Friday, September 10, 2010

Notes on Exploring Educational Research Literacy (Part 2)


Having boldly gone where I had never gone before in my last post, I thought I'd update the blog with some further notes. My plan of action, by the way, is to finish the Shank book, read Salah's notes and then get on with the online task (all of which I hope to accomplish in a couple of weeks)... phew!..

Well, after venturing into the wonderful world of statistics and Quantitative literacy, this post looks at basic qualitative literacy (through the eyes of Shank and Brown) and begins with the notion of meaning. I can't promise that this will be a joy to read - it is just a brief record of what I have been reading.


Qualitative Educational Research

Meaning is core to understanding.

In the scientific world, meaning is a 'thing' (their word not mine) in the world. Meanings like facts are discovered by scientific researchers (e.g. the laws of nature). We're not so much interested in what something is but rather what its practical effects are (also referred to as operationalization). There are the abstract meanings of the world and more specifically meaning of individual things through the way they operate in the world. Of course in science, these meanings tend to be addressed quantifiably. The key to quantitative enquiry is to create a set of theories and findings that are universally applicable despite the fact that researchers may be influenced by family, country, creed and culture. This is where the qualitative notion of meaning differs.

Qualitative researchers may understand that the facts of nature may not just be what we wish or think them to be. Qualitative researchers look at meaning before testing hypotheses and prioritise the examination of processes and types of meanings that we might discover or create in the world.

While the empirical world looks at simplicity being the key to understanding order, complexity is usually a composite of chunks of simplicity. Qualitative researchers look at natural and complex settings and so do not see things mechanically; this may be analogous to quantitative researchers looking at the world like a cuckoo clock while a qualitative researcher looks at it like a danish pastry. Quantitative research is concerned with a more mechanical understanding whereas qualitative research sees understanding as incomplete or poor. In qualitative research we are looking for patterns in the search for meaning often found in the form of themes; underlying principles that help coherence and intelligibility. Researchers are often observers and participants. Whereas quantitative research is about the outside looking in, qualitative reseach can also mean the inside looking out. Qualitative researchers, may be intervierwing, taking notes and staying out of the action.However, there are also those who take part in autobiographical research, give an in-depth personal perspective on research, documenting and reflecting on their experiences. Then there is also what is known as action research pioneered by Friere. Action research is using the research itself to make the world a better place. So what tools do qualitative researchers use?


Tools and procedures for gathering qualitative data.

Tools range from observations where a researcher goes somewhere and pays attention to what is happening around them using all of their senses. Interviews, nothing more than a specialised form of conversation which allows researchers to gather in opinions and insights from participants. Interviews can also come in the form of focus groups - a highly specialised group of six to eight participants interviewed. Materials analysis allows the investigation of materials cultures generate (e.g. buildings to classroom objects). Archival and Historical records analysis builds on from materials analysis and looks at governmental records and newspapers. Furthermore there is Interpretive analysis which involves understanding within a framework and participant observation, where a researcher goes in when and where they need, in order to understand (like ethnographies and action research).


Methods used to conduct qualitative studies.

Here is a list of methods common in qualitative literature:

Ethnography - This is the notion of doing work in the field; researchers are placed somewhere and then told that they have to fend for themselves and report on their findings. There is also what is known as microethnography which means that this is done over a shorter period and autoethnography which combines field research and autobiography.

Grounded Theory - Born withins sociology, it is based in precise and focused field methods and is considered to be the most analytic and scientifically based qualitative research.

Case studies - Researchers take time to probe and observe, gathering information from a variety of sources. there is also what is known as a portraiture where artistic modes and methods are deliberately combined to give readers a unique look at research targets.

Narrative and Oral Historical Analysis - Involves recording stories and accounts and can include analysing word patterns, gestures, and intonation and pauses.

Critical Theoretical Analysis - This uses a an explicit framework to help people on conscious awareness raising; they embark on a journey which are deceiving themselves into believing certain destructive ideologies which will then allow then to move on and progress.

Action Research - At one end of the scale this involves the empowerment of teachers and learners and at the other end, the teacher acts as a researcher.

Qualitative Educational Evaluation - This respects the need to find the truth while realising that new paths and methods are essential to get to the truth, the whole truth and nothing but the truth (whatever that means for you).


Categories of Qualitative Articles.

There are several categories qualitative research is divided into this is mainly to do with its diverse nature. Here are the four that Shank and Brown mention:

Investigative - Here we focus on depth. We are looking at situations that just don't seem to make sense and then investigating them, bringing in our own frameworks waiting for things to fall into place.

Interpretive - This type of article clarifying our focus. We are putting together pieces of a puzzle and looking for the best way to come up with the clearest picture.

Illuminative - Here, our primary goal is insight. We look at a phenomenon in a new way or from a different perspective.

Participatory - Here we are trying to make things better and research helps us to do this.

I think it is important to stress that Shank and Brown stipulate that articles can fall into a number of these different types and we are not just limited to one. Furthermore, a qualitative perspective to research is different to empirical research. Qualitative research tends to examine what role meaning takes on and how people understand the world around them and they do this in many different ways.

Monday, August 30, 2010

Notes on Exploring Educational Research Literacy (Part 1)

I've been wading through this book and thought I'd share some notes with you. This is how I have understood things, so if you feel that there is something you do not agree with. Please feel free to comment.

Educational research procedures are both public and systematic. Educational research itself needs to be purposeful, should also be useful and is normally conducted in classrooms, labs, libraries and informal learning situations. It is governed by rules which specify using correct methods, explain
how one has done their research, inform readers of every important point found and which treat all participants in an ethical fashion.

Novice researchers also need to be aware of conventions which detail the ways in which they have traditionally approached an area or topic. They also need to note the values and limits of these conventions.

Educational Research contributes to shared knowledge and researchers assume that their readers possess an information base made up of both GLOBAL and SPECIFIC shared knowledge.

Article content matters; it must not be deliberately false, should strive to create something new and be accessible to its target readers. Educational research articles can be tackled part by part so start with what you know.

Secondary articles in the form of lay reviews, action plans, interviews or opinion pieces can be used to understand primary articles. However, if one feels that information in these is too good to be true or oversimplified go back to the original and check it out for yourself. Mastering the primary article, taking it apart and engaging with it is far more effective than relying on a secondary article to do this for you; secondary articles should be used as tools in aiding understanding.

QUANTITATIVE LITERACY
Personally, this area scares me a little and I think this has its roots in secondary education mathematics (but hey I'll give it a go anyway?!).

What about variables? A variable is a quantity / element / feature or factor that is liable to variance or change. In scientific research, variables are divided into the dependent and the independent. The former are target variables (something we want to change) while the latter have an impact on the former. An independent variable is one whose value does not depend on that of another (x) while a dependent variable is a variable which does depends on that of another (y).

Types of Articles:
Scientific research is often presented through different types of article. Here are four types:

1. Descriptive articles look at describing processes or situations. This focuses on studying how a poorly understood process or situation might operate in a natural, uncontrolled environment. When looking at opinions or beliefs for example, we often measure them in terms of likelihood or frequency. With this in mind, we are then able to turn to descriptive methods to understand how this information can be better understood, compared or contrasted to other groups.

2. Relation-finding articles are written by researchers interested in establishing that there are perhaps relationships between two variables. The move from a descriptive article to a relation-finding article denotes a move from searching for patterns to a search for impacts.

3. Hypothesis-testing articles bring in the use of (surprise, surprise) hypotheses to say powerful things about how independent and dependent variables are related.

4. Model-building articles move away from descriptive articles looking at what patterns variables reveal to building models which will allow us to put them to work. These models are usually based around a target variable which is of particular interest to researchers. A model is developed when the pattern of other variables are used to say something about the target variable.

The Scientific Method
I understand the scientific method as a cycle of refining knowledge. It begins with a hypothesis or prediction, we then collect data and see if they match with the hypothesis. If the answer is yes, then we are on the right path. If the answer is no then we need to change the hypothesis. It is therefore a cycle of prediction, test, change and so on and so forth. The scientific method is also public, replicable, fallible and correctable, generalisable and is able to simplify understanding of complex things.

A Statistical Worldview
Science introduced the idea of a Newtonian deterministic model; one that says that if you know all your causes, and all of our beginning conditions, then you can predict and describe all your efforts precisely and exactly. However, eventually the sciences began to abandon deterministic models and replace them with probabilistic; a statistical worldview that recognises that probability is built into the very fabric of reality and within the framework of probability, there are systems of order and also stability in the world.

A Quantitative Mini Glossary (Non-Alphabetised)
At this point I thought it might be a good idea to look at some of the language used in scientific articles. Here is a mini glossary:

A datum - An individual score or measurement

Data - A collection of scores or measurements

Distribution - A collection of measurements for a single event or category

Constant Distribution - When all the members of a distribution have the same value

Blob Distribution - When there are no structures or orderly patterns to discover (and you are on the wrong track).

Normal Distribution - When there is a meaningful typical score for the distribution and an orderly process of change that accounts for differences between this typical score and other given scores.

Central Tendency - Clustering in a distribution. There are three common types (Commonness, Clustering above / below and Average Score - See below).

Commonness - This focuses on the mode; the most common. This divides distribution into two lists, the mode score and the rest. In order to be the mode, it merely has to have a higher frequency and it does not matter how much of a higher frequency of occurrence it has. When there is more than one score that has the highest frequency, we refer to this as multi-modal distribution.

Clustering Above/Below - This focuses on the median. An example - Let's take a group of trees, measure their height, and display them in order of their height. When you hit the middle, you have hit the median. This is useful when looking at ranking.

Average Score - This focuses on the mean and is based on the value of ever item in the distribution. This changes if one score changes in the distribution. It is the balance point of the distribution and is the first best guess of any given score in a distribution.

Dispersion* - When there is more than one score and the distribution is spread out in some fashion. This property of distribution to spread out is called Dispersion.

On that note here is a type of dispersion: Standard Deviation

Standard Deviation
I cringed at this at first... but here goes...

Apparently, standard deviation 'captures' the average distance of any given score from the mean. Because the mean is balanced exactly between anything below it and anything above it - any differences cancel themselves out. So the differences are converted from looking at them from a 'above/below' perspective to an 'away from the mean' perspective. I am sure that Shank and Brown had the very best of intentions regarding me understanding this and all I can say is that I was probably in a coma at school when my maths teacher delved into the subject!... But I think I got it in the end.

The size of Standard Deviation (SD) is a good indicator to the degree of variability. In other words, if the SD is large then there are less scores near the mean. If it is small then vice versa. When moving away from the mean, one standard deviation at a time, not only are the events becoming less likely, but the processes behind creating those events are less like the processes that shaped the scores around the mean.

Distributions from Populations or Samples
I have discovered (or I think I have) that distribution is governed by parameters; mean and standard deviation values. But where does this data come from? The answer is a sample. A sample is a subset of a population and sample data are from distributions with means and SDs - a.k.a. statistics... there, I said it and got it out of my system. Now, there are several types of samples you can have:

A convenience sample where the members of a population happen to be conveniently close at hand e.g. work colleagues, your class of five-year-olds, though this is considered the least acceptable type of sample unless you can convince your readers that members of a nearby sample are no different from your own.

A purposive sample where members are chosen because of specific characteristics. In this case you treat the sample as if it were a mini population. There is a restriction in this because there is less generalisation possible so its better for more qualitative research.

A representative sample (or stratified sample) is a population in miniature.

But the crème de la crème for scientific researchers is... the random sample! The random sample has members drawn at random from a population. For scientific researchers, this is the sampling strategy winner.

Stats, Stats and more Stats!
I have to admit that at this point I started to freak out a bit. I was out of my 'qualitative comfort zone' but I'll continue. Scientific researchers use statistics to test hypotheses and assumptions they have about the world and this is known as inferential statistics. At this point I'm going to throw around with a few words.

Correlation - the correlation coefficient is used to determine the probability that two variables are related. The most common is known as the Pearson Product.

A T-test - comparison between two means. A target variable may be under two different conditions. Values from a -test allow researchers to decide whether or not to include these items in a final equation or not.

ANOVA - from ANalysis Of VArience. This does what a T-test does but allows us to compare more than two groups.

Chi-Square - Question: Do the frequencies we observe in the world match those we might expect, or is something different going on? Chi-square helps to answer this.

I suppose that if you want to go down this route (I am not convinced I will) you can pick up a few good stats books to help you along the way.

The authors then get into talking about multiple regression equations, path analysis models, factor analysis and structural equation models at which point I my head exploded so I drifted off into academic purgatory. Please feel free to clarify and comment by the way. I am venturing into safer territory (I think) and looking a Qualitative Educational Research so watch this space!

* ACCORDING TO THE AUTHORS, YOU NEED TO LOOK AT BOTH CENTRAL TENDENCY AND DISPERSION TOGETHER BECAUSE DIFFERENT VALUES ARE ORDERLY IN A PROBABILISTIC WAY AND YOU NEED BOTH TO MAKE SENSE OF THE SCORES.

Saturday, August 21, 2010

Practicing Educational Research without a License

I just saw this article at ED Week, and wanted to post it. I want to share it with others, but I also want to go back and look at it later. If I just bookmark it, it will undoubtedly be forgotten.

Wednesday, August 11, 2010

Collaborative and Interactive Writing for Increasing Communication Skills

Smith, K. (1990). Collaborative and Interactive Writing for Increasing Communication Skills. Hispania,  73, 77-87


Let me start big: with all the talk of sample groups and the tests and the results, it definitely falls into the positivist paradigm, and follows a quantitative research method. 


The researchers looked at the use of three types of writing communities. Group one (the control) used the traditional paper and pen to write essays at home with no collaboration at all. Group two used Wordperfect and typed their essays, again with no collaboration. The third group used conversational writing activities via a computer conferencing system. In essence it was a message board in which they could communicate with each other, and did their writing on line. 


The results?
In summary, from the study it is possible to propose four hypotheses regarding computer-based collaborative and interactive learning environments: 1) computer-based interaction encourages increased time on task; 2) computer-based writing promotes creativity as well as accuracy; 3) excessive emphasis on accuracy can detract from development of interactive communication skills; and 4) development of advanced organizer and sub-vocalization techniques affect students' ability to communicate ideas orally as well as in writing.  (Smith, 81)
In brief, numbers one and three above seems somewhat obvious to me. The second hypothesis made me curious. I want to know more. Number four means that students actually talked themselves through the difficult tasks in the target language.

This article is not what I was expecting. There was no abstract, and I just scanned the introduction quickly before printing and adding to my own reading list. Even though it isn't what I expected, it was informative and interesting. I have used online bulletin boards for writing and speaking in the past, and have even participated in some research on them. It was nice to see something else that looks at the topic from a slightly different angle.



One of the suggestions for further research ties in with what I'm thinking about doing:
To what degree does the ease of editing, organizing, and rewriting influence the number of drafts completed, the length of the composition, and sentence complexity? (Smith, 85)
I think this would be worth looking into. Perhaps not with this upcoming semester, but would be a good follow-up to what I'm thinking about doing with regards to the interference of affective filters in collaborative writing activities.



There was some great information in this article, and I'm sure I'll go back and look at it more closely when I'm putting together a research project on writing.

First task - on the HIVE... ... Due October 1.

Our online task on the Hive is here (It is pretty much a practice run for what we'll have to do later):

Introduction and aims:
This activity will enable students to develop understanding of the interpretive epistemological position in educational research and to understand the implications of this for assessing the quality of educational research. These issues will be considered in relation to a variety of contrasting methodologies and perspectives, including ethnography, phenomenology, hermeneutics, postmodernism and poststructuralism.
Aims:
  • To develop critical awareness of the criteria of judgement which may be used to evaluate quality in interpretive research.
  • To read, understand and critique research papers and reports that have used qualitative approaches.
  • To demonstrate understanding of methodological principles through choice of appropriate research techniques in light of complex problems
It is assumed that student will have attended the NER sessions relevant to this activity and that they can access the NER 031 module Support materials online.
Procedure:
  • Read the following article: Harry, B. (1992) An Ethnographic Study of Cross-Cultural Communication With Puerto Rican-American Families in the Special Education SystemAmerican Educational Research Journal Fall 1992, Vol. 29, No 3, pp. 471-494
  • Evaluate the article, using Klein and Myers’ principles of interpretive research (use a table similar to the one Klein and Myers’ use on p.72 of their paper).
  • Read the article by Hammersley, M. (2007) The issue of quality in qualitative researchInternational Journal of Research & Method in Education, 30:3,287-305
  • Make a list of any areas of the research paper that you consider do not meet Klein and Myer’s criteria for quality. Focusing on TWO of these areas, explain how these could have been addressed by doing things differently drawing on the Hammersely’s perspectives.
  • Consider whether you would add any other criteria for quality to those identified by Klein & Myers and Hammersley.
  • Share your insights/findings with others on the web (check dates above for your group). At the same time you might want to use the insights/findings of others to improve or modify some of your own insights/findings.
we can find it all on the hive


Tuesday, August 10, 2010

A starting point?

I feel that in order to get our heads round the whole issue of educational research it might be an idea to look at something like, An Introduction to Research Methodology and Paradigms by Paul Ernest. It's quite difficult to get hold of if you are away from St. Luke's but I have an e-copy if anyone is interested. This publication is from the School of Education at the University of Exeter and part of the Educational Research Monograph Series (RSU). I really felt that this helped me to grasp very basic concepts before starting out on Shank, G. & Brown, L. (2007). Exploring educational research literacy. London: Routledge... Just a thought?

Currently reading

I'm currently working through the following books and articles.
The books are right from the reading list (for the most part) and the journal articles are to give me some background knowledge to help me with the research project I'm planning, which is related to affective filters and collaborative writing tasks.






Journals:

Conle, C., deBeyer, M. (2009). Appraising the Ethos of Experitential Narratives: Key aspects of a Methodological Challenge. Educational Theory. 59, 41-65

Levykh, M. (2008). The Affective Establishment and Maintenance of Vygotsky's Zone of Proximal Development. Education Theory. 58, 83-101

Smith, K. (1990). Collaborative and Interactive Writing for Increasing Communication Skills. Hispania,  73, 77-87


Books:

Brown, J. and Rodgers T. (2002). Doing Second Language Research. Oxford: Oxford University Press

Cohen, L. Manion, L. and Morrison, K. (2007). Research methods in education 6th Edition. London: Routledge.

Creswell, J.W. (2009). Research design: Qualitative and mixed methods approaches. London: SAGE

Hyland, F. and Hyland, K. (2006). Feedback in Second Language Writing. New York: Cambridge University Press

Richards, K. (2003). Qualitative Inquiry in TESOL. New York: Palgrave MacMillan.

Shank, G. & Brown, L. (2007). Exploring educational research literacy.  London: Routledge.