HE-C03 — Pedagogy and Active Learning

Course Code: HE-C03  |  School: School of Higher Education  |  Cluster: Level 2 — Curriculum and Teaching Practice

Level: Intermediate  |  Duration: 6 weeks · 24–30 learning hours  |  Language: English  |  Certificate: Professional Certificate (non-degree)  |  Format: Self-paced with AI support under human supervision

Overview

The lecture survives not because it is the best way to produce learning but because it is the cheapest way to allocate a room, a timetable slot and one member of staff. The research comparing active methods with continuous exposition is among the more consistent bodies of evidence in education, and it has been available for decades without substantially changing practice.

This course is about closing that gap in a specific setting. It examines what active learning actually requires — preparation, task design, in-room management, and a change in what students believe they are there to do — and it takes seriously the reasons the shift so often fails: large cohorts, unsuitable rooms, staff workload, student resistance, and assessment that continues to reward passive study.

The course is practical and cumulative. Each module produces a component of a redesigned course: pre-class preparation with accountability, in-session tasks with defined roles and outputs, questioning and discussion technique, group structures that avoid free-riding, and an evaluation design that tests whether the change worked. It is written for real constraints, including cohorts of several hundred in fixed tiered lecture theatres.

Learning outcomes

On completion, a successful learner will be able to:

1. Summarise the evidence comparing active and expository methods, including its limits, and explain why guidance remains necessary within active designs.
2. Design pre-session preparation with accountability mechanisms that make in-session activity possible.
3. Construct in-session tasks with clear roles, time limits, visible outputs and a defined mechanism for closing the loop.
4. Apply questioning, discussion and peer instruction techniques that generate participation from more than the confident minority.
5. Design group work that distributes effort, assesses individual contribution, and manages conflict and free-riding.
6. Adapt active methods to constraints of cohort size, room configuration, delivery mode and staff capacity.
7. Evaluate the effect of a pedagogical change with an appropriate design and report the result honestly, including null and negative findings.

Who this course is for

The course serves lecturers and tutors across disciplines, teaching-focused academics, doctoral candidates with teaching duties, academic developers, and programme leaders responsible for teaching quality. It is particularly useful for those teaching large first-year cohorts, where the perceived barriers are highest.

Prerequisites

Completion of HE-F03 or equivalent teaching experience, and current responsibility for at least one taught session series, since every deliverable is applied to a real course.

Syllabus

Module 1 — The evidence and its limits

The module reviews what the comparative research shows and what it does not. Active designs outperform continuous exposition on measured learning and reduce failure rates, but the literature also establishes that minimally guided discovery is inferior to guided instruction. The module resolves the apparent tension: activity must be structured, and guidance must be present within it.

Lessons. 1.1 The comparative evidence base. 1.2 Why minimal guidance fails. 1.3 Structured activity with embedded guidance. 1.4 Reading effect sizes with appropriate scepticism.

Deliverable. Diagnostic note (800 words) auditing one session series against the evidence.

Module 2 — Preparation and accountability

Active sessions fail when students arrive unprepared. This module covers the design of pre-session material of realistic length, low-stakes accountability that is checked rather than assumed, just-in-time adjustment based on what preparation reveals, and the honest management of the workload transfer that flipped designs involve.

Lessons. 2.1 Designing preparation that is actually done. 2.2 Low-stakes accountability mechanisms. 2.3 Just-in-time teaching from preparation data. 2.4 Workload transfer and student consent.

Deliverable. Analytical brief (1,000 words) designing a preparation and accountability system.

Module 3 — In-session task design

The module builds the core of the redesign: tasks with unambiguous instructions, defined roles, hard time limits, visible outputs and a closing mechanism in which the task’s purpose is made explicit. It covers concept tests, think–pair–share, structured problem solving, case analysis, and the choreography of moving a large room through an activity.

Lessons. 3.1 Anatomy of a good in-session task. 3.2 Concept tests and peer instruction. 3.3 Case and problem sequences. 3.4 Choreography in a large room.

Deliverable. Design artefact: a full session plan with tasks, timings, roles and outputs.

Module 4 — Questioning, discussion and participation

This module addresses the social dynamics of the room. It covers question design beyond recall, wait time, cold calling done supportively, the distribution of participation across gender, language background and confidence, and techniques for surfacing disagreement productively rather than allowing consensus to form prematurely.

Lessons. 4.1 Question design and cognitive level. 4.2 Wait time and thinking space. 4.3 Distributing participation equitably. 4.4 Managing disagreement and error publicly.

Deliverable. Evaluation report (1,000 words) analysing participation patterns in one session.

Module 5 — Group work that works

The module treats group learning as a design problem. It covers group formation and size, role allocation and rotation, interdependence structures that make free-riding difficult, assessment of individual contribution within a group product, peer evaluation instruments, and procedures for conflict and non-participation.

Lessons. 5.1 Formation, size and interdependence. 5.2 Roles and rotation. 5.3 Assessing individual contribution. 5.4 Conflict, free-riding and remedy.

Deliverable. Implementation plan (1,000 words) for a group-based component with assessment rules.

Module 6 — Constraints, resistance and evaluation

The final module deals with reality. It covers adaptation to fixed tiered rooms and very large cohorts, online and blended variants, staff workload and sustainability, student resistance and how to address it through explanation and early evidence, and the design of a small evaluation capable of producing an honest answer.

Lessons. 6.1 Adapting to hostile rooms and large cohorts. 6.2 Online and blended variants. 6.3 Student resistance and its management. 6.4 Designing an honest evaluation.

Deliverable. Final capstone: redesigned course with evaluation design and reflective report (3,000 words).

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. Evidence-based design. Whether choices are justified by cited research and whether the learner distinguishes structured active learning from unguided discovery.
2. Task craftsmanship. Whether in-session tasks have clear instructions, roles, timings, outputs and closure, and would function without the designer present.
3. Equity of participation. Whether the design accounts for who speaks and who does not, and includes concrete mechanisms to broaden participation.
4. Evaluation honesty. Whether the evaluation could have produced a negative result, and whether findings are reported without overclaiming.

Reading list

Core. Scott Freeman et al., ‘Active Learning Increases Student Performance in Science, Engineering, and Mathematics’, Proceedings of the National Academy of Sciences, 111:23 (2014), pp. 8410–8415.

Eric Mazur, Peer Instruction: A User’s Manual (Upper Saddle River: Prentice Hall, 1997).

Paul A. Kirschner, John Sweller & Richard E. Clark, ‘Why Minimal Guidance During Instruction Does Not Work’, Educational Psychologist, 41:2 (2006), pp. 75–86.

Elizabeth F. Barkley, K. Patricia Cross & Claire Howell Major, Collaborative Learning Techniques, 2nd edition (San Francisco: Jossey-Bass, 2014).

Louis Deslauriers, Logan S. McCarty, Kelly Miller, Kristina Callaghan & Greg Kestin, ‘Measuring Actual Learning versus Feeling of Learning’, Proceedings of the National Academy of Sciences, 116:39 (2019), pp. 19251–19257.

Carl E. Wieman, Improving How Universities Teach Science (Cambridge, MA: Harvard University Press, 2017).

Academic integrity and use of AI

AI tools may be used in this course for locating literature, organising evidence, drafting non-analytical sections and criticising the learner’s own work. They may not be used to generate the analysis, the evaluation or the recommendation. Every submission carries a use-of-AI statement naming the tools used and the purpose of each use.

All citations must be verified against the primary source, and institutional facts — regulations, standards, accreditation criteria, published data — must be cited to the issuing body. Fabricated references and invented statistics result in failure and referral. Where learners write about their own institution they must not disclose confidential personnel or student data, and illustrative cases must be anonymised.