For information and reference only – not to be submitted as your own work.
This ABS103 ECA video sample shows how an “A Day in the Life of a(n) ___” project can separate crystallised from fluid intelligence without turning into a lecture. It is written against the live ABS103 ECA question page, and the planning logic is explained in our ABS103 video planning guide. If you are working on other SUSS coursework, our SUSS assignment help page lists what we support.
What this sample covers
The ECA has two parts: a video of 4:30 to 5:00 (80 marks) and a reflection of up to 300 words (20 marks). The video must show everyday situations that illustrate crystallised and fluid intelligence, explain how each arises, connect them to your own experience and end with takeaways. You must appear on camera at least at the start, and the narration should sound natural, not like a read-out lecture.
This extract gives you four things: a scene-by-scene storyboard with timings, narration for three scenes, wording for the takeaways screen and a model reflection. The persona, a fictional hawker stall assistant called “the stallholder”, is an illustration. Your own video must use your own day, your own people and your own examples.
Theory the video must get right
Cattell (1963) proposed that general ability has two broad forms. Fluid intelligence (Gf) is the capacity to reason and solve problems that are new to you, when past knowledge does not hand you the answer. Crystallised intelligence (Gc) is the store of knowledge and skill built up through education, culture and experience, such as vocabulary, procedures and facts. Horn and Cattell (1967) then compared age groups and found that the two abilities do not follow the same path across adulthood.
Current evidence supports the broad pattern. Salthouse (2012) describes a steady decrease with age on measures of reasoning and other processing abilities, but stability followed by later decline on measures of acquired knowledge, with knowledge measures typically increasing until about age 60. Salthouse also warns that most of this evidence is cross-sectional, so it shows differences between age groups rather than proving decline in any one person. A good video mentions this caveat in a single sentence. It stops you from claiming that “older people get worse at everything”.
| Feature | Crystallised intelligence (Gc) | Fluid intelligence (Gf) |
|---|---|---|
| Core idea | Knowledge and skills already learned | Reasoning with unfamiliar problems |
| How it develops | Schooling, culture, repeated practice | Ability to hold, manipulate and relate new information |
| Everyday cue | “I know this from before” | “I have never seen this, so I must work it out” |
| Age pattern (Salthouse, 2012) | Rises into later adulthood, then gradually declines | Declines steadily across adulthood in group comparisons |
Video plan and storyboard (model extract)
The table below fits the 4:30 to 5:00 window, with a running time of 4:50. The timings are planning figures, so check yours against your final edit before you export the MP4.
| Scene | Time | What the viewer sees | Purpose |
|---|---|---|---|
| 1. Hook | 0:00–0:25 | You on camera at the stall counter, introducing the day and the two intelligences | Meets the “student appears at the start” rule; states the aim |
| 2. Morning prep | 0:25–1:00 | Prepping ingredients, recalling regulars’ orders, greeting customers in the right dialect | Gc in action |
| 3. How Gc forms | 1:00–1:35 | Photo of a family recipe, short flashback to learning it | Explains origin; links to your own experience |
| 4. Lunch rush | 1:35–2:15 | Payment terminal fails, a customer asks for an unusual order, queue must be rearranged | Gf in action |
| 5. How Gf works | 2:15–2:50 | You at the table sketching the queue problem; a quick puzzle or new app on screen | Explains novel reasoning and working memory |
| 6. Both together | 2:50–3:30 | A delivery app update: you use past app habits (Gc) to spot a pattern, then test a new workflow (Gf) | Shows the two cooperating |
| 7. Across ages | 3:30–4:05 | Conversation with an older relative about recipes and with a younger cousin about the app | Age trends, with the cross-sectional caveat |
| 8. Takeaways | 4:05–4:35 | Three on-screen points with you speaking over footage | Clear message |
| 9. Sign-off | 4:35–4:50 | You on camera again, closing line | Cohesive ending |
Notice what the plan avoids. There are no narrated slides, and every explanation sits next to something the viewer can see happening. That is the line the brief draws between a “day in the life” video and a recorded lecture.
Narration script extract (three scenes)
Scripts should sound spoken. Short sentences, contractions and the odd pause work better than textbook phrasing. Read each aloud while timing it: at a natural pace you will manage roughly 130 to 150 words a minute (an illustrative planning figure), so a 35-second scene holds about 75 to 85 words.
Scene 2: Morning prep (Gc)
“It is six in the morning and I am already on autopilot. I know which stock goes in first, how long the broth needs and what Uncle Tan always orders before he says it. None of that is reasoning from scratch. It is knowledge I have stored from years of watching, doing and being corrected. Psychologists call this crystallised intelligence: facts, skills and language built up through experience and culture. Notice that it is quick and feels effortless.”
Scene 4: Lunch rush (Gf)
“Now the card terminal freezes. Twelve people are queuing, one wants a custom order I have never made, and the stall next door is out of change. There is no routine for this. I have to hold the queue in mind, test options and drop the ones that fail. That is fluid intelligence: reasoning about something new, with no memorised answer to lean on. It feels slower and more tiring, because I am actually working it out.”
Scene 7: Across ages (both)
“My grandmother can still tell if a broth is wrong by smell alone, yet she asks me to set up her phone. My cousin does the opposite. Research comparing age groups, such as Horn and Cattell’s early work and Salthouse’s review, finds that knowledge tends to keep growing into later adulthood while novel reasoning tends to be lower in older groups. That does not mean every person declines in the same way. These are group patterns, not a prediction for my grandmother.”
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Takeaways screen (model wording)
- Gc is what you know. It is built through learning and experience, and it helps with familiar tasks.
- Gf is how you work it out. It is used when the problem is new and memory cannot supply the answer.
- Daily life uses both. Strong Gc often makes new problems easier, because you can recognise parts of them.
Keep takeaways to three short lines. If a viewer cannot repeat them back after one watch, they are too long.
Model reflection (illustration of structure, not to be copied)
Part 2 asks for up to 300 words on one key learning point, covering your feelings and thoughts, the good and bad of the experience, what you learned and what you would do differently. The extract below follows the stages of Gibbs’s (1988) reflective cycle in that order. It is written for the fictional stallholder persona, so it is not your voice. Markers want your own words and your own experience, and your reflection should say things only you could say.
Before filming, I assumed I would be good at showing crystallised intelligence and struggle with fluid intelligence. I felt confident writing about recipes and regular customers, and nervous about staging a problem that needed new reasoning. When I tried to film the payment-terminal scene, I realised I could not fake it. I knew the outcome, so my reasoning on screen looked rehearsed.
The good part was how clearly the contrast appeared once I stopped acting. I changed the scene so I faced a task I had not done before: moving the queue around an unexpected order. My hesitation was real, and it showed what fluid intelligence feels like: slower, more effortful and less sure. The bad part was time. Two takes failed, and my first script sounded like a textbook.
My key learning point is that the two intelligences are easiest to see when I compare how a task feels. Familiar tasks feel automatic, while new ones demand effort. I also learned that relying on knowledge can hide a gap in flexible thinking, because familiar routines quietly solve problems for me.
Next time, I would plan one genuinely unfamiliar task in advance and film it first, before I know how it ends. I would also write bullet points instead of a full script, so the narration sounds like my own voice. This project made me notice how often I use stored knowledge without realising it, and I now pause when something feels automatic to ask whether I am recalling or reasoning.
The model reflection above is about 250 words. Count yours with your word processor, and leave a margin under 300.
Further help
If you want a second pair of eyes on a storyboard or a reflection draft, see our ECA assignment help and reflective essay writing help pages. You remain responsible for your own video, your own reflection and the GenAI rules in your course guide, which allow brainstorming with disclosure but expect the reflection in your own voice.
About the expert
According to his profile, Torrence Aung holds a PhD in Psychology from TCA College in Singapore and writes on psychology subjects including general, cognitive and experimental psychology.
References
Cattell, R. B. (1963). Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology, 54(1), 1–22. https://doi.org/10.1037/h0046743
Gibbs, G. (1988). Learning by doing: A guide to teaching and learning methods. Further Education Unit.
Horn, J. L., & Cattell, R. B. (1967). Age differences in fluid and crystallized intelligence. Acta Psychologica, 26(2), 107–129. https://doi.org/10.1016/0001-6918(67)90011-X
Salthouse, T. A. (2012). Consequences of age-related cognitive declines. Annual Review of Psychology, 63, 201–226. https://doi.org/10.1146/annurev-psych-120710-100328
