Module 3: Model-Based Design

This module delves into Model-based Design in Human-Computer Interaction, focusing on predictive models that analyze user performance and interface usability.

Lecture 1: Introduction

This section introduces Model-based Design in the context of Human-Computer Interaction (HCI), focusing on its concepts, advantages, limitations, and various types of models.

Objective

This section introduces the concept of Model-based Design in Human-Computer Interaction (HCI), highlighting its purpose, benefits, and limitations.

Content

Deconstructing Model-Based Design In Hci

This section delves into Model-based Design in Human-Computer Interaction, focusing on its definitions, objectives, advantages, limitations, and categorization of models.

The Compelling Rationale For Employing Models In Hci

Employing models in Human-Computer Interaction (HCI) enables efficient, early-stage evaluation of user interfaces, optimizing design choices and resource allocation.

Acknowledging The Inherent Limitations Of Model-Based Design

This section discusses the limitations of model-based design in Human-Computer Interaction, stressing the challenges of predicting user behavior.

Categorization Of Models In Hci (Illustrative Overview)

This section categorizes various models used in Human-Computer Interaction (HCI), focusing on their purpose and framework for improving interface design.

Lecture 2: Keystroke-Level Model - I

This section introduces the Keystroke-Level Model (KLM), detailing its operators and the assumptions involved in its application for predicting expert user performance on routine tasks.

Objective

This section articulates the key objectives and foundational concepts of Model-based Design in Human-Computer Interaction (HCI), emphasizing its importance in predicting user performance.

Content

Deep Dive Into The Keystroke-Level Model (Klm)

The Keystroke-Level Model (KLM) is a predictive model for analyzing expert user interaction efficiency in routine tasks within Human-Computer Interaction (HCI).

Exhaustive Definition Of Klm's Fundamental Operators

This section rigorously defines the fundamental operators of the Keystroke-Level Model (KLM), which serves as a crucial tool for analyzing user performance in Human-Computer Interaction.

Core Assumptions And Operational Context Of Klm

This section discusses the fundamental assumptions and operational context guiding the Keystroke-Level Model (KLM) in Human-Computer Interaction, emphasizing its design for expert, error-free tasks.

Initial Workflow For Applying Klm

This section outlines the step-by-step workflow for applying the Keystroke-Level Model (KLM) in evaluating expert user performance in Human-Computer Interaction (HCI).

Lecture 3: Keystroke-Level Model - Ii

This section focuses on the Keystroke-Level Model (KLM) and explores the heuristics for placing the 'Mental Preparation' operator.

Objective

This section introduces Model-Based Design in HCI, highlighting its core principles, advantages, and limitations.

Content

This section delves into model-based design in HCI, emphasizing its role in optimizing interface efficiency through predictive modeling of user interactions.

Detailed Heuristics For Placing The 'm' Operator

This section discusses the heuristics for placing the 'M' (Mental Preparation) operator in the Keystroke-Level Model (KLM), emphasizing its subjective nature and the guidelines provided by Card, Moran, and Newell.

Illustrative Step-By-Step Klm Application Example

This section outlines a detailed practical example of applying the Keystroke-Level Model (KLM) to estimate task execution times for a specific user interaction scenario.

Reflecting On Advantages And Disadvantages Of Klm

This section discusses the advantages and disadvantages of the Keystroke-Level Model (KLM) in human-computer interaction.

Lecture 4: (Cmn)goms

This section delves into the (CMN)GOMS model, highlighting its hierarchical structure and cognitive modeling capabilities in predicting and analyzing user tasks.

Objective

This section outlines the objectives of model-based design in Human-Computer Interaction (HCI), emphasizing its predictive capabilities to evaluate user performance and optimize interface design.

Content

Introduction To The Goms Family Of Models

The GOMS family of models provides a structured framework for predicting user performance in human-computer interaction (HCI).

Comprehensive Components Of The Goms Model

The GOMS model, an essential framework in HCI, outlines the goals, operators, methods, and selection rules necessary for effective user interaction within a system.

The Significance Of Hierarchy In Goms

This section emphasizes the hierarchical structure of the GOMS model, illustrating its significance in understanding and optimizing human-computer interactions.

Profound Benefits Of Employing Goms Models

The GOMS model provides a comprehensive framework for understanding and predicting user interaction patterns, significantly enhancing design efficiency and effectiveness in Human-Computer Interaction.

Important Variations And Advanced Extensions Of Goms

This section discusses advanced iterations and extensions of the GOMS model, particularly focusing on KLM, NGOMSL, and CPM-GOMS, detailing their frameworks and applications in HCI.

Lecture 5: Individual Models Of Human Factors - I

This section introduces Fitts' Law and Hick-Hyman's Law, two fundamental models used in Human-Computer Interaction to predict user performance in tasks involving motor control and decision-making.

Objective

This section focuses on model-based design in Human-Computer Interaction, detailing its core concepts, benefits, limitations, and types of models.

Content

This section delves into Model-based Design in Human-Computer Interaction (HCI), highlighting the various quantitative predictive models that assess user performance and interface efficiency.

Fitts' Law: The Science Of Pointing

Fitts' Law is a predictive model in Human-Computer Interaction that estimates the time required for a user to move to and select a target.

Hick-Hyman's Law: The Science Of Choice Reaction Time

Hick-Hyman's Law quantifies the relationship between the number of choices available to a user and the time it takes to make a decision, illustrating how increased choices lead to longer reaction times.

Lecture 6: Individual Models Of Human Factors - Ii

This lecture delves into the Model Human Processor (MHP), a framework illustrating human cognitive functions in HCI, and its significance in guiding interface design.

Objective

This section provides an in-depth understanding of Model-based Design in Human-Computer Interaction (HCI), exploring its advantages, limitations, and various predictive models.

Content

The Model Human Processor (Mhp): An Architectural Overview

The Model Human Processor (MHP) provides a framework for understanding human information processing in HCI, encapsulating perceptual, cognitive, and motor processing.

The Three Interacting Processors Of Mhp

This section discusses the Model Human Processor (MHP), outlining its three main interacting processors—Perceptual, Cognitive, and Motor—and their roles in human information processing.

Utility And Significance Of Mhp In Hci

The Model Human Processor (MHP) offers a comprehensive framework for understanding human information processing in Human-Computer Interaction (HCI), connecting cognition and motor actions to guide effective interface design.

Lecture 7: A Case Study On Model-Based Design - I

This section explores a practical case study on model-based design techniques, specifically using the Keystroke-Level Model (KLM) to evaluate the efficiency of different interface designs for a common task.

Objective

This section outlines the main objectives of model-based design in Human-Computer Interaction (HCI), focusing on defining key concepts, advantages, limitations, and model categorization.

Content

Setting Up The Case Study: Problem Definition And Design Alternatives

This section describes the establishment of a case study aimed at assessing design alternatives for a copy-paste task, focusing on defining the problem and choosing methods for analysis.

Detailed Analysis Of Interface Alternative 1: Mouse-Centric Copy-Paste

This section analyzes the mouse-centric copy-paste approach, highlighting its workflow, efficiency, and the key aspects of its execution time using the Keystroke-Level Model (KLM).

Detailed Analysis Of Interface Alternative 2: Keyboard-Centric Copy-Paste

This section examines the keyboard-centric copy-paste interface alternative, emphasizing its efficiency for expert users and comparing it to other methods.

Lecture 8: A Case Study On Model-Based Design - Ii

This lecture concludes the case study on model-based design, evaluating a third interface alternative for a copy-paste task and analyzing the results of three different methods using the Keystroke-Level Model (KLM).

Objective

This section introduces the concept of Model-based Design in Human-Computer Interaction (HCI) and its key attributes, including its purpose, advantages, limitations, and the models employed.

Content

This section explores Model-based Design in Human-Computer Interaction, focusing on quantitative predictive models that estimate user performance and optimize interface design.

Detailed Analysis Of Interface Alternative 3: Hybrid Copy-Paste

This section analyzes the Hybrid Copy-Paste mechanism in user interface design, focusing on its efficiency compared to traditional methods.

Comprehensive Comparative Analysis And Informed Interpretation Of Results

The section provides a detailed analysis of three different design alternatives for a common copy-paste task, using the Keystroke-Level Model to quantitatively predict their efficiency.

Profound Implications For Design Decisions

This section discusses the major implications of model-based design decisions in Human-Computer Interaction (HCI), focusing on how predictive models can inform interface design choices.

Conceptual Extension To Goms Models For Complex Scenarios

This section outlines how the GOMS model is extended to include more complex user interaction scenarios.