Understanding Scientific Research Papers: The Introduction Section

Purpose and Structure of the Introduction

The Introduction section forms the foundation of any scientific paper, serving as both a roadmap and justification for the research being presented. This critical opening section creates the intellectual framework that helps readers understand what motivated the study, why it matters, and how it connects to the broader scientific landscape.

A well-crafted Introduction begins by establishing the research problem or knowledge gap being addressed. This helps readers immediately grasp why the study was necessary in the first place. Was there conflicting evidence that needed resolution? An unexplored area of potential significance? A practical problem requiring a scientific solution? By clearly articulating this foundation, the authors set the stage for everything that follows.

The Introduction then typically moves into summarizing relevant prior work in the field. This literature review serves multiple purposes: it acknowledges the intellectual contributions of other researchers, demonstrates the authors' thorough understanding of existing knowledge, and helps readers situate the current study within the broader scientific conversation. Think of this as creating the historical and intellectual context that makes the current research meaningful.

Particularly valuable Introductions highlight areas of scientific controversy or uncertainty. Science progresses through addressing unknowns and resolving conflicting evidence, so this element helps readers understand where the current scientific consensus stands—and where it remains incomplete. This tension creates the intellectual space that the current study aims to address.

The Introduction also clearly articulates the purpose and significance of the current study. This explains not just what was done, but why it matters. Is this study attempting to resolve a theoretical debate? Develop a new methodological approach? Address a gap in our understanding of a phenomenon? The significance statement helps readers understand the potential impact of the research findings.

Building on this foundation, the Introduction explains how the work extends existing scientific knowledge. This connection between past and present research demonstrates the incremental nature of scientific progress and helps readers understand how this particular study contributes to the broader scientific enterprise.

Finally, the Introduction presents the theoretical framework, hypotheses, or research questions that guided the investigation. These elements transform general scientific interests into specific, testable predictions or focused areas of inquiry. Well-formulated hypotheses or research questions serve as the specific promises that the rest of the paper will fulfill.

By carefully analyzing the Introduction section, you gain valuable insights into not just what the researchers did, but why they did it. This contextual understanding helps you better evaluate the methods they chose, the results they emphasize, and the conclusions they draw. A thorough Introduction provides both the scientific foundation and intellectual rationale that makes the rest of the paper meaningful and allows you to assess its potential contributions to scientific knowledge

Deciphering Scientific Terminology

The Purpose of Specialized Language

Scientific papers rely on specialized vocabulary that often creates a barrier for newcomers to a field. Yet this technical language isn't simply jargon designed to exclude outsiders—it serves essential functions that enable precise and efficient scientific communication.

Technical terminology provides a level of precision that everyday language simply cannot match. When scientists use terms like "autophagy," "quantum entanglement," or "neuroplasticity," they're invoking specific concepts with well-defined boundaries. These terms carry exact meanings within their disciplines, allowing researchers to communicate with minimal ambiguity. Think about how in everyday conversation, words often carry multiple meanings or interpretations. Scientific terminology eliminates this fuzziness, creating a shared understanding that ensures everyone is talking about the same phenomenon.

This precision leads directly to efficiency in communication. Consider the difference between saying "tyrosine kinase" and having to explain "a member of a class of enzymes that catalyzes the addition of a phosphate group to the amino acid tyrosine in certain proteins thereby affecting their function." The technical term encapsulates an entire complex concept in just two words. Imagine reading a paper where every specialized term was replaced with its full explanation—it would become unwieldy and nearly impossible to follow the scientific narrative.

Scientific terminology also creates standardization across research communities. When a researcher in Tokyo reads a paper written by colleagues in Toronto, they share a common vocabulary that transcends linguistic and cultural differences. This standardization allows scientific knowledge to build upon itself globally, with researchers around the world contributing to a shared understanding using consistent terminology.

Beyond these practical benefits, technical terms embed papers within specific theoretical frameworks. When authors use terms like "cognitive dissonance," "punctuated equilibrium," or "quantum field theory," they're not just describing phenomena—they're connecting their work to established theories and conceptual structures. The vocabulary signals which intellectual traditions the research draws from and contributes to.

Learning this specialized language requires significant effort—similar to acquiring proficiency in a foreign language. Yet this investment yields substantial returns. As you become familiar with a field's terminology, papers that once seemed impenetrable begin to reveal their insights. You'll start recognizing patterns across publications and understanding how different studies connect to one another.

When approaching a paper with unfamiliar terminology, consider creating a personal glossary. Look up key terms and write down their definitions in your own words. Pay attention to how these terms relate to one another—scientific vocabulary often forms interconnected networks of concepts rather than isolated definitions. With time and practice, these terms will become second nature, allowing you to focus on evaluating the scientific ideas rather than deciphering the language.

Remember that even the most experienced scientists encounter unfamiliar terminology when venturing outside their specific subfields. The process of learning scientific language is ongoing for everyone in the scientific community—it's part of the lifelong journey of scientific learning and discovery.

Strategies for Building Scientific Literacy

To navigate the specialized terminology in research papers, consider these approaches:

1. Create a Terminology Glossary

When reading scientific papers, developing a personal glossary of technical terms dramatically improves comprehension. This practice transforms intimidating scientific language into accessible knowledge that builds your expertise over time.

The most effective approach is to carefully identify recurring technical terminology in the Introduction section, which typically presents the key concepts that will appear throughout the paper. Focus on five main categories of specialized language.

Field-specific jargon includes terms with precise meanings within a discipline that differ from everyday usage. These terms often represent core concepts in the field and understanding them unlocks deeper comprehension of the research.

Methodological terminology describes the specific techniques and approaches researchers used. Understanding these methods helps you evaluate how data was collected and analyzed, providing crucial context for the findings.

Statistical concepts may be particularly challenging without a background in statistics. Developing a functional understanding of statistical approaches helps you interpret the significance and reliability of research findings.

Biological processes or structures often form the central subject matter in life science papers. Even a basic understanding of these phenomena provides essential context for interpreting the study's significance.

Taxonomic classifications help situate organisms within evolutionary relationships. Noting how species and other taxonomic groupings relate to more familiar organisms builds a mental map of biological connections.

When creating your definitions, aim for clarity rather than exhaustive detail. Write them in your own words, focusing on how terms connect to the paper's central questions. This process is cumulative—each paper you read expands your scientific vocabulary, gradually transforming terminology that once seemed impenetrable into familiar concepts that enhance your scientific literacy.

2. Consult Multiple Reference Sources

When navigating the complex landscape of scientific literature, having access to reliable reference materials becomes essential for decoding specialized terminology. Various resources offer different advantages in terms of depth, accessibility, and practicality for different learning contexts.

Scientific dictionaries provide authoritative definitions tailored to specific disciplines. These specialized references—whether focused on biology, biochemistry, medicine, or other fields—offer precise explanations of technical terms with the rigor scientists expect. Both print and online glossaries serve as valuable companions during literature review, allowing you to quickly look up unfamiliar terms without disrupting your reading flow. Discipline-specific encyclopedias expand beyond simple definitions to provide context and relationships between concepts. For highly standardized fields, terminology databases maintained by governing bodies (such as the International Union of Pure and Applied Chemistry for chemical nomenclature or the International Committee on Taxonomy of Viruses for viral classification) ensure you're accessing the most current and officially recognized definitions.

Comprehensive references offer deeper engagement with scientific concepts beyond definitions. Undergraduate and graduate textbooks provide systematic coverage of foundational knowledge in a field, often with helpful visuals and examples that illuminate complex ideas. Review articles and meta-analyses synthesize current understanding across multiple studies, helping you grasp how individual terms fit within broader scientific narratives. Scientific encyclopedias combine depth with breadth, making them valuable for understanding cross-disciplinary connections. Publications from professional societies often include glossaries and primers designed specifically for newcomers to the field. Educational websites developed by research institutions typically offer accessible explanations of complex topics, sometimes enhanced with interactive elements that promote deeper understanding.

Quick-Reference Tools

• Mobile apps for scientific terminology

• Interactive molecular visualization tools

• Field guides and taxonomic keys

• Scientific glossary browser extensions

• Citation management software with note-taking capabilities

3. Develop Contextual Understanding

Scientific terminology becomes truly meaningful when we look beyond mere definitions to understand how terms exist within broader conceptual frameworks. This deeper engagement transforms scientific vocabulary from isolated facts into connected knowledge that reveals how scientists think about their fields.

Tracing the historical development of key terms offers a window into how scientific understanding evolves over time. Consider how the term "gene" has transformed from Mendel's abstract units of inheritance to our current understanding involving specific DNA sequences and complex regulatory networks. This historical perspective reveals science as a dynamic process rather than a static collection of facts. By exploring when and why certain terms emerged, you gain insight into the intellectual journeys that shaped contemporary scientific thought.

Identifying how terms connect to fundamental principles helps you recognize the conceptual architecture of a discipline. For instance, in physics, terms like "entropy," "force," and "energy" aren't just isolated concepts—they form interconnected components of foundational theories about how the physical world operates. When you understand these connections, individual terms become meaningful parts of coherent explanatory frameworks rather than disconnected vocabulary to memorize.

Recognizing when terms represent competing theoretical perspectives alerts you to areas of active scientific debate. When you encounter terms like "punctuated equilibrium" versus "phyletic gradualism" in evolutionary biology, you're witnessing terminology that embodies different interpretations of evolutionary patterns. These terminological distinctions often signal important conceptual divides within a field, revealing where scientific consensus remains unresolved and where new research might yield transformative insights.

Noting how terminology usage varies across subfields or research traditions helps you appreciate the contextual nature of scientific language. The term "plasticity," for example, carries different specific meanings in neuroscience, developmental biology, and materials science, though all relate to adaptability or malleability. These variations reflect how scientific communities develop specialized vocabularies that serve their particular research questions and methodological approaches. Awareness of these variations prevents confusion when navigating interdisciplinary literature.

Understanding when terms represent observational data versus interpretive frameworks helps distinguish between different levels of scientific knowledge. Some terms, like "voltage" or "cell membrane," describe directly measurable phenomena, while others, like "natural selection" or "cognitive dissonance," represent theoretical constructs that help scientists interpret patterns in their observations. This distinction is crucial for evaluating scientific claims and understanding the relationship between evidence and explanation in scientific discourse.

4. Evaluating Digital Information Sources

When navigating the vast landscape of online scientific information, developing strong evaluation skills becomes essential for distinguishing reliable knowledge from questionable content. The digital environment offers unprecedented access to scientific resources but requires careful assessment using multiple criteria.

Authorship and authority serve as primary indicators of reliability. Begin by identifying whether content comes from an individual researcher or an established organization. Examine the author's credentials, including their educational background, institutional affiliations, and relevant expertise in the specific subject area. Their publication history and citation patterns provide insights into their standing within the scientific community. Pay attention to potential conflicts of interest or funding sources that might influence the presentation of information. The author's professional recognition within their field, such as awards or leadership positions, can further signal credibility.

Content scope and depth reveal how thoroughly a source addresses its subject matter. Consider the intended audience and whether the resource assumes appropriate background knowledge. Evaluate how comprehensively the content covers relevant aspects of the topic and whether it achieves a meaningful balance between broad overview and specific details. Strong resources integrate multiple perspectives rather than presenting a single viewpoint as definitive. They also provide historical context that situates current understanding within the evolution of scientific knowledge.

Currency and maintenance indicate whether information reflects contemporary scientific understanding. Check publication dates and look for evidence of regular updates or revisions. Quality resources incorporate recent research findings while maintaining core principles that remain valid. Consider the archival status of the resource—whether it represents active, ongoing development or serves as a historical record. Even the technological aspects of presentation, such as modern formatting and accessibility features, can signal commitment to maintaining relevant content.

Presentation and usability factors affect how effectively information is communicated. Editorial quality, including grammatical precision and consistent terminology, reflects careful attention to accuracy. Visual design elements should enhance understanding rather than simply decorate. Well-structured navigation and effective search functionality make information more accessible. Look for accessibility features that make content available to diverse users. Strong documentation standards, including proper citations that allow verification of claims, demonstrate scholarly rigor.

Purpose and objectivity influence how information is framed and presented. Transparent resources clearly state their mission and organizational goals. They acknowledge their perspective while presenting alternative interpretations fairly. They distinguish clearly between established facts and more speculative interpretations. Quality scientific resources acknowledge limitations in current understanding and areas of ongoing uncertainty rather than overstating conclusions.

Quality control mechanisms provide safeguards against misinformation. Look for evidence of peer review processes, editorial oversight, and fact-checking procedures. Responsible sources maintain clear policies for correcting errors when discovered. Many quality resources incorporate user feedback mechanisms to identify problems and improve content over time. External validation, such as recognition from established scientific organizations, provides additional credibility markers.

The most trustworthy online sources typically include university and research institution websites, government science agencies like the NIH or NSF, professional scientific societies, peer-reviewed journals and their digital platforms, major research foundations, scientific databases and repositories, and academic digital libraries. These sources maintain rigorous standards for accuracy and undergo multiple levels of review before publication.

Remember that even prestigious sources require critical evaluation, as scientific understanding evolves continuously and errors can occur in any publication. The best approach combines awareness of institutional reputation with careful assessment of specific content using multiple criteria. This balanced evaluation strategy helps you build a reliable foundation of scientific knowledge in our increasingly complex information environment.

The Scientific Process: Observations, Explanations, and Experiments

Understanding Scientific Methodology

Scientific studies operate within a methodological framework that integrates various cognitive and practical activities. While the "scientific method" is often presented as a linear process, actual scientific practice involves complex interactions among:

• Systematic observation and data collection

• Pattern recognition and anomaly detection

• Literature Review for current knowledge

• Creative hypothesis generation

• Theoretical modeling and framework development

• Experimental design and execution

• Statistical analysis and interpretation

• Peer critique and community validation

A paper's Introduction typically situates the study within this broader scientific enterprise, indicating which aspects of the process it emphasizes.

Types of Scientific Contributions

Research papers can make diverse contributions to scientific knowledge. The Introduction should clarify which type(s) of contribution the study aims to make:

Observational Studies

Some research primarily focuses on gathering new data or describing phenomena. When evaluating observational studies.

·         Novelty: Do the observations extend beyond what is already known?

·         Methodology: Does the study employ innovative techniques or technologies for data collection?

·         Scope: Is the observational dataset more comprehensive or detailed than previous efforts?

·         Resolution: Does the study examine phenomena at different spatial or temporal scales?

·         Synthesis: Does the work integrate previously disconnected observations?

·         Verification: Does the study confirm or challenge previous observations?

The Introduction should clearly articulate why new observations are valuable and how they relate to existing knowledge.

Question-Driven Research

Scientific inquiries often begin with specific questions triggered by observations or theoretical inconsistencies. The Introduction should address:

• The origin and context of the research questions

• Different types of questions being pursued (how vs. why; proximate vs. ultimate)

• Connections between specific questions and broader theoretical issues

• Prioritization criteria for pursuing certain questions over others

• Practical and conceptual constraints that shape the inquiry

• Potential implications of answering the questions

Well-formulated research questions should be clear, focused, and scientifically consequential.

Theory Development

Some papers aim to create new theoretical frameworks or substantially modify existing ones. When assessing theory-building papers, examine:

·         Motivation: What inadequacies in current theories necessitate new development?

·         Scope: What phenomena does the theory attempt to explain?

·         Foundation: What empirical evidence supports the theoretical development?

·         Methodology: What logical, mathematical, or computational approaches are used?

·         Integration: How does the theory relate to established scientific principles?

·         Testability: What empirical predictions can be derived from the theory?

The Introduction should establish why theoretical innovation is necessary and how the paper's approach improves upon existing frameworks.

Hypothesis Testing

Scientific papers center on testing specific hypotheses that emerge from broader theoretical frameworks. A well-crafted Introduction frames these hypotheses with precision and context, establishing the intellectual foundation for the entire study.

An effective Introduction clearly articulates the central hypothesis or competing hypotheses being examined. This explicit statement serves as the focal point around which the research revolves. The hypothesis should be anchored within relevant theoretical frameworks, showing how it connects to established scientific understanding rather than existing in isolation. For example, a hypothesis about memory formation might be situated within cognitive psychology theories or neuroscience models.

The Introduction explains the logical development of the hypothesis by tracing how it emerged from previous research findings. This progression demonstrates scientific continuity and shows why the current study represents a meaningful next step in knowledge development. The authors then specify the testable predictions generated by their hypothesis—the observable outcomes that would occur if the hypothesis is correct. These predictions translate abstract theoretical ideas into concrete, measurable phenomena.

The Introduction outlines the experimental or analytical strategy for evaluating these predictions. This preview helps readers understand how the methodology aligns with the conceptual framework and prepares them for the detailed methods section that follows. Finally, the Introduction indicates the broader implications of potentially supporting or rejecting the hypothesis, explaining how the results will advance scientific understanding regardless of outcome.

Well-formed hypotheses possess two essential qualities: they must be falsifiable (capable of being proven wrong through observation or experiment) and logically consistent with established knowledge. Falsifiability ensures that hypotheses can be meaningfully tested rather than remaining speculative assertions. Logical consistency with existing evidence creates a coherent scientific narrative, though truly innovative hypotheses may challenge aspects of conventional understanding while remaining grounded in fundamental principles.

Decision-Making in Scientific Research

The Introduction often reveals the complex decision-making processes that guide scientific inquiry. Researchers must balance multiple considerations:

Scientific Factors

• Theoretical significance and potential for knowledge advancement

• Feasibility of addressing the research question with available methods

• Likelihood of obtaining interpretable results

• Potential for resolving existing controversies or contradictions

• Connections to fundamental questions in the field

Practical Considerations

• Technical expertise and resources available to the research team

• Funding opportunities and constraints

• Time limitations and project timelines

• Collaborative possibilities and disciplinary boundaries

• Career development and educational objectives

• Ethical and regulatory requirements

Strategic Elements

• Research priorities within the scientific community

• Competitive landscape and potential for priority claims

• Potential applications and broader impacts

• Opportunities for methodological innovation

• Alignment with institutional or funding agency missions

Understanding these decision-making factors helps contextualize why particular research directions are pursued while others remain unexplored.

The Cyclical Nature of Scientific Progress

Integration of Scientific Activities

Scientific advancement operates through iterative cycles that connect different aspects of the research process:

1.       Observations generate questions and challenge existing explanations

2.       Explanations (theories and hypotheses) organize observations and guide new inquiries

3.       Experiments test explanations and produce new observations

4.       Analysis interprets experimental results and refines explanations

5.       Communication shares findings and enables community validation

6.       Integration synthesizes multiple lines of evidence into coherent frameworks

This cyclical process creates a dynamic relationship between empirical evidence and theoretical understanding. The Introduction should position the current study within this ongoing cycle and clarify how it contributes to progressive knowledge development.

Modes of Scientific Reasoning

Scientific research rests upon distinctive patterns of reasoning that give structure and rigor to the process of discovery. Though rarely made explicit, these reasoning strategies shape how scientists approach problems, design studies, and interpret findings. Understanding these cognitive frameworks helps reveal the intellectual architecture beneath the visible surface of published research.

Inductive reasoning builds knowledge by moving from specific observations toward general principles. This bottom-up approach begins with detailed empirical observations, searches for meaningful patterns within data, and gradually constructs broader generalizations. Consider how Darwin developed his theory of evolution—by methodically collecting countless specific observations across many species, identifying recurring patterns, and gradually formulating general principles about natural selection. Inductive reasoning thrives on rich datasets and careful observation, allowing theories to emerge organically from empirical foundations rather than being imposed from above.

Deductive reasoning travels in the opposite direction, applying general theories to predict specific outcomes. This top-down approach begins with established principles, derives logical consequences, and tests these predictions against reality. When physicists use quantum theory to predict the behavior of specific particles or when economists apply microeconomic principles to forecast consumer responses to price changes, they're employing deductive reasoning. The strength of this approach lies in its logical rigor and ability to extend existing knowledge into new domains through systematic hypothesis generation and testing.

Abductive reasoning seeks the most plausible explanation for observed phenomena—what philosophers call "inference to the best explanation." Unlike deduction or induction, abduction focuses on explanatory power. When medical researchers investigate disease mechanisms or when geologists interpret the formation of unusual rock formations, they're evaluating which explanation most comprehensively accounts for the available evidence. Abductive reasoning becomes particularly vital when multiple theoretical frameworks could potentially explain the same observations, requiring scientists to carefully weigh competing interpretations.

Systems thinking transcends linear cause-and-effect relationships to examine how multiple components interact within complex networks. This approach analyzes how elements influence each other through feedback loops, thresholds, and emergent properties that cannot be predicted by studying components in isolation. Ecological research on food webs, climate science modeling, and studies of cellular signaling networks all employ systems thinking to capture complex, multi-variable relationships that resist simplification. Systems approaches often utilize computational models to simulate interactions too complex for intuitive understanding.

In practice, scientific work rarely relies exclusively on any single reasoning strategy. Most research integrates multiple approaches—perhaps using deduction to generate hypotheses, systems thinking to design experiments that capture complexity, induction to identify unexpected patterns in results, and abduction to develop the most compelling explanation for surprising findings. The Introduction section of a paper may reveal which reasoning modes predominate in a particular study, providing clues about the intellectual approach underpinning the research.

Scientific Consensus and Knowledge Integration

Individual studies represent contributions to an evolving body of knowledge rather than definitive answers. The Introduction should:

• Position the study within the broader scientific literature

• Acknowledge competing perspectives or interpretations

• Indicate areas of consensus and controversy

• Specify which knowledge gaps the study addresses

• Suggest how findings might influence collective understanding

Remember that scientific consensus emerges gradually through accumulation of evidence from multiple studies, critical evaluation by the scientific community, and integration of findings into coherent explanatory frameworks.

Analytical Framework for Evaluating Introductions

Context and Significance

• What is the paper's primary research area and subdiscipline?

• How does the study relate to fundamental questions in the field?

• What societal, environmental, or practical problems connect to this research?

• Why is this research timely or particularly relevant now?

Conceptual Framework

• What theoretical perspectives inform the research?

• What key concepts, models, or frameworks are employed?

• How are central terms defined and operationalized?

• What assumptions underlie the research approach?

Literature Integration

• Which previous studies form the foundation for this research?

• How comprehensive is the literature review?

• Are competing perspectives or contradictory findings acknowledged?

• How is the current study positioned relative to existing work?

Research Purpose

• What specific knowledge gap or problem does the study address?

• What are the stated aims, objectives, or research questions?

• Does the paper test hypotheses, develop theory, or gather observations?

• What specific contributions does the study claim to make?

Methodological Preview

• What approach does the study take to address its questions?

• What innovations in methods or techniques does it employ?

• How are theoretical concepts connected to empirical measures?

• What limitations or constraints does the approach entail?

Overall Assessment

• Does the Introduction provide sufficient justification for the study?

• Is the research question clearly articulated and well-motivated?

• Does the paper address a significant issue in the field?

• Is the study's potential contribution proportionate to the effort involved?

By systematically analyzing these aspects of the Introduction, you'll develop a deeper understanding of the paper's purpose and significance while building critical evaluation skills essential for scientific thinking.

Practical Exercises

To apply these concepts to a specific research article, complete the following exercises:

1. Research Context

Read the Introduction section of your selected paper and identify:

• The main research area and subdiscipline

• Key research questions being addressed

• Connections to broader scientific theories or frameworks

• Potential applications or implications of the research

2. Terminology Analysis

• List the 10-15 most important technical terms used in the Introduction

• Provide a definition for each term, consulting appropriate references

• Create a concept map showing relationships among these terms

• Identify any terms that represent competing theoretical perspectives

3. Literature Synthesis

• Identify 3-5 key previous studies cited in the Introduction

• Summarize each study's main findings and contributions

• Explain how these studies collectively form the foundation for the current research

• Note any contradictions or unresolved questions in the previous literature

4. Controversy Mapping

• Identify areas of scientific disagreement or uncertainty mentioned in the Introduction

• Characterize the different perspectives on each controversial issue

• Explain how the current study might help resolve these controversies

• Consider what evidence would be necessary to settle the disputed questions

5. Research Question Analysis

• Precisely state the main research question(s) addressed in the paper

• Explain why this question is scientifically important

• Describe how it extends or challenges previous work

• Evaluate whether the question is well-defined and answerable

6. Hypothesis Evaluation

If the paper tests specific hypotheses:

• Restate each hypothesis in your own words

• Explain how each hypothesis connects to broader theories

• Identify the specific predictions derived from each hypothesis

• Describe what findings would support or contradict each hypothesis

• Assess the implications of hypothesis rejection for the underlying theory

7. Theory Development Assessment

If the paper aims to develop or refine theory:

• Identify limitations in existing theoretical frameworks

• Explain the approach taken toward theoretical development

• Describe the empirical foundation for the theoretical work

• Evaluate the potential impact of the new theoretical perspective

8. Observational Study Analysis

If the paper primarily reports new observations:

• Characterize the nature and scope of the new dataset

• Explain how these observations extend beyond previous knowledge

• Identify any novel methodologies that enabled the observations

• Consider what new explanations might emerge from these observations

9. Overall Evaluation

• Assess whether the Introduction makes a compelling case for the study

• Identify any weaknesses in the justification or framing

• Consider alternative approaches that might address the same question

• Evaluate the potential significance of the study's contributions