1. Page purpose and target users

The purpose of this page is to help BUET EEE faculty design defensible assessment evidence for Course Outcomes (COs) and Program Outcomes (POs), while respecting the department’s established theory-course assessment structure. The guide is public-facing so that students and stakeholders can understand how learning is assessed, but the templates and tools are designed for faculty preparing course outlines, question papers, rubrics, course files, and accreditation evidence.

2. Research summary: assessment and rubrics in OBE

Key findings from accreditation and engineering-education sources

Why rubrics are needed for selected POs

Routine written problems can assess engineering knowledge and some problem analysis outcomes, but they are often insufficient for design, investigation, ethics, teamwork, communication, and contextual considerations. Rubrics allow assessors to record the quality of design choices, evidence-based interpretation, safe practice, responsible conduct, individual contribution, and communication quality. A rubric does not automatically prove PO attainment; it provides structured evidence that can feed the department-approved attainment process.

3. BUET EEE assessment context

EEE 303-like theory courses

For BUET EEE theory courses, the assessment structure is fixed and should not be changed by this guideline. Faculty should instead align the fixed components with COs, Bloom levels, question tags, evidence collection, and attainment-support tables.

EEE 304-like laboratory/sessional courses

Laboratory and sessional courses have more flexible assessment instruments. An EEE 304-like Digital Systems Laboratory can assess practical skill, Verilog/FPGA implementation, tool usage, debugging, project design, technical documentation, ethics, teamwork, communication, and contextual considerations through a combination of lab performance, reports, practical tests, quiz, project proposal, progress review, demonstration, viva, peer evaluation, and final report/user manual.

4. Recommended page structure

5. BUET EEE theory-course assessment guideline

The fixed 10% + 20% + 70% structure should be treated as the assessment frame. OBE work is done inside this frame by making the assessment traceable: each selected question/sub-question should identify the CO, PO, Bloom level, marks, assessment type, and whether it is used as direct CO evidence.

Recommended workflow

1. Write 3–5 measurable COs with Bloom levels appropriate to the course.
2. Prepare a CO-wise assessment coverage plan across four class tests and final examination.
3. Use class tests to sample early and mid-course COs and provide feedback.
4. Design Section A and Section B compulsory questions to cover the most important direct CO evidence.
5. Tag every relevant sub-question with CO, PO, Bloom level, marks, and direct evidence status.
6. Prepare marking schemes or solution rubrics for compulsory questions.
7. Extract CO-wise marks after evaluation and preserve the evidence trail.

Example CO set for an EEE 303-like course

Sample class test blueprint

Sample final examination Section A/B CO assessment plan

6. Compulsory-question guideline for term final examination

Compulsory questions in Section A and Section B are useful for OBE because all students answer them; therefore, they provide a common direct evidence base for CO assessment. Their design must be intentional and documented.

Warnings for final-exam mapping

• Do not claim CO3/design attainment from a purely numerical substitution problem.
• Do not map PO3/design unless the question requires design choices, constraints, synthesis, or justification.
• Do not map PO4/investigation unless data analysis, experiment interpretation, uncertainty, or evidence-based inference is assessed.
• Do not map PO5/modern tool usage unless actual tool use or tool-based interpretation is assessed.

7. Laboratory/sessional-course assessment guideline

An EEE 304-like course can use experiments in the first part and a design project in the second part. The assessment plan should combine group performance with individual accountability. Group artifacts may demonstrate system-level achievement, but individual viva, peer evaluation, logbooks, and contribution records are needed to support individual CO attainment.

8. Rubric design principles

A rubric is a scoring guide that defines assessment criteria, performance levels, descriptors, and weights. For complex outcomes, an analytic rubric is usually preferable because it separates dimensions such as technical correctness, design justification, safety, teamwork, and communication.

Recommended 4-level scale

Descriptors should avoid vague labels such as “good,” “average,” and “poor” unless they are explained by observable evidence. Rubric scores may be converted to marks by multiplying the level score by criterion weight. The resulting marks can support CO attainment only when the criterion is explicitly mapped to the relevant CO.

9. Sample assessment templates

10. Rubric library

The following rubrics are ready-to-adapt. Weights are suggested values and may be modified by the course teacher if the department/course committee approves the assessment plan. Keep criterion-to-CO mapping explicit.

11. Interactive tools

All tools run fully offline in the browser. No data is sent to a server. Tables generated here are support tools; official attainment calculation should follow approved department policy.

Generate a rubric to preview Markdown.

12. JavaScript data model

The editable JavaScript data are stored in the appData object near the top of the script. Faculty can update POs, Bloom levels, rubric criteria, evidence types, warning rules, sample question plans, and checklist items without changing the user interface logic.

const appData = {
  theoryFixed: { classParticipation: 10, classTestsTotal: 20, classTests: 4, finalExam: 70 },
  bloomLevels: ["C1 Remember", "C2 Understand", "C3 Apply", "C4 Analyze", "C5 Evaluate", "C6 Create"],
  pos: ["PO(a) Engineering Knowledge", "PO(b) Problem Analysis", "PO(c) Design/Development", ...],
  rubricTemplates: { "lab performance": [["Preparedness",10], ...] },
  evidenceTypes: ["Final compulsory question", "Class test", "Lab report", "Project demonstration", ...],
  checklist: ["Course outline", "CO-assessment mapping", ...]
};

13. Common mistakes and corrective actions

14. References and source notes

The following sources should be cited or consulted when finalizing the page. Verify document versions before publication.

1. Board of Accreditation for Engineering and Technical Education (BAETE), accreditation manuals and OBE-related documents: https://www.baetebangladesh.org/
2. International Engineering Alliance, Graduate Attributes and Professional Competencies: https://www.ieagreements.org/
3. ABET, Criteria for Accrediting Engineering Programs and assessment resources: https://www.abet.org/accreditation/
4. Anderson, L. W. and Krathwohl, D. R. (eds.), A Taxonomy for Learning, Teaching, and Assessing, revised Bloom’s taxonomy.
5. Biggs, J., constructive alignment in university teaching and assessment.
6. Brookhart, S. M., rubric design and assessment validity.
7. BUET undergraduate academic rules and regulations, as applicable to term final, class tests, and course assessment.
8. Department of EEE, BUET, local course outlines for EEE 303 Digital Systems and EEE 304 Digital Systems Laboratory.

15. Integration notes for Grav