Items where Year is 2025

Spec for D4

Introducing Class, Sequence, Use Case, Activity and State Machine Diagrams

This evidence-based Excel calculator provides comprehensive time and cost estimates for eLearning development projects within higher education and healthcare contexts. The tool generates detailed project costings by incorporating multiple variables, including content duration, platform selection, authoring tool requirements, scenario complexity, assessment specifications, compliance levels, and media production needs. The calculator draws on peer-reviewed research and industry benchmarks (Chapman Alliance, 2010; ATD Research, 2023; Tucker, 2025) to produce realistic development time multipliers for different authoring tools and complexity levels. It automatically calculates platform-specific development hours (ranging from basic platform creation to advanced tools such as Articulate Storyline 360), applies appropriate compliance multipliers for WCAG 2.1 AA, PSBAR, and European Accessibility Act requirements, and generates risk assessments based on project specifications. Key features include automatic platform selection based on target audience (Blackboard Ultra for students, Totara for staff, Course Catalog for external professionals), dynamic cost breakdowns showing development hours and associated costs, scenario-based learning calculations with complexity ratings, and integrated risk assessment with mitigation strategies. The calculator is particularly suited for learning designers, project managers, and academic staff planning eLearning projects who require accurate budget estimates and timeline projections. It includes comprehensive maintenance documentation and lookup tables that can be updated to reflect changing institutional rates and industry standards.

This resource provides a comprehensive framework of 20 scoping questions designed to guide initial discussions between learning designers and subject matter experts (SMEs) when planning eLearning projects, particularly those with clinical or healthcare content. The document systematically addresses critical project planning areas including strategic alignment, stakeholder management, learning design approaches, assessment strategies, accessibility requirements, technical specifications, and resource allocation. It incorporates evidence-based time estimates for different levels of content complexity (basic to advanced) and includes specific cost projections based on development hours. Key features include: Structured questions covering project fundamentals through to risk management Specific guidance on scenario-based learning and branching complexity Compliance and accessibility considerations aligned with WCAG 2.1 AA standards Platform-specific development time estimates (Blackboard Ultra, Articulate Rise 360, Storyline 360) Budget frameworks with realistic hour-per-finished-content ratios Healthcare-specific considerations including clinical accuracy validation and SME involvement timeframes This resource would be particularly valuable for learning designers initiating healthcare or clinically-focused eLearning projects, project managers establishing realistic timelines and budgets, or institutions seeking to standardise their eLearning scoping processes. The framework ensures comprehensive early-stage planning whilst managing scope, compliance requirements, and stakeholder expectations effectively.

Full details to follow

Lab 4 COMP3207 2526

All lectures for week 2 in one file

Slides for COMP1312 Lecture 1.3 - Python basics: Variables, input & output

lab script and worksheet for twilight session, and data pack information

SCDTP UKRI Policy Internship 2024

lab script and worksheet

Revision

preparation for end of module CAA exam

extra material to support lecture 10.1

enums, number, var and ellipsis

Bonus lockdown lectures covering the non GUI material covered on nested classes and lambdas. May be useful if you are unclear on nested classes. Lectures delivered to a programming 2 module at UEA

A couple of videos of old lectures on the topics of Functors and Iterators in Java

overview of Maven and a first JavaFX project

Past exams paper for COMP2214.

Overview of design patterns and detailed look at the Functor, Iterator and Composite pattern

: Apart from what (little) OpenAI may be concealing from us, we all know (roughly) how Large Language Models (LLMs) such as ChatGPT work (their vast text databases, statistics, vector representations, and huge number of parameters, next-word training, etc.). However, none of us can say (hand on heart) that we are not surprised by what ChatGPT has proved to be able to do with these resources. This has even driven some of us to conclude that ChatGPT actually understands. It is not true that it understands. But it is also not true that we understand how it can do what it can do. I will suggest some hunches about benign “biases”—convergent constraints that emerge at the LLM scale that may be helping ChatGPT do so much better than we would have expected. These biases are inherent in the nature of language itself, at the LLM scale, and they are closely linked to what it is that ChatGPT lacks, which is direct sensorimotor grounding to connect its words to their referents and its propositions to their meanings. These convergent biases are related to (1) the parasitism of indirect verbal grounding on direct sensorimotor grounding, (2) the circularity of verbal definition, (3) the “mirroring” of language production and comprehension, (4) iconicity in propositions at LLM scale, (5) computational counterparts of human “categorical perception” in category learning by neural nets, and perhaps also (6) a conjecture by Chomsky about the laws of thought. The exposition will be in the form of a dialogue with ChatGPT-4.

Some examples

MULTI elevator coursework

SEG project specification (only for Biomedical Engineering students)

Inter-thread communication, producer-customer model

Synchronisation

Multi-threading 2

Multi-threading 1

static variables and static methods

Serialisation / Serialization

file i/o, stream, char and byte based

interface, abstract, final, class diagram

Overriding

Super and Sub-classes, class diagram

public, private, getters, setters, class diagram

overloading

primitive VS reference, methods, overloading.

Intro to the module, OOP, Java, if-statement