HE-Q06 — Continuous Quality Improvement

Course Code: HE-Q06  |  School: School of Higher Education  |  Cluster: Quality Assurance

Level: Intermediate  |  Estimated duration: 6 weeks (approximately 40 hours)  |  Language: English  |  Certificate: Professional Certificate (non-degree)  |  Format: Self-paced with AI support under human supervision

Overview

Continuous quality improvement arrived in higher education as an import from manufacturing, carrying Deming’s statistical process control, the Toyota Production System and the plan-do-study-act cycle. The import has a mixed record. Robert Birnbaum’s study of management fads in higher education documents a recurring pattern in which an industrial technique is adopted enthusiastically, applied superficially, declared successful, and abandoned quietly.

This course takes the improvement tradition seriously enough to ask which of its elements actually transfer. The disciplined answer is that its core logic — small tested changes, measurement over time, attention to process variation, and respect for the people doing the work — transfers well, while its assumption of a standardisable production process transfers badly to teaching and research, which are variable by design and by professional right.

Learners run an improvement cycle rather than reading about one. Each learner selects a real process within reach, maps it, identifies waste and variation, designs a small change, measures it over time, and reports honestly on whether it worked. The course is deliberately hostile to improvement theatre: unmeasured claims of success receive no credit.

Learning outcomes

On completion, a successful learner will be able to:

1. Explain the intellectual origins of continuous improvement and evaluate which of its assumptions hold in academic settings.
2. Map an institutional process accurately and identify waste, rework, delay and unnecessary variation within it.
3. Distinguish common-cause from special-cause variation and select responses appropriate to each.
4. Design and execute a plan-do-study-act improvement cycle with defined measures collected over time.
5. Assess critically the record of quality management approaches imported into higher education.
6. Build the conditions for sustained improvement, including frontline ownership and psychological safety.
7. Report improvement results honestly, including negative results, and specify the conditions for spread.

Who this course is for

Professional services managers, registry and admissions leaders, quality officers, department administrators, and academic leaders responsible for the efficiency and reliability of institutional processes. Suitable for anyone who owns a process they believe is broken.

Prerequisites

Access to a real institutional process the learner can observe and, ideally, influence. HE-Q01 Quality Assurance in Higher Education is recommended.

Syllabus

Module 1 — Origins, Claims and the Fad Problem

Improvement methodologies enter higher education with strong claims and weak evidence for transfer. This module establishes the intellectual lineage and reads Birnbaum’s account of the adoption cycle as a warning.

Lessons. 1.1 Deming, statistical process control and the system view  ·  1.2 Lean, Six Sigma and the Toyota inheritance  ·  1.3 Birnbaum on the life cycle of management fads in universities  ·  1.4 What transfers to academic work and what does not

Deliverable. A diagnostic note assessing one improvement methodology’s fit to a named academic or administrative process, with reasons for and against.

Module 2 — Process Mapping and Waste

Most institutional processes have never been drawn end to end, and drawing them typically reveals handoffs, queues and duplicated approvals that no one designed. This module produces the map from observation, not from policy documents.

Lessons. 2.1 Value stream mapping in a service context  ·  2.2 Categories of waste applied to administrative work  ·  2.3 Handoffs, queues, rework loops and approval accumulation  ·  2.4 Mapping the process as performed rather than as documented

Deliverable. An analytical brief presenting an observed process map with quantified delay and rework, contrasted with the documented process.

Module 3 — Variation and Measurement Over Time

Comparing this month with last month is the most common and least informative measurement practice in institutional management. This module replaces it with the discipline of observing a process over time.

Lessons. 3.1 Common-cause and special-cause variation  ·  3.2 Run charts and simple control charts for institutional processes  ·  3.3 Selecting outcome, process and balancing measures  ·  3.4 Why two-point comparisons mislead

Deliverable. A design artefact: a measurement plan with outcome, process and balancing measures and a run chart built from at least twelve observations.

Module 4 — Running the Improvement Cycle

The plan-do-study-act cycle is valuable precisely because it is small, fast and falsifiable. This module runs a real cycle and requires the learner to report what actually happened.

Lessons. 4.1 Designing a change small enough to test quickly  ·  4.2 Predicting the result before testing it  ·  4.3 Studying results, including unintended effects  ·  4.4 Iterating, abandoning or adopting a change

Deliverable. An evaluation report on a completed improvement cycle including the prior prediction, the measured result and an honest verdict.

Module 5 — Sustaining and Spreading Improvement

Improvements decay when the person who made them moves on, and spread fails when a local solution is mandated centrally. This module designs against both failures.

Lessons. 5.1 Standard work, documentation and decay of improvement  ·  5.2 Frontline ownership and the limits of centralised improvement  ·  5.3 Psychological safety and the reporting of failure  ·  5.4 Conditions for spread and the adaptation of local solutions

Deliverable. An implementation plan for sustaining one improvement and specifying the conditions under which it should and should not be spread.

Module 6 — Capstone: A Documented Improvement Project

The capstone reports a complete improvement project on a real process, and is explicitly permitted to report failure. Honest negative results score higher than unevidenced claims of success.

Lessons. 6.1 Framing the problem with baseline data  ·  6.2 Executing and documenting the cycle  ·  6.3 Interpreting results against prediction  ·  6.4 Recommending adoption, adaptation or abandonment

Deliverable. A 2,500-word improvement project report covering process map, baseline measurement, change tested, time-series results and a sustainment or abandonment recommendation.

Assessment

Pass mark 70 per cent. All assessed components must be attempted. Every mark in this course is issued by a human assessor; no assessment outcome is generated automatically.

Rubric criteria

Each assessed artefact is marked against four criteria at four levels (distinction, pass with merit, pass, fail).

1. Measurement discipline. Claims about improvement are supported by data collected over time rather than by two-point comparison.
2. Process fidelity. The process is mapped as actually performed, with evidence of direct observation.
3. Honesty. Negative, null and unintended results are reported plainly.
4. Contextual judgement. Industrial methods are adapted to academic conditions rather than applied mechanically.

Reading list

Core. Deming, W. E. (2000) Out of the Crisis. Cambridge, MA: MIT Press.

• Langley, G. J., Moen, R. D., Nolan, K. M., Nolan, T. W., Norman, C. L. and Provost, L. P. (2009) The Improvement Guide: A Practical Approach to Enhancing Organizational Performance, 2nd edn. San Francisco: Jossey-Bass.
• Birnbaum, R. (2000) Management Fads in Higher Education: Where They Come From, What They Do, Why They Fail. San Francisco: Jossey-Bass.
• Balzer, W. K. (2020) Lean Higher Education: Increasing the Value and Performance of University Processes, 2nd edn. New York: Productivity Press.
• Liker, J. K. (2004) The Toyota Way: 14 Management Principles from the World’s Greatest Manufacturer. New York: McGraw-Hill.
• Senge, P. M. (2006) The Fifth Discipline: The Art and Practice of the Learning Organization, revised edn. New York: Doubleday.

Academic integrity and use of AI

Generative AI may be used in this course as a drafting, translation and critique aid, and its use must be disclosed. Every submission carries a short use-of-AI statement naming the tools used, the tasks they performed and the checks the learner applied to the output. Using AI to fabricate data, invent sources, impersonate an interview participant, or produce an artefact the learner cannot explain in a live viva is prohibited.

All citations are verified before submission; a reference that cannot be located by the assessor is treated as fabricated. Fabrication, plagiarism and undisclosed ghost-authorship result in failure of the component and referral to the academic integrity panel. Marks in this course are issued by human assessors, and any learner may be asked to defend a submission orally before a mark is confirmed.