ITEE IT Passport common mistakes
ITEE IT Passport · Understand the traps and how to avoid them.
Treating 'which is the MOST appropriate' items as simple true/false and picking the first option that is technically a true statement, without comparing it against the other options.
The IT Passport often presents four options that are all factually correct, and only one that best fits the scenario or the stated purpose. Candidates who evaluate each option in isolation stop at the first plausible one and never rank them.
What to do instead
Before choosing, restate the question's goal (cost reduction, security, availability, etc.) and score every option against that goal. Eliminate options that are true but irrelevant to the stated purpose. Practise by writing one line per option explaining why it is or is not the best fit.
Confusing the roles of primary key, foreign key, and unique key, and answering normalization questions by intuition rather than applying the definition of each normal form.
These concepts are taught together and share vocabulary ('key', 'uniqueness', 'dependence'), so candidates blur them under time pressure. Normalization is often memorized as a slogan rather than as a testable condition.
What to do instead
Drill the definitions as decision rules: a primary key uniquely identifies a row and cannot be null; a foreign key references another table's key and may repeat; a unique key enforces uniqueness but is not the row identifier. For normal forms, check functional dependencies step by step (1NF: atomic values; 2NF: no partial dependency on part of a composite key; 3NF: no transitive dependency) rather than guessing.
Mixing up which OSI/TCP-IP layer a device or protocol operates at, and confusing IP address, subnet mask, and default gateway roles when reading a small network scenario.
Devices and protocols are learned as a list rather than mapped to layers, and subnetting arithmetic is avoided because it feels mathematical, so candidates pattern-match on keywords like 'router' or 'switch' without reasoning.
What to do instead
Build a one-page layer table with a representative device and protocol per layer and memorize it as a lookup. For addressing, practise a fixed routine: identify network portion via the mask, then host portion, then gateway. Do several small hand calculations until the mask-to-network mapping is automatic.
Answering security questions by choosing the strongest-sounding control (e.g., encryption everywhere, biometrics) instead of the control that addresses the specific threat described in the scenario.
Candidates equate 'more secure' with 'correct', but exam items test matching a control to a threat (spoofing, tampering, repudiation, information disclosure, denial of service, elevation of privilege) and to the CIA property at risk.
What to do instead
For each scenario, first name the threat and the asset, then the CIA property being harmed, then select the control that directly mitigates that threat. Reject options that protect a different asset or a property not mentioned. Learn the standard control categories (preventive, detective, corrective) and classify each option.
Confusing copyright, patent, trademark, and trade secret protection, and misapplying rules about software licensing and employee inventions in workplace scenarios.
The four intellectual property regimes overlap in everyday language, and candidates rely on colloquial usage ('copyright the name') instead of the legal subject matter each protects.
What to do instead
Memorize a subject-matter table: copyright protects expression (programs, text, images) and arises on creation; patents protect novel technical inventions and require application and examination; trademarks protect signs identifying goods/services; trade secrets protect confidential information kept secret. Then map each scenario's object to the correct regime before reading options.
Treating waterfall and agile as interchangeable and picking 'agile' or 'waterfall' as a default answer without checking whether the scenario emphasizes changing requirements, documentation, or fixed scope.
Agile is fashionable, so candidates assume it is always the 'modern' correct answer, but items test whether the chosen method fits the stated constraints (fixed contract scope, regulatory documentation, frequent requirement change).
What to do instead
Read the scenario for signals: unstable or frequently changing requirements and incremental delivery favor agile; fixed, well-understood requirements and heavy documentation favor waterfall. Note that hybrid approaches exist and are sometimes the intended answer. Practise classifying scenarios by these signals before looking at the options.
Confusing AI, machine learning, deep learning, and rule-based systems, and attributing capabilities such as explainability or guaranteed accuracy to machine learning when the scenario calls for human oversight.
The terms are nested and marketed loosely, so candidates treat them as synonyms. Items often test the limitation (black-box nature, data dependency, bias) rather than the definition.
What to do instead
Learn the nesting explicitly: AI is the broad field, machine learning is a subset that learns from data, deep learning is a subset using multilayer neural networks, and rule-based systems encode explicit logic. Memorize the standard limitations (needs large labelled data, can inherit bias, low explainability) and match them to scenario questions about governance and human review.
Solving computational-thinking items by jumping to a formula or code trace without first restating the problem in plain language and identifying inputs, outputs, and the stopping condition.
Algorithm and pseudocode questions look like math, so candidates start manipulating symbols immediately and lose track of what is being computed, especially with loops and counters.
What to do instead
Adopt a fixed routine: write the inputs, the output, and the loop's termination condition in words, then trace with a small table of variable values for two or three iterations. Check the final iteration explicitly. This converts symbol manipulation into bookkeeping.
Misreading quantitative business items (break-even, ROI, productivity, capacity) by using the wrong base or mixing units, and skipping the unit check at the end.
The arithmetic is simple but the framing is verbal, so candidates pick the formula that 'looks right' and forget whether the answer should be a rate, a total, or a difference. Units (thousands of yen, percent, hours) are easily dropped.
What to do instead
Before calculating, write the target quantity and its unit. Then write the formula in words (e.g., break-even units = fixed costs divided by contribution margin per unit). Compute, then verify the unit and the order of magnitude against the answer choices; a plausible number in the wrong unit is a common trap.
Answering office-tool and information-design items from habit with one specific product's menu behaviour rather than from the general concept being tested (e.g., absolute vs relative references, mail merge data source, aspect ratio, resolution).
Candidates transfer muscle memory from daily use of a particular application, but items test general spreadsheet, document, and media concepts independent of vendor, and habit-driven answers often describe a shortcut rather than the underlying rule.
What to do instead
Study the concepts abstractly: relative vs absolute reference behaviour when copied, the roles of data source and template in mail merge, the relationship between resolution, pixel dimensions, and print size, and the difference between raster and vector graphics. For each item, state the underlying rule before choosing, and ignore which specific product you normally use.