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Usability Testing
Published in Samuel G. Charlton, Thomas G. O’Brien, Handbook of Human Factors Testing and Evaluation, 2019
Stephen D. Armstrong, William C. Brewer, Richard K. Steinberg
The basic GOMS family of models attempts to capture the cognitive behavior of a user by decomposing the operator’s activity into subgoals and goal stacks. Because it focuses on operator goals, the GOMS model is an excellent tool for making error predictions for a particular design. The GOMS model assumes that the more methods and operations an operator must learn, the more chances the user has to make errors (Eberts, 1994). Besides error analysis, the GOMS models can be used to enhance ease of use and speed performance and increase ease of learning for users. Detailed information on applying the GOMS family of models, including the original Card, Moran, and Newell (1983) GOMS model, the Natural GOMS Language (NGOMSL), and the human information processing model can be found in Card et al. (1983, 1986), John and Kieras (1994, 1996), and Eberts (1994).
Task Analysis Methods
Published in Neville A. Stanton, Paul M. Salmon, Guy H. Walker, Chris Baber, Daniel P. Jenkins, Human Factors Methods, 2018
Neville A. Stanton, Paul M. Salmon, Guy H. Walker, Chris Baber, Daniel P. Jenkins
The Goals, Operators, Methods and Selection Rules (GOMS; Card, Moran and Newell, 1983) method is part of a family of human computer interaction (HCI) based techniques that is used to provide a description of human performance in terms of user goals, operators, methods and selection rules. GOMS attempts to define the user's goals, decompose these goals into sub-goals and demonstrate how the goals are achieved through user interaction. GOMS can be used to provide a description of how a user performs a task, to predict performance times and to predict human learning. Whilst the GOMS methods are most commonly used for the evaluation of existing designs or systems, it is also feasible that they could be used to inform the design process, particularly to determine the impact of a design concept on the user. Within the GOMS family, there are four techniques: NGOMSL, the keystroke level model (KLM), CMN-GOMS, and CPM-GOMS. The GOMS methods are based upon the assumption that the user's interaction with a computer is similar to solving problems. Problems are broken down into sub-problems, which are then broken down further and so on. The GOMS method focuses upon four basic components of human interaction, goals, operators, methods and selection rules. These components are described below.
Task Analysis Methods
Published in Neville A. Stanton, Paul M. Salmon, Laura A. Rafferty, Guy H. Walker, Chris Baber, Daniel P. Jenkins, Human Factors Methods, 2017
Neville A. Stanton, Paul M. Salmon, Laura A. Rafferty, Guy H. Walker, Chris Baber, Daniel P. Jenkins
The GOMS (Card, Moran and Newell, 1983) technique is part of a family of HCI-based techniques that is used to provide a description of human performance in terms of user goals, operators, methods and selection rules. GOMS attempts to define the user’s goals, break these goals down into sub-goals and demonstrate how the goals are achieved through user interaction. GOMS can be used to provide a description of how a user performs a task, to predict performance times and to predict human learning. Whilst the GOMS techniques are most commonly used for the evaluation of existing designs or systems, it is also feasible that they could be used to inform the design process, particularly to determine the impact of a design concept on the user. Within the GOMS family, there are four techniques, which are described below: NGOMSL (Natural GOMS Language).KLM (Keystroke Level Model).CMN-GOMS (Card, Moran and Newell – GOMS).CPM-GOMS (Cognitive Perceptual Model – GOMS).
Development of an Approach to Measuring Learnability Based on NGOMSL from Perspectives of Extended Learnability
Published in International Journal of Human–Computer Interaction, 2020
A GOMS analysis is a model of the knowledge required for a user to complete a task in a system (Kieras, 1988), based on the model human processor (Card, Moran, & Newell, 1983). The acronym GOMS represents Goals, Operators, Methods, and Selection rules, and describes the knowledge around completion of intended tasks in a relatively formal and established way. A goal is what a typical user intends to accomplish. A goal can be composed of a set of subgoals in a hierarchical structure. Operators are the primitive actions involved in the achievement of goals, and methods are ways to complete the goals in a series of steps. Section rules are the criteria by which an appropriate operator or method can be chosen among two or more options in a step. Basically, a GOMS model is constructed through description of methods with lower-level operators involved in the completion of a goal (or subgoal).
Modelling user reactions expressed through graphical widgets in intelligent interactive systems
Published in Behaviour & Information Technology, 2022
F. Cena, C. Gena, E. Mensa, F. Vernero
Among predictive models, GOMS (Goals, Operators, Methods, Selection rules) is a family of models (Card, Moran, and Newell 1983) which focus on the procedural knowledge users need to carry out tasks (Kieras 1994), can be used to improve interaction efficiency and are domain independent. However, similarly to UpRISE, KLM (Keystroke-Level Model, Card, Moran, and Newell 1980) and TLM (Touch-Level Model), two specific techniques that instantiate the GOMS on keyboard and touchscreen interaction, restrict the set of operations that analysts can take into account to a specific domain. Differently from UpRISE, GOMS models aim at predicting how expert users carry out their tasks, producing quantitative predictions and allowing for the comparison of alternative methods.