TAILIEUCHUNG - Lecture Human computer interaction: Lecture 26 - Professor Dr. Sajjad Mohsin

We have seen several task analysis methods. Hierarchical task analysis decomposes a task into subtasks. These can be recorded either in a textual outline format or in a tree diagram. Knowledge-based techniques build taxonomies of the objects used during a task and the actions performed upon them. Cutting the taxonomy at some level gives us a set of generic objects and actions. Finally, we can again look at objects and actions, but concentrate on different kinds of object: passive object and active human and non-human agents, and the relationships between the objects and actions. | Lecture 26 Modelling Rich interaction Today’s Lecture Today we shall discuss about, Status–event analysis Aspects of rich environments Rich Context Sensor based interactions Introduction Human Computer Interaction is “Normally” considered as relationship between human and computer. This is an ideal or exceptional situation that one human is interaction with one computer. Thus it focused on individual planned user actions. In real world, like in offices several individuals and systems are taking part. Introduction In this lecture we look at several ways in which this ‘normal’ situation can be modeled either by new methods or by adapting existing ones. Modelling Rich Interaction Status–event analysis Rich environments in task analysis Sensor-based systems What is Status? Status for example includes the position of a mouse on a table and the current screen contents, as well as the internal state of the system. The word ‘state’ has connotations of the complete state of the system, rather than the selective particular views meant here by status. Status Versus Events The distinction between status and event is between being and doing. Status phenomena always have a value one could consult. For example, you can ask the question ‘what was the position of the mouse on the tabletop at 3:27pm?’. An event, on the other hand, happens at a particular moment. For example ‘at what time did the user press the mouse button?’. Status–Event Analysis Unifying framework – system (formal analysis) – user (psychology & heuristics) Time behaviour – detect delays, select feedback Transferable phenomena For example Polling Given Brian only had a status – the watch face – and he wanted an event –7:35 – he looked periodically at his watch. In computing terms, Brian polled his watch. Polling is a normal activity that people do as well as machines. It is a standard way to turn a status into an event. Rich set of phenomena events status input Keypress mouse .

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