Learning theories in the Literature Review

• Overview of Learning Theories and Learning Styles
  • Active Learning
  • Adult Learning Theory
  • Motivation
  • Learning Styles
• Faculty Development Theories and Programs
  • General Faculty Development Approaches
  • Faculty Development in Instructional Technology
  • Cost Benefit of Instructional Technology

He interviewed 10 faculty, with very different fields (art, medicine, etc.). The learning process was similar. The professors had all attended workshops in instructional technology.

The interviews were very deep with then interviews. He listened to their learning stories. Note to self! Read this dissertation! From Indiana University.

The data analysis was looking at the themes across the cases. There were several factors that influenced their learning.

• Personal dominant characteristic
• Learning styles
• Personal motivation
• Personal beliefs about the role of technology in education
• Quality of professional development interventions they attend
• Overcoming institutional barriers such as time commitment and the lack of financial and academic rewards

The results are in a table with each of the 10 cases and their dominant characteristic, their learning style, and the theoretical support for their style of learning.

Instructional technology was defined as whatever each person defined it as. The top ones were PowerPoint and teaching online. People told stories about everything including overhead projectors, cassette tapes, digital cameras, etc.

Some learning theory names to check out: Gregorc, Felder, Myers, Brightman, Kolb.

Vinita looked at the collaboration involving the 15 colleges in NAD

First step was to do research, funded by NAD

• looked at why we’re losing our young people to public colleges
• the SDA population is declining
• used a mixed-methods
• input from enrolment managers
• 2005, 7 focus groups in 2 cities with professional moderators, scripts; parent group, student groups
• major themes that we learned were applied in a nationwide telephone survey (253 results)
• result: complete lack of awareness among those who do not attend academies
• we have no way of finding out where the students are or who they are – the church has no database of youth (challenge also affects academies and elementary schools)
• tested marketing messages to see what would resonate – three key ones:
  • faith-based environment with Christian worldview
  • vast network of friends, peer mentors, professors with Christian worldview
  • connection (one-on-one) with professors vs. 200 in a class at public universities

  did joint website, mailing, etc.

• hoping to be pre-defending in the fall, hooding by Christmas
• finances? students who don’t attend have an income of about 20,000 less than those who are planning to attend -especially on the West coast
• enrolment managers meet twice a year, trying to meet away from academies
• working with local pastors and e-Adventist (NAD database), buying lists
• academies need to learn to work together as well.

Session by Vinjar Fønnebø, a medical doctor in Norway who teaches statistics

Definition: Looking at data that has more than one variable. Single out one variable and see what influence it has on the outcome you’re looking at. It helps you reduce the “noise” from the other variables. It can also be used to explore data – hypothesis generating analysis. If you want results though, you will use a different approach.

This is used on experimental studies that ask “does it work?” “efficacy”. Does it work in real life is more about “effectiveness.”

Confounding variables. In any research situation a misrepresentation of a true causal association can arise when…

• individuals are not randomized with regard to exposure
• OR individuals and/or evaluators are not blinded as to the alotted exposure

Quantitative research is usually asking is this better than this or does this influence this in this way.

In the example shown, age was a confounding factor. The multivariate analysis helps to get to more accurate representation of the data. Population distribution is really important. Age was a confounding factor in the example data because it confused the association between ethnic group and incidence.

How do you deal with confounding variables? By using multivariate analysis.

A factor can only confound if it is:

• Associated with the exposure
• AND associated with the outcome (in this case disease)

A factor is only called a confounding factor if a different, similar, relative rate is found in every level of the confounding factor. This is really important. It has to be both different, but consistently similar within the strata of the confounding factor.

Most multivariate analyses have a purpose of controlling for confounding factors. Something to consider when reading research is that you should have thought through how if the confounding variables meet the criteria above. It’s not appropriate to use this “just for the fun of it” to see what it does in the data. You should choose the confounding factors BEFORE you analyze your data. Which variables do I think could be confounding based on my reading and research?

How do deal with confounding variables:

• Either avoid it in the planning phase of your research.
  • Make the compared groups similar on possible confounding variables.
• Adjust for it in the analysis phase
  • Stratified analysis
  • Multivariate techniques

You have to get to know your data and justify why you need those techniques. Vinjar thinks these techniques are used too much in the literature. Some researchers tend to give their data to a statistician to make sense of it and then don’t really understand the results.

Do not be too impressed by fancy intricate statistical techniques to “control” confounding variables. They could be a “cover-up” of poor study planning. We shouldn’t be impressed because it isn’t good research. They have had some big challenges in their research.

If you do quantitative research in your dissertation you will be asked a lot of questions about this in your defense.

Interaction/Effect Modification
Even if individuals are randomized with regard to exposure AND the individuals and/or the evaluators are blinded as to the allotted exposure, you can still have a crude estimate of relative rate that can be completely misleading.

In one example, diet is probably an effect modifier in the connection between smoking and heart disease. We think that smoking causes heart disease, but in Japan there is hardly any heart disease and the people generally smoke. Why? Diet is probably the effect modifier.

Sometimes the “standardized” relative rate can be just as misleading as the crude rate. If you standardize the “confounding” variable and the rates are not similar, then the standardized rate is misleading. In the example the numbers were different across all the age groups. Then you can’t summarize it together. You have to present each age group separately.

A factor can only be interactive if: the association between exposure and outcome (disease) is different in the levels of the interaction factor.

How to deal with interaction:
Avoid it in the planning phase. Be aware of possible interaction factors and give your study sufficient power within every subgroup of the interaction factor. OR you can limit your study to one subgroup of the interaction factor.

Or adjust for it int he analysis phase. Present your data strata-specifically. Use only multivariate methods for “testing” of interactions. BUT be aware of your low power to detect interaction. I.e. the analysis may not look statistically significant but it may still be a really important factor. You need to tabulate your data and see what it looks like.

We should think through the data and the variables and not just do it mechanically (i.e. with software).

Interaction may be difficult to detect; therefore; always look closely at your data before shoving them into fancy statistical programs. Remember that the computer is extremely stupid!!!  What comes out will make sense only if what you put in makes sense.

Think about these two concepts when thinking and planning your study. Then you will be able to reach the RIGHT summit.  Confounding is “clean dirt” that you can do something about. Interaction is very difficult to deal with. Often you don’t see the interaction. It’s easy to overlook. Be aware of this when you read other scientific work. Can you think of any confounding variables or interaction that the author didn’t think of?

Recommended Books

• Statistical First Aid – buy used on Amazon.com. it gives an overview like: If you have this type of data, then this is the test you use.
• Statistics in Small Doses – only if you’ve taken a stats class. It is made up of questions and answers.

Software

• Microsoft Excel
• Epi-Info
• STATA
• SPSS
• SAS

In this exercise, we looked at the articles which the Glasers have written alone and in collaboration, to attempt to understand the link between the research and some of the things they shared yesterday. Our goals was to read an article and discuss how the research has guided:

1. the Glaser’s consultant work
2. their book
3. their presentation

The research is the foundation for their consulting, book, and presentations.

Now we’re going to trace research back:

• How have others (researchers, consultants, and practitioners) used and applied the Glaser’s research and work?
• Is the Glasers’ research still relevant? (If so, where and why?)
• Has their research on their topical areas changed and moved into new areas?

ISI – tracks all citations.

http://scholar.google.com

I was mostly lost in the beginning of the research / Glaser activity. I understood the big picture, but the application of it was boggling my mind. However the one AHA moment I had was when I learned how Google Scholar can be used to trace who cites who. After searching a name, under the article is a link “Cited By X” with the number of articles that have cited this article. Clicking the link takes you to the articles (in Google Scholar) that cite the first article. This was a revelation to me; fitting this into the whole idea of following research trails.

I knew how to do “backwards links” in google already; now I understand how this idea follows through in the academic world.

The other idea I wanted to right down was Duane Covrig’s idea of roots and fruits. Following the roots and fruits of research. What are the roots for this author’s research? Where did they get their ideas? And what are the fruits of their research. Who else has used their research? Who has built on it? This is helpful for understanding the literature review.

Breakout session by Isadore Newman, Shirley Freed, Paul Kaak, and Eileen White.

The dissertation has to be tied to a theoretical framework.

Eileen started her research with some basic theories that supported her work, but as the data emerged, she looked for other theoretical frameworks to address the needs/data. She had a theoretical framework for each major component of her dissertation.

A theme coming through the stories of Leadership graduates is that the theoretical framework evolves as the study changes as you read and do your research.

There is work that exists, for example some qualitative research, that isn’t tied to a theoretical framework.

Paul: You need to be reading in a way that you can find that again. You need to be linking theory to your topic of interest all along as you’re reading so it’s useful to you in two years when you’re writing your proposal. You’ll throw half of it out in the future. Also that you will find things in the bibliographies of the articles you read too.

Carol Bradfield shared how her advisor wouldn’t sign off her proposal until she had a theoretical framework for her study.

Methodological framework and theoretical framework.

Bob Paulson shared the Stages of Change Model by Prochaska and DiClemente.
To write as a scholar you have to make connections and show that you read the literature and that you are weaving the literature together. It’s easier to write chapter five if you have the theoretical framework – either the data supports the theory or it doesn’t.

Newman made a distinction between “theory” and “worldview”.

Qualitative perspective: Constructivist underlying philosophy – inductive.  World view: critical theory, grounded theory, feminist theory.

Quantitative perspective: Positivistic underlying assumptions – deductive. Theory as defined by Kuhn, Poper, Kerlinger, Nomological net.

You shouldn’t use theory and worldview interchangeably because it’ll be confusing.

A theory is made up of a set of nomological nets.

A theory is never totally right. It has a certain amount of support.

Principle: Research question in the context of the purpose should determine the method.

The purpose answers the question, “so what?” The purpose also comes from your worldview.

Examples of purpose. (A study isn’t going to do just one of these.)

• Explain and predict
• Add to the knowledge base – this one is a given for your study.
• Have a personal, social, institutional, or organizational impact
• Measure change
• Understand complex phenomena
• Test new ideas
• Generate new ideas
• Inform constituencies
• Examine the past
• Other

The theory is interwoven throughout all the chapters of the dissertation.

Newman says you can’t do quantitative research without the concepts of qualitative judgment. If you are a constructivist, you won’t generalize the study to other situations. If you a positivist, you are more likely to generalize.
Newman says, you can mix methods, but you can’t mix worldviews. You can’t mix philosophy.  It’s not the method that qualitative or quantitative. It’s the way you use the method.

It’s important to outline in chapter one where you are coming from, and then be consistent to that throughout the study.

Quite an entertaining conversation came around post-positivist, probabilist, and constructivist. I like listening to Newman as my brain is stretched.

Shirley said, you don’t have to put yourself in a box (constructivist, etc.), but you should know what you’re going to do and why you’re doing it.

Newman: If you have a framework you’re connected to, it’s easier to make connections to the literature. Then it’s scholarly. You don’t “talk” scholarly. But you write scholarly. You make a statement. You reference it. You support it.

Questions I have now:

• Is there a menu of theoretical frameworks? How do I find them? My understanding is that this will emerge through the reading.
• What are the theoretical frameworks of my topic – implementing technology change – videoconferencing – in K12 schools?
• What is the purpose for my research? What is the purpose for the research in the area of videoconferencing?
• What is your worldview and how does it affect your research? This is the beginning of the dissertation proposal. It allows you to defend your point of view, which is the beginning of your defense.

Handouts were:

• Draft The Role of Theory in Research by Newman, Newman and Bliss.
•  A Typology of Research Purposes and It’s Relationship to Mixed Methods. Chapter Six p. 167 in Handbook of mixed methods in social & behavioral research

Books Suggested:

• Theoretical Frameworks in Qualitative Research