HCI 3e - Ch 11: User support
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This document discusses different approaches to providing user support, including quick reference help, tutorials, documentation, wizards, and adaptive help systems. It covers the requirements of user support like availability, accuracy, consistency, and flexibility. Approaches discussed include command assistance, context sensitive help, online tutorials, documentation, wizards, assistants, and adaptive help systems. Key challenges of adaptive help systems include the knowledge requirements and controlling the interaction.
HCI 3e - Ch 11: User support
- 1. chapter 11 user support
- 2. user support Issues di ff erent types of support at different times implementation and presentation both important all need careful design Types of user support quick r eference, task speci fi c help, full e x planation, tutorial Provided by help and documentation help - problem-oriented and spec if ic documentation - system-oriented and general same design principles apply to both
- 3. Requirements Availability continuous access concurrent to main application Accuracy and completeness help matches and covers actual system behaviour Consistency between different parts of the help system and paper documentation Robustness correct error handling and npredictable behaviour Flexibility allows user to interact in a way appropriate to experience and task Unobtrusiveness does not prevent the user continuing with work
- 4. Approaches to user support Command assistance User requests help on particular command e.g., UNIX man, DOS help Good for quick reference Assumes user know what to look for Command prompts Provide information about correct usage when an error occurs Good for simple syntactic errors Also assumes knowledge of the command
- 5. Approaches to user support (ctd) Context sensitive help help request interpreted according to context in which it occurs. e.g. tooltips On-line tutorials user works through basics of application in a test environment. can be useful but are often in flexible. On-line documentation paper documentation is made available on computer. continually available in common medium can be difficult to browse hypertext used to support browsing.
- 6. wizards and assistants wizards task specific tool leads the user through task, step by step, using user’s answers to specific questions example: resumé useful for safe completion of complex or infrequent tasks constrained task execution so limited flexibility must allow user to go back assistants monitor user behaviour and offer contextual advice can be irritating e.g. MS paperclip must be under user control e.g. XP smart tags
- 7. Adaptive Help Systems Use knowledge of the context, individual user, task, domain and instruction to provide help adapted to user's needs. Problems knowledge requirements considerable who has control of the interaction? what should be adapted? what is the scope of the adaptation?
- 8. Knowledge representation User modeling All help systems have a model of the user single, generic user (non-intelligent) user-configured model (adaptable) system-configure model (adaptive)
- 9. Approaches to user modelling Quantification user moves between levels of expertise based on quantitative measure of what he knows. Stereotypes user is classified into a particular category. Overlay idealized model of expert use is constructed actual use compared to ideal model may contain the commonality or difference Special case: user behaviour compared to known error catalogue
- 10. Knowledge representation Domain and task modelling Covers common errors and tasks current task Usually involves analysis of command sequences. Problems representing tasks interleaved tasks user intention
- 11. Knowledge representation Advisory strategy involves choosing the correct style of advice for a given situation. e.g. reminder, tutorial, etc. few intelligent help systems model advisory strategy, but choice of strategy is still important.
- 12. Techniques for knowledge representation rule based (e.g. logic, production rules) knowledge presented as rules and facts interpreted using inference mechanism can be used in relatively large domains. frame based (e.g. semantic network) knowledge stored in structures with slots to be filled useful for a small domain. network based knowledge represented as relationships between facts can be used to link frames. example based knowledge represented implicitly within decision structure trained to classify rather than programmed with rules requires little knowledge acquisition
- 13. Problems with knowledge representation and modelling knowledge acquisition resources interpretation of user behaviour
- 14. Issues in adaptive help Initiative does the user retain control or can the system direct the interaction? can the system interrupt the user to offer help? Effect what is going to be adapted and what information is needed to do this? only model what is needed. Scope is modelling at application or system level? latter more complex e.g. expertise varies between applications.
- 15. Designing user support User support is not an `add on’ should be designed integrally with the system. Concentrate on content and context of help rather than technological issues.
- 16. Presentation issues How is help requested? command, button, function (on/off), separate application How is help displayed? new window, whole screen, split screen, pop-up boxes, hint icons Effective presentation requires clear, familiar, consistent language instructional rather than descriptive language avoidance of blocks of text clear indication of summary and example information
- 17. Implementation issues Is help operating system command meta command application Structure of help data single file file hierarchy database What resources are available? screen space memory capacity speed Issues flexibility and extensibility hard copy browsing