Journal of Software Engineering Research and Development, 2022, 10:4, doi: 10.5753/jserd.2021.1878  

  This work is licensed under a Creative Commons Attribution 4.0 International License.  

 

Investigating Knowledge Management in Human-

Computer Interaction Design 

Murillo V. H. B. Castro [ Federal University of Espírito Santo | murillo.castro@aluno.ufes.br ] 

Simone D. Costa [ Federal University of Espírito Santo| simone.costa@ufes.br ] 

Monalessa P. Barcellos [ Federal University of Espírito Santo| monalessa@inf.ufes.br ] 
Ricardo de A. Falbo [ Federal University of Espírito Santo | falbo@inf.ufes.br ]  

 

Abstract 

Developing interactive systems is a challenging task. It involves concerns related to human-computer 

interaction (HCI), such as usability and user experience. Therefore, HCI design must be addressed when 

developing such systems. HCI design often involves people with different backgrounds, which makes 

communication and knowledge transfer a challenging issue. In this scenario, knowledge management can support 

understanding concepts from different knowledge areas and help learn from previous experiences. Aiming at 

investigating how knowledge management has supported HCI design and contributed to the development of 

interactive systems, we performed a mapping study in the literature and analyzed 15 publications reporting the use 

of knowledge management in HCI design. Following that, we conducted a survey with 39 HCI design professionals 

to find out how knowledge has been managed in their HCI design practice. In this paper, we present the studies 

and discuss their main findings. In summary, the results indicate that knowledge management has been used in 

HCI design mainly to improve product quality and reduce the effort and time spent on design activities. However, 

there is a need for simpler and more practical knowledge-based solutions to support HCI design. Such approaches 

would be capable of reaching more HCI design practitioners that could benefit from them. 

Keywords: HCI Design, Mapping Study, Survey, Knowledge Management, Interactive System 

 

1  Introduction 

The interest in interactive systems and their im-

pact on people’s life has promoted the study and 

practice of usability (Carroll, 2014). Usability is 

a key aspect of a successful interactive system 

and is related to user efficiency and satisfaction 

when interacting with the system. For an interac-

tive system to reach high usability levels, it is nec-

essary to take human-computer interaction (HCI) 

design aspects into account during its develop-

ment process (Carroll, 2014). 

HCI is concerned with usability and other as-

pects related to the interaction between users and 

computer systems, necessary to produce more us-

able software (Carroll, 2014). It involves 

knowledge from multiple fields, such as ergo-

nomics, cognitive science, user experience, hu-

man factors, among others (Sutcliffe, 2014). Due 

to the diverse body of knowledge involved when 

designing interactive systems, interactive system 

development teams are frequently multidiscipli-

nary, joining people from different backgrounds, 

with their own technical language, terms and 

knowledge. Collaboration among team members 

is not straightforward, since HCI designers and 

developers, for example, look at the same prob-

lem under different perspectives, which leads to 

difficulties that include a lack of a shared vocab-

ulary and harsh epistemological conflicts (Neto 

et al., 2020). Even the conceptualization of the 

product may be conflicting among different 

stakeholders, which hampers communication and 

knowledge transfer (Carroll, 2014; Rogers et al., 

2011).  

Developing software is a knowledge-inten-

sive task. Knowledge Management (KM) princi-

ples and practices have been successfully applied 

to support knowledge capture, storage, use and 

transfer in the software development context in 

general (Rus & Lindvall, 2002; Valaski et al., 

2012). KM can also be helpful to address chal-

lenges in the design of interactive systems since 

it might provide support to capture and represent 

knowledge in an accessible and reusable way and 

facilitate collaboration among team members. 

For example, design solutions developed by an 

organization can be stored and related to the re-

quirements that motivate them, components and 

patterns used to build them and evaluation re-

sults. As a result, the team can learn from previ-

ous experiences and share a common understand-

ing of the system, producing better products and 

performing processes more efficiently. 

Considering the challenges of designing in-

teractive systems, mainly due to the diversity of 

knowledge and people involved, and the potential 

of KM to help address those challenges, we de-

cided to investigate the use of KM in HCI design. 
Although KM can be used in different domains 

and there are some general motivations for using 

it (e.g., knowledge structuring) and benefits (e.g., 

improve knowledge reuse) provided by its use, 

KM can be applied to solve specific problems in 

each domain, different techniques can be used, 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

and so on. Thus, the main question that guided 

our investigation refers to how KM has been used 

in the HCI design domain. Besides investigating 

general motivations and benefits observed in the 

use of KM in the HCI design domain, we also in-

tended to identify specificities of the use of KM 

in that domain. First, we searched for secondary 

studies addressing the research topic. Since we 

did not find any, we decided to perform a system-

atic mapping in the literature. We analyzed 12 

different KM approaches used in HCI design, 

identified from 15 publications. In general, KM 

has aided in HCI design mainly by enabling rep-

licability of knowledge and solutions, improving 

product quality and communication. However, 

difficulty to generalize knowledge, issues related 

to features of the system and low engagement of 

the team have been pointed out as challenges to 

implement KM in the HCI design context. After 

investigating the literature, we performed a sur-

vey with 39 Brazilian HCI design practitioners 

that were asked about how knowledge has been 

managed in HCI design practice. Most partici-

pants are concerned with managing HCI design 

knowledge and perceive that KM helps them to 

improve product quality and reduce effort and 

time spent on HCI design activities. They follow 

organizational or individual KM practices and 

apply technologies such as brainstorming, mental 

models and electronic spreadsheets. 

This paper presents our studies (the mapping 

study and the survey) and their main results. It 

extends our previous work (Castro et al., 2020), 

in which we presented the main results of our 

mapping study, by adding information about the 

survey and presenting a more comprehensive 

view of the mapping results, updating the search 

period and providing new information (e.g., new 

graphs and details about the identified KM ap-

proaches). The mapping and the survey results 

are further analyzed together, providing an over-

view of the research and practice of KM in HCI 

design and pointing out some gaps that can be ad-

dressed in future research. 

The paper is organized as follows: Section 2 

provides the background for the paper, address-

ing HCI design and KM; Section 3 concerns the 

mapping study; Section 4 addresses the survey; 

Section 5 provides a consolidated view of the 

mapping and the survey results; and Section 6 

presents our final considerations. 

2  Background 

2.1 HCI Design 

HCI design focuses on how to design a system to 

support the user to achieve her goals through the 

interaction between her and the system (Sutcliffe, 

2014). It is concerned with usability and other 

important attributes such as user experience, ac-

cessibility and communicability. Usability is the 

extent to which a system, product or service can 

be used by specified users to achieve specified 

goals with effectiveness, efficiency and satisfac-

tion in a specified context of use (ISO, 2019). It 

addresses the effort and ease of the user during 

the interaction, considering her cognitive, per-

ceptive and motor skills. User experience relates 

to users' emotions and feelings and is essential for 

interaction design because it takes into account 

how a product behaves and is used by people in 

the real world (Rogers et al., 2011). Accessibility 

refers to the removal of barriers that prevent in-

terface and interaction access. Finally, communi-

cability concerns the ability of the interface to 

communicate design logic to the user (De Souza, 

2005). 

HCI design is user-centered, hence it is said 

User-Centered Design (UCD) (Chammas et al., 

2015). UCD is based on ergonomics, usability 

and human factors. It focuses on the use and de-

velopment of interactive systems, with an empha-

sis on making products usable and understanda-

ble. It puts human needs, capabilities and behav-

ior first, then designs the system to accommodate 

them. Its main principles are user focus (its char-

acteristics, needs and objectives), observable 

metrics (user performance and reactions) and it-

erative design (repeat as often as needed) 

(Chammas et al., 2015; ISO, 2019). The term Hu-

man-Centered Design (HCD) has been adopted 

in place of UCD to emphasize the impact on all 

stakeholders and not just on those considered us-

ers (ISO, 2019). 

In general, UCD involves: understand and 

specify context of use, which aims to study the 

product users and intended uses; specify require-

ments, which aims to identify user needs and 

specify functional and other requirements for the 

product; produce design solutions, which aims to 

achieve the best user experience and includes the 

production of artifacts such as prototypes and 

mock-ups that will be used in the future as a basis 

for developing the system; and evaluation, when 

the user evaluates the results produced in the pre-

vious activities (ISO, 2019). 

HCI design can be understood as an intensive 

knowledge process, requiring effective mecha-

nisms to collaboratively create and support a 

shared understanding about users, the system, its 

purposes, context of use and the design necessary 

for the user to achieve her goals. Therefore, HCI 

design could take advantage of KM solutions. 

2.2 Knowledge Management 

According to Schneider (2009), knowledge is a 

human specialty stored in people's minds, ac-

quired through experience and interaction with 

their environment. Historically, an organization’s 

knowledge was undocumented, being repre-

sented through the skills, experience and 

knowledge of its professionals, typically tacit 

knowledge (Rus & Lindvall, 2002), which made 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

its use and access limited and difficult (O’Leary, 

1998). 

Knowledge Management (KM) aims to trans-

form tacit and individual knowledge into explicit 

and shared knowledge. By raising individual 

knowledge to the organizational level, KM pro-

motes knowledge propagation and learning, mak-

ing knowledge accessible and reusable across the 

entire organization (O’Leary, 1998; Rus & 

Lindvall, 2002; Schneider, 2009). Knowledge 

helps software organizations to react faster and 

better, supporting more accurate and precise re-

sponses, which contributes to increasing software 

quality and client satisfaction (Schneider, 2009). 

When an organization implements KM, its expe-

riences and knowledge are recorded, evaluated, 

preserved, designed and systematically propa-

gated to solve problems (Schneider, 2009). Thus, 

KM addresses knowledge in its evolution cycle, 

which consists in creating, capturing, transform-

ing, accessing and applying knowledge (Rus & 

Lindvall, 2002; Schneider, 2009). 

In the software process context, KM works 

for explicitly and systematically managing 

knowledge, addressing knowledge acquisition, 

storage, organization, evolution, retrieval and us-

age. Among other aspects, KM has been applied 

in the software development context to support 

document management, competence manage-

ment, experts identification, software reuse, sup-

port learning and product and project memory 

(Rus & Lindvall, 2002). By investigating empir-

ical studies of KM in Software Engineering, 

Bjørnson & Dingsøyr (2008) reported that the 

studies’ major focus has been on explicit 

knowledge and there is a need to focus also on 

tacit knowledge.  

3 Systematic Mapping: KM in 

HCI Design according to the 

literature 

Considering the challenges involving knowledge 

transfer and sharing in the HCI design context 

and the benefits of using KM in the software de-

velopment context, we decided to investigate the 

use of KM in HCI design through a mapping 

study. A mapping study is a secondary study de-

signed to give an overview of a research area 

through classification and counting contributions 

concerning the categories of that classification. It 

makes a broad study on a topic of a specific 

theme and aims to identify available evidence 

about that topic (Petersen et al., 2015). Moreover, 

the panorama provided by a mapping study al-

lows identifying issues in the researched topic 

that could be addressed in future research. We 

followed the process defined in Kitchenham & 

Charters (2007), which comprises three phases: 

(i) Planning: In this phase, the topic of interest, 

study context and object of the analysis are estab-

lished. The research protocol to be used to per-

form the research is defined, containing all the 

necessary information for a researcher to perform 

the research: research questions, sources to be 

searched, publication selection criteria, proce-

dures for data storage and analysis and so on. The 

protocol must be evaluated by experts and tested 

to verify its feasibility, i.e., if the results obtained 

are satisfactory and if the protocol execution is vi-

able in terms of time and effort. Once the protocol 

is approved, it can be used to conduct the re-

search. 

(ii) Conducting: In this phase, the research is per-

formed according to the protocol. Publications are 

selected and data are extracted, stored and quanti-

tatively and qualitatively analyzed. 

(iii) Reporting: In this phase, the produced re-

search results are recorded and made available to 

potentially interested parties. 

Next, in Section 3.1, we present the research 

protocol followed in our study. Section 3.2 sum-

marizes the mapping study results.  Section 3.3 

discusses the results and Section 3.4 regards 

threats to validity. 

3.1 Research Protocol 

This section presents the protocol used in the 

mapping study. It was defined gradually, being 

tested with an initial set of publications and then 

refined until we reached the final protocol, which 

was evaluated by another researcher, resulting in 

the protocol used in the study and presented in 

this section. 

The study goal was to investigate the use of 

KM in the HCI design context. For achieving this 

goal, we defined the research questions presented 

in Table 1. 

Table 1. Systematic Mapping: research questions and their rationale. 

ID Research Question Rationale 

RQ1 When and where have publications been pub-

lished? 

Give an understanding of when and where (journal/conference/work-

shop) publications about KM in the HCI design context have been pub-

lished. 

RQ2 Which types of research have been done? Investigate which type of research is reported in each selected publica-

tion. We consider the classification defined in (Wieringa et al., 2005). 

This question is useful to evaluate the maturity stage of the research topic.  

RQ3 Why has KM been used in the HCI design con-

text? 

Understand the purposes and reasons for using KM in the HCI design and 

verify if there have been predominant motivations. 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

RQ4 Which knowledge has been managed in the 

HCI design context? 

Investigate which knowledge items have been managed in the HCI de-

sign context, aiming to verify if some of them have been managed more 

frequently and if there has been more interest in certain HCI aspects. 

 

RQ5 How is the managed knowledge related to the 

HCI design process? 

Understand, in the context of the HCI design process, where the man-

aged knowledge has come from and where it has been used. 

 

RQ6 How has KM been implemented in the HCI de-

sign context? 

Investigate how KM has been implemented in the HCI context in terms 

of the adopted technologies. 

 

RQ7 Which benefits and difficulties have been no-

ticed when using KM in the HCI design con-

text? 

Identify the benefits and difficulties of using KM in the HCI design con-

text and analyze if there is a relation between them. 

 

 

RQ1 and RQ2 are common systematic map-

ping questions that provide a general panorama 

of the research topic. The other questions aim to 

investigate why (RQ3 and RQ7), how (RQ4 and 

RQ6) and when (RQ5) KM has been used in HCI 

design, which are important questions to provide 

an understanding of the research topic.  

The search string adopted in the study con-

tains two groups of terms joined with the operator 

AND. The first group includes terms related to 

HCI design. The general term “Human-Com-

puter Interaction” was used to provide wider 

search results. The second group includes terms 

related to Knowledge Management. Within the 

groups, we used the OR operator to allow syno-

nyms. The following search string was used: 

("human-computer interaction" OR "user inter-

face design" OR "user interaction design" OR 

"user centered design" OR "human-centered de-

sign" OR "UI design" OR "HCI design") AND 

("knowledge management" OR "knowledge re-

use" OR "knowledge sharing"). For establishing 

the string, we performed tests using different 

terms, logical connectors and combinations 

among them, selecting the string that provided 

better results in terms of the number of publica-

tions and their relevance (i.e., the number of pub-

lications returned by the search string and, con-

sidering a sample, the inclusion of the really rel-

evant ones for the study). If a new term added to 

the search string resulted in a much larger num-

ber of returned publications, without adding new 

relevant ones to the study, then that term was not 

considered in the search string. In that sense, 

more restrictive strings excluded important pub-

lications identified during the informal literature 

review that preceded the study. More comprehen-

sive strings (e.g., those including “usability”) re-

turned too many publications out of the scope of 

interest. 

The search was performed in four sources, 

namely Scopus, Science Direct, Engineering Vil-

lage and Web of Science. We selected these 

sources because Scopus is one of the largest da-

tabases of peer-reviewed literature. It indexes pa-

pers from other important sources such as IEEE 

and ACM, providing useful tools to search, ana-

lyze and manage scientific research. Comple-

mentarily, to increase coverage, we selected Sci-

 
1 http://bit.ly/StArt-tool 

ence Direct, Engineering Village and Web of Sci-

ence, which are also widely used in secondary 

studies recorded in the literature and on other ex-

periences in our research group.   

Publications selection was performed in five 

steps. In Preliminary Selection and Cataloging 

(S1), the search string was applied in the search 

mechanism of each digital library used as a 

source of publications (we limited the search 

scope to the title, abstract and keywords metadata 

fields). After that, in Duplications Removal (S2), 

publications indexed in more than one digital li-

brary were identified and duplications were re-

moved. In Selection of Relevant Publications - 

1st filter (S3), the abstracts of the selected publi-

cations were analyzed considering the following 

inclusion (IC) and exclusion (EC) criteria: (IC1) 

the publication addresses KM in the HCI design 

context; (EC1) the publication does not have an 

abstract; (EC2) the paper was published only as 

an abstract; (EC3) the publication is not written 

in English; (EC4) the publication is a secondary 

study, a tertiary study, a summary, an editorial or 

a tutorial. In Selection of Relevant Publications - 

2nd filter (S4), the full text of the publications se-

lected in S3 were read and analyzed considering 

the cited inclusion and exclusion criteria. In this 

step, to avoid study repetition, we considered an-

other exclusion criterion: (EC5) the publication is 

an older version of an already selected publica-

tion. When the full text of a publication was not 

available either from the Brazilian Portal of Jour-

nals, from other Internet sources or by contacting 

its authors, the publication was also excluded 

(EC6). Publications that met one of the six cited 

exclusion criteria or that did not meet the inclu-

sion criteria IC1 were excluded. Finally, in Snow-

balling (S5), as suggested in Kitchenham & 

Charters (2007), the references of publications 

selected in S4 were analyzed by applying the first 

and second filters and, the ones presenting results 

related to the research topic were included in the 

study. 

We used the StArt tool1 to support publica-

tions selection. To consolidate data, publications 

returned in the publication selection steps were 

cataloged and stored in spreadsheets. We defined 

an id for each publication and recorded the pub-

lication title, authors, year, and vehicle of publi-

cation. Data from publications returned in S4 and 

http://bit.ly/StArt-tool


 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

S5 were extracted and organized into a data ex-

traction table oriented to the research questions. 

The spreadsheets produced during the study can 

be found in  http://bit.ly/Mapping-KM-in-HCI-

design. 

The first and second authors performed pub-

lication selection and data extraction. The third 

and fourth authors reviewed both. Once data has 

been validated, the first and the second authors 

carried out data interpretation and analysis, and 

again third and fourth authors reviewed the re-

sults. Discordances were discussed and resolved. 

Quantitative data were tabulated and used in 

graphs and statistical analysis. Finally, the four 

authors performed qualitative analysis consider-

ing the findings, their relation to the research 

questions and the study purpose. 

3.2 Results 

The study considered papers published until Oc-

tober 2020. Searches were conducted for the last 

time in November 2020. Figure 1 illustrates the 

followed process and the number of publications 

selected in each step.

 

Figure 1. Publication selection process.

In the 1st step, as a result of searching the selected 

sources, a total of 381 publications was returned. 

In the 2nd step, we eliminated duplicates, 

achieving 228 publications (reduction of 

approximately 40%). In the 3rd step, we applied 

the selection criteria over the abstract, resulting in 

21 papers (reduction of approximately 91%). At 

this step, we only excluded publications that were 

clearly unrelated to the subject of interest. In case 

of doubt, the paper was taken to the next step. In 

the 4th step, the selection criteria were applied 

considering the full text, resulting in 11 

publications (reduction of approximately 48%). 

Finally, in the 5th step, we performed snowballing 

technique by checking the references of the 11 

selected publications and identified 4 more 

publications, which in total added up to 15 

publications. When analyzing the publications to 

identify the KM approaches applied in the HCI 

design context, we noticed that some publications 

addressed complementary works from the same 

research group. Hence, we considered 

complementary works as a single KM approach 

when extracting data about RQs 3, 4, 5, 6 and 7. 

Table 2 shows the list of identified KM 

approaches, their descriptions and corresponding 

publications. Two papers were grouped into a KM 

approach and three other papers were grouped in 

another KM approach. Thus, we considered a 

total of 12 different KM approaches found in 15 

publications. Along with this and the next section, 

we refer to the approaches by using the id listed 

in the table. After Table 2, we present the data 

synthesis for each research question. Further 

information about the selected publications, 

including detailed extracted data, can be found in  

http://bit.ly/Mapping-KM-in-HCI-design. 

Table 2. Selected publications. 

ID Approach Brief description Ref. 

#01 Trading off usability and 

security in user interface 

design through mental 

models 

Proposes the development of an Organizational Mental Model through 

knowledge transfer and transformation, using collaborative brain 

power from various knowledge constellations to design. 

(Mohamed et al., 

2017) 

#02 Knowledge management 

challenges in collaborative 

design of a Virtual Call 

Centre 

Proposes a knowledge-based system with the following functionalities: 

(a) storing design primitives and formal knowledge in an online library; 

(b) preserving procedures and rules that proved successful in past 

design problems; (c) formal modeling of knowledge elements that 

might be applicable for usability improvements; (d) providing multiple 

mechanisms for knowledge acquisition, preserving, transfer and 

sharing. 

(Sikorski et al., 2011) 

#03 Applying knowledge 

management in UI design 

process 

Defines a process to automate the transformation of a task description 

into an interaction description. First, it identifies and uniformizes 

existing knowledge about UI design process using knowledge 

classification techniques. Then, captured knowledge is represented in 

the form of ontologies, deriving a Task Metamodel and an Interaction 

Metamodel. This extracted knowledge is integrated to design defining 

a transformation of task description into interaction description using 

an intermediate model between them and a two-step transformation. 

(Suàrez et al., 2004) 

#04 A knowledge management 

tool for speech interfaces 

Proposes a knowledge-based system to help developers of speech-

driven interfaces learn with previous design solutions. These solutions 

are collected, made accessible and divided into categories regarding 

their content type. Solutions with corresponding structures are 

clustered and compared within their own category, providing designers 

with a suggestion mechanism based on their desired kind of solution. 

(Bouwmeester, 1999) 

http://bit.ly/Mapping-KM-in-HCI-design
http://bit.ly/Mapping-KM-in-HCI-design
http://bit.ly/Mapping-KM-in-HCI-design


 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

There is also a ranked suggestion mechanism of design elements based 

on available design material and design guidelines. 

#05 Design knowledge reuse 

based on visualization of 

relationships between 

claims 

Presents a tool that aims to improve design and knowledge acquisition 

by exploring relationships between claims. It allows a better search and 

retrieval mechanism to a design knowledge repository, which is 

obtained by applying KM strategies (generalize, classify, store, 

retrieve) to claims. 

(Wahid, 2006; Wahid 

et al., 2004) 

#06 Design knowledge reuse 

and notification systems to 

support design in the 

development process 

Presents a system connected to a design knowledge repository based 

on claims. It allows teams to leverage knowledge from previous design 

efforts by searching for reusable claims relevant to their current project 

and to extend the repository by updating existing claims and creating 

new ones. 

(Chewar et al., 2004; 

Chewar & 

McCrickard, 2005; J. 

L. Smith et al., 2005) 

#07 Exploring knowledge 

processes in user-centered 

design process 

Proposes a conceptual framework that guides the design process based 

on five propositions: (1) designers and users should be actively 

included as actors in the process since they both have the knowledge 

needed for a successful design; (2) this knowledge possessed by them 

is context-specific; (3) there is useful knowledge that has not been 

articulated by both users and designers and, therefore (4) knowledge 

processes transforming tacit knowledge into explicit knowledge by 

users and designers are linked and should be combined; and finally, (5) 

resulting knowledge obtained along the process is embedded into 

concepts, products or services. 

(Still, 2006) 

#08 Lessons learnt from an 

HCI repository 

Concerns about the implementation of a knowledge repository using 

Windows Help Files. It is maintained by a group within the 

organization that receives content updates from the team and properly 

inserts this new material into the repository. New versions are released 

from time to time and distributed as physical copies to be installed on 

each computer. 

(Wilson & Borras, 

1998) 

#09 A pattern language 

approach to usability 

knowledge management 

Presents a KM system that used principles of use case writing and 

pattern languages to describe problems found in user testing sessions 

and the following solutions to them. Patterns can be retrieved by forms 

with filters, text search and database queries. Filters include goals and 

subgoals, being useful respectively to show all problems related to a 

specific user goal and possible solutions and to provide insights of what 

interactions or devices have been problematic regardless of user goal. 

(Hughes, 2006) 

#10 An expert system for 

usability evaluations of 

business-to-consumer e-

commerce sites 

Proposes a knowledge-based system to help with e-commerce usability 

evaluations. A knowledge engineer is responsible for acquiring and 

representing knowledge, eliciting knowledge from textual, non-live 

sources of expertise about design guidelines that affect the usability of 

11 e-commerce elements. The elicited knowledge is consolidated and 

presented in a form of rules in the expert system. 

(Gabriel, 2007) 

#11 A framework for 

developing experience-

based usability guidelines 

Presents a KM system to manage design guidelines contextualized by 

usability examples. The system allows designers to describe their 

current problems and requirements and then search for cases with 

similar characteristics. They can also follow hyperlinks to more general 

guidelines, which also point to other cases and search from a list of 

hierarchically arranged guidelines and follow other related guidelines 

and cases. The system is initially seeded with organization-wide 

usability guidelines and is updated as new projects are developed.  

(Henninger et al., 

1995) 

#12 Prototype evaluation and 

redesign: structuring the 

design space through 

contextual techniques 

Proposes a method based on contextual inquiry and brainstorming to 

identify usability issues in interface evaluations and derive proper 

design solutions to them. First, interface evaluation sessions are 

conducted with users when they share their perceptions while 

interacting with a high-fidelity prototype of the system. Those sessions 

are recorded and, later, relevant comments are transcribed into usability 

flaws. In a second moment, there are brainstorm meetings where 

developers, designers and HCI specialists propose design solutions to 

the previously identified usability flaws. 

(A. Smith & 

Dunckley, 2002) 

 

Publication year and type (RQ1): Figure 2 shows the distribution of the 15 selected publications 

over the years and their distribution considering the publication type. Papers addressing KM in the HCI 

design context have been published since 1995 in Journals and Conferences (no Workshop publications 

were found). Conferences have been the main forum, encompassing 73.3% of the publications (11 out 

of 15). Four papers (26.78%) were published in journals. 

 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

 

Figure 2. Publications over the years. 

The venues of each selected publication were 

also analyzed to investigate if they were more re-

lated to HCI, KM or Software Engineering (SE). 

Table 3 summarizes the venues of the selected 

publications and indicates their main focus. Fig-

ure 3 presents the distribution of the venue orien-

tation across the publications. 53.3% of the pub-

lications (8 out of 15) were published in HCI ven-

ues and the remaining of the publications are di-

vided into KM (26.7%) and SE (20.0%) venues.

Table 3. Venue orientation of the selected publications. 

Ref. Venue Area 

(Mohamed et al., 2017) Behavior & Information Technology HCI 

(Sikorski et al., 2011) International Conference on Knowledge-Based and Intelligent 

Information and Engineering Systems 

AI 

(Wahid, 2006) Conference on Designing Interactive Systems HCI 

(Suàrez et al., 2004) Conference on Task Models and Diagrams HCI 

(Bouwmeester, 1999) International ACM SIGIR Conference on Research and 

Development in Information Retrieval 

Information Retrieval 

(J. L. Smith et al., 2005) IEEE International Conference and Workshops on Engineering 

of Computer-Based Systems 

Software Engineering 

(Chewar et al., 2004) International Conference on Computer-Aided Design Design 

(Wahid et al., 2004) IEEE International Conference on Information Reuse and 

Integration 

Data Science 

(Chewar & McCrickard, 2005) Hawaii International Conference on System Sciences Information Systems 

(Still, 2006) European Conference on Knowledge Management KM 

(Wilson & Borras, 1998) International Journal of Industrial Ergonomics HCI 

(Hughes, 2006) Journal of Usability Studies HCI 

(Gabriel, 2007) ISOnEworld Conference Information Systems 

(Henninger et al., 1995) DIS - conference on Designing interactive systems: processes, 

practices, methods, and techniques 

HCI 

(A. Smith & Dunckley, 2002) Interacting with computers HCI 

 
Figure 3. Venue orientation of the selected publications. 

Research Type (RQ2): Figure 4 presents the 

classification of the research types (according to 

the classification proposed in Wieringa et al. 

(2005)) reported in the 15 selected publications. 

13 publications (86.7%) propose a solution to a 

problem and argue for its relevance. Thus, they 

were classified as Proposal of Solution. Five of 

them (33.3%) also present some kind of evalua-

tion, being one (6.7%) evaluated in practice (i.e., 

also classified as Evaluation Research), and four 

(26.7%) investigating the characteristics of the 

proposed solution not yet implemented in prac-

tice (i.e., Validation Research). One publication 

(6.7%) refers exclusively to Evaluation Re-

search, discussing the evaluation of KM in an in-

dustrial setting, and another is a Personal Expe-

rience Paper, reporting the experience of the au-

thors in a particular project in the industry. 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

 

Figure 4. Research type of the identified publications.  

Motivation for using KM in HCI design 

(RQ3): we identified six reasons for using KM in 

HCI design, as shown in Table 4. Some ap-

proaches presented more than one motivation, 

thus the total sum is greater than 12. 

Table 4. Motivations for using KM in HCI design. 

Motivation Approaches Total 

Improve product quality #01, #02, #04, #05, #06, 

#07, #10, #11, #12 

9 

Reduce design effort #02, #03, #08, #09, #10 5 

Reduce design time #04, #05, #08 3 

Reduce design cost #05, #10 2 

Improve design team 

performance 

#06 1 

Improve HCI design 

learning 

#06 1 

 

Nine approaches (75%) use KM to improve 

product quality, most of them concerning usabil-

ity. These approaches aim to provide benefits re-

lated to the quality of the interactive system in 

terms of its interaction with users. For example, 

approach #11 is proposed to help developers to 

design effective, useful and usable applications. 

Approach #01, in turn, aims to improve align-

ment between design features and users’ require-

ments. Seven approaches (58.3%) are motivated 

by improving one or more aspects related to the 

HCI design process, namely: effort, time and 

cost. From these, reducing effort is highlighted. 

Five approaches (41.7%) use KM to reduce de-

sign effort, mainly by not depending on internal 

usability experts to perform HCI design activi-

ties. Approach #02, for example, applied KM to 

decrease the need for experts to support the de-

sign team with their knowledge and experience, 

due to lack of knowledge to be reused. Ap-

proaches #04, #05 and #08 were motivated by re-

ducing HCI design time through the reuse of pre-

vious solutions implemented for similar prob-

lems. Reducing costs in the HCI design process 

was the motivation for approaches #05 and #10, 

which focus on minimizing the involvement of 

external usability experts in the process and con-

ducting usability evaluation more effectively. 

Approach #06 aimed to improve design team per-

formance by providing support for team coordi-

nation and collaboration. This approach also 

aimed to improve HCI learning for the students 

involved in the project. 

Managed knowledge in HCI design (RQ4): 

Analyzing the publications, we identified 24 dif-

ferent types of knowledge items managed by the 

KM approaches, as shown in Table 5. Some items 

are shown in the same line to save space. The 

most common knowledge items have been De-

sign Guidelines and Design Solutions, addressed 

by four approaches, followed by Test Results, ad-

dressed by three approaches. We noticed that, in 

the context of HCI design, KM approaches have 

dealt with only one (#10) or two (#01, #03, #05, 

#06, #09, #11 and #12) different knowledge 

items.  

Table 5. Managed knowledge items. 
Knowledge Item Approaches Total 

Design Guidelines #04, #08, #10, #11 4 

Design Solutions #02, #04, #07, #08 4 

Test Results #02, #04, #12 3 

Claims #05, #06 2 

Design Features #01, #12 2 

Design Patterns #09, #11 2 

Lessons Learned #04, #08 2 

Usability Measures #02, #08 2 

Claims Relationships #05 1 

Design Changes #06 1 

Design Feature Checklists; 

Design Methods; Design 

Processes; Design Standards; 

Design Templates; Interface 

Objects 

#08 1 

Interaction Model; Task 

Model 

#03 1 

Scenarios; Test Scenarios #02 1 

User Knowledge; User Needs #07 1 

User Requirements #01 1 

User Tasks #09 1 

 

We identified four different HCI aspects ad-

dressed by the identified KM approaches. The 

main aspect is Usability, which is treated in all 

the identified approaches. Two approaches (#03 

and #08) also address Ergonomics. #03 and #04 

focus on particular types of design or interfaces. 

The former focuses on Task-based Design while 

the latter on Speech Driven Interfaces. Figure 5 

shows the HCI aspects addressed in the identified 

KM approaches. The sum exceeds 12 because 

some approaches address more than one aspect. 

 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

 

Figure 5. HCI aspects addressed in KM approaches. 

When knowledge is captured and used 

(RQ5): Table 6 shows when HCI design 

knowledge has been captured and when it has 

been used along the HCI design process. Three 

approaches capture and use knowledge through-

out the whole process. Eight approaches (66.7%) 

use knowledge when producing design solutions. 

A smaller number (six, 50%) capture knowledge 

in this activity. The behavior is the opposite in 

design evaluation: more approaches are capturing 

(five, 41.7%) than using (three, 25%) knowledge 

in this activity. Only one (8.3%) approach cap-

tures knowledge during requirements specifica-

tion. 

Table 6. Capture and use of knowledge along the HCI de-

sign process. 
Activity  

(ISO, 2019) 

Knowledge 

Capture 

Knowledge Use 

Specify 

requirements 

1  

(#01) 

0 

Produce design 

solutions 

6  

(#02, #03, #04, 

#07, #10, #11) 

8  

(#01, #02, #03, 

#04, #07, #09, 

#11, #12) 

Design Evaluation 5  

(#02, #04, #09, 

#10, #12) 

3  

(#02, #09, #10) 

Whole cycle 3  

(#05, #06, #08) 

3  

(#05, #06, #08) 

 

Technologies used in KM approaches 

(RQ6): Table 7 shows the technologies (systems, 

methods, tools, theories, etc.) used in the ana-

lyzed KM approaches. The most common tech-

nologies were knowledge-based systems and 

knowledge repositories, which are used in three 

approaches. For example, #04 proposes a 

knowledge-based system to help developers of 

speech-driven interfaces learn with previous de-

sign solutions. #08, in turn, proposes the imple-

mentation of a knowledge repository using Win-

dows Help Files.  

Knowledge management systems and 

knowledge-based analysis were used in two ap-

proaches. A knowledge management system is 

proposed in #09 to describe problems detected in 

user test sessions and the respective solutions and 

in #11 to describe design problems and require-

ments and then search for usability examples 

with similar characteristics and hyperlinks to 

more general related guidelines. Knowledge-

based analysis, in turn, was used in #03 and #07 

combined with other technologies, such as ontol-

ogy and model transformation (#3) and concep-

tual framework (#7). 

Other technologies such as brainstorming, 

contextual inquiry, heuristic evaluation and men-

tal models were used in only one KM approach. 

Table 7. Technologies used in KM approaches in HCI de-

sign context.  

Technology Approaches Total 

Knowledge-based System #02, #04, #10 3 

Knowledge Repository #05, #06, #08 3 

Knowledge Management System #09, #11 2 

Knowledge-based Analysis #03, #07 2 

Ontology; Model Transformation #03 1 

Conceptual Framework #07 1 

Contextual Inquiry; Brainstorming-

based Technique 

#12 1 

Mental Model; Internalization 

Awareness; Observation; 

Behavioral Interviews; Absorptive 

Capacity; Heuristic Evaluation 

#01 1 

 

Benefits and challenges of using KM in 

HCI design (RQ7): Table 8 summarizes the ben-

efits and difficulties reported in the publications. 

Two approaches (#04 and #10) did not report any 

benefit or challenge in using KM in HCI design. 

Considering the 10 other approaches, it can be 

noticed that, in general, more benefits than diffi-

culties were reported. 

The most reported benefit was to enable rep-

licability of domain or context knowledge. For 

example, #07 reached wide scope applicability 

because of the common conceptualization pro-

posed as a conceptual framework. On the other 

hand, the most reported difficulty was that 

knowledge is often too specific for a given con-

text. For example, in #11 it is stated that the ap-

proach is best suited for contexts in which com-

mon customer needs are being addressed in sim-

ilar application domains.  

 

 

 

 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

Table 8. Benefits and difficulties of using KM in HCI design context. 

Benefits Approaches Total 

Enable replicability of domain/context knowledge #03, #06, #07, #09, #12 5 

Improve product quality #02, #05, #06, #12 4 

Improve communication #01, #03, #11 3 

Increase team engagement/empowerment #02, #06 2  

Increase organizational integration #03, #08 2  

Reduce design effort #03, #12 2  

Improve design conceptualization #03, #07 2  

Promote standardization #02 1  

Increase productivity #11 1  

Promote organizational competitive advantage #02 1  

Decrease implementation and maintenance effort #08 1  

Decrease implementation and maintenance costs #08 1  

Difficulties Approaches Total  

Knowledge is often context-specific #02, #06, #09, #11 4  

Issues related to features of the KM technologies #05, #06, #09 3  

Low team engagement/empowerment #01, #05, #08 3  

User involvement #07, #12 2  

Integration of the KM approach into the organization #06, #11 2  

KM implementation and maintenance effort #08, #09 2  

Lack of consensus about HCI design conceptualization #01, #02 2  

 

3.3 Discussion 

Taking the period of publications into account 

(RQ1), we can notice a long-term effort regard-

ing the use of KM in HCI design, since this topic 

has been targeted by researchers for more than 20 

years. However, the low average of publications 

per year (0.6 since 1995) shows that the topic has 

not been widely addressed. We can also notice 

that most of the publications are from the 2000s 

decade.  The low percentage of journal publica-

tions, which generally require more mature 

works, can be seen as a reinforcement that the re-

search on this topic is not mature enough yet. Be-

sides, results about the research type (RQ2) show 

that only 40% of the works included some kind 

of evaluation, being only 13% evaluation of so-

lutions in practice. This can be a sign of difficulty 

in applying the proposed approaches in industry, 

which reinforces that research on this topic is not 

mature enough yet and there seems to be a gap 

between theory and practice. 

Concerning RQ3, we can notice that using 

KM in HCI design has been motivated mainly by 

delivering better products to users or optimizing 

the HCI design process in terms of effort, time 

and cost. Improving the performance of the HCI 

design team was also mentioned, which is con-

sistent with the other motivations related to the 

HCI design process since increasing performance 

can contribute to decreasing effort, time and cost. 

By analyzing the results of approaches that ap-

plied some validation or evaluation, we noticed 

that only two (#03 and #12) provided results re-

lated to the initial motivation for using KM in 

HCI design (reduce design effort and improve 

product quality, respectively). The other publica-

tions were more focused on validating or evalu-

ating features or functionalities of the proposed 

solutions. A common concern in several publica-

tions was the need for HCI design expert consult-

ants, which can increase HCI design cost and ef-

fort. Capturing and reusing knowledge contribute 

to retaining organizational knowledge and reduc-

ing dependence on external consultants. Another 

concern refers to communication problems. A. 

Smith & Dunckley (2002) highlight that barriers 

to effective communication between designers, 

HCI specialists and users, due to their differing 

perspectives, affect product quality. KM solu-

tions are helpful in this context. 

Usability has been the focus of the KM initi-

atives in the HCI context (RQ4). In fact, this is 

not a surprise, because usability has been one of 

the most explored HCI aspects in the last years. 

Moreover, this property is quite comprehensive 

and includes other important aspects of HCI de-

sign, such as learnability, memorability, effi-

ciency, safety and satisfaction (ISO, 2019). How-

ever, there are other important properties not ad-

dressed in the analyzed papers, such as user ex-

perience, communicability and accessibility. The 

knowledge items managed by the KM ap-

proaches are quite diverse. Design solutions, 

guidelines, test results and design patterns are 

some knowledge items found in different publi-

cations. Despite the variety of knowledge items, 

we noticed that most of the approaches (66.7%) 

manage up to two different knowledge items. By 

analyzing the coverage of the approach in terms 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

of single or multiple projects, we found out that 

four approaches (#01, #03, #07 and #12) manage 

knowledge involved in a single project, while the 

other eight approaches are more extensive, accu-

mulating knowledge from multiple projects. In 

order to elevate knowledge reuse to the organiza-

tional level, a KM approach must comprehend 

multiple projects in that organization. 

Concerning knowledge use and capture 

(RQ5), at first, we expected that knowledge was 

captured and used in the same activity of the HCI 

design process.  Therefore, results showed us that 

the same knowledge could be produced and con-

sumed in different parts of the HCI design pro-

cess. For example, there are more approaches 

capturing knowledge in the design evaluation ac-

tivity than using it. This reinforces the iterative 

characteristic of HCI design, where knowledge 

obtained in evaluation activity in one cycle can 

be used to improve the design in the next cycle. 

Different technologies have been used to im-

plement KM in the HCI design context (RQ6). 

The most common are system-based approaches 

that use software to support the KM process and 

store knowledge. We expected this result because 

KM systems, knowledge-based systems and 

knowledge repositories are widely adopted tech-

nologies in the KM area. On the other hand, only 

two approaches use specific HCI techniques, 

namely contextual inquiry and heuristic evalua-

tion. This may indicate that KM traditional ap-

proaches are suitable for addressing KM prob-

lems in HCI design (what was indeed expected) 

and that HCI techniques can be used to address 

specificities of the HCI design domain. Earlier 

steps of the development of KM solutions, such 

as knowledge analysis and modeling, are also ad-

dressed in some publications. Moreover, there is 

also concern with later steps, like the integration 

of the KM system into the organization. Some ap-

proaches combine different technologies, which 

can be a sign that the use of different techniques 

is a good strategy to address a more complete KM 

approach in HCI design. 

As for the benefits and challenges of using 

KM in the HCI design context (RQ7), when cat-

egorizing the findings, we noticed that several of 

them are benefits and challenges of using KM in 

general. However, by analyzing the context of 

each KM approach, we can better understand 

how the findings relate to HCI design. For exam-

ple, regarding the benefit improve communica-

tion, the works highlight the use of KM to support 

communication among the different actors in-

volved in the HCI design process. In #10, com-

munication between HCI specialists, designers 

and users is mediated by prototypes aiming at an 

agreement about the system design. In #01, KM 

facilitates the elicitation of the user’s knowledge 

for the designer to apply it to the design. In #03, 

KM reduces errors of interpretation and contex-

tualization among the people involved in the sys-

tem design. 

Some of the identified challenges and benefits 

are opposite each other. For example, there is the 

challenge of low team engagement on one hand 

and the benefit of increasing team engagement 

on the other hand. We kept both because they 

were cited in different publications, thus under 

different perspectives. Moreover, we can see the 

challenge as a difficulty that, when overcome by 

the use of KM, can be turned into a benefit. 

By analyzing the most cited benefits and chal-

lenges, we noticed that the generality level of the 

knowledge is an important question in a KM ap-

proach. The most cited benefit points to 

knowledge replicability in a specific context/do-

main.  The most cited challenge points to the fact 

that it is difficult to generalize knowledge. Look-

ing at data from RQ5, we noticed that approaches 

handling knowledge from multiple projects re-

ported the knowledge generalization challenge, 

while approaches handling knowledge in a single 

project reported easy replication of knowledge. 

Thus, the generality level of knowledge should 

be determined by the context where the KM ap-

proach will be applied. When dealing with a high 

diversity of knowledge and contexts, it becomes 

harder to produce general knowledge to be 

widely used to solve specific problems and be 

adopted in different contexts. One way of achiev-

ing improvements in replicability is using 

knowledge-based analysis methods, as reported 

by approaches #03 and #07. 

Based on the panorama provided by the map-

ping study results, in summary, we can say that 

KM has not been much explored in the HCI con-

text; it has been used mainly to improve software 

quality and HCI design process efficiency; it has 

focused on usability; and the KM approaches 

have been based on systems and repositories. As 

for benefits, KM has enabled knowledge replica-

bility, improved product quality and communica-

tion. The main difficulties have been to general-

ize knowledge, address issues related to features 

of the system and low engagement of the team. 

3.4 Threats to Validity 

As with any study, our mapping study has some 

limitations that must be considered together with 

the results. Following the classification pre-

sented by (Petersen et al., 2015), next we discuss 

the main threats to the mapping study results. 

Descriptive Validity is the extent to which ob-

servations are described accurately and objec-

tively. To reduce descriptive validity threats, a 

data collection form was designed to support data 

extraction and recording. The form objectified the 

data collection procedure and could always be re-

visited. However, data extraction and recording 

still involved some subjectivity and was depend-

ent on the researcher’s decisions. An important 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

limitation in this sense is related to the classifica-

tions we made. We defined classification schemas 

for categorizing data in some research questions. 

Some categories were based on classifications 

previously proposed in the literature (e.g., type of 

research (Wieringa et al., 2005)). Others were es-

tablished during data extraction, based on data 

provided by the analyzed publications (e.g., 

RQ4). With an aim towards minimizing the threat, 

data extraction, classification schemas and data 

categorization were done by the first and second 

authors and reviewed by the other two authors. 

Discordances were discussed and resolved. How-

ever, determining the categories and how data fit 

them involves a lot of judgment. Thus, different 

results could be obtained by other researchers. 

Theoretical Validity is determined by the re-

searcher’s ability to capture what is intended to 

be captured. In this context, one threat refers to 

the sources. We used four digital libraries se-

lected based on other secondary studies in Soft-

ware Engineering. Although this set of digital li-

braries represents a comprehensive source of 

publications, the exclusion of other sources may 

have left some valuable publications out of our 

analysis. ACM was not included in the sources 

because Scopus covers most of its publications. 

However, there are HCI publications indexed by 

ACM and not indexed by Scopus, which may 

have jeopardized the mapping results. To mini-

mize this risk, we performed snowballing. An-

other threat refers to the fact that the study fo-

cused on scientific literature and did not include 

other alternatives, such as grey literature, that 

could enhance the systematic mapping coverage. 

Hence, extending this study with a multivocal lit-

erature review through grey literature analysis 

could complement and enrich the obtained re-

sults.  

There are also limitations related to the 

adopted search string. Even though we have used 

several terms, there are still synonyms that we did 

not use. For example, since KM is a subjective 

area, many publications may have addressed KM 

aspects using other words such as “collaboration” 

and “organizational learning”, which were not 

covered by our search string. Moreover, we did 

not include HCI and KM acronyms alone (HCI 

was combined with “design”), which could be an 

additional threat. However, the string includes 

the full terms referring to HCI and KM and we 

believe that it is probable that publications in-

cluding the acronyms also include the full terms 

in either their title, abstract or keywords. Hence, 

our search string might have covered them any-

way. 

The researcher bias over publications selec-

tion, data extraction and classification is also a 

threat to theoretical validity. To minimize this 

threat, as we previously said, the steps were ini-

tially performed by the first and second authors 

and, to reduce subjectivity, the other two authors 

performed these same steps. Discordances and 

possible biases were discussed until reaching a 

consensus. 

Finally, Interpretive Validity is achieved when 

the drawn conclusions are reasonable given the 

data obtained. The main threat in this context is 

the researcher bias over data interpretation. To 

minimize this threat, like in the other steps, inter-

pretation was performed by the first and second 

authors and reviewed by the other two. Discus-

sions were carried out until a consensus was 

reached. However, subjectivity still relies on 

qualitative interpretation and analysis. 

Even though we have treated many of the 

identified threats, the adopted treatments involved 

human judgment, therefore the threats cannot be 

eliminated and must be considered together with 

the study results. 

4 Survey: KM in HCI Design 

practice 

The systematic mapping provided information 

about KM approaches to support HCI design ac-

cording to the literature records. After conducting 

the mapping study, we performed a survey with 

39 Brazilian HCI design practitioners to investi-

gate KM in HCI design practice. 

A survey is an experimental investigation 

method usually done after the use of some tech-

nique or tool has already taken place (Pfleeger, 

1994). Surveys are retrospective, i.e., they allow 

to capture an “instant snapshot” of a situation. 

Questionaries and interviews are the main instru-

ments used to apply a survey, collecting data 

from a representative sample of the population. 

The resulting data are analyzed, aiming to draw 

conclusions that can be generalized for the whole 

population represented by that sample (Mafra & 

Travassos, 2006). In this work, we intended to 

reach many participants and analyze data objec-

tively and quantitatively. Thus, in our survey, we 

decided to use a questionnaire containing objec-

tive questions. 

We followed the process defined in (Wohlin 

et al., 2012) which comprises five activities. 

Scoping is the first step, where we scope the study 

problem and establish its goals. Planning comes 

next, where the study design is determined, the 

instrumentation is considered and the threats to 

the study conduction are evaluated. Operation 

follows from the design, consisting in collecting 

data which then are analyzed and evaluated in 

Analysis and Interpretation. Finally, in Presenta-

tion and Package, the results are communicated. 

Next, in Section 4.1 we present the survey 

planning and execution. Section 4.2 concerns the 

survey results. Section 4.3 discusses the results 

and Section 4.4 presents threats to validity. 

 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

4.1 Survey Planning and Execution 

The study goal was to investigate aspects related 

to KM in HCI design practice. Aligned to this 

goal, we defined the research questions pre-

sented on Table 9, which were based on the sys-

tematic mapping research questions and results. 

Table 9. Survey: research questions and their rationale. 

ID Research Question Rationale  

RQ1 Which stakeholders have been in-

volved in HCI design practice? 

Identify which stakeholders have been involved in HCI design practice, which helps 

identify different perspectives and information needs in HCI design. 

RQ2 Which knowledge has been involved 

in HCI design practice? 

Investigate which knowledge has been involved in HCI design practice, particularly 

knowledge items (e.g., design solutions, guidelines and lessons learned) and design 

artifacts (e.g., wireframes, mockups and prototypes) used as sources of knowledge or 

produced to record useful knowledge.  

RQ3 Which HCI design activities have 

demanded better KM support? 

Investigate which HCI design activities have needed better support of KM (e.g., be-

cause there have not been enough knowledge resources to support their execution). 

RQ4 How has KM been applied in HCI 

design practice? 

Investigate how KM principles have been applied and identify technologies (e.g., 

tools, methods, etc.) that have been used to support knowledge access and storage 

in HCI design practice. 

 

RQ5 Which benefits and difficulties have 

been noticed when using KM in 

HCI design practice? 

Identify benefits and difficulties that have been experienced by practitioners when 

applying KM in HCI design practice and verify if practitioners have experienced 

more benefits or difficulties. 

 

RQ6 Which goals the use of KM in HCI 

design practice has contributed to 

achieving? 

Identify which goals the use of KM in HCI design has contributed to, aiming to 

figure out predominant reasons for using KM in HCI design practice. 

 

The participants were 39 Brazilian profes-

sionals with experience in HCI design of interac-

tive software systems. The participants profile 

was identified through questions regarding their 

current job positions, education level, knowledge 

of HCI design and practical experience in HCI 

design activities. Most participants (79.5%) de-

clared to play roles devoted to HCI design activ-

ities (nine UX/UI designers; six UX designers; 

four product designers, two designers, two UX 

research designers, one art director, one IT ana-

lyst & UX designer, one interaction designer, one 

lead designer, one lead UI designer, one staff 

product designer and one UI designer). Others 

20.5%) play roles that perform some activities re-

lated to HCI design (one programmer, one re-

quirement analyst, one chief growth officer, one 

product owner, one IT analyst, one IT manager, 

one marketing manager and one project leader). 

Although these roles cannot be considered HCI 

design experts, we did not exclude these partici-

pants because they declared to have practical ex-

perience and knowledge in HCI design (probably 

acquired in their previous job and academic ex-

periences). Moreover, even playing roles not 

dedicated to HCI design, they are often involved 

in HCI design in some way. Eight participants 

(20.5%) had masters’ degrees, 26 (66.7%) had 

bachelor’s degrees, and five (12.8%) had not yet 

finished bachelor’s degree courses. 

All participants declared theoretical 

knowledge of HCI design. Four of them (10.3%) 

declared low knowledge (i.e., knowledge ac-

quired by himself/herself through books, videos 

or other materials). 16 participants (41%) de-

clared medium knowledge, acquired mainly dur-

ing courses or undergraduate research. Finally, 

19 participants (48.7%) declared high knowledge 

(i.e., they are experts or have a certification, Mas-

ters or Ph.D. degree related to HCI design). Some 

areas of the courses cited by participants that de-

clared medium or high knowledge are Design 

(46.2%), Computer Science (38.5%), Arts 

(28.2%), Social Communication (15.4%) and 

User Experience (7.7%). The participants were 

allowed to choose more than one option, hence 

the sum of the values is over 100%. Other areas 

such as Anthropology, Neuroscience, Infor-

mation Science, Psychology were also mentioned 

by one participant each. 26 participants (66.7%) 

declared more than three years of experience in 

HCI design practice, 11 participants (28.2%) de-

clared between one and three years and two 

(5.1%) declared less than one year.  

The instrument used in the study consisted of 

a questionnaire composed of 10 objective ques-

tions. Most answer options for each question 

were defined based on the mapping study results. 

For example, when asked about the goals 

achieved with the help of KM in HCI design 

(RQ6), the options provided to the participants 

refer to the goals we found in the mapping study. 

However, some options were rewritten in a way 

that could enhance participants understanding 

(e.g., we changed “test results” to “previous de-

sign evaluation results” on RQ2) and others were 

added based on the authors’ knowledge and ex-

perience (e.g., we included forums, blogs and so-

cial networks in RQ4). Furthermore, most ques-

tions also allowed the participant to provide ad-

ditional information in text boxes to complement 

his/her answers. For example, besides selecting 

goals from the list provided in the question re-

lated to RQ6, the participants were also allowed 

to include new goals in their answers. The ques-

tionnaire is available at http://bit.ly/Question-

naire-KM-in-HCI-design. 

http://bit.ly/Questionnaire-KM-in-HCI-design
http://bit.ly/Questionnaire-KM-in-HCI-design


 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

The procedure adopted in the study consisted 

in sending the invitation to participate in the 

study, receiving the answers, verifying them, 

consolidating and analyzing data. The invitation 

was posted in discussion groups on Facebook, 

LinkedIn and Interaction Design Foundation’s 

website2. The authors also sent the invitation by 

email to potential participants. Since the plat-

forms did not inform how many people visual-

ized the posts, we could not infer the percentage 

of invites that led to answers 

Before sending the invitation, we performed 

a pilot with three participants. Considering the 

participants’ feedback, we improved the ques-

tionnaire aiming to ensure that the questions were 

clear and understandable. The invitation to par-

ticipate in the study was posted on social media 

and sent by email on December 16th, 2020. We 

received answers until January 11th, 2021. We re-

ceived 40 answers to the questionnaire, however, 

after analyzing the participants profile related to 

HCI design knowledge and experience, we ex-

cluded one participant who reported to have low 

knowledge and experience with HCI design and 

did not answer some of the questionnaire ques-

tions. After that, each provided answer was veri-

fied and data was consolidated and analyzed 

against the research questions.    

4.2 Results 

In this section, we present the data synthesis for 

each research question. 

Stakeholders involved in HCI design prac-

tice (RQ1): aiming to identify stakeholders in-

volved in HCI design practice, we asked the par-

ticipants to identify the stakeholders they directly 

interact with within their HCI design practice. As 

it can be seen in Table 10, developer has been the 

most common stakeholder involved in HCI de-

sign practice, being mentioned by 37 participants 

(94.9%). Following that, project manager, de-

signer, user and client were mentioned, respec-

tively, by 34 (87.2%), 33 (84.6%), 27 (69.2%) 

and 26 (66.7%) participants. Product owner was 

cited by three participants (7.7%) and others 

(business analyst, customer experience analyst, 

data analyst, HR people, product manager and 

scrum master) were mentioned only once. 

Table 10. Stakeholders involved in HCI design practice. 

Stakeholder Number of participants % 

Developer 37 94.9% 

Designer 34 87.2% 

Project Manager 33 84.6% 

Client 27 69.2% 

User 26 66.7% 

Product Owner 3 7.7% 

Business Analyst 1 2.6% 

Customer 

Experience Analyst 

1 2.6% 

 
2 https://www.interaction-design.org 

Data Analyst 1 2.6% 

HR People 1 2.6% 

Product Manager 1 2.6% 

Scrum Master 1 2.6% 

 

 Knowledge involved in HCI design prac-

tice (RQ2): first, the participants were asked 

about the knowledge items they use or produce 

during HCI design activities. We consider as 

knowledge items pieces of knowledge that can be 

useful in HCI design, such as lessons learned, 

standards, guidelines and patterns. Figure 6 pre-

sents the results of this question. Some items 

have been used and produced by a high number 

of participants: organizational design standards 

(used by 34 participants, 87.2%, and produced by 

26 participants, 66.7%), lessons learned (used by 

34 participants, 87.2%, and produced by 24 par-

ticipants, 61.5%), guidelines (used by 34 partici-

pants, 87.2%, and produced by 22 participants, 

56.4%) and libraries of design components or el-

ements (used by 32 participants, 82.1%, and pro-

duced by 23 participants, 59%). Other knowledge 

items have also been used by many participants, 

but produced by a smaller number, such as exam-

ples (used by 34 participants, 87.2%, and pro-

duced by 14 participants, 35.9%), design solu-

tions from the organization (used by 35 partici-

pants, 89.7%, and produced by 18 participants, 

46.2%) and design solutions from outside the or-

ganization (used by 35 participants, 89.7%, and 

produced by 11 participants, 28.2%). In general, 

HCI design practitioners have used and produced 

different knowledge items (11.1 and 6.6 in aver-

age, respectively). 

 

Figure 6. Knowledge items used and produced in HCI de-

sign practice. 

https://www.interaction-design.org/


 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

The participants were also asked about design 

artifacts they use or produce during HCI design 

activities. We use the term design artifact to refer 

to documents, models, prototypes and others that 

record information about the design solution. 

Figure 7 shows the results. User requirements, 

scenarios and interaction models were the most 

cited artifacts used during HCI design. On the 

other hand, wireframes, functional prototypes 

and mockups were the most cited artifacts pro-

duced during HCI design. 

 

Figure 7. Design artifacts used and produced in HCI design 

practice. 

We also asked the participants to inform 

whether the artifacts used and produced by them 

sufficiently provide all information needed to de-

scribe the HCI design solution (i.e. if the 

knowledge recorded in the artifacts is enough for 

the implementation and evaluation of the solu-

tion). 26 participants (66.7%) answered “yes” 

and 13 (33.3%) answered “no”. Eight out of the 

13 participants pointed out they missed infor-

mation about personas, user research data and us-

ability tests. These 13 participants were also 

asked about the ways the missing information is 

communicated. The results are presented in Table 

11. Annotations and talks have been the most 

used ways (eight participants, 61.5%) to comple-

ment the information provided in design artifacts. 

Seven participants (53.9%) reported the use of 

meetings, while one used documentation or spe-

cific tools. The participants indicated that anno-

tations and talks had been used informally, while 

meetings, documentation or tools have been used 

systematically, following organizational prac-

tices.  

Table 11. Ways to obtain missing information. 

Method Number of 

participants 

% 

Annotations 8 61.5% 

Talks 8 61.5% 

Meetings 7 53.9% 

Documentation or Tool 1 7.7% 

None 1 7.7% 

 

HCI design activities demanding better 

KM support (RQ3): taking the HCI design ac-

tivities established by ISO 9241-210 (ISO, 2019) 

as a reference, the participants were asked to 

judge whether the knowledge resources (e.g., 

knowledge items, artifacts) used by them have 

provided sufficient knowledge to support each 

activity. Figure 8 presents the results. In general, 

most participants consider that they have access 

to enough knowledge to perform HCI design ac-

tivities. Produce design solutions has the highest 

number of participants (31 participants, 79.5%) 

reporting to have had sufficient knowledge to 

perform it. On the other hand, evaluate design so-

lutions has the highest number of participants (10 

participants, 25.6%) declaring that the available 

knowledge has not been enough. Sixteen partici-

pants (41%) declared to have not had sufficient 

knowledge to support at least one HCI design ac-

tivity. They pointed out that, in order to address 

the lack of knowledge, they have performed user 

research, searched for successful use cases, 

talked to stakeholders, and looked at the litera-

ture. 

 

Figure 8. Available knowledge to support HCI design activi-

ties. 

How KM has been applied in HCI design 

practice (RQ4): Figure 9 shows the approaches 

that have been used to support knowledge access 

or storage in HCI design practice.  Brainstorming 

and blogs have been the most used ways to access 

knowledge (28 participants, 71.8%), followed by 

mental models and electronic documents and 

spreadsheets (26 participants, 66.7%). Except for 

blogs, those have also been the most used ways 

to store knowledge: brainstorming has been used 

by 27 participants (69.2%); mental models and 

electronic documents and spreadsheets by 24 

(61.6%). Ontologies have been the less used way 

by the participants. Only 7 participants (18%) 

have used ontologies to access knowledge and 5 

participants (12.8%) have used it to store 

knowledge. Concerning knowledge storage, so-

cial networks (6 participants, 15.4%) and forums 

(8 participants, 20.5%) have also not been much 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

used. In general, the approaches shown in Figure 

9 have been more used to support knowledge ac-

cess than to support knowledge storage. 

 

 

Figure 9. Approaches to support knowledge access and stor-

age in HCI design. 

Benefits and difficulties of using KM in 

HCI design practice (RQ5): 34 participants 

(87.2%) reported performing KM practices to 

support HCI design activities. 16 of them 

(41.0%) have followed institutionalized organi-

zational practices, while 18 (46.2%) have per-

formed on their own initiative. These 34 partici-

pants were asked about the benefits and difficul-

ties they have perceived in using KM to support 

HCI design. The results are summarized in Table 

12 and Table 13. 

Table 12. Benefits of using KM in HCI design practice. 
Benefit Number of 

participants 

% 

Enable replicability of 

domain or context 

knowledge 

27 79.4% 

Promote standardization 26 76.5% 

Improve communication 25 73.5% 

Increase productivity 24 70.6% 

Reduce design effort 24 70.6% 

Improve product quality 23 67.6% 

Improve design 

conceptualization 

20 58.8% 

Improve team learning 18 52.9% 

Reduce dependency on 

specialists  

18 52.9% 

Increase team engagement 

or empowerment 

17 50.0% 

Increase organizational 

integration 

16 47.1% 

Reduce design cost 16 47.1% 

Promote organizational 

competitive advantage 

11 32.4% 

 

Table 13. Difficulties of using KM in HCI design practice. 

Difficulty Number of 

participants 

% 

Low team engagement or 

empowerment 

16 47.1% 

KM implementation and 

maintenance effort 

15 44.1% 

Integration of the KM approach 

into the organization 

15 44.1% 

Lack of consensus about HCI 

design conceptualization 

14 41.1% 

Find relevant knowledge to a 

given context 

13 38.2% 

Low user involvement 9 26.5% 

Issues related to features of the 

KM technologies 

8 23.5% 

Unclear business model 1 2.9% 

 

Goals to which the use of KM in HCI de-

sign practice has contributed (RQ6): Aiming 

to identify the predominant reasons for using KM 

in HCI design practice, the participants were 

asked how much KM support to HCI design con-

tributes to achieving certain goals. The goals pre-

sented to them were identified in the systematic 

mapping as motivations to perform KM in the 

HCI design context. Figure 10 shows the results. 

 

Figure 10. KM contribution to goals achievement when sup-

porting HCI design. 

According to the participants, the goals to 

which using KM in HCI design contributes the 

most are improve product quality (84.6% of the 

participants stated that KM contributes a lot or 

contributes to it) and reduce effort spent on de-

sign activities (79.5% of the participants stated 

that KM contributes a lot or contributes to it). On 

the other hand, the participants have seen less 

contribution of KM in HCI design to reduce the 

usage of financial resources in design and to re-

duce the dependency on specialists (43.6% of the 

participants stated that KM contributes little or is 

indifferent to both of them).   



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

4.3 Discussion 

In this section, we present some discussions 

about the results shown in the previous section. 

By analyzing the participants’ profile, we no-

ticed that several stakeholders (20.5%) who had 

knowledge of and experience with HCI design 

did not play a role devoted to HCI design by the 

time of the survey execution. We believe that this 

reinforces the multidisciplinary nature of HCI de-

sign and corroborates with a recent finding from 

(Neto et al., 2020) that some professionals may 

choose to pursue a double background involving 

design and development areas. 

Concerning stakeholders (RQ1), it can be no-

ticed that a variety of them are involved in HCI 

design. Considering that the interactions usually 

occur in the context of projects, the results indi-

cate that teams of HCI design projects have in-

cluded designers, developers, project managers, 

and frequently also have involved clients and us-

ers. These stakeholders have different roles in 

HCI design, and thus may have different HCI de-

sign knowledge needs. For example, a developer 

may need to implement the design solution pre-

sented in a design artifact. For that, this artifact 

should present technical decisions that affect the 

implementation. A project manager, in turn, may 

need to have a broader view of several design ar-

tifacts to verify if the implemented solution satis-

fies the requirements agreed with the client. 

Hence, KM approaches must consider the needs 

of different stakeholders to properly support HCI 

design. Moreover, it may be necessary to inte-

grate knowledge from different sources to pro-

vide a solution that integrates the needs of differ-

ent stakeholders. This can be done, for example, 

with a knowledge management system with mul-

tiple views for each different role.   

Regarding knowledge involved in HCI design 

(RQ2), by analyzing the knowledge items used 

and produced in HCI design practice, we can no-

tice which knowledge has been more useful to 

practitioners. Most participants use knowledge 

items that provide design knowledge obtained 

from previous design experiences, such as design 

solutions from the organization, design solutions 

from outside the organization and examples. This 

can be a sign that new designs have been created 

based on previous experiences adapted to the new 

context. However, these knowledge items have 

not been much produced by the participants. This 

may be due to the effort required to record 

knowledge for future reuse. Hence, it would be 

important to facilitate capture, recording and re-

trieval of knowledge embedded in design solu-

tions. On the other hand, two of the knowledge 

items produced by the highest number of partici-

pants (organizational design standards and guide-

lines) record general principles and practices to 

be followed when designing HCI solutions. This 

may indicate that the participants have found it 

easier to produce knowledge independent of spe-

cific solutions. Considering the relation between 

the number of knowledge items used and pro-

duced by the participants, the higher number of 

used items shows that, in general, the participants 

have acted more as knowledge consumers than 

knowledge producers. This may happen because 

either the participants do not have enough time to 

produce knowledge items, or the knowledge pro-

duction is done by someone else. Consulting 

knowledge directly helps designers in the activi-

ties they were doing at that moment. In contrast, 

knowledge production does not seem to be im-

mediately useful to them, although it is important 

at an organizational level. We believe that ap-

proaches that promote knowledge recording and 

storage requiring less effort could motivate de-

signers to act as knowledge producers. 

As for design artifacts, we noticed that the 

ones produced by more participants (wireframes, 

functional prototypes and mockups) represent ab-

stractions of the design solution. Hence, the cre-

ation of such artifacts is part of the design solu-

tion development. On the other hand, the artifacts 

used by more participants (user requirements, 

sceneries and interaction models) provide useful 

information to develop the design solution (i.e., 

they represent inputs to design development).   

One-third of the participants (33.3%) considered 

the artifacts used or produced by them limited to 

meet information needs about the design solution 

and reported the use of complementary ways to 

transfer missing knowledge. When analyzing the 

three most cited ways, we observed that two of 

them (talks and meetings) are based on the con-

versation between team members. This can be a 

sign that it may be difficult to articulate certain 

pieces of knowledge in artifacts. This is rein-

forced by the high usage of annotations, which 

are less formal and structured, and the low usage 

of documentation and tools. Besides, considering 

that the use of more than one method of 

knowledge transfer is a common practice used by 

the participants, it is likely that they prefer to 

have this communication redundancy as a way of 

reinforcing the understanding of all stakeholders 

about the design. Therefore, we believe that the 

missing knowledge in HCI design artifacts can be 

transferred, for example, by performing regular 

meetings and by providing means to easily attach 

additional annotations on design artifacts. 

Concerning HCI design activities (RQ3), 

‘produce design solutions’ was the one that more 

participants (79.5%) indicated to have access to 

enough knowledge to perform it. This can be a 

sign that participants have used knowledge 

mainly to support the creation of design solu-

tions. On the other hand, a high number of partic-

ipants indicated that they had not had sufficient 

knowledge to perform the activities ‘understand 

and specify the context of use’ (23%), ‘specify 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

user requirements’ (23%) and ‘evaluate the de-

sign solution’ (25.6%). Therefore, it is necessary 

to identify useful knowledge to support these ac-

tivities (e.g., missing knowledge related to per-

sonas and user research data, as reported in RQ2) 

and provide means to represent and access it in 

an easy way.     

As for the approaches to support knowledge 

access and storage in HCI design (RQ4), it can 

be observed that the most used approaches, such 

as brainstorming, mental models and electronic 

spreadsheets and documents, usually support 

both knowledge access and storage. This may 

suggest that it is easier and simpler to implement 

and use them. Brainstorming, for example, has 

the advantage of the participants sharing and ob-

taining knowledge at the same time. On the other 

hand, web-based resources, such as blogs, forums 

and social networks are more used to support 

knowledge access than knowledge storage. Prob-

ably, these resources have been used more as 

sources of inspiration to bring new ideas from 

outside the organization. In addition, the reason 

why these resources have been less used by prac-

titioners to record knowledge may be a concern 

in not exposing organizational design knowledge 

on the internet. HCI design knowledge must be 

captured, recorded and propagated in order to be 

raised from the individual level to the organiza-

tional level. Hence, we believe that KM initia-

tives in HCI design should consider approaches 

such as the ones most used by practitioners to 

support both knowledge access and storage. 

Concerning the benefits and difficulties of us-

ing KM in HCI design (RQ5), most participants 

declared to have experienced KM practices in 

HCI design.  41.0% followed institutionalized 

practices and 46.2% have performed on their own 

initiative. This indicates that HCI design profes-

sionals have been concerned with the need for 

practices that help manage knowledge and are 

seeking solutions by themselves when they are 

not provided by the organization. According to 

the participants, in general, using KM to support 

HCI design brings more benefits than difficulties. 

The most cited benefits were related to standard-

ization, reuse, communication and productivity, 

while the most cited difficulties were related to 

the lack of consensus in HCI design conceptual-

ization and to the effort of implementing, engag-

ing the team and integrating the KM approach in 

the organization. Based on that, to effectively im-

plement a KM approach, it would be interesting 

to convince people and the organization that the 

additional effort in the beginning is worth the 

benefits they obtain afterward. 

Finally, by analyzing goals to which the use 

of KM in HCI design has contributed (RQ6), ‘re-

duce the usage of financial resources’ and ‘re-

duce the dependency on specialists’ have been 

considered less impacted by the use of KM in 

HCI design. This may be because reducing costs 

can be a side effect of reducing time spent on de-

sign or producing better designs, with fewer er-

rors. Moreover, even if expert’s knowledge is 

transferred and managed at the organizational 

level, user-centered design deals with people, 

hence there are subjective aspects that still need 

to be addressed by specialists. Another point to 

be considered is that the participants of the survey 

were, in the majority, HCI design experts, which 

could have biased their answers about the impact 

of using KM to reduce the dependency on HCI 

design experts. It is also important to note that 

‘reduce the effort spent on design activities’ was 

the goal which participants believe to be most im-

pacted by the use of KM in HCI design. By hav-

ing in hand proper knowledge resources, the de-

signer can learn from previous experiences, reuse 

solutions and explore more design alternatives, 

which can lead to designing better and more effi-

ciently.  

4.4 Threats to Validity 

As discussed in the context of the systematic 

mapping, when carrying out a study, it is neces-

sary to consider threats to the validity of its re-

sults. In this section, we discuss some threats in-

volved in the survey using the classification pre-

sented in (Wohlin et al., 2012). 

Internal Validity: It is defined as the ability of 

a new study to repeat the behavior of the current 

study with the same participants and objects. The 

main threat to internal validity is communication 

and sharing of information among participants. 

To address this threat, the questionnaire was made 

available online, so that the participants could an-

swer it at the time they considered most appropri-

ate. This can minimize the threat of communica-

tion since participants were not physically close 

during the study and did not necessarily perform 

the study at the same time. 

External Validity: It is related to the ability to 

repeat the same behavior with different groups of 

participants. In this sense, the limited number of 

participants and the fact that all of them are Bra-

zilian professionals are also threats to the results. 

Moreover, some of the participants were invited 

based on the authors’ relationship network, which 

may also have influenced the answers.  

Construction Validity: It refers to the relation-

ship between the study instruments, participants 

and the theory being tested. In this context, the 

main threat is the possibility that the participants 

have misunderstood some questions. To address 

this threat, we performed a pilot that allowed us 

to improve and clarify questions. Moreover, we 

provided definitions for the terms used and exam-

ples of information that should be included in the 

survey, so that the participants could better under-

stand how to answer it.   

Conclusion Validity: It measures the relation-

ship between the treatments and the results and 

affects the ability of the study to generate conclu-

sions. A threat to conclusion validity refers to the 

subjectivity in data analysis, which may reflect 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

the authors’ point of view. In addition, the results 

reflect the participants’ personal experience, in-

terpretation and beliefs. Hence, the answers can 

embed subjectivity that could not be captured 

through the questionnaire. These and the other 

threats discussed above affect the representative-

ness of the survey results and, thus, the results 

must be understood as preliminary evidence and 

should not be generalized. 

5 Consolidated View of Find-

ings 

In this section, we present some discussions in-

volving the systematic mapping and survey re-

sults, aiming to provide a consolidated view of 

the findings from both studies. 

The three most cited motivations for using 

KM found in the systematic mapping (RQ3) are 

the same as the three goals most impacted by the 

use of KM in HCI design practice, according to 

survey participants (RQ6). This shows that, in 

general, it is expected that the use of KM in HCI 

design can contribute to improving product qual-

ity and reducing effort and time spent on design 

activities. 

Considering the most reported benefits and 

difficulties of using KM in HCI design, the sur-

vey results provided some of them that were not 

observed in the literature. For example, most sur-

vey participants reported ‘standardization’ and 

‘productivity’ as benefits and ‘KM implementa-

tion and maintenance effort’ and ‘lack of consen-

sus about HCI design conceptualization’ as diffi-

culties. This difference is not a surprise, since the 

mapping results showed that most proposed ap-

proaches had not been applied in the industry. We 

believe that to achieve success in implementing 

knowledge management, it is important to con-

sider HCI design professionals’ perspectives, 

pursuing the benefits and implementing strate-

gies to overcome the difficulties. 

There are other differences between the map-

ping and survey results. For example, traditional 

KM technologies, such as knowledge manage-

ment systems, knowledge repositories and 

knowledge-based systems, have been the most 

used approaches reported in the literature, but 

have not been much used by HCI design profes-

sionals. The reasons why they do not use those 

approaches may be quite diverse, including not 

being aware that they exist or considering them 

too complex. Since 46.2% of the participants per-

form KM practices on their own initiative, they 

have likely preferred simpler approaches that can 

be implemented by themselves. This reinforces 

the gap between industry and academy perceived 

from the analysis of the systematic mapping re-

sults. In order to decrease this gap, KM ap-

proaches to support HCI design should be closer 

to approaches that professionals are already fa-

miliar with, which can contribute to simpler and 

easier implementation and use. 

Results from both studies show that design 

guidelines and design solutions have been reused 

in HCI design. Organizational design standards, 

lessons learned and design component libraries 

have also been useful for HCI design profession-

als. Therefore, KM approaches to support HCI 

design should be able to handle these knowledge 

items, supporting their capture, storage and re-

trieval. As indicated by results from both studies, 

these knowledge items have probably been most 

used to support the activity ‘produce design solu-

tions’. This was the activity in which most ap-

proaches found in the literature use knowledge 

and most participants considered having suffi-

cient knowledge support. KM approaches should 

also provide support to other activities such as 

‘understand and specify context of use’, ‘specify 

user requirements’ and ‘evaluate design solu-

tions’, contributing to the HCI design process as 

a whole.  

6 Conclusion 

In this paper, we presented an investigation about 

the use of knowledge management in the HCI de-

sign context. To investigate the state of the art, we 

performed a systematic mapping. After that, we 

carried out a survey with 39 Brazilian profession-

als who work on HCI design. As the main result 

of the studies, we provided a panorama of re-

search related to the topic and identified gaps and 

opportunities for improvements to organizations 

interested in applying KM initiatives in the HCI 

design context.  

We noticed that, although HCI design is a fa-

vorable area to apply knowledge management, 

there have been only a few publications exploring 

this research topic. Due to the increasing im-

portance of interactive systems and the diversity 

of interfaces that have been made available for 

people’s use, we believe that there are many chal-

lenges and questions to be addressed in future re-

search. For example: (i) The lack of a common 

conceptualization of HCI design (pointed out in 

#01 and #02 in the mapping study and also by 

35.9% of the survey participants) leads to com-

munication problems between the different actors 

involved in the HCI design process. We believe 

that the use of ontologies to establish this com-

mon conceptualization could help in this matter. 

However, since ontologies are not much familiar 

to practitioners (survey RQ4 results), ontology-

based KM approaches in HCI design should ab-

stract the ontology to final users (e.g., using the 

ontology to derive the conceptual model of a 

knowledge-based system). (ii) The gap between 

theory and practice (systematic mapping RQ2 re-

sults) shows that it is necessary to take KM solu-

tions to practical HCI design environments. The 



 

Investigating Knowledge Management in HCI Design Castro et al. 2022 

   

 

survey results show that HCI design profession-

als are familiar with more robust KM approaches 

(such as knowledge management systems), but 

prefer to use simpler ways to deal with 

knowledge, such as brainstorming sessions and 

electronic spreadsheets and documents. There-

fore, lightweight technologies and a divide and 

conquer strategy to reduce the complexity of the 

conception, implementation and evaluation of a 

KM approach might be useful, allowing to pro-

vide results for the organizations in smaller peri-

ods of time and increasing benefits as the ap-

proach evolves. (iii) Other aspects besides usabil-

ity (e.g., user experience, communicability and 

accessibility) should be explored in KM initia-

tives to improve HCI design. (iv) The benefits 

and difficulties identified in the mapping (RQ7) 

and reported by the survey participants (RQ5) in-

dicate issues that can be investigated in future re-

search. For example, case studies can be carried 

out in organizations to evaluate the use of KM 

approaches in the HCI design context. 

Concerning related works, we did not find 

any study investigating the use of KM in the HCI 

design context. A work that can be related to ours 

is (Stephanidis & Akoumianakis, 2001), consist-

ing of a literature review about categories of com-

puter-aided HCI design tools and a proposal of a 

new category to address the knowledge complex-

ity involved in HCI design. However, the study 

focused on computational tools, not investigating 

how other kinds of KM approaches can help in 

the HCI design process. 

As future work, concerning the systematic 

mapping, new studies can be conducted to better 

understand the state of the art of KM in HCI de-

sign and improve the use of KM in this context. 

For example, the results obtained in our mapping 

study could be compared with results from other 

studies investigating KM use in other domains 

(e.g., requirements engineering). Moreover, KM 

solutions proposed in other domains can inspire 

new proposals to support HCI design by using 

KM. As for the survey, it can be extended to in-

clude more participants from different countries 

and also to investigate other aspects. Considering 

the studies’ results, which showed us a gap be-

tween the HCI design professionals and the ap-

proaches proposed in the literature, we have 

worked on the development of a tool to support 

KM in the context of HCI design of interactive 

systems (Castro et al., 2021). By making use of 

the information provided by this study, we aim to 

reduce the gap between academy and industry by 

proposing a tool able to meet the needs of HCI 

design professionals. 

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	Investigating Knowledge Management in Human-Computer Interaction Design
	1  Introduction
	2  Background
	2.1 HCI Design
	2.2 Knowledge Management

	3 Systematic Mapping: KM in HCI Design according to the literature
	3.1 Research Protocol
	3.2 Results
	3.3 Discussion
	3.4 Threats to Validity

	4 Survey: KM in HCI Design practice
	4.1 Survey Planning and Execution
	4.2 Results
	4.3 Discussion
	4.4 Threats to Validity

	5 Consolidated View of Findings
	6 Conclusion
	References