Bridging the Communication Gap: A User Task Vocabulary for Multidisciplinary Web Development Team Sara Tena
David Díez
DEI Lab, Universidad Carlos III Avda. Universidad, 30 28911 Leganés, Spain +34 624 88 31
DEI Lab, Universidad Carlos III Avda. Universidad, 30 28911 Leganés, Spain +34 624 94 99
[email protected]
[email protected]
Paloma Díaz
Ignacio Aedo
DEI Lab, Universidad Carlos III Avda. Universidad, 30 28911 Leganés, Spain +34 624 94 56
DEI Lab, Universidad Carlos III Avda. Universidad, 30 28911 Leganés, Spain +34 624 94 90
[email protected] ABSTRACT The design of Web-based systems is specially characterized by the multidisciplinary nature of Web Development Teams (WDTs). Due to this multidisciplinary, WDT members use different terminology that can lead to misunderstanding along the development process and, consequently, affect the resulting design. This problem has been identified during the physical design of websites, characterized by the sharing of ideas and the need of reaching a common understanding of the problem. With the purpose of avoiding misunderstanding among WDT members during this phase, it is proposed a controlled vocabulary of web user task. The definition of the vocabulary is based on the analysis of interaction design patterns. The paper describes the definition process followed for the construction of the user task vocabulary as well as the vocabulary itself. The final version of the controlled vocabulary compiles a total of thirty-four web user tasks and forty-one semantic relationships represented as synonyms. The vocabulary has been assessed through a heuristic evaluation, proving its correctness and completeness.
Categories and Subject Descriptors H.5.3 [Information Interfaces and Presentation]: Group and Organization Interfaces – web-based interaction.
General Terms Design, Human Factors
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[email protected] Keywords Multidisciplinary, web development team, user task, interaction, physical design, communication, misunderstanding
1. INTRODUCTION Team working is built on the assumption that the group members are able to communicate and collaborate. That seems obvious, but in many teams insufficient understanding during collaboration is one of the reasons for project failure. As Larsson [1] posits, “successful collaboration requires the establishment of shared understanding or common ground between team members”, but the achievement of that is not a trivial task. During design, the way in which a team member communicates with the rest of the team is essential to get shared understanding, but in many cases team members use a jargon that isn’t clear or commonly understood by others [1]. These communication problems may be greater if teams are composed by a group of people with a full set of complementary skills, knowledge, and backgrounds –what it will be called multidisciplinary teams from now on. Multidisciplinary teams have to deal not only with the challenge of communicating different perspectives but also with the challenge of communicating among people with different background and terminology. That is why a common language in terms on vocabulary could make sense in collaboration. The design of Web-based systems is specially characterized by the multidisciplinary nature of Web Development Teams (WDT) [2]. These teams can normally involve profiles such as web developers, graphic web designers, and usability experts. This multidisciplinary of the team makes that each team member provides a different perspective of the same problem. While the web developer is worried about the behavior or the functionality of the system, the graphic web designer is concerned of the layout and appearance of the web. These different points of view allow building more usable, maintainable, and reliable web systems. However, differences in their terminology can lead to misunderstandings among WDT members. This terminological problem is mainly identified during physical design, which involves considering concrete and detailed issues of designing the
interface [3], such as the interaction elements or the user interface components to use. The lack of a shared vocabulary in this phase may complicate the physical design in two ways: on the one hand, the process of discussing and making a preliminary solution will be hindered by the use of ambiguous terminology that is not understood in the same way by different members of the team; on the other hand, the misunderstanding between designers and developers about the same user task may cause the building of unsuitable solutions. An example of this problem was observed during the design of an e-commerce website. In this kind of website, one of the main goals of the user is to find desired products to buy them. The search of products requires moving around the site, trying to identify which product satisfies the user needs. This ‘moving around’ can be performed by following a predefined path or just surfing the site. These two different ways of achieving the goal refer to different user tasks, carried out with different user interface components. In particular, designers with a computer background usually use the terms ‘navigate’ and ‘browse’ to respectively refer to these two tasks. ‘Navigate’ refers to follow a planned course on, across, or through the products, leading to the use of menus or action buttons. Otherwise, ‘browse’ refers to look around the products, without seeking anything in particular, leading to the use of search fields or tables. However, graphic web designers and even usability experts use either ‘navigate’ or ‘browse’ without distinction. Therefore, the use of different terminology may affect the physical design of the homepage. For instance, referring to “use an element to browse around the products” the graphic designer may propose a layout to render an action menu, while the web developer would think in a search bar. This paper proposes a vocabulary of web user tasks conceived to enhance the communication of WDT members. The vocabulary collects common tasks related to the user interaction with web systems. The definition of the vocabulary is based on the analysis of interaction design patterns. The rest of the paper is organized as follows. Next section includes the review of different works devoted to identifying lists, taxonomies, and classifications of web user tasks. These works might be used as a reference to define the controlled vocabulary. Section 3 describes the definition process of the vocabulary, including the explanation of the sources of information analyzed to collect web-user tasks and the proposed vocabulary. Section 4 presents the expert evaluation of the vocabulary. Finally, conclusions and further work will be presented.
2. RELATED WORK Exchanging information among participants with different background requires a shared terminology that can support some level of common understanding [1]. In particular, focusing on the design of web user interface, this shared terminology should allow designers to understand in the same way the meaning of most common user tasks. This condition implies not only the collection of terms but also the definition of such terms as a way of assuring their understanding. A controlled vocabulary is highlighted as an effective and natural mechanism to reduce ambiguity at low cost [4]. In particular, it could be defined as a user-friendly resource that does not require too much experience or knowledge to use it. This kind of vocabulary consists on a list of terms explicitly listed and defined in an unambiguous and non-redundant way [5], oriented to address two main problems:
- Homonymy: If the same term is commonly used to mean different concepts, then its name is explicitly qualified to resolve this ambiguity in the vocabulary. - Synonymy: If multiple terms are used to mean the same thing, one of the terms will be identified as the preferred term and the others are listed as synonyms. According to this definition, a generic controlled vocabulary of web user tasks must be characterized by being domainindependent, by compiling user tasks in a broad sense, and by providing the definition of such terms that designate user tasks. There are so far different works devoted to define lists, taxonomies, or tasks classifications that may be used as reference to identify interactions between users and web applications that can lead to identify the terms of a controlled vocabulary. This section reviews such existing controlled vocabularies to “ascertain whether an existing controlled vocabulary covers the same or an overlapping domain of knowledge” [5]. This review also served as a starting point to compile broadly used terms in related fields. Bryne et al. [6] proposed a web-user-task taxonomy that collects the most frequent tasks performed while surfing the web. This taxonomy proposes six main classes of tasks: use information, locate on page, go to page, provide information, configure browser, and react to environment. A user-task taxonomy oriented to specifically categorize the underlying goals of user searches is introduced in [7]. This taxonomy consists of three types of web search: navigational, informational, and resource. The goal of navigational search is to go to a specific known website that the user already has in mind; informational search is centered in learning something by reading or viewing web pages; and, finally, resource search represents the goal of obtaining something the user is looking for. In addition, each of these goals is divided into sub-goals, such as locate, download, entertainment, etc. Morrison et al. [8] described another taxonomy of web searching taking into account three variables: the purpose of the search, the method used, and the content of the information being searched for. Although [6], [7], and [8] are called as user-task taxonomies for the web, they are limited to search tasks on the web. Besides, these taxonomies are focused on offering a hierarchy of user tasks without including the definition of the tasks. Without such definitions designers may understand the user tasks in a different way, making it difficult a share understanding of the tasks. In a more generic way, Heath et al. [9] proposed a list of online tasks that emphasizes user’s goals without the use of a particular tool or technology. This list collects a total of eleven tasks: locating, exploring, monitoring, grazing, sharing, notifying, asserting, discussing, evaluating, arranging, and transacting. Gonzalez-Calleros et al. [10] presented a list of canonical tasks with the purpose of providing user interface designers with guidance for task modeling. The list compiles a total of fifteen canonical tasks with their correspondent definitions. However, some of the definitions use the own key term to explain the meaning of the task, making it difficult the understanding of such tasks. As an example, the ‘modify’ canonical task is defined as “the action of modifying an item”, leaving it open which kind of changes are allowed so different interpretations the designer gives to this imprecise definition is valid. Based on a study by twentyfour knowledge workers, Sellen et al. [11] created a classification of tasks in web usage. As a result, six main categories were defined: finding, information gathering, browsing, transacting, communicating, and housekeeping. These works do not, for example, identify tasks related with such processes aimed at helping the user to accomplish a specific task or to product new
content on the web, such as require Web 2.0, and, consequently, do not provide enough broad sense of user tasks on the web. However, due to the fact that they provide generic user tasks as well as their definition, they have been considered as a starting point in the present proposal to compile terms. Finally, a list of tasks dependent on domains such as banking, customer service, credit investigation, and finance was proposed in [12]. Another model of tasks [13], proposes a list of tasks to support the design of multidimensional visualization techniques. Both works are not only domain-dependent, covering only user tasks in the analyzed domains, but also uncompleted: they do not provide the definition of the tasks.
3. CONSTRUCTION PROCESS The aim of this paper is to define a user task vocabulary for web user interface design. This vocabulary compiles terms related to the use of web applications, regardless of the business domain, as a way of providing a shared understanding of web user tasks. Next subsections explain the rationale of the construction process of the user task vocabulary, defining the content objects, the construction method applied to collect terms as well as the vocabulary itself.
3.1 Content Objects A content object is considered as any item that is to be described for inclusion in an information retrieval system, website, or other source of information [5]. Since the identification of user tasks refers to an instrumental activity, the construction of the vocabulary was based on interaction design patterns, a wide-used web-design resource. Interaction design patterns are successful solutions and best practices to recurrent design problems. They document patterns of interaction that make it easier for users to understand the interface and perform their tasks [14]. This kind of design resource describes interactions between the user and the system in order to understand how users accomplish their goals. Hence, the narrative of an interaction design pattern describes a set of tasks that may be part of an activity supported by the system in order to accomplish a user goal. Although there are several interaction design pattern libraries, and patterns descriptions vary somewhat, the majority of the libraries include a set of common elements: the pattern name, its description, the problem to solve, the solution to this problem, and the rationale of the solution. Fig. 1 shows an example of an interactive design pattern. Since both the problem and the solution compile interaction between the user and the system, these two elements were analyzed to identify terms related to user tasks. With the purpose of identifying these user tasks, four of the most popular interaction design pattern libraries were reviewed: Yahoo Patterns [15], Designing Interfaces [14], Quince Patterns [16], and RIA Patterns [17]. These libraries compiles terms not only related to traditional web but also to rich internet applications (RIA). The term RIA refers to any component-based web application that provides desktop functionalities through the use of richer user interface components [18]. As a result, a total of ninety-eight patterns were analyzed.
3.2 Selection of Terms The selection of terms was based on the identification of those verbs and phrasal verbs related to web user tasks. A verb describes the fact or process of doing something, typically to achieve an aim; as a consequence, verbs determine the goals, activities, and actions to be carried out by the user on the web.
With the intention of building a user task vocabulary independent of the domain, those verbs related to the way of accomplishing a goal or performing an activity must be collected. Such verbs represent generic interaction activities on the Web and, as a consequence, the most significant web-user tasks of a web application. The identification of terms was carried out in a manual way, without applying machine-readable text or computerized indexing systems. Machine-aided indexing may increase the efficiency of process but require well-defined rules about the terms to select. Given the characteristics of the process of indexing user tasks, based on subjective aspects and its aim of describing tasks, machine assistance was discarded. As shown in Fig. 2, some verbs refers to the goal – ‘enter’- and others such as ‘enable’, ‘allow’, ‘provide’ or ‘forcing’ are used as links and clarifications in the narratives but do not describe user tasks. Therefore, the selection of terms had to consider not only the grammatical form of words but also the sense of the narrative and the relationship with other words. The selection of terms was based on the top-down technique, identifying first the broadest terms and then the narrowest ones. The process was divided into the following steps: 1. Extraction. The first step of the process is aimed at identifying those verbs that represent interaction between the user and the system. An example of the extraction process is presented in Figure 2. It shows the description of the problem and solution of the ‘Date and Time Input’ pattern of the ‘Quince Patterns’ catalog. Verbs such as ‘enable’, ‘enter’, ‘provide’, ‘allow’, ‘select’, and ‘forcing’ are highlighted; however, just those verbs that semantically and contextually represent an action with the system –such as ‘select’ and‘enter’– are selected. 2. Registration. During the extraction process, the frequency with which a term has been used in indexing is registered. Terms with low scores can be considered as candidates for rejection. 3. Prioritization. With the purpose of establishing key terms, extracted verbs are sorted in keeping with the number of occurrences. As an example, some of the verbs that had more occurrences were ‘browse’, ‘filter’, ‘search’, and ‘select’. 4. Definition. Once the verbs have been extracted and prioritized, the meaning of the verbs has to be established. Online dictionaries –such as WordReference [19], Cambridge Dictionary [20], and Wordnet [21]- are used to look up the definition of the terms as a way of defining user tasks. In this way, the definitions are established selecting those related to the interaction of the user with the web. When the definitions are similar among dictionaries, we take those that express more accurately the nature, scope or purpose of the interaction activity. 5. Classification. This step aims at identifying whether a verb has a semantic relationship with other verbs in the list. If such a relation exists the verb with more occurrences is identified as a key term and the others as synonyms; in addition, using the above-mentioned dictionaries the list of synonyms was completed. An example of this step is reflected in the verbs ‘enter’ and ‘insert’. As shown in Fig. 2, ‘enter’ and ‘insert’ are initially identified in the analysis of the narratives. Based on the definitions provided by the online dictionaries, it was detected a semantic relationship between both terms, establishing ‘insert’ as the key term due to the number of accounted occurrences and ‘enter’ as its synonym.
Figure 1. Definition of the ‘Date and Time Input’ pattern of the Quince library [16]
Figure 2. Example of extraction step. Verbs underlined were highlighted but only rounded ones were extracted Key term
3.3 User Task Vocabulary The structure and display format of the controlled vocabulary affects the types of cross-references and relationship indicators that are provided [5]. The user task vocabulary is presented in a tabular way, compiling the key term, the synonyms, and the definition of each user task. Tabular is the plainest presentation structure of controlled vocabulary. This kind of structure is oriented to display the most significant references and relationships between terms with particular emphasis on usability. With the purpose of easing the search of terms, the vocabulary is alphabetically sorted by key terms; similarly, the synonyms of each task are also alphabetically arranged. As far as the delivered format is concerned, a web-enabled format is adopted. This delivered format allows designers to look up terms online, moving through the web page by using menu options such as ‘find’ or ‘find next’. The user task vocabulary compiles a total of thirtyfour key terms and forty-one synonyms. Table 1 presents the final draft of the vocabulary. Table 1. User task vocabulary of web user tasks. Key term
Synonyms
Add
Assign
Set apart, Specify
Associate
Colligate, Connect,
Definition Join (something) to something else so as to increase the size, number, or amount Designate or set (something) aside for a specific purpose Make a logical or causal
Browse
Synonyms Link, Link up, Relate, Tie in Surf
Change
Commute, Convert, Exchange
Check
Verify
Combine Compare
Complete Consult
Look up, Refer
Delete
Remove, Erase
Download
Definition connection Look around casually and randomly, without seeking anything in particular Exchange or replace with another, usually of the same kind or category; Make sure or demonstrate that (something) is true, accurate, or justified Join for a common purpose or in a common action Draw an analogy between one thing and (another) for the purposes of explanation or clarification Bring to a whole, with all the necessary parts or elements Seek specific information about (something) Wipe out digitally or magnetically recorded information Transfer a file or program from a central computer to a smaller computer or to a computer at a remote
Key term
Synonyms
Export Fill Filter
Filter out, Filtrate, Strain, Separate out
Format Import Insert Modify
Enter, Infix, Introduce Alter
Move
Displace
Navigate Rate
Grade, Place, Order, Range, Rank
Return Rotate Save Search Select
Pick out, Choose, Take
Send Show Sort Store Switch Upload Validate
Assort, Class, Classify, Send out, Sort out, Separate
Definition location Transfer (data) in a format that can be used by other programs To complete (a form, for example) by providing required information Process or treat with a piece of software that processes data before passing it to another application Arrange or put into a defined structure for the processing, storage, or display of data Transfer (data) into a file or document Put or introduce into something Make partial or minor changes to (something) Cause to move or shift into a new position or place To follow a planned course on, across, or through information Assign a standard or value to (something) according to a particular scale To come or go back to a previous place Move in a circle round an axis Keep (data) by moving a copy to a storage location Try to find something by looking or otherwise seeking carefully and thoroughly Pick out or choose from a number of alternatives To cause or order to be taken, directed, or transmitted to another place Be, allow, or cause to be visible Arrange or order by classes or categories Retain or enter (information) for future electronic retrieval Change the position, direction, or focus of (something) Transfer (data) to a larger computer system Check or prove the validity or accuracy of (something)
4. HEURISTIC EVALUATION The evaluation of the vocabulary is aimed at determining “if the controlled vocabulary matches users’ expectations of the terms contained therein” [5]. For example, if the vocabulary is not sufficiently rich, designers may not find their required terms. With such an aim, the evaluation was oriented towards assessing the completeness and correctness of the vocabulary. The evaluation of these two facets was carried out by a heuristic evaluation. This evaluation method is based on asking the opinion to a panel of experts. The opinion of experts was collected through a five-level Likert scale questionnaire, ranging from (1) ‘strongly disagree’ to five (5) ‘strongly agree’. Before analyzing the results of the survey, and in order to ensure the reliability and validity of the questionnaires, it was performed a reliability test based on the αCronbach. The internal consistency of the questionnaires would be considered as acceptable if the α-Cronbach coefficient is 0,7 or higher [22]. Due to Likert scale is considered as an ordinal scale, the analysis of the results was based on the central tendency through the median. For the evaluation of the vocabulary, a set of questions (see Table 2) about the acceptance usage of the terms, the completion of the vocabulary, and its expected usefulness was used. Referring to the selection of experts, the evaluation of the vocabulary was carried out by a total of eighteen experts (SME, subject-matter expert). These experts’ profile corresponded to usability experts (5 SMEs), graphic web designer (4 SMEs), accessibility experts (5 SMEs), and web developer (4 SMEs). Additionally, in order to assure the validity of their opinions, they should be part of a WDT for a minimum of two years. Because of the larger number of experts and their diversity, the questionnaire was filled through a public web site. The online completion of the questionnaire made it easier to collect results and to apply statistical methods to the data (Table 3). In the home page, the web site provided information about both the main object of the research and the object of the evaluation. Once the experts were put into context, they could access to the evaluation. Table 2. Experts’ opinion about the vocabulary Id
Question
Q01
The vocabulary collects common user task in interaction with the web
Q02
Up-to-date, terms are of accepted usage on the web
Q03
The definition of the terms design the reality of the user task on the web
Q04*
Too many key terms must be added to the vocabulary
Q05*
Too many synonyms must be added to the vocabulary
Q06
The vocabulary does not contain terms that are synonymous or equivalent without indicating the relationship
Q07
The definition of the terms are unambiguous
Q08
The definition of the terms are non-redundant
Q09
The use of a common vocabulary among WDT members avoid misunderstandings
Q10
The use of a common vocabulary facilitate the communication among WDT members
Table 3. Results of experts’ opinion about the vocabulary (Questions marked with an asterisk were formulated with a negative sense in order to avoid bias for acceptance)
7. REFERENCES [1] Pan, T. Y., Newman, R.M., Porter, S. and Tovey, M. 2002. Verbal language and Sketching. In Common Ground: Proceedings of the Design Research Society International Conference at Brunel University, Staffordshire University Press
Id
Average
Median
Standard Deviation
Q01
4.06
4
0.52
Q02
3.89
4
0.49
[2] Díaz, P., Montero, S. and Aedo., I. 2005. Ingeniería de la web y patrones de diseño. Pearson Education, Madrid, Spain
Q03
3.72
3.5
0.59
Q04*
3,89
4
0,3
[3] Rogers, Y., Sharp and H., Preece, J. 2011. Interaction Design: beyond human-computer interaction. Wiley, UK
Q05*
4,17
4
0,65
Q06
3.94
4
0.52
Q07
4.17
4
0.46
Q08
4.39
4.5
0.61
Q09
4,17
4
0,65
Q10
3,56
4
0,49
The α-Cronbach’s was 0,828, assuring the reliability of the questionnaire. The results show experts value of the vocabulary, considering that it collects common user tasks in interaction on the web and that it can be used for the design of web interactions. In particular, the definitions of the user tasks were assessed as correct and truthful. Regarding the usefulness of the vocabulary, experts consider that the vocabulary could be useful to avoid misunderstandings and facilitate communication among WDT members during the physical design of websites.
5. CONCLUSIONS The use of different terminologies may lead to communication problems when the understanding of the information differs depending on the participants’ background. With the purpose of avoiding such communication problems during physical design of websites, a controlled vocabulary of web user tasks has been proposed. This vocabulary, initially conceived for the physical design, could be applied to other activities of the development process in which WDT members have to exchange their ideas, thoughts, and suggestions about the interaction between the user and the system. The assessment of the vocabulary has demonstrated the completeness and correction of the vocabulary. The evaluation of the vocabulary has verified the validity of the construction process and, specially, the recognition of interaction design patterns as a suitable source of information for collecting common user tasks on the web. Our experience during the construction of the vocabulary, along with the results of the evaluation, suggests that interaction design patterns can be considered as a convenient source of information for defining the common ground of web design. Additionally, interaction design patterns can be considered as a rigorous source of information, so reliable as research articles, technical reports, or white papers. However, in order to confirm this preliminary impression, further work will be oriented to study other sources of information such as use cases narratives or design principles.
6. ACKNOWLEDGMENTS This work has been partly supported by the urThey project (TIN2009-09687) funded by the Spanish Ministry of Science and Innovation (MICINN).
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