Državna Matura Geography common mistakes
Državna Matura Geography · Understand the traps and how to avoid them.
When asked to explain a process (e.g. karst formation, föhn effect, soil profile development), the candidate names the landform or phenomenon and stops, without stating the sequence of causes and mechanisms.
The candidate memorised labels from the textbook and recognises the term, but never practised producing the causal chain. Under time pressure, naming feels like a complete answer, so the mechanism is skipped and the point for explanation is lost.
What to do instead
Before writing, force a three-step skeleton: trigger/input, intermediate process, resulting form. Practise on ten standard processes (chemical weathering of limestone, orographic precipitation, lateral erosion and meander migration, podzolisation, urbanisation of a settlement) and write each in 3–4 linked sentences using causal connectives. Check every answer contains at least one 'because' or 'which leads to' link.
The candidate reads a climograph or a hyetograph and reports only the total or the maximum, ignoring the axis units, the seasonal distribution and the derived classification (climate type, regime).
Graph-reading is treated as describing what is visible rather than interpreting it. Candidates also misread scales (mm vs °C, monthly vs annual) because they skim the axes and jump straight to the curve shape.
What to do instead
Adopt a fixed reading protocol: identify both axes and units, note the highest and lowest month, compute annual range and total, then state the hemisphere and climate type with a justification. Practise on at least eight climographs from different continents and write the classification plus two reasons each time.
In population questions the candidate confuses rates with absolute numbers and confuses natural increase with total population change, so a country with high emigration is described as having high natural increase, or a birth rate is quoted as a count of births.
The vocabulary (natalitet, mortalitet, prirodni prirast, migracijski saldo) is learned as synonyms rather than as distinct measures. The candidate also carries over everyday usage where 'growth' means any change.
What to do instead
Build a one-page formula sheet: natural increase = births − deaths; total change = natural increase + net migration; rates are per 1,000 inhabitants per year. Then solve five short numerical tasks where migration and natural change have opposite signs, and always state which component dominates and why.
When classifying a settlement or an economic activity, the candidate gives a single trait (e.g. 'it has a factory, so it is industrial') instead of applying functional, demographic and morphological criteria together, and does not distinguish a town's function from its size.
Classification schemes are memorised as lists of types rather than as sets of criteria. The candidate answers the question 'what is it?' instead of 'by which criteria is it classified?' and so misses the multi-criterion marking scheme.
What to do instead
For each classification, write the criteria first (population size, share of active population by sector, density, layout, centrality) and only then assign the type. Practise with three Croatian settlements of different size and three world cities, justifying each label with two criteria and one counter-argument.
In regional geography the candidate locates a country or feature on the wrong continent or in the wrong macroregion, or answers a question about one country with generic facts that apply to the whole region.
Regional knowledge is stored as loose associations from news and maps rather than as a structured mental map. Candidates also over-generalise because regional summaries in revision materials list common traits, and the candidate cannot retrieve the country-specific exception.
What to do instead
Maintain a blank outline map and place each studied country with three unique facts (a landform, an economic speciality, a demographic feature). Weekly, do a locate-and-name drill: mark 20 countries and 20 physical features from memory, then check. For each macroregion, list one country that contradicts the regional stereotype and why.
In Croatian geography the candidate swaps macroregional names and attributes (e.g. assigns karst and Mediterranean crops to a continental region, or places a river or mountain in the wrong region), and gives no locational evidence.
Croatian regions are learned as lists of counties and towns without a spatial frame, so relief, climate and economic traits get attached to the wrong region. The candidate also relies on vague memory of the home region and generalises it to the whole country.
What to do instead
Draw Croatia from memory three times: relief units, drainage basins, and macroregions, labelling each. For every macroregion write a five-line profile: relief, climate, dominant soils, main economic activities, one development problem. Anchor facts to a map location rather than to a list.
On topographic and thematic maps the candidate ignores scale and contour interval, misreads gradient direction, and confuses the map legend symbols, so slope, distance and relief are all estimated wrongly.
Map work is treated as picture-reading. Candidates do not convert scale to real distance and do not check the contour interval before judging steepness, and they read the legend only after answering.
What to do instead
Practise a fixed routine on every map: read scale, contour interval and legend first; compute one real distance from a measured length; determine slope aspect from contour values; identify the steepest segment by contour spacing. Do ten exercises with a ruler and write the calculation, not just the answer.
In GIS and remote-sensing questions the candidate confuses raster with vector data, mixes up resolution types (spatial, spectral, temporal, radiometric), and describes a layer or a satellite image as if it were an analysis.
The concepts are learned as vocabulary pairs without any hands-on operation, so the candidate cannot connect a data model to what it can and cannot represent, and treats any digital map as GIS.
What to do instead
Learn four contrast pairs with one concrete example each: raster vs vector, spatial vs spectral resolution, passive vs active sensors, overlay vs buffer. Then take one real task (finding a landfill site) and list the layers, the data model for each, and the operations in order.
When interpreting fieldwork data or a table, the candidate describes the numbers ('the value rose from 12 to 18') without computing the change, comparing areas, or linking the pattern to a geographical cause, and ignores units and sample size.
Candidates believe a correct reading of the table is the answer, and they lack practice in converting data into a geographical statement. Fear of arithmetic and unclear units reinforce purely descriptive answers.
What to do instead
Use a three-sentence template for every data set: state the pattern with a computed figure (percentage change, ratio, rank), identify the anomaly or exception, and propose one geographical explanation with a check on data reliability. Apply it to five tables and five field-measurement sets.
On environment and sustainable-development questions the candidate gives a moral verdict ('pollution is bad', 'we must recycle') instead of naming the mechanism, the spatial scale and a concrete measure with its trade-off.
These topics invite opinion, and candidates substitute attitude for analysis because they have not learned the causal chains (eutrophication, greenhouse effect, land degradation) or the difference between mitigation and adaptation.
What to do instead
For each issue, write a four-part card: cause, mechanism, scale of impact (local to global), and one measure classified as prevention, mitigation or adaptation, with one limitation. Practise distinguishing mitigation from adaptation on ten real examples before the exam.