A complete psychology FYP has five chapters built around one running thread: a problem statement in Chapter 1 that a theory in Chapter 2 can explain, a design in Chapter 3 that can actually test it, results in Chapter 4 that answer the exact question Chapter 1 asked, and a discussion in Chapter 5 that closes the loop. Below is a full, labelled worked example — not a real thesis to copy, but a complete model of the structure examiners expect.
The Illustrative Topic This Example Uses
To keep every chapter connected, this example follows one invented but plausible study throughout: Social Media Use and Self-Esteem Among Malaysian Undergraduates. All names, numbers and quotations below are illustrative — built to show structure, not to be copied as real findings. Adapt the topic, theory and instrument to your own supervisor-approved study.
Chapter 1: Introduction
Chapter 1 states the problem, not the topic. “Social media use among students” is a topic; “heavy social media use has been linked to lower self-esteem in some populations, but the relationship among Malaysian undergraduates specifically has not been examined” is a problem statement — it names a gap a reader can see. From there, Chapter 1 sets one general objective and two to three specific objectives, each with a matching research question:
- Objective 1: To determine the level of self-esteem among Malaysian undergraduates.
RQ1: What is the level of self-esteem among Malaysian undergraduates? - Objective 2: To determine the pattern of daily social media use among Malaysian undergraduates.
RQ2: What is the pattern of daily social media use among Malaysian undergraduates? - Objective 3: To examine the relationship between social media use and self-esteem among Malaysian undergraduates.
RQ3: Is there a significant relationship between social media use and self-esteem among Malaysian undergraduates?
Chapter 1 closes with significance (who benefits: student counselling units, future researchers in this sub-field) and scope (one or two named universities, undergraduates only, a defined data-collection period) — stated as boundaries, not apologised for.
Chapter 2: Literature Review
Chapter 2 does three jobs: reviews what is already known about self-esteem, reviews what is already known about social media use and wellbeing, then builds the theoretical framework that predicts how the two should relate. A commonly used framework for this kind of comparison-driven topic is Social Comparison Theory (Festinger, 1954), which proposes that people evaluate their own worth by comparing themselves to others — a mechanism frequently used in the literature to explain why curated, highlight-reel social media content might be associated with lower self-esteem in frequent users. The chapter should state the theory’s core proposition in the researcher’s own words, connect it explicitly to the two study variables, and close with a conceptual framework diagram: Social Media Use (independent variable) → Self-Esteem (dependent variable), with Social Comparison Theory named as the mechanism linking the two boxes.
Chapter 3: Methodology
Chapter 3 for this example uses a quantitative correlational design — appropriate because the research question asks about a relationship between two variables, not a cause-and-effect claim, and not a lived-experience question that would call for a qualitative design instead. The instrumentation section names two specific tools: the Rosenberg Self-Esteem Scale (a widely used, ten-item validated instrument with a published Bahasa Malaysia version), and a researcher-adapted set of items measuring daily social media use in hours and platforms used — labelled explicitly as researcher-adapted, not presented as an independently validated scale, since no single universally standard “social media use scale” exists for this exact purpose. Population and sampling should name a specific, realistic frame (undergraduates at one named faculty), a sampling method (simple random or stratified, matched to how the sampling frame is actually accessible), and a sample-size justification using a recognised formula or table rather than an arbitrary round number. The chapter closes with the ethics paragraph: university ethics committee approval obtained before data collection, informed consent, and confidentiality of individual scores.
Chapter 4: Results
Chapter 4 reports findings in the same order as the objectives in Chapter 1 — descriptive statistics for RQ1 and RQ2 first, then the correlation test for RQ3. A worked, illustrative example of how the correlation result might be reported: “A Pearson correlation was conducted to examine the relationship between daily social media use and self-esteem scores. Results indicated a statistically significant negative correlation, r(198) = −.31, p < .01, suggesting that higher daily social media use was associated with lower self-esteem scores among the sampled undergraduates." Every number in that sentence is illustrative for this example — your own Chapter 4 must report your own study’s actual computed values, never a number copied from an example like this one. A results table presenting descriptive statistics (mean, standard deviation) for both variables, followed by the correlation coefficient and its significance level, typically accompanies this narrative.
Chapter 5: Discussion, Conclusion and Recommendations
Chapter 5 opens by restating the key finding in one sentence, then explains it using the theoretical framework from Chapter 2: if the illustrative result above held, the discussion would explain the negative correlation through the lens of Social Comparison Theory — frequent exposure to curated peer content may prompt more frequent upward social comparison, plausibly lowering self-esteem over time — while being careful to use hedged language (“the finding is consistent with,” “this may suggest,” not “this proves”), since a single correlational study cannot establish causation. The chapter then compares the finding with prior studies (agreeing or disagreeing, and offering a plausible reason either way), states limitations honestly (cross-sectional design cannot establish direction of causality; single-institution sample limits generalisability; self-adapted social-media-use items were not independently validated), and closes with recommendations split for future researchers (a longitudinal design to test direction of causality) and for practice (student counselling services informed by the finding, stated cautiously given the design’s limits).
How the Five Chapters Connect — A Consistency Check
| Chapter | What it must match |
|---|---|
| 1. Introduction | Objectives and research questions set the agenda for everything after |
| 2. Literature review | Theory explains why the variables in Chapter 1 should relate the way you predict |
| 3. Methodology | Design and instruments are capable of testing exactly what Chapter 1 asked, nothing broader |
| 4. Results | Reported in the same order as the objectives, using the exact statistical test named in Chapter 3 |
| 5. Discussion | Explains the Chapter 4 finding using the Chapter 2 theory, then states limitations tied to Chapter 3’s actual design choices |
An examiner reading a psychology FYP checks this chain first — a mismatch anywhere in it (an objective with no matching result, a theory in Chapter 2 that never reappears in Chapter 5) is a faster way to lose marks than any single weak paragraph.
Formatting the Chapter 4 Results Table
A clean results section for this example separates two tables rather than crowding everything into one. The first is a descriptive statistics table: variable name, mean, standard deviation, and interpretation band (for example, where a Rosenberg score falls on a low/medium/high self-esteem banding, if your chosen scale publishes one). The second is the inferential statistics table for the correlation itself: the two variables, the correlation coefficient, degrees of freedom or sample size, and the p-value, with a single asterisk convention noted beneath the table (for example, * p < .05, ** p < .01) so a reader does not have to search the narrative text to interpret significance. Keep the narrative paragraph and the table doing complementary jobs — the table carries the precise numbers, and the paragraph carries the plain-language interpretation an examiner reads first.
Common Mistakes This Example Is Built to Avoid
- A theoretical framework chapter that names a theory but never explicitly connects it to the study’s own variables.
- An instrument section that does not distinguish between a published, validated scale and researcher-adapted items — presenting the latter as if it carries the same evidence base as the former.
- A results chapter reporting statistics in a different order from the objectives listed in Chapter 1, forcing the reader to hunt for which result answers which question.
- A discussion chapter that claims causation from a correlational design.
- Limitations copied generically from another thesis instead of tied to this specific study’s actual sample, design and instruments.
Frequently Asked Questions
Can I use this exact topic for my own FYP?
You can use it as a structural model, but choose your own topic, variables and theoretical framework in consultation with your supervisor — this example is illustrative, not a template meant to be reused as a real study.
Do all psychology FYPs need a quantitative correlational design?
No — qualitative, experimental and mixed-methods designs are all used in psychology FYPs depending on the research question; a correlational design fits this particular example because the question asks about a relationship between two measured variables.
What if my correlation isn’t statistically significant?
A non-significant result is still a legitimate finding — report it honestly, discuss possible reasons (sample size, measurement, a genuinely weak relationship), and avoid the temptation to selectively report only significant sub-analyses.
Do I need a validated scale for every variable in my study?
Use a validated scale wherever one exists and fits your construct and population; where none fits precisely, researcher-adapted items are acceptable if clearly labelled as such and, ideally, piloted before full data collection.
How long should each chapter be in a psychology FYP?
Length varies by faculty and topic depth rather than a fixed universal split — check your own faculty’s handbook, and prioritise a complete, well-connected chain over hitting a specific page count per chapter.
Can my theoretical framework use more than one theory?
Yes, if genuinely relevant — some psychology FYPs integrate two complementary theories (for example, a social-comparison mechanism alongside a self-determination or attachment framework), provided each is explicitly connected to the variables, not simply listed side by side.
What’s the difference between my conceptual framework and my theoretical framework?
The theoretical framework is the established theory you are borrowing (Social Comparison Theory, in this example); the conceptual framework is your own diagram mapping your specific variables into that theory’s logic.
Should I mention the theory by name in my discussion chapter?
Yes — naming it explicitly when explaining your findings shows the examiner your discussion is grounded in the framework you set up in Chapter 2, rather than a generic commentary disconnected from your literature review.
How do I choose between a correlational and an experimental design for a similar topic?
Choose experimental only if you can actually manipulate a variable (for example, randomly assigning participants to different social media exposure conditions) within the ethical and practical constraints of an undergraduate FYP; most naturally occurring behaviour like existing social media habits is studied correlationally instead.
Tesify can help you turn a structure like this into a fully drafted chapter set for your own approved topic — you remain responsible for every claim, statistic and citation it produces. Draft your FYP chapters with Tesify.
For validated instruments with a published Bahasa Malaysia version, including the Rosenberg Self-Esteem Scale used in this example, see validated Malay-language scales for a psychology FYP. For the difference between the two frameworks this example builds, see what is the difference between a theoretical framework and a conceptual framework. For choosing the right test for your own results chapter, see which statistical test should you use for your FYP data. For sample-size reasoning behind Chapter 3’s population and sampling section, see how many respondents you need for your FYP or thesis. For a comparable full worked example in a different field, see how to build a complete sample FYP for computer science in Malaysia.