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Identifying the needs of unknown users

Identifying the needs of unknown users. CMPT 455/826 - Week 3, Day 1 (Based on Lars-Erik Axelsson ). Why this paper?. In considering each paper there are a number of things we can use to get the most out of the paper: The name of this course Information Modeling and Retrieval

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Identifying the needs of unknown users

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  1. Identifying the needs of unknown users CMPT 455/826 - Week 3, Day 1 (Based on Lars-Erik Axelsson) Sept-Dec 2009 – w3d1

  2. Why this paper? • In considering each paper there are a number of things we can use to get the most out of the paper: • The name of this course • Information Modeling and Retrieval • The focus of this course • Dimensions are a/the MAJOR FOCUS of this course • The topic for this week • e.g. Information and users • This set of notes provides an example of how to use these as a basis for understanding and applying the contents of this paper Sept-Dec 2009 – w3d1

  3. Unknown users • How can you know anything about “unknown users”? • Instead of giving up and treating this as impossible, • we just need to accept it as a wicked problem • Remember Conklin talked about wicked problems • there is no clear and agreed upon definition of the problem • how can you know the “unknown” • the abstract says, “Most traditional models for system development presuppose that users of the system are known and possible to communicate with. If this is not achievable traditional design methods are less usable in order to analyze and describe the requirements of the users.” • the problem itself is apt to change over time • once you know, then the users are no longer “unknown” Sept-Dec 2009 – w3d1

  4. The problem • Traditional database modelling presupposes • that it is possible to identify user views and • by means of view modelling, • define all views or user profiles for the database • A user profile is defined as • a group of individuals with the same perspective regarding information • who share a common view of the Universe of Discourse (UoD). • We need to be able to identify suitable groups of users • (including groups that are not currently known) • who share common needs for data • (because they are not currently known does not mean that they cannot be discovered) Sept-Dec 2009 – w3d1

  5. User Profiles • This slide is more of an aside than a major point • The term “user profile” is used in a less than usual way in this paper • The term “user profile” is more commonly used to describe a set of information that is used by the computer (rather than by the designer) for the purpose of determining how to individualize the interactions between the computer and the user • But the paper moves away from user profiles to personas anyhow Sept-Dec 2009 – w3d1

  6. View modeling • View modelling is a process of transforming • many individual users’ requirements • into a few conceptual views (or models) • The models rely on the assumption that • the users of the information systems have • declared their future needs and expectations • It is possible to establish a requirement specification • because the opinions of the users have been sought • or at least the needs of the different users have been considered • Regardless, you still need to know who the users are Sept-Dec 2009 – w3d1

  7. Personas • “Sundgren argues that all known and imaginable users and user situations should be listed, every user or every usage is then described in a detailed way” • Personas: • Personas are user models • that are represented as specific, individuals • and are carefully described in terms of needs, goals and tasks • The persona is a precise description of a hypothetical user • Every persona is carefully described in terms of the key issues, • namely needs, behaviour patterns and goals • i.e. Specific examples with their own specific attribute values • [Think of how UML uses examples as a basis for design] Sept-Dec 2009 – w3d1

  8. Personas vs. Stereotypes • We can better understand personas by comparing them to what they are not • Personas are examples of users • developed bottom up • grouped to provide a reasonable set of examples • with no particular guarantee of exclusivity • Stereotypes are classes of users that are • developed top down • generally mutually exclusive (to avoid multiple inheritance) • expected to allow the classification of all possible users • Personas are not stereotypes Sept-Dec 2009 – w3d1

  9. Personas in Design • At the end of the process, • several sets of qualities or characteristics • will have been formed • The recommended number of personas in one set of characteristics lies between three and seven. • One of these (the primary persona) represents the primary goal for the design and the characteristics for any of the other personas cannot satisfy this particular persona. • The needs of the other personas in the set (secondary personas) do not pose a problem as long as they do not interfere with the needs of the primary persona. Sept-Dec 2009 – w3d1

  10. Putting this in English • The procedure advocated in the paper is: • Identify known users • Identify their characteristics • Create personas that have typical characteristics • that can represent clumps of users • Group personas based on similar characteristic values • choose one per group as the main persona • The problem is this is just the start. • The author doesn’t go beyond here. • If we do, then we can identify the needs of unknown users Sept-Dec 2009 – w3d1

  11. Let’s rethink this in terms of data • Personas • can represent typical users • differ based on various characteristics • Characteristics • can be represented as data attributes • with their own set of individual values • The set of personas, • identify important attributes of users • Individual personas, • identify different attribute valuesof individual users Sept-Dec 2009 – w3d1

  12. Identifying the Unknowns • There may be other combinations of attribute values • these could identify different (currently unknown) personas • There may be other attributes • that are related to the currently identified attributes • that could identify many other groups of (currently unknown) potential users and lead to new (currently unknown) personas • Then the expanded set of personas • can be used to identify an expanded set of data requirements • that will meet • the (previously) unknown needs • of (previously) unknown users Sept-Dec 2009 – w3d1

  13. Predicting the Future • Isn’t a carnival act based on wild guessing • (even carnival “mind-readers” need information) • Good predictions of the future • analyze and extrapolate trends • identify what’s related but missing Sept-Dec 2009 – w3d1

  14. Successful Predictions • If you want your predictions to be well received • they need to be believable (which means) • people need to be able to understand how they could evolve • from the current circumstances • along some newly identified transformation / relationship • It doesn’t pay to be too far ahead of your time • people will not understand it today • people will have forgotten you predicted it by the time it actually occurs • someone else will get the credit for making it believable • Thus one or two levels of extrapolation is enough (for now) Sept-Dec 2009 – w3d1

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