Understanding Research through Design: Qualitative, Quantitative and Mixed Methods, Study notes of Design Patterns

Download Understanding Research through Design: Qualitative, Quantitative and Mixed Methods and more Study notes Design Patterns in PDF only on Docsity! Design < > Research Essay Mathias Verheijden – 1234306 In this essay I will show my understanding of the aims and principles of research through design, and more specifically, discuss the properties, strengths and weaknesses of the qualitative, quantitative and mixed method research methods. Research through design Throughout history, design and research have usually been seen as two separate processes. The former aiming to create specific solutions to problems, which translate into real world appliances. The latter focusing to generate knowledge on a more general note to be used by others. Their similarity however, is that they both contain planned activities with the goal of creating something new (Stappers and Giaccardi, 2017). This does not mean however, that they do not influence each other. In the process called ‘research for design’ for example, research is performed to base design decisions upon. Existing out of several methods (e.g. usability tests, field visits, diary studies, etc.), they aim to understand how people interpret and use products or services (Goodman, et al., 2012). In this case, design is a follow- up for research. A different combination of the two, is ‘research through design’ (RtD): A more iterative process where design is done as part of doing research. Positioned in-between the research and design disciplines, RtD uses design – typically in the form of a prototype – to create a new combination of elements, or create a previously impossible interaction between people and products (Stappers and Giaccardi, 2017). To achieve this, the RtD process includes activities that are usually found in design professions. In RtD, research refers to generating general, abstract knowledge. This knowledge can then be shaped into a theory aimed for long-term use (Stappers and Giaccardi, 2017). This theory can then be used by others to use in future research or decisions. On the other hand, design in RtD refers to specific short- term solutions that are meant to support the research. So whereas knowledge from research is typically used to influence design, the prototypes – or design in general – in RtD serve as an instrument to create new situations or factors to research (Stappers and Giaccardi, 2017). In essence, prototypes are meant to test a hypothesis or answer a pre-set research question and ultimately produce knowledge (Stappers and Giaccardi, 2017). Depending on the results, the design can be changed to find more accurate or significant results. This process of making and re-making these prototypes can also produce valuable knowledge before the testing even begins (Stappers and Giaccardi, 2017). This iterative process ultimately leads to the right results to answer the research question. A good example of this is Wensveen’s alarm clock, as mentioned by Stappers and Giaccardi (2017), where a total of 19 prototypes were made in order to get the best results. These prototypes, and especially their purpose, is where RtD differs from user studies. Although user studies also focus on user behavior or their interactions with a product, they are based on current-world situations and do not aim to intentionally create new interactions and situations, but are purely executed as an observant activity (Goodman, et al., 2012). Said otherwise, user studies do not include the ‘designerly activities’ like found in RtD, where design is integrated in the research process and used as an instrument. Because of this, user studies are ‘research for design’ rather than RtD. Ultimately, the goal of RtD is to generate knowledge or as described by Stappers and Giaccardi (2017) it is: “the production of knowledge by means of design activities”. This knowledge, gained from the data retrieved in the study, can then be generalized, abstracted and formed into a theory. Other researchers or designers can then use this theory to base their own research or design upon. Here the theory is seen as the leading component for the research or design process (Stappers and Giaccardi, 2017). This however, is not the only use for theory. Other researchers may also test the validity of the theory. This is done by re-doing the study and comparing the theory with the results. If the results do not match up, the theory could be weakened or even discarded. If the results do match up, the theory could be strengthened since it is supported by multiple sources. Finally, knowledge from a study does not always form into a theory. This mostly occurs when new areas and technologies are researched. In this case, small – not necessarily structured – explorations are performed, that serve to inspire designers about new technologies (Stappers and Giaccardi, 2017). Because of the small scale and lack of structure, the knowledge cannot be generalized and abstracted into a theory. Research methods As mentioned, qualitative, quantitative and mixed method research methods are described. Respectively, these methods tend to have a subjective, objective and mixed approach to the research where they respectively produce open-ended, closed-ended and mixed data. These characteristics might imply that one can either perform qualitative or quantitative research. However, Creswell (2014) emphasized that neither qualitative nor quantitative should be seen as rigid, distinct categories or opposites. Instead, they are situated at different ends of a continuum. Therefore, “a study tends to be more qualitative or more quantitative” (Creswell, 2014). The mixed method approach then, situates somewhere in the middle of this continuum, containing both qualitative and quantitative elements. Qualitative research is very suitable for situations where a new topic has to be explored or when the researcher is uncertain about the topic (e.g. what variables to focus on / are important). Its inductive approach focusses on individual meaning, often collects data in the participant’s setting and aims to gain in-depth and detailed information about the participants (Creswell, 2014). Qualitative research uses questions rather than objectives or hypotheses. No more than two central questions are set to explore the central phenomenon and aim to find the related relevant factors. To support the main research question, no more than five to seven sub questions are formulated that help narrow the study (Creswell, 2014). The questions focus on a single aspect to explore and specify the participants and research site. To convey an open and emerging design, the questions start with ‘how’ or ‘what’. Finally, the questions use a non-directional way of writing to prevent creating an unintended hypothesis (Creswell, 2014). To answer these questions, detailed information about the participants is gathered using interviews, videotaping, audio recording etc. This generates very rich and unstructured data that is then transcribed, coded (categorized) to find patterns where after the codes are clustered in different themes to draw conclusions (Creswell, 2014). Because of this type of data, qualitative research allows participants to explain their answers, so the researcher can get a deeper understanding of the target group. On the other hand, the qualitative way of data gathering is sensitive for misinterpretation by the researcher due to background or socioeconomic status for instance (Creswell, 2014). To preserve the validity – which is actually one of the strongpoints of qualitative research – of the study, Creswell (2014) describes several methods like triangulation (finding corresponding data from multiple sources), member checking (reflecting findings back to target group) and bias clarification (reflect possible biases from the researcher to the audience). Quantitative research, on the other hand, often works based on a theory, which will be tested. It tests the relationship between variables – a characteristic of an individual or group that is measurable – and uses closed-ended questions. This is more suitable for situations where there is significant prior research and the field has already been explored. It exists out of a research question, hypothesis and objectives (Creswell, 2014). The research question searches the relationship among variables, while the hypothesis makes a prediction about that same relationship. The objectives state what the goals are for the study, which can be reflected on afterwards, or used in order to find funding (Creswell, 2014). When approaching the variables, research questions typically compare the impact of independent variables on dependent variables, relate independent variables to dependent variables or describe how variables are responded upon (Creswell, 2014). To start conducting the study, a sample of participants has to be selected which has to represent the target population. A good sample could be achieved by randomly selecting participants from the population. When selecting a sample, the researcher has to avoid selecting a convenience sample (Creswell, 2014). This sample is selected purely on convenience factors like time and distance; hence the name. To gather data from this sample, instruments are used that generate numerical data assigned to a specific variable. Examples of these instruments are likert scales, body data measurements or simply counting occurrences. This data is then formatted and cleaned, where after descriptively analyzed to indicate basic data like means, standard deviations and range. This gives a basic insight in