Question at position 4 You are modelling a university timetable system where you need to answer questions such as 'which students are in the same classes as this student?' and 'how are students connected through shared courses over time'. Which structure is likely to be more flexible for this analysis and why?A network structure, because nodes (students, courses) and edges (enrolments) can be walked to explore complex relationshipsA flat file, because all records are stored in one table and are easy to scanNo structure is needed; normalisation alone is sufficientAn ER structure, because it never requires joins and automatically handles many-to-many relationshipsClear my selection单项选择题
A
A network structure, because nodes (students, courses) and edges (enrolments) can be walked to explore complex relationships
B
A flat file, because all records are stored in one table and are easy to scan
C
No structure is needed; normalisation alone is sufficient
D
An ER structure, because it never requires joins and automatically handles many-to-many relationships

Question

Question at position 4 You are modelling a university timetable system where you need to answer questions such as 'which students are in the same classes as this student?' and 'how are students connected through shared courses over time'. Which structure is likely to be more flexible for this analysis and why?A network structure, because nodes (students, courses) and edges (enrolments) can be walked to explore complex relationshipsA flat file, because all records are stored in one table and are easy to scanNo structure is needed; normalisation alone is sufficientAn ER structure, because it never requires joins and automatically handles many-to-many relationshipsClear my selection单项选择题

A

A network structure, because nodes (students, courses) and edges (enrolments) can be walked to explore complex relationships

B

A flat file, because all records are stored in one table and are easy to scan

C

No structure is needed; normalisation alone is sufficient

D

An ER structure, because it never requires joins and automatically handles many-to-many relationships

BlackTom AI · Accepted Answer

Graph (network) structures model entities as nodes and relationships as edges, so nodes = students/courses and edges = enrolments (with properties like term, grade, timestamp). This makes traversals (walks) natural: you can follow edges to find classmates, chains of co-enrolment, connected components, or shortest paths between students.

Relevant knowledge points and concepts
- Nodes/edges: nodes represent entities, edges represent relationships and can carry attributes (e.g., semester).
- Traversal algorithms: BFS/DFS, shortest path, connected components, reachability — efficient on graph structures.
- Temporal/attributed graphs: edges can be filtered by time to show connections "over time."
- Relational/flat structures: require joins or recursive SQL (CTEs) for multi-step relationship queries and are less efficient for deep traversals.

Step-by-step reasoning for the sample queries
1. “Which students are in the same classes as student X?”  
   - Find node X. Traverse enrolment edges to reach course nodes. From each course node, traverse enrolment edges to all other student nodes. Remove X and deduplicate results. This is a two-hop traversal (student → course → student).
2. “How are students connected through shared courses over time?”  
   - Use enrolment edges annotated with term/year; traverse paths of any length connecting students via courses, optionally filtering edges by time to examine evolving connections. Graph algorithms can compute components or shortest co-enrolment chain.

Why the network answer is correct
- Graphs directly encode the relationship structure so these multi-hop, relationship-centric queries are expressed and executed naturally and efficiently.

Why the other options are incorrect
- Flat file: storing everything in one table makes multi-hop queries expensive and cumbersome to compute (full scans, complex filtering), and it doesn’t model relationships naturally.  
- “No structure; normalisation alone”: Normalisation helps relational integrity but doesn’t make relationship traversals or temporal path queries efficient.  
- “ER structure, because it never requires joins...”: ER is a design model; relational implementations still require joins and are not optimized for deep relationship traversals. The claim “never requires joins” is false.

Conclusion
A network structure, because nodes (students, courses) and edges (enrolments) can be walked to explore complex relationships, is the most flexible choice — matching the provided correct answer.

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