Research: Understanding basics and getting started – Part II

(Part I of this article appeared yesterday)

Identification of a Research Problem

A well-defined research problem is the foundation of any meaningful research. It serves as the driving force that shapes the research process, distinguishing it from a general essay, where a research problem is not necessarily required. In an essay, one may present an argument or analysis without systematically addressing an unresolved question. However, in research, identifying a research problem is essential because it establishes the purpose and direction of the study.

A research problem arises in situations where a) The answer is entirely unknown, b) There are multiple, often conflicting answers.) Existing answers are inadequate or unsatisfactory.

A strong research problem should ideally be theoretical and analytical rather than merely descriptive. This means that the issue under investigation should contribute to a broader body of knowledge and be applicable beyond a single case. A well-formulated research problem allows for systematic inquiry, critical engagement with existing literature, and the development of new insights that can be tested, debated, and applied in different contexts.

Effective research problems often emerge from gaps in existing knowledge, inconsistencies in theoretical perspectives, or unresolved debates within a particular field. Researchers must critically assess prior studies, identify limitations, and frame their research problem in a way that advances scholarly understanding.

How to begin a research?

Research begins with the identification of a problem. A well-defined problem is the foundation upon which the entire study is built. Without a clear and focused problem, the research lacks direction. Once the problem is identified, the next step is to define it in specific terms, ensuring that the scope is manageable and relevant.

The process of research starts with recognising a gap in existing knowledge or a real-world issue that requires exploration. This problem could arise from theoretical questions, societal needs, or unresolved practical challenges. Once identified, the problem must be clearly defined to guide the research process and ensure that the results are meaningful and applicable.

Once the research problem is clearly defined, the next step is to form hypotheses. Hypotheses are educated guesses or assumptions based on initial observations of the problem. They provide a tentative explanation or prediction that can be tested through research. Hypotheses guide the direction of the study, suggesting what the researcher expects to find or how the problem might be addressed.

Hypotheses are used to gather data. Researchers design methods, such as experiments, surveys, interviews, or observations, to collect information that either supports or challenges the hypotheses. The type of data collected will depend on the nature of the problem and the hypotheses being tested.

The validity of hypotheses is tested through experimentation, further observations, and surveys. Researchers analyze the data to determine whether the hypotheses are supported or refuted. If the data aligns with the hypothesis, it can be considered as supporting evidence. Conversely, if the data contradicts the hypothesis, it must be refuted, prompting a reevaluation of the research approach or the formulation of new hypotheses.

Observations and Surveys: Two Key Components of the Research Process

Observation is a systematic and focused approach to perceiving and understanding something. It is the initial step in the research process that involves actively perceiving a phenomenon, recording what is seen, and seeking to derive meaning from the observed data.Observation often serves as the foundation for testing a theory or hypothesis. By observing the world, researchers gather real-world data that either supports or challenges established theories or hypotheses.The insights derived from observation provide the initial data necessary for deeper analysis. They allow researchers to identify variables and relationships that will be examined in subsequent steps of the research.While observation is critical, it is not sufficient on its own for acquiring deeper knowledge. It offers descriptive data but requires further investigation and interpretation to draw conclusions about underlying causes or implications.

A survey is a methodical process for collecting and analysing data through direct examination of facts, measurements, and other variables. Surveys are typically structured to gather quantitative data, offering a broad understanding of the subject under study.Surveys often involve the measurement of specific variables, whether through numerical data or other measurable factors, to understand their magnitude or distribution.Surveys involve systematically recording factors and variables that could influence or explain the research phenomenon. These records often serve as a comprehensive database for analysis.The data collected through surveys is often categorized into relevant groups, which helps in identifying trends, correlations, and potential insights that can further inform the research process.In sum, both observation and survey are integral to the research process.

Collection and Examination of Data

The collection of data is a fundamental and initial step in any research. Data is raw, unprocessed information—experience without interpretation. It is akin to a signal that provides useful information but without context or meaning.

One of the fundamental principles of data collection is the distinction between objectivity and subjectivity. Objectivity ensures that data is gathered free from personal bias or interpretation, maintaining neutrality and factual accuracyIncontrast, subjectivity, personal perspectives, prejudices and experiences, can distort data and lead to inaccurate conclusions. This distinction underscores the principle that facts are sacred; opinions are free—facts should remain unaltered by personal bias, while opinions are inherently subjective and open to interpretation.

Once collected, data must be systematically categorised to facilitate analysis and interpretation. Traditionally, it has been classified as primary or secondary, but this distinction is increasingly seen as outdated, as the boundaries between these categories have blurred. Contemporary research prioritises a more nuanced approach that considers data sources, context, and potential biases.

There is no one-size-fits-all approach to data collection in research. The choice of methods depends on the field of study and the specific research questions. Broadly speaking, research methods are categorized into qualitative and quantitative approaches. Qualitative methods, such as interviews, focus groups, and ethnography, aim to explore underlying themes, perceptions, and experiences. The data collected is often non-numerical and lends itself to in-depth analysis within natural contexts. In contrast, quantitative methods involve the collection of numerical data through surveys, experiments, or statistical analysis. These methods are typically used to test hypotheses, identify patterns, and generate statistical insights.

Beyond these methods, advancements in data science and emerging technologies have revolutionised data collection and analysis. From big data analytics to AI-driven tools, modern research methods are expanding how data is gathered, categorized, and interpreted.

Critical examination of data is an essential element in research, as it ensures the validity and reliability of findings. A commonly used method for examining data is through analysis and synthesis. Analysis involves a detailed and systematic examination of data by breaking it down into parts, features, and qualitieswhile synthesis allows them to integrate and combine information from different sources to form a comprehensive understanding. This requires thoughtful consideration and reasoning to uncover patterns, relationships, and underlying structures.

Main steps in the research process

Identification of Research Problem: The first step in any research process is to clearly define the problem you want to explore. This involves understanding the issue at hand, reviewing existing literature to see what has been researched before, and pinpointing gaps in knowledge. A well-defined research problem sets the stage for the entire project and guides the subsequent steps.

Hypothesis Formation: Once the problem is identified, the next step is to form a hypothesis or a tentative statement that predicts the outcome of the research. A hypothesis should be based on existing theory or observations. It acts as the foundation for guiding the research design.

Making Observations: This step involves gathering preliminary information through direct observation, literature review, or secondary data collection. Observations help refine the research questions further and build an understanding of the context. It’s essential to document the information you observe systematically to identify patterns or insights.

Conducting Surveys: Surveys, interviews, or experiments are commonly used tools to gather primary data. Depending on the nature of the research, surveys help collect data from participants to support or challenge the hypothesis. It’s crucial to design surveys carefully, ensuring they are valid, reliable, and ethical, while aligning with the research objectives.

Building Concepts: After gathering data, the next step is to analyze and organise the information. This may involve creating new concepts or refining existing ones, categorising the data, and identifying relationships between variables. Building concepts helps transform raw data into meaningful insights that are necessary for drawing conclusions.

Arriving at Judgments: At this stage, researchers evaluate the data and test the hypothesis. They assess whether the findings align with the initial hypothesis or if new interpretations are needed. This is the point where critical thinking and analysis come into play to determine the significance and implications of the findings.

Making Conclusions: The final step in the research process is drawing conclusions based on the evidence gathered throughout the study. This includes interpreting the results, explaining how they address the research problem, and offering recommendations for future research or practical applications. It’s also important to acknowledge limitations and suggest ways in which the research can be expanded.

Unpacking Scientific
Research Method

Since the 1970s, the Linguistic Turn in Western philosophy has critically re-examined the assumptions underlying the traditional scientific research approach. This intellectual shift, influenced by thinkers such as Friedrich Nietzsche, Wilhelm Dilthey, and Martin Heidegger, challenged the idea that knowledge could be purely objective and independent of language. Their work laid the groundwork for later scholars who argued that language, interpretation, and human experience fundamentally shape our understanding of truth and reality.

The Linguistic Turn prompted a reconsideration of several foundational premises of the scientific method, particularly its claims to neutrality and universality. Below are key aspects of this intellectual movement and its impact on the philosophy of knowledge and science:

The Truth or Truths:

Traditional scientific thought holds a singular, objective truth that is discoverable through empirical research. However, philosophers of the Linguistic Turn, influenced by Nietzsche’s critique of objective truth, argued that truth is not absolute but is contingent on language, culture, and perspective. Truths, therefore, are plural and are shaped by the subjective frameworks we use to understand the world.

Knowledge – Truth Nexus:

In Modern Science, knowledge is seen as a pathway to uncovering truths about the world, grounded in objective observation. The Linguistic Turn, however, proposed that knowledge itself is not neutral or purely empirical, but deeply intertwined with the language we use to interpret our

experiences. It suggests that knowledge is always mediated by linguistic and cultural structures, making it subject to interpretation rather than a direct reflection of objective reality.

Objectivity of Data:

The scientific method relies on the assumption that data can be collected and interpreted in an objective, unbiased manner. Yet, thinkers like Heidegger and Dilthey contended that all human understanding, including the analysis of data, is inherently influenced by subjective preconceptions and historical contexts.

Subjectivity – Objectivity Dichotomy:

The traditional Scientific Approach draws a sharp line between subjectivity (personal bias, emotions, etc.) and objectivity (rational, detached analysis). The Linguistic Turn critiques this dichotomy; subjectivity cannot be entirely separated from objectivity. Knowledge and truth are seen as always influenced by the individual’s perspective, background, and language, making the separation of the two a false ideal.

Uni-lineal Progress:

The Scientific Approach is often grounded in the assumption of linear progress, where each discovery necessarily leads to a subsequent advancement in understanding. However, drawing on the ideas of Nietzsche and Heidegger, Jean-François Lyotard challenged this assumption, arguing that progress is not always linear. He contended that historical and cultural contingencies significantly influence the trajectory of intellectual and scientific development. Thus, the concept of linear progress is an oversimplification of a far more complex and multifaceted reality.

Grand (Meta) Narration: The Scientific Research Approach often embraces grand narratives—overarching theories or models that aim to explain all phenomena in a single, unified framework (e.g., theories of evolution, theories of relativity). The Linguistic Turn, however, challenges the validity of such grand narratives, arguing that they tend to exclude alternative perspectives and experiences. The focus, instead, shifts toward smaller, local narratives that acknowledge complexity and difference, emphasizing the plurality of viewpoints rather than one dominant, overarching explanation.

The intellectual revolution sparked by the Linguistic Turn has significantly reshaped how we approach knowledge, truth, and research, urging a more nuanced and critical engagement with the scientific paradigm. By emphasizing the role of language, interpretation, and historical context, it calls into question the objectivity and universality that were once the cornerstones of scientific inquiry.

(Gamini Keerawella taught Historical Method, and Historiography at the University of Peradeniya, where he served as Head of the Department and Senior Professor of History. He is currently a Professor Emeritus at the same university)

by Gamini Keerawella