ARCO Mapping the Cognitive Dynamics of Communication Expectations: An Approach to Designing Usable Content Based on Audience Expectations

Abstract

The usability of items is connected to cognition, or how the brain processes information. Many of the related processes occur subconsciously and are guided by the mental models individuals have created based on their experiences. The better communication professional and communication students understand such dynamics, the more effectively they can create usable content for an audience. This article presents an approach, the Actualization, Recognition, Categorization, Operationalization (ARCO) method, for identifying the mental models that influence usability expectations. Individuals can use the results of this process to create content that better addresses an audience’s usability expectations.

Keywords

usability design cognition user experience design mental models methodology psychology

Usability is central to effective communication, for audiences must often use content to perform particular activities (Content Strategy Basics, 2022). Essentially, the more audiences grapple with what a message conveys, the less likely they are to use the related information (Nielsen, 2012a). Yet achieving usability in today's interconnecting world is not easy. It increasingly requires a familiarity with cognition—or how the human brain perceives, processes, and acts upon information when using it. By understanding how cognitive dynamics affect communication expectations, one can create content an audience considers relatively easy to use (Boichuk, 2020). Approaches that identify these usability factors can help communication professionals, educators, and students create usable messaging for different groups.

This article presents an approach for addressing core cognitive factors that shape an audience's usability expectations. Known as the ARCO method, the approach examines the underlying cognitive processes that shape how humans use verbal, visual, and other kinds of content. Through a process, called “mapping,” the ARCO method systematically reviews the mental processes affecting how audiences focus attention, identify items, and determine the uses of objects when interacting with information. Communication professionals can apply the results of this mapping process to create verbal, visual, or multimedia content audiences can more readily use. Communication educators can also employ the ARCO method to teach students about usability as related to audience expectations for different messages. In these ways, the ARCO method helps technical communicators better identify and design for audience expectations.

Cognition and Communication

Cognition involves how the brain processes information (Cognition, 2022; What is Cognition, n.d.), and cognitive factors can affect communication practices in different ways. As a result, cognitive dynamics represent an area of continued interest for communication scholars. A growing body of research, for example, examines how social cognition influences different communication situations. These include family communication dynamics (Koerner, 2007; Koerner & Fitzpatrick 2002) as well as broader interpersonal interactions (Imhof et al., 2014; Sillars & Parry, 1982). Other scholars have examined how cognitive factors affect communication in romantic relationships (Honeycutt & Cantrill, 2014; Theiss & Solomon, 2006) as well as in interpersonal interactions involving stress and emotions (Brand, 1987; Planalp, 1993). Additionally, researchers have noted how cognitive dynamics can affect communication in health and medical contexts (Liu & Yanga, 2021; Williams-Piehota et al., 2003) and in business and entrepreneurial practices (Clarke & Cornelissen, 2011; Spinuzzi et al., 2014).

Scholars in genre studies have also explored connections between cognition and communication in certain contexts. Such work includes more subtle comments on how genre dynamics could shape cognitive expectations associated with messages (Miller, 1984; Miller & Selzer, 1985). It also includes more direct examinations of how communities condition members into developing patterns—or cognitive mechanisms—for identifying and using genres (Berkenkotter & Huckin, 1995; Spinuzzi, 2004). Additionally, some researchers have noted how conditioned perceptions influence the assumptions of what genres are and how they are used (Berkenkotter & Huckin, 1995; Spinuzzi, 2004; Virtanen, 2011). More recently, individuals have explored connections between genres and cognition in health communication contexts (Liu & Yang, 2021; Williams-Piehota et al., 2003) and in international and intercultural exchanges (Barber & Badre, 1998; St.Amant, 2019).

In the area of intercultural and international communication, scholars have examined the intersection of culture and cognition in different communication situations (Arasaratnam, 2014; Chen & Starosta, 1996; Koyanagi, 2018). These include the study of cross-cultural interactions in general as well as more specific instances (Escandell-Vidal, 2009). They also encompass the teaching of communication in international and intercultural contexts (Xiaohui & Li, 2011). Continued interest in these areas has produced texts that further explore such connections as related to academic theory (Fussell & Kreuz, 2014; Roskos-Ewoldsen & Monahan, 2007) as well as instructional practice (Sanborn & Jackson, 2018; Young, 2011).

Connections between cognition, communication, and practice have been more closely explored in the area of usability. Here, individuals have examined how the design of information affects individuals’ perceptions and uses of different products (Nielsen, 2012a; Norman, 2002). Such examinations have included more scholarly works (Cham et al., 2021; Kushniruk & Patel, 2004; Prastawa et al., 2019) covering theoretical examinations and empirical inquiries into this area. They have also included practitioner-oriented texts focused on addressing such dynamics when creating different informational products (Wendel, 2021; Yablonsky, 2020; Yocco, 2016).

This work in usability parallels research done in the affiliated field of technical communication. Such overlap includes examinations of how to integrate cognitive-based concepts and approaches from usability into technical communication practices (Albers, 2012; Cooke, 2010; Rivers, 2011). They also encompass ongoing discussions of how technical communicators can employ usability techniques to become more involved in systems and product development (Archraya, 2016; Carliner, 2000; Siau & Tan, 2005). Additionally, technical communication scholars have argued for the integration of cognitive aspects of usability into the educational processes (Cleary & Flammia, 2012; Cooke & Mings, 2005).

Within technical communication, the focus on these connections has expanded to include the adoption of cognitive-based usability approaches when studying international contexts including. Such work includes reviews localization processes, product design practices, and healthcare interactions (Batova, 2010; McDonald et al., 2012; Sun, 2012). Other technical communication scholars have noted how members of the field could adopt cognitive approaches from usability to expand more common professional practices including conducting research (McNely et al., 2015; Redish, 2010), crafting technical presentations (Garner et al., 2009), and even editing technical documents (Redish & Selzer, 1985; Soderston, 1985). More recently, technical communication researchers have begun to examine these connections as a mechanism for engaging in issues of social justice (Acharya, 2022; Cheung, 2017), exploring design thinking (Pope-Ruark et al., 2019; Verhulsdonck et al., 2021), and considering behavioral design practices (Verhulsdonck & Shalamova, 2020).

This article represents a continuation of this prior work at the intersection of technical communication, usability, and cognition. Specifically, it combines prior examinations of cognition and communication into a method for identifying the psychological dynamics affecting an audience's usability—and therefore communication—expectations. The approach described in this article involves the application of different mental models—or cognitive mechanisms—to examine how humans focus on, identify, and use different items. Technical communicators have discussed such factors per specific applications (Beck, 1994; Hailey & Hailey, 1998) or have examined such factors more generally or theoretically (Kilingsworth & Rosenberg, 1995; Winsor, 2001). Yet such dynamics have not been combined into a unified method for systematically identifying how mental models shape audience perception, comprehension, and use of information in technical communication contexts. The method described here provides such a framework. This method is also generative, for it can provide a foundation for crafting messages that better meet the cognitive dynamics affecting an audience's usability expectations for content. As such, this method can help technical communicators better understand how certain cognitive dynamics can shape communication processes. Understanding such factors requires one to consider how the conceptualization of ideas affects communication practices and related usability expectations.

Conceptualization and Communication

The human brain has limitations affecting how much sensory information it can engage with at one time (Paas et al., 2004; Sweller, 1988). To address these limitations, the brain often combines different sensory inputs into single units of information for easier processing (Cook, 2006; Pass et al., 2004; van Merrienboer & Sweller, 2010). Instead of the brain reviewing each aspect of an object as a separate item, it packages this sensory input into a single unit to process as one item versus as many different items (Sweller, 1988; Tse et al., 2007; Yamada & Itsukushima, 2013). When we look at a pen, for example, the brain does not address the related sensory input as multiple, separate items (e.g., color, size, texture, shape, etc.); rather, it combines all of that input into a single unit (i.e., a pen) for easier processing.

These units of information often take the form of mental models, which allow the brain to quickly organize sensory information into conglomerate “chunks” it can address more easily (Sweller, 1988; Tse et al., 2007; Yamada & Itsukushima, 2013). As a result, these models often affect how humans use items—including textual, visual, and multimedia content (St.Amant, 2022). The better communication professionals understand these dynamics, the more effectively they can create easy-to-use (i.e., usable) content for audiences (Meek, 2013). Similarly, the better communication students understand such factors, the better they can learn to identify and address audience expectations related to communication activities (St.Amant, 2022).

A cognitive approach to communication requires an understanding of how mental models affect the creation of content (Martin, 2021; Meek, 2013; Tyrkiel, 2021). Communication often involves two kinds of mental models. When humans think about the item central to a message, they often access an initial mental model that depicts what something looks like, sounds like, feels like, etc. (Aitchison, 1994; Meek, 2013; Rosch, 1978). When individuals think about a cup, for example, they often access a mental model for an object possessing features they associate with a cup (e.g., size, shape, texture, etc.). They next access a second mental model for how to perform an activity associated with that item (Eyal, 2014; Lindstrom, 2010; St.Amant, 2018). This second mental model allows individuals to see, hear, feel, etc. a process unfold in their mind—similar to watching a fully immersive mental movie. They then use words to describe what occurs in this second mental model, use images to depict that process, or use other media formats to re-create the dynamics appearing in that model. The audiences for such materials then uses this content to re-create a parallel mental model in their own mind (Meek, 2013; St.Amant, 2018).

Once audience members have re-created this mental model, they try to follow the process it depicts in order to perform the related activity (Meek, 2013; St.Amant, 2022). The more effectively the audience can re-create the mental model as depicted by the content creator, the better it can use that content to achieve an objective (Eyal, 2014; Meek, 2013; Lindstrom, 2010). This process of conveying and re-creating mental models can cause issues affecting the usability of content.

Models and Meaning

From a usability perspective, one needs to understand how mental models influence communication practices. The process of content creation based on mental models often involves multiple assumptions (Eyal, 2014; Tyrkiel, 2021). These include what the object central to a process resembles (e.g., “looks like”) and what using that item entails (e.g., how to use it) (Aitchison, 1994; Norman, 2002; Rosch, 1978). The sentence “Use the cup to take a drink of coffee” contains multiple assumptions including what a cup is and what features identify a cup as a cup. The sentence also contains assumptions for what a cup does (in this case, holds fluid), and how individuals use it (how to drink from a cup).

This sample sentence works—or is usable—for many readers because they have common assumptions of what these factors of cup, hold fluid, and drink encompass (Aitchison, 1994; Rosch, 1978). This commonality occurs because the audience's mental models for what a cup is and how it is used align with those of the content creator (Eyal, 2014; Lindstrom, 2010; Meek, 2013). If, however, an audience's mental models for “cup” did not contain such factors, then confusion could occur as audience members struggle to conceptualize the ideas being conveyed—for example, “What is a cup?” or “How do you drink from a cup?” (St.Amant, 2018, 2022).

The cup example reveals a core communication problem: the mental models underlying communication can differ between content creator and audience (Eyal, 2014; Meek, 2013; Norman, 2002; Tyrkiel, 2021). These differences occur because individuals learn—or develop—the mental models via experiences (Aitchison, 1994; Eyal, 2014; Lindstrom, 2010). Essentially, individuals’ experiences expose them to different items and activities during their lives. The more frequently individuals encounter a certain object or are exposed to a certain use of that object, the more those experiences shape the mental models those individuals rely on to conceptualize such items and actions (Aitchison, 1994; Tyrkiel, 2021).

Per the “cup” example: Individuals learn what a cup is, does, and how to use it via experiences where they observe others identifying the item (e.g., “This is a cup.”) and using it in certain ways (e.g., drinking from a cup). The more an individual is exposed to a hollow, cylindrical object with a handle as being a “cup,” the more their mental model for “cup” contains those expectations for the features something should have in order to be a cup. Similarly, the more individuals are exposed to examples of other persons drinking from cups, the more these activities become central to the mental model of how to use a cup. Accordingly, different experiences could result in the development of different mental models, and such variations can affect the usability of the associated content.

Consider a situation where individuals have only experienced cups being used to trap animals (e.g., placing a cup over an insect to catch it); in this instance, the phrase “Use the cup to take a drink of coffee.” might cause confusion. As the audience's mental model for the cup does not include the activity “drinking,” the notion of doing so would be new, unknown, and perhaps odd. Couple this factor with a mental model of cups used to trap animals, and the suggestion of “drink” might seem inappropriate (e.g., unsanitary) (see St.Amant, 2005). This example illustrates how differing mental models can cause communication issues that affect the usability of content.

In other cases, the audience might have been exposed to a different object associated with the term “cup”—say, a large, gilded chalice with no real opening to hold something (e.g., a trophy “cup”). In that case, the expectations of what a cup is and what features it has could differ between the content creator and the audience. Individuals whose mental model of the “cup” is a large trophy might consider it impossible to “Use the cup to take a drink of coffee,” as their mental model for a cup (i.e., its features and design) makes drinking from such a heavy, shallow object difficult to conceptualize. This situation represents another example of how differing mental models can cause usability problems (Atchison, 1994; Dube, 2021; Norman, 2002; Tyrkiel, 2021).

To address such issues, content creators must realize

Their communication practices are guided by mental models that have resulted from their own life experiences.

Their mental models for conceptualizing a process might differ from those of the audience who will use the content they create.

The need to identify and address their audience's mental models for a topic, item, or activity when creating related content for that audience.

By addressing these factors, individuals can create content audiences can more easily use.

The goals of a cognitive approach to communication involve

Identifying the mental models an audience uses to think about and communicate about a topic, object, or process.

Using this information to develop content that aligns with the audience's mental models for that topic, object, or process.

Content creators can use an approach called “mapping”—or identifying the dynamics of an audience's mental models—to achieve these goals.

Identifying Assumptions and Expectations

Mapping audience expectations involves identifying the mental models that subconsciously guide how individuals use items (St.Amant, 2018, 2022). These processes generally occur in a particular sequence. As a result, an issue with one part of the sequence affects how (or if) the brain can engage in the next process in the sequence (Eyal, 2014; Lindstrom, 2010; St.Amant, 2019). The ARCO method helps identify the mental models and the associated subconscious dynamics driving these processes.

ARCO stands for actualization, recognition, categorization, and operationalization—four activities the mind subconsciously performs when humans interact with content, objects, or other persons (St.Amant, 2019). The ARCO method applies cognitive concepts to examine the process an audience's mind performs when individuals use something. The four cognitive activities of the ARCO method involve determining

Actualization: What individuals focus attention on when using something.

Recognition: How individuals identify an item after focusing their attention on it.

Categorization: How individuals determine what an identified item does and know how to use that item accordingly.

Operationalization: How individuals select which potential use(s) of an item is/are appropriate in a given context.

These four processes collectively drive perception and behavior (Bargh & Morsella, 2008). They also represent core factors to address in relation to an audience's usability expectations (Norman, 2002; UXness, 2018).

As these processes occur subconsciously, individuals are rarely aware of when they perform them, nor do they usually notice how these processes occur in an interconnected sequence (Bargh & Morsella, 2008; UXness, 2018). These processes, however, affect the ease with which audiences understand and use content across various media (St.Amant, 2022; UXness, 2018). The ARCO method involves studying each process to determine how mental models affect the way(s) audiences use something (St.Amant, 2019, 2022). Foundational to this mapping is the realization that the content creator's assumptions cannot be projected onto an audience when conveying information to that audience (Meek, 2013; Norman, 2002; Tyrkiel, 2021). Rather, the content creator must interact with members of that audience—via interviews, focus groups, or a combination of both—to determine

What mental models an audience has for a topic and for the use of related content

and

How these mental models affect the way the audience uses content (Content Strategy Basics, 2022; Dube, 2021; Nielsen, 2012a).

The answers to such questions are central to an audience's perceptions of and responses to content.

Accordingly, the ARCO method involves

Identifying the audience for which content will be created.

Asking audience members to participate in data-collection activities (i.e., interviews and focus groups) for a content-creation project.

Using interviews and focus group data to identify the mental models audiences associated with each step in the process of using something.

Reviewing these findings to develop usable content for that audience (Content Strategy Basics, 2022; Dube, 2021; Nielsen, 2012a).

By asking audience members questions associated with each step in the ARCO method, content creators can determine how mental models shape an audience's usability expectations. Content creators can then use the resulting information to develop content (e.g., text, visuals, etc.) that better meets the audience's usability expectations (St.Amant, 2019). Mapping such ARCO dynamics works as follows:

Actualization

The first step in the ARCO method is Actualization—or what do audiences focus their attention on when using something (e.g., content) (St.Amant, 2019; Tyrkiel, 2021). At this initial step, the objective is to determine what individuals focus their attention on when performing a process. Central to this first step is findability, for individuals can only use the content they can locate in a situation (Nielsen, 2012a). Usable content must therefore be something audiences can readily find when seeking information in a context. Accordingly, ARCO mapping begins with identifying how mental models influence the process individuals use when searching for items to focus their attention on.

From a cognitive perspective, the process of searching and finding generally occurs in one of two ways:

Radom Searching: If individuals do not know what they are searching for, then contrast—or how greatly an item differs from its surroundings—becomes central to focusing attention (Wolfe, 1994, 2007). In these instances, individuals do not rely on mental models to guide behavior. Rather, all stimuli are “equal” in terms of how the mind perceives them. In such situations, the stimulus that stands out most from the rest becomes the thing on which individuals focus their attention. For example, when individuals are in new and unknown surroundings and do not know what to search for, bright colors or loud noises that stand apart from the related context tend to attract attention.

The central factor is that contrast—not color or design—attracts attention (Wolfe, 1994, 2007). Essentially, conventional wisdom advocating the use of bright colors to draw attention only works if that coloring allows an item to contrast markedly with its surroundings (e.g., a bright red “On” button on a dark-colored control panel). If the surroundings are also brightly colored, then it will be darker-colored items that contrast the most from—and attract attention in—that context. From a textual perspective, large print (e.g., a title or headline) only draws attention if it contrasts with smaller print around it, loud noises (e.g., computer error messages) only attract attention if they contrast with prior silence, etc.

Guided Searching: In certain cases, individuals might know what they are seeking. This is the point when mental models begin to influence usability via findability. When the audience seeks out a particular thing—or knows what it is searching for, individuals access a mental model representing what the item is. This model is comprised of the characteristics of that object—or central traits the audience associates with that item. Audience members then scan their environment to find items that match the characteristics of this mental model (Wolfe, 1994, 2007). Items that have enough characteristics in common with the model will become the focus of the audience's attention—or what an audience will focus on and consider in that setting.

When guided searching occurs, it is not contrast that drives how individuals focus attention. Rather, it is matching that attracts attention (Wolfe, 1994, 2007). Essentially, audiences find items that most closely match their mental model of the thing they wish to find. In guided searching, audiences often overlook high-contrast items and focus on finding a match to a related mental model. As a result, audiences might miss the intended content if it does not match the mental model that guides their search. This process is central to why audiences can overlook core content even if that content contrasts greatly from its surroundings. (Consider how slight changes in an interface's design can render it unusable to audiences familiar with prior versions of that interface.)

Identifying and addressing these initial expectations of findability is essential to creating usable content at its most fundamental level.

To determine which process an audience will use when searching, the content creator needs to ask audience members to answer questions such as

Have you ever performed this process or used this kind of item (the content to be created) before?

Example: “Have you ever used this software program – or a prior version of it – before?”

If yes,

What did you use for this process?

Example: “What software program did you use to do X?”—Asked to identify the specific experience that might have shaped an associated mental model used to locate something.

How often did you perform this process and/or use this kind of content before?

Example: “How often did you use software X in the past—monthly? Weekly? Daily?” This question helps determine how established a mental model might be as frequent usage often creates more established mental models for an item.

Can you tell me what you searched for when starting this process? Can you describe it for me?

Example: “What did you search for in order to start using software X? Can you describe that item for me?” This question helps identify the specific mental model that might guide searching activities and the specific characteristics of the model individuals seek to match when trying to locate a known item.

Responses to these questions help content creators determine if an audience will rely on random or guided searching when using content.

If an audience has performed a process or previously used similar content, then audience members likely have an associated mental model that guides how they locate the content central to starting the related activity. If the audience is unfamiliar with such content, then mental models will likely not guide their searching behavior. Instead, they will rely on contrast to determine what to focus their attention on in order to begin an activity. By identifying such seeking and finding expectations, individuals can design content audiences can easily find in order to use it at the start of a process.

Recognition

The next step in the ARCO method is Recognition – or can individuals recognize, or identify, the item on which they have focused their attention (St.Amant, 2019). At this stage, mental models again become important. If individuals cannot identify the content that caught their attention, then they cannot use it, and the ability to recognize something is tied to mental models (Atchison, 1994; Norman, 2002; St.Amant, 2022). When humans attempt to recognize the item that caught their attention, they engage in two interconnected activities. First, they review the characteristics of that item; next, they attempt to match the characteristics, or features, of that item to those of existing mental models they have for objects (Atchison, 1994; Rosche, 1978). If a new item has enough characteristics in common with an existing mental model, then the individual will identify that item per that match. If, for example, an item has enough characteristics in common with an individual's mental model for a pen, the individual will identify that item as a pen.

The dynamics involved in this identification process are different from those that affect prior guided searching processes. Just because individuals used a mental model to locate something via guided searching does not inherently mean the individual also recognized what that item is upon finding it (Aitchison, 1994; Norman, 2002) (these are two different processes). In both guided and random searching, once the audience has focused its attention on something, that audience next needs to identify what that object of focused attention is. Again, the matching of the features of the item to those of an audience's existing mental models is central to this process. Content creators therefore need to identify the mental models an audience uses to recognizes something upon finding it regardless of the approach the audience used to locate that item (Eyal, 2014; Keränen et al., 2016; St.Amant, 2022).

In the case of visual messaging, as with images or visual features of texts (e.g., formatting of primary headings), this matching process affects if audiences recognize an item once attention is focused on it. This recognition factor can influence if individuals are able to identify what a visual message conveys (for images) or how to read a text (for primary headings). It also affects if audiences recognize certain textual content based on the visual features of that content—such as “Does this document look like an instruction set/do I recognize this document as an instruction set based on page design/layout?” At this step in the process, knowing what something is affects if and how individuals will use that item. Breakdowns at this step can affect if an audience are able to use visual, verbal, or other content. If recognition is not possible, then the related content is not usable, and audiences might abandon it and search for something else.

In the case of verbal/textual communication, a different cognitive process happens in relation to recognition. Individuals often associate each word they use with a mental model for what that word represents (Atchison, 1994; Keränen et al., 2016). That mental model is comprised of the characteristics of the item individuals associate with a given term. Problems occur if the content creator and the audience associate different mental models—or mental models with different features—with the same word used in a text. Consider if the author of a text associates a mental model of a mobile phone with the word “phone.” The audience for that text, however, associates the mental model of a rotary dial telephone with that same term. If the author of an instructional document were to write “Be sure the screen of your phone is clean and the brightness is adjusted accordingly,” the related audience might not recognize the item the author references. An inability to recognize what the author is referencing could then occur, and the related content might be of limited use to that audience.

To avoid recognition issues, content creators need to engage with the intended audience via interviews and focus groups in order to collect data on the mental models the audience associates with recognizing and understanding the content. Essentially, content creators need to map out

What mental models audiences use to recognize items central to a message

What features audiences associated with recognizing such items

Performing such mapping involves asking audience members questions such as

Can you describe an X (type of content to create) for me?

Example: “Can you describe a login website for me?” or “Can you describe a user manual for me?”

What features does it (the content/item being created) have?

Example: “What features does a login website have?” or “What features does a user manual have?”

Can you (if possible) draw an example of X for me?

As you describe (X), I’ll draw a picture of it; can you let me know if I need to revise or change anything as I draw this picture?”

Example: “As you describe a login screen, I’ll draw an example of it; can you let me know if I need to revise or change anything as I draw that login screen?”

The objective of this questioning is twofold. First, content creators need to identify the mental model an audience associates with particular content (e.g., text, visual, multimedia content, etc.). Next, content creators need to identify the features the audience uses to identify that item per the related mental model. By mapping both factors, content creators can better determine how to design content audiences can recognize and use per their experiences and associated expectations.

Categorization

After recognizing what an item is, audience members need to categorize it—or determine what it does, for what it is used, or how it is used (Aitchison, 1994; Norman, 2002, 2005; German & Barrett, 2005). Usability issues can arise from assumptions that the recognition of an item indicates an understanding of its functions. Just because audience members recognize what something is, does not mean they inherently know what that item is or does or how to use it to perform an activity. Rather, function and use factors reflect the mental models audiences have developed from their experiences (German & Barrett, 2005; McCaffrey, 2012; Norman, 2002, 2005). As with recognition, different experiences can result in varying associations for the category to which a recognized item belongs and the related uses of an item based on that category.

Consider the key cards used to access hotel rooms in certain areas. An individual might recognize an item as a key card or conceptualize an expected depiction of a key card. This factor does not automatically mean the individual also knows how to use a key card within the context of a hotel. Based on relatively common experiences, many individuals might categorize key cards as a “key” used to open a door. Some individuals, however, might not know that certain audiences also associate hotel key cards with the category of “light switch.” This is because, in certain locations, key cards are also often inserted into a slot in a hotel room wall in order to activate the room's lights. If individuals are unaware hotel key cards can fall into the category of light activation mechanism, confusion could occur as guests try to determine why the lights in their room do not work.

For content creators, the factor to map is how audience members categorize items central to a document or message (Norman, 2002, 2005; St.Amant, 2022). Essentially, are audience members familiar with the particular function of something as presented in the associated content? If so, they could have an existing mental model to guide the use of that item. Relatively little, if any, content, would then be needed to explain such uses (e.g., “Use your key card to open your hotel room door and activate the room's lights”). If not, then content creators need to make audience members aware of that use (i.e., a new category for considering the item). Doing so involves creating content that explains previously unknown uses of an item to the related audience: For example, “Use your key card to activate the lights in your room. To do so, place your key card in the slot to the right of your door as indicated in the image below” (German & Barrett, 2005; Norman, 2002, 2005; St.Amant, 2022).

To map an audience's contextualization expectations, content creators need to interact with audience members via the questions:

What does X (type of content or design) do?

Example: “What does a hotel key card do?” or “What do you use a hotel key card to do?” If audience members do not recognize a particular category/use, then content creators need to include information specifying that use is (e.g., “You need to use your key card to activate the lights in your room.”) and explain the related process for using the item (e.g., “To activate your room lights with your key card, do the following:”).

Can you describe that process for me?

Example: “How do you use a hotel key card to open a door? To activate the lights in the room?” The fact an audience recognizes that an item can perform a function does not meant the audience also knows how to use the item to perform that function. (Just because an audience knows a key card can enable the lights in a room doesn’t mean they know how to use it to do so.) Likewise, the recognition of a function does not mean all individuals expect to perform it in similar ways. Answers to this question help address both factors and determine if certain content is needed to facilitate the use (or the intended use) of a recognized and categorized item.

Content creators can use the resulting answers to identify the uses audiences associate with certain content or the topic covered in that content. The mapping of such factors helps determine if audiences expect or require certain category-related content to use documentation or associated items.

Operationalization

The final step in the ARCO method is Operationalization—or determining the specific way audiences will use items in a context (St.Amant, 2019). Individuals often associate different categories—or uses—with an item (e.g., using a key card to open a door and to activate the lights in a room). The operationalization stage of the ARCO method maps factors that prompt individuals to select a specific use of an item or of content from all other possible uses of that item or content (e.g., the intended use of a written text, an infographic, a website, etc.).

At the operationalization stage, context—or the setting individuals are in when using an item/content—becomes important (Soegaard & Dam, n.d.; User-Centered Design Basics, 2022). A particular mental model, called a script, plays a central role at this point in the process. Scripts are the mental models humans have for how to engage in activities that are regularly performed in a certain location (Schank & Abelson, 1977; Tomkins, 1978, 1987). Once individuals know where they are, the script for how to act and interact in that location is activated, and individuals begin to engage with other persons and to use objects as depicted in that script (St.Amant, 2018, 2022). For example, once individuals recognize they are in a restaurant, their mind accesses the script for “restaurant.” That script guides them in how to find a table, order a meal, receive and eat that meal, and then pay and exit the restaurant. This script also contains other mental models the audience uses to recognize and interact with individuals (e.g., waitstaff) and items (e.g., menus) in that setting.

This behavior occurs subconsciously as individuals reflexively follows the behavior noted in the script for that location. As a result, scripts restrict the perceptions and uses of items to those functions associated with the location depicted in the script. This is why audiences seem to inherently know the specific use of objects in a location vs. struggle to determine the appropriate use of that item. So, at the operationalization stage, individuals know the specific way to use items they have focused their attention on and identified in a location.

Content creators thus need to map an audience's script for a location to understand how mental models shape the use of items and content in that setting (St.Amant, 2018, 2022). Such mapping involves

Determining the location where individuals will use a document or other communication materials (e.g., infographics, interfaces, etc.)

Identifying if individuals have a script for such contexts, and if so

Noting what items individuals expect to use, and how, in that setting (i.e., identifying other mental models the audience relies on locate, identify, and use items in that setting).

If mapping indicates the audience has a script that matches the objectives of the content creator, chances are the audience will use items as the content creator intends. If, however, research indicates audiences have

No existing script for how to use certain content in a location

A script that associates a different use of that content in a location

then the content creator must clarify the intended use of that content in the related context (e.g., “This digital guide is designed to help you install this software on your office computer. To use this digital guide to install the software in your office, you need to perform the following steps: …”). Such clarification either

Provides individuals who have no existing script with a new one that explains how to perform a process in a location

Augments an audience's existing scripts to help individuals more readily use the content as intended by the content creator.

Identifying and mapping an audience's script for a process (or identifying the lack of such a script) involves asking audience members the following questions:

Where do you perform X (intended activity associated with content)?

Example: “Where do you usually use software to perform your job activities?

Where do you usually do updates of that software?”

Can you describe that environment to me? If possible

Can you sketch out that setting for me?Or

Can I sketch this setting as you describe it, and you let me know if I need to change anything?

Example: “Can you describe the office where you use this software and do software updates? What is in it/there? Who is there?” Answers to these questions help identify variables to account for when developing content. If, for example, the office contains tool audience members expect to use during the process, the related content must reference the use of that tool in performing the process (Buxton, 2007; System Concepts, n.d.).

How do you perform this process in that setting? Can you describe how you perform this process?

Example: “How do you perform software updates in your office?” Answers to this question can help identify activities or items the content must include in order to address the audience's script expectations for that process.

How do you use this kind of content in that setting?

Example: “How do you use instructional guides to do software updates in your office?” The resulting responses help identify the medium the audience associates with the process (e.g., print or digital) and the design of related items (e.g., does a printed document need to lay flat so it remains open as individuals use it; does it need to have highly visible headings as individuals will shift their attention while using it).

The answers to these questions help identify the setting individuals associate with using content. These answers also help determine how associated scripts can affect the use of and design expectations for that content used in that setting.

Applications and Testing

The ARCO method of mapping audience expectations helps communication professionals and communication students identify factors that affect how audiences use content. Both practitioners and students can review the results of ARCO mapping to understand the mental model(s) shaping an audience's usability expectations for content. These results can help

Identify if an audience is familiar with certain content (or not) as well as identify the behavior audience members might use to locate and focus attention on content

Determine what mental models an audience might use to identify content and also determine the features the audience uses to identify such content

Note both the uses an audience associates with identified content and if audience members are familiar with the intended use of that content

Recognize both the location in which audiences will use content and the expectations the audience has for using content in that setting (St.Amant, 2018, 2019, 2022).

Communication professionals and communication students can apply this information to create content that meets an audience's usability expectations as related to mental models.

Initial content created from ARCO mapping, however, might not accurately reflect an audience's mental models (Nielsen 1997, 2010; Pernice, 2018). Certain information might have been missed during data collection in interviews and focus groups, or the interpretation of that data might require adjustment. For these reasons, individuals who use the ARCO method to create content should always test that content before finalizing it. Such testing must

Involve members of the intended audience (i.e., users of that content) (Tullis & Albert, 2013).

Follow ARCO factors to identify the mental models affecting the use of content (St.Amant, 2019).

Testing results can then be used to revise ARCO-related materials in order to better reflect the mental models affecting an audience's perceptions of usable content.

This testing should involve the content creator asking members of the intended audience to try using draft content to achieve a particular objective associated with that material (e.g., try to use draft instructions to perform that related task). This testing should take place in the setting audience members identified as where they perform that content-related activity (Context of use, n.d.; Tullis & Albert, 2013). These tests should also use think-aloud protocols to assess the usability of that draft content. Such protocols involve asking audience members to try using draft content to perform a particular activity (e.g., “Using this draft guide, try to update your office's computer software”) (Gibs, 2008; Nielsen, 2012b). As test subjects attempt to perform this activity, the content creator would

Observe audience members as they use draft content to perform the process

Record the audience member's activities (via written notes, video recording, audio recording, or a combination of these methods)

Record comments audience members make as they use draft content to perform a process.

At the start of this testing process, audience members would be told that they

Should speak/talk out loud as they use the draft content and specifically state

What they are about to do and why throughout the process

What are their reactions and perspectives throughout the process

Cannot ask questions about using the draft content or performing the process

Can stop the process at any time, but should note why they abandoned that process.

Once audience members complete or abandon the process, the observer would ask them a series of final questions (see Pernice, 2018) including

What aspects of the content were effective and easy to use?

What aspects of the content were ineffective, confusing, or difficult to use, and why?

What suggestions do you have for how to revise those items?

Content creators can use the results of these observations and question sessions to identify where content needs revision and how to revise it per an audience's usability expectations (Tullis & Albert, 2013). If time permits, the content creator should follow this same process to evaluate revised content in order to assess how effectively it meets the audience's usability expectations (Morales, 2020).

Final Thoughts

Competition for attention is fierce in the modern marketplace (The Economist, 2017). In this context, usability can provide organizations with an edge to stand out from their competitors (Ćwik, 2021; March, 1994). By understanding the cognitive dynamics shaping audience expectations, professional communicators and communication students can create content that addresses such factors. The ARCO method described here represents a mechanism both groups can use to map the mental models underlying such expectations. ARCO mapping results can then help with developing content that better addresses audience usability expectations in different contexts.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Kirk St.Amant

Author Biography

Kirk St.Amant is a professor and the Eunice C. Williamson Chair in Technical Communication at Louisiana Tech University where he serves as the Director of Louisiana Tech's Center for Health and Medical Communication (CHMC).

References

Acharya

K. A.

(2016). User value and usability in technical communication: A value-proposition design model. Communication Design Quarterly, 4(3), 26–34. https://doi.org/10.1145/3071078.3071083

Acharya

K. R.

(2022). Promoting social justice through usability in technical communication: An integrative literature review. Technical Communication, 69(1), 6–26. https://doi.org/10.55177/tc584938

Aitchison

(1994). Bad birds and better birds: Prototype theory. In Clark

V. P.

Eschholz

P. A.

Rosa

A. F.

(Eds.), Language: Introductory Readings (4th ed, pp. 445–459). St. Martin’s Press.

Albers

M. J.

(2012). Human-information interaction and technical communication: Concepts and frameworks. IGI Global.

Arasaratnam

L. A.

(2014). Ten years of research in intercultural communication competence (2003–2013): A retrospective. Journal of Intercultural Communication, 35(5), 66–73. https://doi.org/10.1080/13216597.2007.9674715

Barber

Badre

(1998, June). Culturability: The merging of culture and usability. In Rubart

Atzenbeck

(Eds.), Proceedings of the 4th Conference on Human Factors in Hypertext (pp. 1–10). Association for Computing Machinery.

Bargh

J. A.

Morsella

(2008). The unconscious mind. Perspectives on Psychological Science, 3(1), 73–79. https://doi.org/10.1111/j.1745-6916.2008.00064.x

Batova

(2010). Writing for the participants of international clinical trials: Law, ethics, and culture. Technical Communication, 57(3), 266–281.

Beck

C. E.

(1994). Perspectives on the self in communication: The cognition continuum and the Johari Window. Technical Communication, 41(4), 753–756.

10.

Berkenkotter

Huckin

T. N.

(1995). Genre knowledge in disciplinary communication: Cognition/culture/power. Routledge.

11.

Boichuk

(2020). The nine principles of UX design psychology: Can you predict the behavior of your users? UX Magazine, Retrieved, from https://uxmag.com/articles/the-nine-principles-of-ux-design-psychology-can-you-predict-the-behavior-of-your-users.

12.

Brand

A. G.

(1987). The why of cognition: Emotion and the writing process. College Composition and Communication, 38(4), 436–443. https://doi.org/10.2307/357637

13.

Buxton

(2007). Sketching user experiences: Getting the design right and the right design. Morgan Kaufmann.

14.

Carliner

(2000). Physical, cognitive, and affective: A three-part framework for information design. Technical Communication, 47(4), 561–576.

15.

Cham

Shakiry

Yates

(2021). Dual cognitive UXD and explainable AI. Journal of Usability Studies, 17(1), 1–11.

16.

Chen

G. M.

Starosta

W. J.

(1996). Intercultural communication competence: A synthesis. Annals of the International Communication Association, 19(1), 353–383. https://doi.org/10.1080/23808985.1996.11678935

17.

Cheung

I. W.

(2017). Plain language to minimize cognitive load: A social justice perspective. IEEE Transactions on Professional Communication, 60(4), 448–457. https://doi.org/10.1109/TPC.2017.2759639

18.

Clarke

Cornelissen

(2011). Language, communication, and socially situated cognition in entrepreneurship. Academy of Management Review, 36(4), 776–778. https://doi.org/10.5465/amr.2011.0192

19.

Cleary

Flammia

(2012). Preparing technical communication students to function as user advocates in a self-service society. Journal of Technical Writing and Communication, 42(3), 305–322. https://doi.org/10.2190/TW.42.3.g

20.

Cognition (2022). APA Dictionary of Psychology – American Psychological Association. Retrieved, from https://dictionary.apa.org/cognition.

21.

Content strategy basics (2022). usability.gov. Retrieved, from https://www.usability.gov/what-and-why/content-strategy.html.

22.

Context of use (n.d.). Interaction Design Foundation. Retrieved, from https://www.interaction-design.org/literature/book/the-glossary-of-human-computer-interaction/context-of-use.

23.

Cook

M. P.

(2006). Visual representations in science education: The influence of prior knowledge and cognitive load theory on instructional design principles. Science Education, 90(6), 1073–1019. https://doi.org/10.1002/sce.20164

24.

Cooke

(2010). Assessing concurrent think-aloud protocol as a usability test method: A technical communication approach. IEEE Transactions on Professional Communication, 53(3), 202–215. https://doi.org/10.1109/TPC.2010.2052859

25.

Cooke

Mings

(2005). Connecting usability education and research with industry needs and practices. IEEE Transactions on Professional Communication, 48(3), 296–312. https://doi.org/10.1109/TPC.2005.853938

26.

Ćwik

(2021). Why usability is key to your digital product success? KISS Digital. Retrieved, from https://kissdigital.com/blog/why-usability-is-key-to-your-digital-product-success.

27.

Dube

(2021). The psychology in UX design-mental models. DVT Software Engineering. Retrieved, from https://medium.com/dvt-engineering/mental-models-c9b0f95144.

28.

Escandell-Vidal

(2009). Social cognition and intercultural communication. Intercultural business communication and simulations and gaming methodology. In Guillén Nieto

Vargas-Sierra

Marimón-Llorca

(Eds.), Intercultural Business Communication and Simulation and Gaming Methodology (pp. 65–96). Peter Lang.

29.

Eyal

(2014). Hooked: How to build habit-forming products. Portfolio/Penguin Books.

30.

Fussell

S. R.

Kreuz

R. J.

(Eds.) (2014). Social and cognitive approaches to interpersonal communication. Psychology Press.

31.

Garner

J. K.

Alley

Gaudelli

A. F.

Zappe

S. E.

(2009). Common use of PowerPoint versus the assertion–evidence structure. Technical Communication, 56(4), 331–345.

32.

German

T. P.

Barrett

H. C.

(2005). Functional fixedness in a technologically sparse culture. Psychological Science, 16(1), 1–5. https://doi.org/10.1111/j.0956-7976.2005.00771.x

33.

Gibbs

W. J.

(2008). Examining users on news provider websites: A review of methodology. Journal of Usability Studies, 3(3), 129–148.

34.

Hailey

D. E.

Hailey

(1998). Hypermedia, multimedia, and reader cognition: An empirical study. Technical Communication, 45(3), 330–342.

35.

Honeycutt

J. M.

Cantrill

J. G.

(2014). Cognition, communication, and romantic relationships. Routledge.

36.

Imhof

Välikoski

T. R.

Laukkanen

A. M.

Orlob

(2014). Cognition and interpersonal communication: The effect of voice quality on information processing and person perception. Studies in Communication Sciences, 14(1), 37–44. https://doi.org/10.1016/j.scoms.2014.03.011

37.

Keränen

Syrjälä

Salonen

Takkinen

(2016). The usability of the annotation. In Proceedings of the 7th Workshop on the Representation and Processing of Sign Languages: Corpus Mining (pp. 111–116). Institute for German Sign Language and Communication of the Deaf.

38.

Killingsworth

M. J.

Rosenberg

M. E.

(1995). The icon as a problem in cognition and social construction: Complexity and consensual domains in technical rhetoric. IEEE Transactions on Professional Communication, 38(4), 216–227. https://doi.org/10.1109/47.475593

39.

Koerner

(2007). Social cognition in family communication: Family communication patterns theory. In Roskos-Ewoldsen

D. R.

Monahan

J. L.

(Eds.), Communication and Social Cognition: Theories and Methods (pp. 197–216). Lawrence Erlbaum Associates.

40.

Koerner

F. A.

Mary Anne

(2002). Understanding family communication patterns and family functioning: The roles of conversation orientation and conformity orientation. Annals of the International Communication Association, 26(1), 36–65. https://doi.org/10.1080/23808985.2002.11679010

41.

Koyanagi

(2018). Impact of intercultural communication during short-term study-abroad of Japanese students: Analysis from a perspective of cognitive modification. Journal of Intercultural Communication Research, 47(2), 105–120. https://doi.org/10.1080/17475759.2018.1435423

42.

Kushniruk

A. W.

Patel

V. L.

(2004). Cognitive and usability engineering methods for the evaluation of clinical information systems. Journal of Biomedical Informatics, 37(1), 56–76. https://doi.org/10.1016/j.jbi.2004.01.003

43.

Lindstrom

(2010). Buyology: Truth and lies about why we buy. Broadway Books.

44.

Liu

Yang

(2021). Public support for COVID-19 responses: Cultural cognition, risk perception, and emotions. Health Communication, 38, 1–11. https://doi.org/10.1080/10410236.2021.1965710

45.

March

(1994). Usability: the new dimension of product design. Harvard Business Review. Retrieved, from https://hbr.org/1994/09/usability-the-new-dimension-of-product-design.

46.

Martin

(2021). 5 Cognitive psychology theories that contribute to the quality of UX design. UX Magazine. Retrieved, from https://uxmag.com/articles/5-cognitive-psychology-theories-that-contribute-to-the-quality-of-ux-design.

47.

McCaffrey

(2012). Innovation relries on the obscure. Psychological Science, 23(3), 215–218. https://doi.org/10.1177/0956797611429580

48.

McDonald

Edwards

H. M.

Zhao

(2012). Exploring think-alouds in usability testing: An international survey. IEEE Transactions on Professional Communication, 55(1), 2–19. https://doi.org/10.1109/TPC.2011.2182569

49.

McNely

Spinuzzi

Teston

(2015). Contemporary research methodologies in technical communication. Technical Communication Quarterly, 24(1), 1–13. https://doi.org/10.1080/10572252.2015.975958

50.

Meek

(2013). Basics of communication: The communication basics we all need to know. Psychology Today. Retrieved, from https://www.psychologytoday.com/us/blog/notes-self/201307/basics-communication.

51.

Miller

C. R.

(1984). Genre as social action. Quarterly Journal of Speech, 70(2), 151–167. https://doi.org/10.1080/00335638409383686

52.

Miller

C. R.

Selzer

(1985). Special topics of argument in engineering reports. In Odell

Goswami

(Eds.), Writing in Non-Academic Settings (pp. 309–341). New York: Guilford Publications.

53.

Morales

(2020). All you need to know about iterative usability testing. Adobe XD Ideas. Retrieved, from https://xd.adobe.com/ideas/process/user-testing/process-user-testing-iterative-usability-testing-best-practices/.

54.

Nielsen

(2012a). Usability 101: Introduction to usability. Nielsen Norman Group. Retrieved, from https://www.nngroup.com/articles/usability-101-introduction-to-usability/.

55.

Nielsen

(2012b). Thinking aloud: The #1 usability tool. Nielsen Norman Group. Retrieved, from https://www.nngroup.com/articles/thinking-aloud-the-1-usability-tool/.

56.

Nielsen

(1997). The use and misuse of focus groups. Nielsen Norman Group. Retrieved, from https://www.nngroup.com/articles/focus-groups/.

57.

Nielsen

(2010). Interviewing users. Nielsen Norman Group. Retrieved, from https://www.nngroup.com/articles/interviewing-users/.

58.

Norman

(2002). The design of everyday things. Basic Books.

59.

Norman

. (2005). Emotional design: Why we love (or hate) everyday things. Cambridge, MA: Basic Books.

60.

Pass

Renkl

Sweller

(2004). Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32(1), 1–8. https://doi.org/10.1023/B:TRUC.0000021806.17516.d0

61.

Pernice

(2018). User interviews: How, when, and why to conduct them. Nielsen Norman Group. Retrieved, from https://www.nngroup.com/articles/user-interviews/.

62.

Planalp

(1993). Communication, cognition, and emotion. Communications Monographs, 60(1), 3–9. https://doi.org/10.1080/03637759309376288

63.

Pope-Ruark

Tham

Moses

Conner

(2019). Introduction to special issue: Design-thinking approaches in technical and professional communication. Journal of Business and Technical Communication, 33(4), 370–375. https://doi.org/10.1177/1050651919854054

64.

Prastawa

Ciptomulyono

Laksono-Singgih

Hartono

(2019). The effect of cognitive and affective aspects on usability. Theoretical Issues in Ergonomics Science, 20(4), 507–531. https://doi.org/10.1080/1463922X.2018.1547458

65.

Redish

(2010). Technical communication and usability: Intertwined strands and mutual influences. IEEE Transactions on Professional Communication, 53(3), 191–201. https://doi.org/10.1109/TPC.2010.2052861

66.

Redish

J. C.

Selzer

(1985). The place of readability formulas in technical communication. Technical Communication, 32(4), 46–52.

67.

Rivers

N. A.

(2011). Future convergences: Technical communication research as cognitive science. Technical Communication Quarterly, 20(4), 412–442. https://doi.org/10.1080/10572252.2011.591650

68.

Rosch

(1978). Principles of categorization. In Rosch

Lloyd

B. L.

(Eds.), Cognition and Categorization (pp. 27–48). Lawrence Erlbaum.

69.

Roskos-Ewoldsen

D. R.

Monahan

J. L.

(Eds.). (2007). Communication and social cognition: Theories and methods. Lawrence Erlbaum Associates.

70.

Sanborn

F. W.

Harris

R. J.

(2018). A cognitive psychology of mass communication (7th ed). Routledge.

71.

Schank

R. C.

Abelson

R. P.

(1977). Scripts, plans, goals, and understanding. Erlbaum Associates.

72.

Siau

Tan

(2005). Technical communication in information systems development: The use of cognitive mapping. IEEE Transactions on Professional Communication, 48(3), 269–284. https://doi.org/10.1109/TPC.2005.853933

73.

Sillars

Parry

(1982). Stress, cognition, and communication in interpersonal conflicts. Communication Research, 9(2), 201–226. https://doi.org/10.1177/0093650820090020

74.

Soderston

(1985). The usability edit: A new level. Technical Communication, 32(1), 16–18.

75.

Soegaard

Dam

R. F.

(n.d.). The encyclopedia of human-computer interaction (2nd ed). Interaction Design Foundation. Retrieved, from https://public-assets.interaction-design.org/ebooks/hci/hci.pdf.

76.

Spinuzzi

(2004). Four ways to investigate assemblages of texts: Genre sets, systems, repertoires, and ecologies. In Tilley

Huang

(Eds.), Proceedings of the 22nd annual international conference on Design of communication: The engineering of quality documentation (pp. 110–116). Association for Computing Machinery.

77.

Spinuzzi

Nelson

Thomson

K. S.

Lorenzini

French

R. A.

Pogue

Burback

S. D.

Momberger

(2014). Making the pitch: Examining dialogue and revisions in entrepreneurs’ pitch decks. IEEE Transactions on Professional Communication, 57(3), 158–181. https://doi.org/10.1109/TPC.2014.2342354

78.

St.Amant

(2005). A prototype theory approach to international website analysis and design. Technical Communication Quarterly, 14(1), 73–91. https://doi.org/10.1207/s15427625tcq1401_6

79.

St.Amant

(2018). Reflexes, reactions, and usability: Examining how prototypes of place can enhance UXD practices. Communication Design Quarterly, 6(1), 45–53. https://doi.org/10.1145/3230970.3230976

80.

St.Amant

(2019). Ethos prototypes: The intersection of rhetoric, cognition, and communicating health policy internationally. World Medical and Health Policy, 11(4), 464–473. https://doi.org/10.1002/wmh3.323

81.

St.Amant

(2022). Context, cognition, and the dynamics of design thinking: Cognitive methods for understanding the situational variables affecting usable design. Technical Communication, 69(1), 26–38. https://doi.org/10.55177/tc796562

82.

Sun

. (2012). Cross-cultural technology design: Creating culture-sensitive technology for local users. New York: Oxford University Press.

83.

Sweller

(1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4

84.

System Concepts (n.d.). How mental models enhance usability. Retrieved, from https://www.system-concepts.com/insights/how-mental-models-enhance-usability/.

85.

The Economist (2017, Feb. 9). The battle for consumers’ attention: Forget the long tail. Retrieved, from https://www.economist.com/special-report/2017/02/09/the-battle-for-consumers-attention.

86.

Theiss

J. A.

Solomon

D. H.

(2006). Coupling longitudinal data and multilevel modeling to examine the antecedents and consequences of jealousy experiences in romantic relationships: A test of the relational turbulence model. Human Communication Research, 32(4), 469–503. https://doi.org/10.1111/j.1468-2958.2006.00284.x

87.

Tomkins

S. S.

(1978). Script theory: Differential magnification of affects. Nebraska Symposium on Motivation, 26, 201–236.

88.

Tomkins

S. S.

(1987). Script theory. In Arnoff

Rabin

A. I.

Zucker

R. A.

(Eds.), The Emergence of Personality (pp. 147–216). Springer.

89.

Tse

Langston

R. F.

Kakeyama

Bethus

Spooner

P. A.

Wood

E. R.

Witter

M. P.

Morris

R. G. M.

(2007). Schemas and memory consolidation. Science, 316(76), 76–82. https://doi.org/10.1126/science.1135935

90.

Tullis

Albert

(2013). Measuring the user experience: Collecting, analyzing, and presenting usability metrics. Morgan Kaufmann.

91.

Tyrkiel

(2021). How mental models affect both users and designers. Editor X. Retrieved, from https://www.editorx.com/shaping-design/article/mental-models.

92.

User-Centered Design Basics (2022). usability.gov. Retrieved, from https://www.usability.gov/what-and-why/user-centered-design.html.

93.

UXness (2018). What is the subconscious mind? Retrieved, from https://medium.com/uxness/what-is-the-subconscious-mind-fc7ce9d3162f.

94.

van Merrienboer

J. J. G.

Sweller

(2010). Cognitive load theory in health professional education: Design principles and strategies. Medical Education, 44(1), 85–93. https://doi.org/10.1111/j.1365-2923.2009.03498.x

95.

Verhulsdonck

Howard

Tham

(2021). Investigating the impact of design thinking, content strategy, and artificial intelligence: A “streams” approach for technical communication and user experience. Journal of Technical Writing and Communication, 51(4), 468–492. https://doi.org/10.1177/00472816211041951

96.

Verhulsdonck

Shalamova

(2020). Creating content that influences people: Considering user experience and behavioral design in technical communication. Journal of Technical Writing and Communication, 50(4), 376–400. https://doi.org/10.1177/004728161988028

97.

Virtanen

(2011). Text, discourse, and cognition: An introduction. In Virtanen

(Ed.), Approaches to Cognition Through Text and Discourse (pp. 1–16). Walter de Gruyter.

98.

Wendel

(2021). Designing for behavior change: Applying psychology and behavioral economics (2nd ed). O’Reilly.

99.

What is Cognition (n.d.). Psychology – OpenStaxCollege. Retrieved, from https://opentext.wsu.edu/psych105nusbaum/chapter/what-is-cognition/.

100.

Williams-Piehota

Schneider

T. R.

Pizarro

Mowad

Salovey

(2003). Matching health messages to information-processing styles: Need for cognition and mammography utilization. Health Communication, 15(4), 375–392. https://doi.org/10.1207/S15327027HC1504_01

101.

Winsor

D. A.

(2001). Learning to do knowledge work in systems of distributed cognition. Journal of Business and Technical Communication, 15(1), 5–28. https://doi.org/10.1177/105065190101500101

102.

Wolfe

J. M.

(1994). Guided search 2.0: A revised model of visual search. Psychonomic Bulletin and Review, 1(2), 202–238. https://doi.org/10.3758/BF03200774

103.

Wolfe

J. M.

(2007). Guided search 4.0: Current progress with a model of visual search. Integrated Models of Cognitive Systems. Oxford University Press.

104.

Xiaohui

(2011). Teacher cognition of intercultural communicative competence in the Chinese ELT context. Intercultural Communication Studies, 20(1), 175–192. https://doi.org/10.3389/fpsyg.2022.939516

105.

Yablonsky

(2020). Laws of UX: Using psychology to design better products & services. O’Reilly.

106.

Yamada

Itsukushima

(2013). The effects of schema on recognition memories and subjective experiences for actions and objects. Japanese Psychological Research, 55(4), 366–377. https://doi.org/10.1111/jpr.12016

107.

Yocco

V. S.

(2016). Design for the mind: Seven psychological principles of persuasive design. Manning.

108.

Young

(2011). How audiences decide: A cognitive approach to business communication. Routledge.