Learning Engineer Training

Lesson 1 • Ethical and Equity Considerations

Addresses bias, accessibility, and learner privacy as non-negotiable design constraints. Establishes ethical reasoning as a foundational professional skill.

Lesson 2 • Systems Thinking in Education

Introduces systems thinking as the lens through which learning engineers analyse problems. Builds the habit of mapping inputs, processes, and outcomes.

Lesson 3 • Theoretical Foundations of Learning Science

Surveys cognitive load theory, constructivism, and behaviourism as applied to engineered learning systems. Connects theory to practical design decisions.

Lesson 1 • Learner Research Methods

Covers surveys, interviews, observations, and artefact analysis for gathering learner data. Produces the evidence base for persona development.

Lesson 2 • Building Learner Personas and Profiles

Synthesises research data into actionable personas that represent target audiences. Personas guide content, tone, and modality decisions throughout design.

Lesson 3 • Stakeholder Alignment and Scoping

Establishes techniques for aligning sponsor expectations with learner realities. Produces a scoped project brief that prevents scope creep.

Lesson 1 • Validating and Refining Objectives

Uses SME review and pilot feedback to stress-test objectives before full development. Prevents costly redesign by catching misalignment early.

Lesson 2 • Taxonomy-Based Objective Writing

Applies cognitive, affective, and psychomotor taxonomies to classify and write objectives. Ensures objectives target the correct depth of learning.

Lesson 3 • Conditions, Performance, and Criteria

Teaches the three-component objective structure: condition, behaviour, and criterion. Produces objectives that are directly assessable and unambiguous.

Lesson 1 • Modular and Reusable Content Design

Designs content as discrete, reusable learning objects that can be recombined across programmes. Reduces long-term maintenance costs and supports personalisation.

Lesson 2 • Content Chunking and Sequencing

Applies cognitive load principles to break content into learnable units and sequence them logically. Reduces extraneous load and supports schema formation.

Lesson 3 • Instructional Design Models in Practice

Compares ADDIE, SAM, and agile design models for different project contexts. Equips practitioners to select and adapt the right model per project.

Lesson 4 • Designing Instructional Strategies

Selects and designs direct instruction, worked examples, problem-based learning, and practice strategies. Matches strategy to objective type and learner profile.

Lesson 1 • Principles of Valid Assessment

Covers validity, reliability, and alignment as the three pillars of sound assessment design. Prevents assessments that measure test-taking skill rather than competence.

Lesson 2 • Item Writing and Review

Teaches best practices for writing multiple-choice, constructed-response, and scenario-based items. Includes bias review and item analysis after pilot testing.

Lesson 3 • Summative and Performance Assessments

Builds end-of-module tests, performance tasks, and simulations that certify competence. Ensures summative tools reflect real-world task demands.

Lesson 4 • Evaluation Frameworks and ROI

Applies multi-level evaluation models to measure learning impact beyond test scores. Connects training outcomes to business results for stakeholder reporting.

Lesson 1 • Learning Standards and Data Interoperability

Explains xAPI, SCORM, and LRS architecture for capturing and exchanging learning data. Enables engineers to specify data requirements during platform selection.

Lesson 2 • Learning Data Sources and Types

Maps the landscape of learner data: completion, interaction, assessment, and behavioural signals. Establishes what data is available and what it can and cannot reveal.

Lesson 3 • Building a Learning Analytics Dashboard

Designs stakeholder-facing dashboards that surface actionable insights from learning data. Balances detail with clarity for different audience types.

Lesson 4 • Predictive Analytics and Early Intervention

Introduces predictive modelling to flag at-risk learners before they fail. Connects predictions to timely instructional interventions.

Lesson 1 • Platform Configuration and Governance

Covers LMS configuration, user roles, content organisation, and governance policies. Ensures platforms remain usable and maintainable over time.

Lesson 2 • Integrating Technology into Learning Design

Aligns technology capabilities with instructional strategies to avoid technology-driven design. Ensures tools serve learning goals rather than dictate them.

Lesson 3 • Technology Needs Analysis

Applies a structured framework to identify functional, technical, and budget requirements before evaluating vendors. Prevents misaligned technology purchases.

Lesson 4 • Learning Technology Ecosystem Overview

Maps the categories of learning technology: LMS, LXP, authoring tools, and performance support. Provides a shared vocabulary for technology decision-making.

Lesson 1 • Establishing a Feedback Collection System

Designs multi-source feedback loops capturing learner, facilitator, and business data continuously. Creates the infrastructure for evidence-based improvement decisions.

Lesson 2 • A/B Testing in Learning Programmes

Applies controlled experimentation to compare instructional design variations and identify what works. Builds a culture of evidence over intuition in design teams.

Lesson 3 • Scaling and Sustaining Learning Programmes

Addresses the organisational, technical, and resource challenges of scaling programmes beyond pilot. Produces a sustainability plan that maintains quality at scale.

Lesson 4 • Strategic Programme Reporting

Translates programme data into executive-level narratives that demonstrate learning's business value. Secures ongoing investment by connecting outcomes to organisational priorities.