19-Soft-B2 User Interface · May 2015
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
National Exams, May 2015 — 04-Soft-B2, User Interface (closed book, 3 hours). Part A: answer any FIVE of the NINE questions (10 marks each); Part B: answer ALL FIVE questions (10 marks each), all based on the same case study — Happy Medical Clinic, a Toronto medical clinic switching from paper-based practice to an electronic health record (EHR) system purchased from VisualEHR Inc., an off-the-shelf vendor willing to customize the product to the clinic's needs. Most questions call for essay-format answers; clarity and organisation count. This solution answers all fourteen questions as a full study resource.
Reference texts. Rogers, Sharp & Preece, Interaction Design: Beyond Human-Computer Interaction, 5th ed., Ch. 1–3 (interaction design, cognitive aspects, mental models), Ch. 9–10 (prototyping, personas), Ch. 11–12 (data gathering, requirements), Ch. 15–16 (evaluation, lab vs. field studies); Nielsen, Usability Engineering, Ch. 4–6 (usability heuristics, iterative design, usability testing); Shneiderman, Designing the User Interface, 6th ed., Ch. 2 (guidelines, principles), Ch. 12 (internationalization); Norman, The Design of Everyday Things, Ch. 1–4 (visibility, affordances, feedback, conceptual models).
Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.
Part A — mental models. A mental model is the internal, simplified representation a person builds and carries in their head of how a system works — what it does, why it behaves as it does, and what will happen if they take a given action — built from experience, instruction and analogy rather than from the system's actual internal logic. Mental models matter to UI design because users act on their mental model of the system, not on how it actually works internally: if the interface's behaviour matches what the user's mental model predicts, the system feels predictable and learnable; if it diverges, the user makes errors and reinforces an inaccurate model that causes further errors (e.g. a clinic receptionist who believes closing an appointment window without clicking "Save" still records a booked slot will lose real appointments without realising it). Relationship to information processing: a mental model is the structure that organises how incoming information from the interface is perceived, interpreted and remembered — it acts as a filter and interpretive frame at every stage of information processing (attention, perception, working memory, long-term memory), so two users with different mental models of the same EHR screen will attend to different elements, interpret the same message differently, and recall the interaction differently afterward.
Part B — recognition over recall. Recognition (identifying a correct item when it is presented, e.g. picking a medication name from a displayed list) draws on long-term memory's strong associative matching and needs only a low-effort "have I seen this / does this look right" judgement. Recall (retrieving an item from memory with no cue present, e.g. typing a diagnosis code from memory) requires actively reconstructing the information with no external support, is far more effortful, and is much more error-prone, especially under time pressure or for infrequently used items. Because working memory is limited and fragile (easily disrupted by an interruption — a phone ringing, a colleague asking a question), an interface that forces recall repeatedly taxes a scarce cognitive resource and produces more transcription and selection errors. Example: in Happy Medical Clinic's EHR, offering a searchable, auto-suggesting dropdown of diagnosis (ICD) codes as the receptionist types — so the correct code is recognised and selected from a shown list — is far safer and faster than requiring staff to recall and type the exact numeric code from memory, which invites keying the wrong code for a similarly-named condition.
