit since we were told last semester that everyone would be pushed to 931 regardless of status of your Chapter 4. In other words, pass the student. However, if you go to the IRB portal and look at 931, you'll see the requirement to submit your dissertation to your committee and then once they approve, you'd submit to the Graduate school for full manuscript QC - which could take 2 weeks for feedback. Once they approve, then you can schedule defense. But, again, in the grade book of 931, you just submit everything to the Chair - no requirements listed to send to Graduate school. So, really, I'm just not sure of what the actual process is.

 

[QUOTE="wingshot, post: 594049, member: 38398"
If you do what I said in my post here and this post, there's no reason why this shouldn't be a straightforward process.![/QUOTE]


I am in my first week of 736 leadership and took their suggestion to switch from a qualitative to a quantitative approach using Cumberland's vetted data collection instrutments. I going to hire SurveyMonkey as you suggested. My chair was pleased with this change of direction. He noted that while qualitative research may seem easier, there are many hurdles to overcome like validating instruments and increased IRB scrutiny.

Why recreate the wheel

Thank you so much Wingshot

 

DSRT 931 update:

In week 2, you apply for graduation - a very straightforward process (click a couple buttons and you're done). I find it interesting we apply for graduation so early on, especially in a program like a doctorate where everything hinges on your defense. For me, reaffirms my thoughts I expressed in my previous post.

 

More observations/thoughts.

There is this idea that nobody outside of your committee will read your dissertation. That it's just designed to show you can conduct legitimate research to a limited pool of people. However, for those not in the dissertation phase, let me tell you. Looking at others dissertations within ProQuest has been hugely beneficial to me. It has shown me how others outlined their sections, sub sections, etc., and I recommend looking at a lot of them. It can spark ideas, make you look at things or write about things you had not previously considered, etc. Unfortunately, I found something interesting last night. In ProQuest, using boolean logic to search "University of the Cumberlands" and then sorting by newest, I found 2 dissertations that were full of identically written information (blatant plagiarism).

Look at Chapter 3, 4 and 5.
https://www.proquest.com/docview/2878187310/4B719E0C546242B6PQ/7?sourcetype=Dissertations%20&%20Theses

Look at Chapter 3, 4 and 5.
https://www.proquest.com/docview/2878182412/4B719E0C546242B6PQ/8?sourcetype=Dissertations%20&%20Theses

Clearly, they are nearly identical or in a lot of different areas, word for word copies. These are dissertations approved in 2023!

This makes me think that TurnItIn and/or SafeAssign is not able to evaluate a dissertation.

Possible reasons:
Length of dissertation makes it impossible for the software to read every page.
The software is not being used on dissertations.
The professors simply don't look.
The professors simply don't care.
The broader graduate school doesn't look.
The broader graduate school doesn't care.

/perplexed

 

A school can take a long time to build a good reputation.
It takes very little time to have it torn down. I hope that doesn't happen to this school.

Have you communicated this info to the powers-that-be, at the school? Please let us know what you can, when you can.
This sounds very big indeed.

 

Such a risky thing. They can have their Doctoral revoked

 

deleted - J.

 

Absolutely! And you're simply shortchanging yourself in the end. You may get the title of Dr., but your lack of knowledge would be seen greatly the minute someone in the field is discussing things you should know about or worse, asks you information from your research.

No, I haven't since I just saw it. And to be honest, I'm not sure what good it would do when you think about it. If dissertations aren't being scrubbed by software to look for these things, then it's probably far more rampant and I've simply found 2. In fact, the only reason I caught it was because I was going down the list and read them back-to-back. Had they been separated by a few or I read them on different nights, it likely would have been overlooked.

 

Well, at least the cat is out of the bag. People have to start looking. And we can't blame everything on software.
SAAS (Software as a Scapegoat) has been so cruelly overworked it's barely alive, poor creature.

 

You should report it. The person who plagiarized deserves to have it revoked. It devalues the entire school.

 

I notice they have the same last name. Perhaps they are brothers or cousins who decided to collaborate in a way that violates accepted academic publishing norms.

Not good.