Merlin in Oulu

LET studies 2015-2017

Protected: Merlin as an Expert Vol. 2

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Mentoring Session Vol. 3

The third (and last) mentoring session was focused on getting an understanding of what the future might look like for us as LET graduates and experts. We got very good presentations about both – the academic, research-focused and private sector possible futures.

Even though the session was short, it meant a great deal to me to actually get a good, first-hand talk about how the expertise I am developing as a LET student might be useful for not only me, but also to the world. Experts are supposed to share their expertise and apply their knowledge to practice to take things forwards and it was inspiring to see that this can be done in many ways.

Analyzing the Data

Merlin’s notes from the third QUALI lecture: Different data analyzing methods in qualitative research

Data analysis process:

  1. Preparing and the data
    1. organize the documents or the visual data
    2. transcribe the text
    3. prepare the data for analysis with a computer program
  2. Exploring the data
    1. read it through
    2. write memos
    3. develop code book
  3. Analyzing the data
    1. code the data
    2. assign labels to codes
    3. group codes into themes
    4. interrelate categories
    5. use analysis software
  4. Representing the analysis
    1. represent findings in discussion
    2. present visuals
    3. be innovative, don’t give up!
  5. Interpreting the analysis
    1. assess how the research questions were answered
    2. compare findings to the literature
    3. reflect the meaning of the findings
    4. state new interesting research questions based on your results
  6. Validating the data and interpretations


Additional notes:

  1. Quantitative methods require big samples, qualitative methods need small samples.
  2. Work rigorously inselecting or developing and validating the data collection instrument. Whenever possible, use an already existing one.
  3. Coding can give you a possibility to use quantitative analysis methods for data that was collected with qualitative methods.

Data Collection Methods

Merlin’s notes from the second QUALI lecture: Different data collection methods in qualitative research

The aim of collecting qualitative data is to answer the question “Why?” and to generate new hypotheses. It aims to explain what the world is like and why things are the way they are.

  • Why do people behave the way they do?
  • How do opinions and attitudes form?
  • How does the environment affect us?
  • How are social groups different from each other?


REVEAL (understand) LISTEN

Qualitative methods are flexible and complex, since the goal is to understand people and therefore they will be explaining things with their own understanding and words. Researchers also get to react immediately to the answers and go deeper to understand better.

Why use open-ended questions? They receive culturally and linguistically meaningful answers that can be reliably analyzed and they are rich and explanatory in nature.

QUALITATIVE APPROACHES – general ways of thinking about conducting qualitative research (purpose, role of researcher, stages, method of data analysis)

  • ethnography
  • phenomenology
  • design-based research: combining the design of learning environments with the empirical exploration of them


It’s time-consuming and “expensive”. Main methods are individual and focus group interviews, observations and written (etc) materials.

Interviews can be structured, semi-structured or unstructured. good quality interviews involve thought, preparation and practice, schedule, care and consideration in analyzing the data.

Observations take place in “natural” settings and include long notes of descriptions of what is happening. Video observations.

Written documents can include essays, diaries, newspapers, transcripts of conversations, annual reports and so on. Documents are analyzed with some form of content analysis.


  • credibility
  • transferability
  • dependability
  • confirmability

Most common samplings in qualitative research: purposive, quota and snowball



  1. General topic of interest
  2. Specific research question(s)
  3. Respondents
  4. Methods
  5. Data collection, analysis and reporting the findings




Mentoring Session Vol. 1

I am writing the reflection very late, so really recalling what happened and what I thought is a bit challenging. But it really made me realize and think about something.

Namely, each of the mentees read one article about mentoring in different situations and we had a very interesting discussion about mentorship during the session. The article I read was about a learning experiment where students played a work simulation game with assigned real-life mentors in the field of environmental design. What the research concluded is that mentors (who are experts in the field) really do define the language, work ethic and processes used among the group in that specific working field.

And that made me realize two things:

  1. Experts are often very bad teachers. On one hand definitely because they lack pedagogical skills, because that is simply not their area at all. But also because they are very in their field and are therefore so used to the language, terms, actions and work ethics used there that is difficult for them to step out of these shoes to understand how to instruct the entrance to the field for people who have no idea of what it all means.
  2. Experts are the key to leading novices on their way to achieving expertise. Because, to become an expert, you would need ot think the same way, use the same language and work the same way in order for you to communicate with peple of the field and to be considered an expert by the community

These two things contradict each other, but that is possibly where mentoring comes to the rescue: the whole idea of mentoring is not to instruct, but to support the adaptation and development process of a novice by an expert. It is widely and rather effectively used in corporations, medicine and research. Now we just need to make more use of it in education and teachers’ in-service training.


Planning the Empirical Research

Merlin’s notes from the first QUALI lecture: What are the main things to consider when planning the empirical part of your research?

Whatever the phenomana is that we aim to describe, measure or analyse, we can never grasp it in its entire nature with one single measuring instrument. That is why there are different qualitative and quantitative research methods – to help us out in observing different things.

“We have to remember that what we observe is not nature itself, but nature exposed to our method of questioning” – Werner Heisenberg

The biggest difference between qualitative and quantitative methods is that qualitative methods mainly deal with describing and understanding whether occurences are a general laws or consequences, but qualitative methods deal with understanding why these occurences are happening. Therefore, the choice of research question very much defines the research methods you need choose.

Research Design

  1. What?
    Research plan is a comprehensive plan and procedure for assessing a research problem.There is a variety of options for research design that depend on paradigms, methods, experience and the audience.
  2. Why?
    You need to have a clear plan and a good methodological framework to actually start collecting anu kind of data
  3. Who?
    The researcher – me!
  4. When?
    For Master’s thesis – as soon as possible!
  5. How?
    1. What are the philosophical assumptions that underpin my research?
    2. What is the methodological basis for my research?
    3. How will it be operationalised?
    4. Who is the intended audience of my research project?
    5. What is the most appealing research method and why?

The framework:

Research problem (question, hypothesis, aim)
Strategy (experiment, survey, case study, action research, grounded theory)
Sampling (random sample, one case, purposeful sample, snowball sample)
Data collection (questionnaire, structured/open interview)
Data anlysis (descriptive and inferential statistics, discourse analysis, coding)
Results (descriptions, generalisations)

Sampling design: where does the deata come from?
Methodological design: how will the data be gathered?
Analytical design: how will the data be analysed?
Operational design: how will the data be put into words/results?

Research design categories: qualitative, quantitative, mixed methods

Mixed methods research design refers to a research design that combines elements of qualitative and quantitative approach in various ways during the different phases of the study.

How to continue work on my thesis:

  1. Define why my study is important.
  2. Learn strategies from published papers.
  3. Make summaries of key literature.
  4. Define the philosophical assumptions behind my study.
  5. Describe my operational approach.



Mentoring Session Vol. 2

This mentoring session was all about ed tech tools that in one way or another migut be useful for us as learners or educators. We got a very practical overview about how to use Mendeley for our Master’s thesis, tried learning some rhythms with BandBlast and finally figured out how to analuse the readability of our text for different target groups with Hemingway. We also got a good overview about the Finnish educational system and its future.

Me and the “Third World Teacher” Maida chose to do our presentation about virtual reality. Equipped as the LET tech guru Jari always is, we managed to borrow a few google cardboards from him and got to work. Turns out there are a lot of VR resources out there but if you are öooking for something educational by itself, it is very difficult to find. Most of these applications can easily be included into classrooms and learning environments but only if you can create an educational purpose around them. Another problem with the apps is that they require from phones specs that not all of them have and are often not made for different operation systems. But Maida and I found our way around it and managed to intorduce them anyway. Since the goal of the presentation in our eyes was not only about presenting the tool itself, but showing how it can be used in authentic learning environments, we wanted to model learning chemistry and using Chemistry VR to do that.

What thoughts or ideas the meeting evoked?

1. What I learnt from my partner Maida: it is not that difficult to think outside of the box, but it does take courage to apply a different way of thinking and that is exactly what a good educator should do. When the instrution that you get is to do a presentation about something, it doesn’t mean it has to be a simple powerpoint presentation, even though 99% of people would do just that. Sure, it takes a lot more tome and effort, but isn’t that what lifelong learning is all about? And shouldn’t an educator lead the way in lifelong learning?

2. There are so many practical limitations to apply cool educational technology in the classrooms: number of available devices, compatibility, language, ease of access, the tech factor and so on. A teacher who really wants to implement CSCL has to be ready for accidents and has to know how to deal with that kind of challenges.

3. No technological tool is perfect nor does it cover all the needs of instruction. Neither is any educational system perfect (not even Finland’s). But there are some that are pretty close and there is a lot to learn from such tools and systems.

What was meaningful for you, and why?

I believe the whole session was meaningful as everything we covered and talked about was interesting and useful. The whole reason why most of LETs are here, is the hype about Finnish educational system and how it is leading the world. It was great to hear a Finn’s description and evaluation of it and to reslly understand what it was about. Mendeley is a wonderful tool and I am really glad I was introduced to it. I am also vefy glad I got to work in a pair with Maida as it really made me reflect on myself and my conformity.
How is it connected to learning of expertise?

I think that since it was all about learning something from people who are more knowledgeable than you in some areas of your desired expertise and I was learning about topics that help me develop my expertise in education and educational technology, it was all about learning of expertise.
How you could make use of or apply in your life (personal, studying or work context) what you learned today?

I definitely learned some very practical things about Mendeley and already started using it for my Master’s thesis literature curation. I now know where to go to get a quick readability test for my texts and got inspiration to think outside of the box.

Working on Our Masterpiece

Having comfortably settled down in the vecinity of our university, it turns out that this semester takes us every morning to a 30-minute bus ride in
order to participate in EduLAB.

So, there we are, the LET family working in different interdisciplinary teams to develop an educational technology solution for the world to benefit from!IMG_20160128_162910


Quantitative Fun

Turns out quantitative research can be as fun as it is confusing. At least when snowball sampling is described with the help of Olaf, systematic random sampling is modelled by filming Maida playing with candies and there are yoga balls involved.


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