Theoretical perspectives and research methodologies

In a previous post, I briefly touched on how different theoretical perspectives can guide methodology and ultimately research methods. In this post, I will talk about a wider range of theoretical perspectives, mainly because I need help familiarising myself with them :P

Objectivism

Objectivism posits that reality exists independently of consciousness (i.e. there is an ultimate truth out there to be found).

Positivism

Positivism, like objectivism, posits that reality is external to the researcher and that there should be a focus on facts, rather than on values. Positivism suggests that reality consists of what is available to the senses, and inquiry should be based on scientific observation, which may or may not be theory-laden. Post-positivists, while also agreeing that there is an independent reality to be studied, believe that all observation is inherently fallible.

Interpretivism

Interpretivism looks for culturally-derived and historically situated interpretations of the social life world.

Symbolic interactionism

In symbolic interactionism, meanings arise from social interaction and are handled in, and modified by, an interactive process. Meanings are not fixed or stable, but are rather revised on the basis of experience.

Phenomenology

Phenomenology suggests that attempts to understand social reality must be grounded in people's experiences of it. There is a focus on allowing phenomena to "speak for themselves" and to find the internal logic of subject. To this end, researchers using a phenomenological perspective tend to use interviews.

Realism

The realist perspective states that science paints an accurate picture of the world; however, measuring external reality may be difficult as some observable "facts" may be merely illusions. Realism sometimes lends itself to the pluralism methodology, in which nothing is ruled out. There are different types of realist perspectives. Naïve realism states that the world is largely knowable and is just as it appears to be. Scientific realism suggests that science can find the true representations of the world, though science may be fallible. Critical realism states that the way we perceive the world depends on beliefs and expectations.

Hermeneutics

In hermeneutics, social reality is socially constructed and is considered to be too complex to be understood via observation. As such, interpretation is considered more important in hermeneutics than explanation and description.

Naturalistic inquiry

Naturalistic inquiry looks at multiple constructed realities that can only be studied holistically. It consists of a body of knowledge that describes individual cases.

Critical inquiry

Critical inquiry questions currently-held values and assumptions. It posits that ideas are mediated by power relations and that facts cannot be disentangled from ideology.

Postmodernism

Postmodernism emphasises multiplicity, ambiguity, ambivalence and fragmentation. Researchers using the postmodernist perspective may deconstruct texts to expose how values and interests are embedded within.

Pragmatism

Pragmatism is... well, pragmatic. It basically says that you should use what works.

Research Methodologies

Now that we've gone through a list of ideological perspectives, let's look at some of the methodologies that we can use! This is only a brief list and is by no means exhaustive.

• Experimental and quasi-experimental- RCTs, cohort studies, case-control studies, etc.
• Phenomenological research- Producing "thick descriptions" of people's experiences and perspectives. Often based on small case studies.
• Analytical surveys- Carefully-designed surveys with careful random selection of samples and a tight survey structure.
• Action research- Carried out in close collaboration between researchers and practitioners. There is an emphasis on promoting change. Both quantitative and qualitative approaches may be used. Case studies are the main medium of research.
• Heuristic inquiry- Open-ended, self-directed inquiry in which researchers are immersed in active experience. There is deep, personal questioning. A disadvantage of heuristic inquiry is that it is only weakly generalisable.

Selecting Research Approaches

So now that you've heard a few different research approaches, the next question is which approach to use. Firstly, you need to figure out what it is you want to research and what questions you want to answer. For instance, do you want to explore what is happening and figure out if a phenomenon warrants further research? If so, you would use an exploratory study design. Do you want to "draw a picture" of a situation? If so, you would use a descriptive study design, being mindful that these kinds of studies cannot explain why things occur. If you want to know why things occur, you would use an explanatory study design, and if you want to explore people's experiences, views and perspectives, you would use an interpretive study design.

References

Gray, DE 2014, Doing Research in the Real World, SAGE Publications Ltd.

Conducting rigorous qualitative research

Qualitative research often gets criticised for being subjective and prone to bias, and those concerns are probably not unfounded. There are, however, ways in which we can improve qualitative research. Here are some methods:

Member checking

In member checking, the researchers return the data (transcripts etc.) and/or the results to the participants to allow them to assess the trustworthiness and ask for input. Member checking has its basis in epistemological foundationalism, which assumes that this method is neutral and can control for bias, allowing for the sorting of the more trustworthy information from the less trustworthy information. However, since there is no "true reality" in qualitative studies to compare to, it is impossible for researchers to truly objectively sort trustworthy from untrustworthy information. Similarly, there is no evidence that member checking enhances credibility or trustworthiness.

There are also practical problems with member checking. For instance, the participant and researcher may disagree with or contradict each other, though this is rarely reported in papers. In case of a disagreement, participants may be inclined to simply agree with the researcher, due to the power imbalance between participant and researcher. Participants may skim over the data, be unable to understand the data, or simply not remember what they said when the data were initially generated, making them unable to offer truly useful insight. Furthermore, political leanings and personal interests may also influence the member checking process, particularly if the topic studied is a sensitive one (e.g. illicit drug use).

Fortunately, all is not lost. Member reflection may not be perfect for verifying results, but it may help to generate additional data. When participants re-read the data, they may generate useful insights. Another positive aspect of member checking is that it may help to ensure that descriptions of the participants do not accidentally reveal who they are.

Calculating inter-rater/inter-coder reliability

This method is exactly what it says on the tin: trying to calculate some kind of inter-rater reliability metric. As simple and objective as it sounds, calculating inter-rater reliability comes with its own disadvantages. Firstly, different coders may perform unitisation (identify blocks of text for coding) differently to one another, making it difficult to compare coders. Secondly, if coders then combine to discuss their differences in results, power differentials etc. between coders may skew the final answers. Thirdly, it is difficult to determine a satisfactory level for inter-coder reliability.

One way to get around problems such as unitisation differences is to use a set of guidelines. Coders can develop a framework and firm coding rules prior to coding. The downside of this is that it may constrain creativity and limit the identification of unanticipated knowledge.

Another way to get around the problems with inter-rater reliability is to use the "critical friends" technique. In this technique, there is critical dialogue between people. Researchers voice interpretations to others who listen and offer feedback. The goal here is to create a "sounding board" or reflexivity, rather than total agreement.

Yet another way to get around the problems with inter-rater reliability is to simply ignore reliability altogether. After all, you will never be able to reproduce the exact same interview.

Universal criteria

Another possible method for improving the quality of qualitative research is to try and adhere to a set of criteria, such as the universal criteria proposed by Tracy (2010). These universal criteria consist of eight main hallmarks: worthy topic, rigor, sincerity, credibility, resonance, significant contribution, ethics and meaningful coherence. Instead of using fixed criteria, an alternative approach is a relativist one: using criteria from open-ended lists so that the criteria are appropriate for the study design.

References

Smith, B, McGannon, KR 2017, 'Developing rigor in qualitative research: problems and opportunities within sport and exercise psychology', International Review of Sport and Exercise Psychology, DOI: 10.1080/1750984X.2017.1317357

Tracy, SJ 2010, 'Qualitative quality: Eight "big tent" criteria for excellent qualitative research', Qualitative Inquiry, vol. 16, no. 10, pp. 837-851.

Qualitative vs. Quantitative Methodologies

You've probably heard of qualitative and quantitative studies before: quantitative studies tend to be focused on numbers and cold, hard facts, whereas qualitative studies aren't. There are also some other ideological differences underpinning different types of studies, which I'll talk about in this post.

Firstly, some terminology. Ontology is the study of reality, and ontological positions describe what entities exist and what kinds of relationships exist. Ontology can inform epistemology, which is the study of knowledge and how we can truly know things. In turn, epistemology can inform methodology, which is the theoretical and philosophical system that structures the way that research is conducted, and ultimately determines the methods that we use to learn things.

Quantitative paradigm

The quantitative paradigm comes from positivism, which is a "realist orientation" that posits that an ultimate truth exists and can be described as it really is. Furthermore, the truth can be described using facts, which are separated from values. In quantitative studies, the investigator is seen to be able to study phenomena without influencing or being influenced by them.

Qualitative paradigm

The qualitative paradigm, on the other hand, is derived from idealism. According to idealism, reality depends on one's mental structure and activity, and cannot be accessed independent of our minds. As such, there is no single reality; instead, there are multiple realities based on one's construction or interpretation of reality. Our perception of reality is not value-free, and things cannot be described as they really are but only as we perceive or interpret them. The "truth" in qualitative studies is essentially defined as the extent to which a researcher's statements correspond to how people out there really interpret or construct their realities. Generally, the main goal in qualitative studies is not to find the "ultimate truth," but instead to understand a phenomenon better from the point of view of study participants, and to allow readers of the study to make use of these experiences based on their descriptions in the text.

References

Slevitch, L 2011, 'Qualitative and Quantitative Methodologies Compared: Ontological and Epistemological Perspectives', Journal of Quality Assurance in Hospitality and Tourism, vol. 12, no. 1, pp. 73-81.

Thematic analysis

For my Honours project, I will be doing some qualitative analysis on focus group data. One common form of qualitative analysis is called thematic analysis. Thematic analysis involves looking at themes, which represent some kind of patterned response or meaning within the data set. There is some flexibility in how a theme is defined, and this may depend on the research question. Themes can be either semantic (explicit) or latent (interpretative). They may be determined via an inductive ("bottom-up") process, in which data is coded and sorted without fitting it into a pre-existing framework, or via a theoretical/deductive ("top-down") process, which is explicitly analyst-driven.

There are several steps in a thematic analysis:

Phase 1: Familiarisation with the data

In this step, a rigorous and thorough transcription (for interviews and other verbal data) is done. The transcripts are read at least once. During this time, the analyst takes notes and marks ideas for coding.

Phase 2: Generating initial codes

During this phase, the analyst organises the data into units of meaning, or codes. All of the data extracts are coded for as many themes as possible and collated. Coding can be done manually or via software.

Phase 3: Searching for themes

Once the codes have been generated, they can be sorted into themes. Tables and mind-maps may be used to aid in this process.

Phase 4: Reviewing themes

During this step, the analyst refines themes to create internal homogeneity (i.e. making sure everything within a theme is similar) and external heterogeneity (i.e. making sure different themes have different contents). Firstly, the data are reviewed at the level of coded extracts to see if they form a coherent pattern. Next, the data are reviewed at the level of the whole data.

Phase 5: Defining and naming themes

Once the themes have been reviewed and refined, the analyst has to identify the "essence" of each theme, or the aspect of the data that the theme captures. The analyst then has to figure out how each theme fits into the "story" and if there are any relevant sub-themes. It may help to try and describe the scope and content of each theme in 1-2 sentences.

Phase 6: Producing the report

Once the themes have been found and defined, it's now time to write! However, care needs to be taken to ensure that claims remain grounded in the data, but are still able to go beyond the "surface" of the data.

Pitfalls

There are many errors that can be made while doing thematic analysis, particularly by beginners in qualitative analysis (*cough*me*cough*). Some of these pitfalls are as follows:

• Sorting but not analysing the data
• Using questions (i.e. the questions that participants were asked) as "themes"
• Non-coherent themes
• Overlapping themes
• Insufficient examples in report
• Mismatch between data and claims
• Mismatch between theory and claims
• Mismatch between research questions and the type of analysis

References

Braun, V, Clarke, V 2008, 'Using thematic analysis in psychology', Qualitative Research in Psychology, vol. 3, no. 2, pp. 77-101

Creating engaging games

Wow, it's been a while since I last posted! I've been busy writing up a systematic review, but now that's pretty much done, I have time to write again :)

One of the posts I wrote before my blogging hiatus concerned the principles of serious gaming. Since they are not set in stone, many other researchers have written up their own ideas as to what should be included in a game. Some of these ideas, however, fit neatly into one of the principles of serious gaming, so I'm going to organise the ideas in some other papers I've read under these categories.

Storylines/Characters

If you want to keep players hooked in your game, you need to create an immersive environment. It is important, for instance, to create authentic activities; brownie points if these activities allow for engagement with other learners. One way to create an immersive, engaging environment is to use a first-person point of view, where objects are obscured from view and encountered as the learner moves through the environment. Immersive 3D environments allow players to interact first-hand with virtual objects so that concepts can be approached as "1st-person nonsymbolic experiences" rather than as "3rd-person symbolic experiences. Virtual reality (VR) is also positively associated with active engagement and motivation. VR enhances neural reorganisation and optimises rehabilitation outcomes, with moderate evidence supporting use of VR for balance and motor skills. There is also weak evidence for the use of VR for upper extremity skills, joint control, gait and strength.

Another important aspect of the game environment, as you can tell from the heading, is the inclusion of a storyline of some sort. Storylines give some kind of context for learning, and "cutscenes" can help to provide feedback. It would also be good if the storyline could be partially constructed by the player, for instance allowing them to make choices. Interactive choices may also help players to bond with their characters, and help link the characters to their environments. (Choice is another one of the five principles of serious gaming.)

Goals

It is also important to provide clear goals that players can work towards, with unambiguous feedback. Ideally, there should also be relatively few consequences for risks, supporting players' natural curiosity. Continuously offering new and challenging task-oriented goals can also help to maintain players' interest in the game.

Levels of Difficulty

As well as providing different levels of difficulty, it is also important to provide different scenarios for players to test their skills. In rehabilitation games targeting motor control, it may be important to vary the types of movements that are needed, with a mixture of easier and harder movements. Such variation may help prevent fatigue and loss of motivation.

Individualisation

Individualisation is very important in designing rehabilitation games as disability affects different people in different ways. As such it is important to tailor the difficulty level to each player, so that they may achieve a "flow state interaction," characterised by deep concentration and a sense of control and satisfaction in response to challenges that are matched to their skills. One way to individualise the gaming system is to amplify the effects of movements as necessary (i.e. allow a small movement to achieve a large in-game effect) so as to avoid discouragement in players.

Other Considerations

Another important consideration is the hardware used. For instance, Kinect sensors are relatively affordable and are generally useful for exercises at home. However, Kinect sensors have limitations in detecting fine movements and rotations. They may also have problems detecting the movements of wheelchair users due to metallic reflections.

Yet another important consideration is the incorporation of "hooks," which are things that require players to make decisions and encourage them to keep playing. "Hooks" can include action hooks, which are basically choices of some kind (e.g. quests); resource hooks, which may include trying to accumulate ammunition or wealth; tactical hooks, which require players to make decisions about resource allocation and so on; and time hooks, which are actions that have to be completed within a certain time frame.

References

• Dickey, MD 2005, 'Engaging by design: How engagement strategies in popular computer and video games can inform instructional design', Educational Technology Research and Development, vol. 53, no. 2, pp. 67-83.
• Eckert, M, Gomez-Martinho, I, Meneses, J, Martinez, JF 2017, 'New Approaches to Exciting Exergame-Experiences for People with Motor Function Impairments', Sensors (Basel), vol. 17, no. 2.
• Ravi, DK, Kumar, N, Singhi, P 2017, 'Effectiveness of virtual reality rehabilitation for children and adolescents with cerebral palsy: an updated evidence-based systematic review', Physiotherapy, vol. 103, no. 3, pp. 245-258.