=Paper=
{{Paper
|id=Vol-2075/FIRE18_paper1
|storemode=property
|title=Requirements Engineering Elicitation for Mobility Assistance Dogs: Meeting Canine User Needs Through Technology Enabled Interpretation
|pdfUrl=https://ceur-ws.org/Vol-2075/FIRE18_paper1.pdf
|volume=Vol-2075
|authors=Luisa Ruge,Clara Mancini,Rachael Luck
|dblpUrl=https://dblp.org/rec/conf/refsq/RugeML18
}}
==Requirements Engineering Elicitation for Mobility Assistance Dogs: Meeting Canine User Needs Through Technology Enabled Interpretation==
https://ceur-ws.org/Vol-2075/FIRE18_paper1.pdf
Requirements Engineering Elicitation for Mobility
Assistance Dogs: Meeting Canine User Needs Through
Technology Enabled Interpretation
Luisa Ruge Clara Mancini Rachael Luck
The Open University The Open University The Open University
Milton Keynes, UK Milton Keynes, UK Milton Keynes, UK
luisa.ruge@open.ac.uk clara.mancini@open.ac.uk rachael.luck@open.ac.uk
Abstract
Current requirements engineering methods are heavily reliant on verbal
techniques, which are inaccessible to non-verbal users, such as mobil-
ity assistance dogs (MAD). Findings from a recent pilot study, con-
ducted at a MAD training facility, show that the elicitation of canine
stakeholder needs while in training is highly dependent on employee
interpretation. This paper promotes the use of technology in support
of meeting canine user needs, as suggested by the emerging field of
Animal-Computer Interaction (ACI), by enabling trainers and employ-
ees to accurately elicit and interpret canine stakeholder requirements.
1 Introduction
Current requirement engineering (RE) methods are heavily reliant on verbal techniques for eliciting stakeholder
expectations of technological applications [1]. However, in the case of special groups - including people with
cognitive impairments, young children and animals - the baseline for verbal capability has a high level of
variance, and in some cases such a capability is non-existent, as in the case of dogs. Since they routinely
interface with the built environment on behalf of their assisted humans, MAD are widely recognized within
the ACI community as technology users [2]. In order to design interfaces that can better support their work,
ACI researchers have started to investigate MADs’ interactions with the built environment, and the training
processes that the dogs undertake to learn their work skills and be matched with a human partner [2]. In this
regard, developing accessible requirements elicitation techniques for those who do not possess verbal capabilities
- such as MADs in training - is vital to meeting their needs.
Most RE methods include some form or other of interpretation [3]. However, when it comes to other
species, the complexity of interpretation increases due to differences in cognitive, physiological and sensory
capabilities between elicitors (humans) and users (dogs) [2]. In the case of MADs, the result of the training
stage of their development is used to identify a compatible placement with a disabled individual and their living
environment. Hence, the methods used to assess MADs’ behavior and temperament to match them within a
partnership are highly influential on their future.
This paper reports preliminary findings from a recent pilot study using ethnographic methods to investi-
gate the current MAD training and matching assessment processes, and their reliance on employees‘ ability to
interpret canine behavior. Although, employee practices are carefully designed to utilize objective assessment
Copyright c by the paper’s authors. Copying permitted for private and academic purposes.
criteria, they may still be open to instances in which inaccurate interpretations of canine behavior(s) may result
in the misrepresentation of MAD stakeholder needs.
2 The Study
2.1 Aim
The aim of the pilot study was to gain an overall understanding on processes and interactions involved in
whelping, training, matching and placing MADs with clients, as a means to identify areas that may directly
impact their wellbeing and performance. This early work is part of doctoral research within the project Dog-
Smart Homes: Portable Controls Optimized for Mobility Assistance Dogs, whose objective is to improve the
performance and wellbeing of MAD partnerships.
2.2 Participants, Data Collection Methods and Study Limitations
The fieldwork was conducted at the facilities of Dogs For Good (DFG), a UK-based charity focused on “creating
partnerships between people living with disability and specially trained assistance dogs.” [4]. During the week
long study the researcher interviewed 13 staff members who work within the areas of training and development,
and service support and administration, 1 MAD dog partnership, and 1 puppy volunteer, as well as extended
observations of 3 MADs in training. Data collection methods included observation, shadowing, participatory
research, semi-structured and contextual interviews, which were recorded, based on participant preference,
in the form of photography, audio, and video. The processes observed during the study represent common
examples of operations within the industry [5] [6].
The ethnographic data collection methods and analysis of this study were limited in as much as all in-
terviews were mediated through the researcher. In addition, the study is based within a particular context,
that of DFG, which although a common example of MAD industry operations is still a particular charity, with
characteristic processes, roles and methods.
2.3 Data Analysis
Coded interview guides were created in advance containing nominal categories such as interviewee name, role,
and time employed at DFG and focused on categories of inquiry regarding: employee past experience, reason
for working at DFG, role and responsibilities at DFG, role challenges and successes, information management,
canine behavior, and their individual experience in interacting with MADs.
Video and audio recordings were transcribed as individual files for every participant. Subsequently, the
file content was categorized into individual text cells and coded with participant identifiers and those established
in the interview guides. Content that did not fall into any of the pre-established codes was categorized under
the heading “other”, and was then reviewed in order to identify emerging content themes among the various
participants [7] [8].
The result was a consolidated content database that allowed the researcher to review each content cell
and allow a secondary categorization into content relating to: A) Functional DFG Interactions: all content
regarding any process, method or activity carried out by DFG in order to complete any part of the whelping,
socializing, training, matching, placement or aftercare of MAD, and/or client application, selection, matching
and placement; and B) MAD and Human Interactions: all content pertaining to specific instances where any
participant was engaged in an interactive experience with another participant or a MAD.
This secondary categorization of the individual content cells by type of interaction was used to create a
variety of analysis documentation, including a database of notable canine behaviors of detailed descriptions of
episodes in which canine behaviors elicited value-based verbal assessments on the part of the study participants
and/or the researcher. The episodes are indicative of employee intent to ensure objectivity, yet illustrate the
importance that employee interpretation has in accurately representing MAD stakeholder needs. This paper
uses one of the incidents from the database, identified as Incident F, as a means to show how the elicitation of
canine stakeholder needs while in training is highly dependent on employee interpretation.
3 Incident F Background
3.1 Focus on Training and Matching
To prepare them for the services offered by DFG, dogs identified as potential MADs partake in purposefully
designed training and development programs. These services extend during the working lifespan of a MAD and
include the following stages: breeding, socialization, training and matching, placement with client, partnership
aftercare, and retirement. Based on the amount and influence of assessments and human intervention observed,
services carried out during the MAD training and matching phase have the most influence on how their future
will unfold; as it is here that their suitability and aptitude for working as MADs is assessed, and used to match
them with their human partners.
At approximately 18 months of age, dogs that have been living with volunteer socializers come back to
DFG and are placed with temporary boarders while undergoing a 16-week training program. During this time
they are taught the necessary skills to develop from well-behaved companion dogs to specialized MADs. MAD
training and matching activities are guided by a total of 11 assessments, complemented by constant observation
and discussion of the dogs behavior and development by charity staff and, in certain occasions, also by their
temporary boarders, potential clients and future caretakers. The number, variety and frequency of assessments
being performed evidence the complexity involved when eliciting and assessing training requirements for MADs.
3.2 Kennel Behavior/Training Request (KBTR) Assessment
One of these assessments is the KBTR form, essentially an incident report form, used between MAD trainers and
kennel staff to clearly identify potential behavior issue(s) exhibited by MADs in order to quickly and consistently
intervene and resolve said behavior(s). These forms are designed to collect very detailed data to enable trainers
to identify exactly whether kennel staff intervention is warranted. The information recorded includes: (a) name
of the dog, (b) name of trainer and allocated kennel staff; (c) the date in which the behavior was observed; (d)
the description of the behavior or reason for the request; (e) the request itself; (f) the date in which the issue
and dog are to be reviewed; (g) signatures and dates confirming the discussion of the potential behavior issue
between trainer and kennel assistant; (h) and the date in which the request was submitted to the management,
signed by the trainer, and health and welfare manager. All staff at DFG are constantly observing MADs in
training and are in a position to highlight any behavioral issues. If this happens, they are encouraged to alert
the MAD’s assigned trainer and describe the incident.
4 Incident F Description
During the study, while waiting in the training and instructor office, a large room outfitted with hot desk tables
where employees come and go continuously and MADs in training (no more than 3) are kenneled throughout
the day, the researcher observed one dog in training (Dog A) pacing and whining. Hearing the whining, a few
employees offered calming feedback and a toy. Shortly afterwards, Dog A whined again. Even though, to the
researchers knowledge, the whining had just started, one of the employees (Employee A) expressed concern and
called Dog A’s trainer (Trainer A) to alert them to this behavior.
Later on, while interviewing Trainer A regarding canine behavior, and specifically how trainers interpret
and assess MADs’ behavior during training, the following comments were made:
Trainer A: “This afternoon the fact that Employee A called me and told me Dog A was quite stressed in
the office, I dont know what it was that particularly caused that. I took Dog A out this morning, I did not take
Dog A out at lunch but it‘s not like I usually do. It‘s not like there is much change. I did pop into the office but
then I have done that many times before. I don‘t know. Was there lots going on or very little going on? Did
Dog A need to toilet? Because there are so many things we don‘t see. Had Dog A been on a walk or not? Is Dog
A then anticipating other things? But the fact that we came in here and within a few minutes Dog A fell asleep
or has been asleep the whole time, you know it could have been very isolated to that situation. If Dog A was still
pacing here I would be like, oh maybe Dog A has an upset tummy or what has happened today, then send an
email, has anything been different? Have there been any changes? The fact that Dog A has just come out and
slept. Who knows?”
5 Findings
5.1 Incident Impact on Trainer and MAD
Based on study observations, interview data and the above mentioned database of canine notable behaviors
analysis document, incidents such as the one described above are a common occurrence. Trainers are not always
present when the MADs they are training exhibit behavior(s) that could be construed as KBTR assessment
worthy. Thus, they are left to find clues, discern the validity of employee accounts, and run through a mental
inventory of possible reasons as to what might have affected the dogs. On their part, non-verbal MADs are unable
to offer an explanation and are entirely dependent on the trainers‘ ability to accurately interpret the incident,
which is highly influenced by the trainers knowledge of canine behavior, as well as DFG staff and processes.
5.2 Accurate Interpretation
On this occasion, Trainer A knew enough about MADs and Dog A to accurately discern and assess the behavior
in a context-aware manner (i.e. keeping her knowledge of Dog A’s usual temperament in mind and thinking
about Dog A’s usual daily activities) and to realize that filling in a KBTR request was not necessary. An
inexperienced trainer might have misinterpreted the behavior and filled out a KBTR request which would have
caused staff time to be wasted on addressing a non-existent issue. More importantly, it could have impacted Dog
A’s progress during training, due to either unnecessary requests for further assessment and/or intervention, or
inaccurate associations between Dog A and anxious behavior.
5.2.1 Clear Interpretation
Furthermore, the observation of this episode highlights the importance of employees clearly and unambiguously
interpreting canine behavior. During the call between Trainer A and Employee A, words were used to describe
the behavior of Dog A without Trainer A having witnessed the behavior or without it being recorded (i.e. on
video). This exchange evidences an assumption that both Trainer A and Employee A are versed in the vocabulary
used to describe MAD behavior, and more specifically MAD behavior within the organizational context of DFG.
Getting to know, align on, and reach a common understanding of descriptive vocabulary used within a specific
domain (e.g. canine, assistance dog, MAD, Dog A) and context (e.g. canine training, assistance dog training,
MAD training, DFG training) requires experience. A new employee might witness behavior from Dog A that
they might describe as anxious, when the dog might just be excited. This too could cause wasted time and
effort on the part of DFG staff members, and - again most importantly - a recorded instance in a KBTR of
misrepresented behavior attributed to Dog A, which could impact on how and with whom the dog is ultimately
matched.
5.2.2 Explicit Interpretation
Finally, in our records of the incident reported above, the researcher noted down, when Employee A phoned
Trainer A, Dog A’s whining as “just having started”. However, in Employee A’s account to Trainer A, there was
no mention of the duration of the whining, only its frequency. While this might appear to be a minor piece of
information, its inclusion or omission implies important assumptions on the part of all human interpreters of Dog
A’s behavior. For example, the researcher interpreted the behavior as a non-issue due to it having just begun,
even though it might have been ongoing throughout the day without the researcher being aware of it. On the
other hand, employee A assumed the frequency of the whining was enough to call Trainer A, even though Dog A
might be prone to intermittent whining spouts that end as quickly as they begin. As a result, Trainer A might
have assumed that Dog A had been whining frequently, and for a long time, conflicting with their prior knowledge
of Dog A’s whining spouts, as mentioned above. In this episode, the information being implicitly assumed by all
human witnesses opens possibilities for reaching a misleading interpretation. Mitigation of assumptions could
come either from knowing how to accurately assess and discern MAD behavior, as mentioned in 5.2, or from
knowing what information to elicit from employees that witness a notable behavior incident. Regardless, the
result for Dog A is based on Employees A’s previous knowledge of MAD behavior in general, rather than Dog
A’s specific circumstances, which could lead to the dogs behavior being misinterpreted.
6 Discussion
The KBTR episode illustrates the complexity encountered by DFG employees in accurately interpreting canine
behavior(s) in order to elicit and to meet user needs for MADs in training. Such thorough practices rely
on numerous assessments, staff knowledge, and employee experience – yet they remain open to the risk of
behavioral misinterpretation, leading to possible misrepresentation of MAD stakeholder needs. In this respect,
meeting MAD user requirements could be further supported through technology that promotes human-animal
communication, as proposed by researchers within the emerging field of ACI, by supporting the process of human
interpretation of canine behavior(s).
6.0.1 Vocal Activity Monitor
For example, behaviors that result in vocal expression, such as whining or barking, are usually behaviors that
need to be highlighted during MAD training, due to their possible effect on clients, and implications for public
access. Here, taking advantage of the fact that MADs in training work to specific schedules, where their activities
are closely tracked, the dogs could be outfitted with non-invasive vocal activity monitors to track frequency and
duration of vocalizations throughout the day. By knowing the context the dog was in, and their vocal patterns
and behaviors, the activity monitor could create an individual profile for dogs. The profiles could then be used
to establish individual vocal baselines and thus inform an accurate assessment of the impact the behavior could
have on the dog’s ability to work as a MAD. In addition, if recorded behavior was out of range of the individual’s
profile, the monitor could prompt trainers and employees to record the incident, thus enabling a more objective
assessment of the behavior. Furthermore, behavior that was unusual to a particular dog could enable trainers to
quickly identify new requirements and adjust the dog’s training experience.
6.0.2 Vocabulary Standardizer
Another instance where technology could support human interpretation of MAD stakeholder needs is by
supporting the standardization of terminology used when recording information about MAD behavior witnessed
by employees. For such a system to work DFG would need to invest time on the discussion and definition of
detailed behavior descriptions. Once this DFG behavior descriptive language was defined, it could then be coded
and specific descriptors could be associated with a range of linguistic expressions more or less commonly used
to describe the same behaviors within the dog and/or MAD training industry. This initial linguistic mapping
would still allow DFG employees to choose their preferred expressions when describing a particular canine
behavior and thus develop their own tailored vocabulary profile linked to standard descriptors. When recording
their written assessments into digital formats -a common practice within the industry, their vocabulary could
be traced back to the standard descriptors thus improving the consistency of language usage and interpretation
within the organization. In addition, by highlighting any substitutions, the envisaged system could prompt
employees to notice the adjustments made by the system thus promoting the future usage of the standardized
DFG behavior terminology. This could facilitate the interpretation of MAD user needs by fostering the use of a
standardized vocabulary across all assessments and among all DFG employees, thus enabling a more consistent
and accurate interpretation of MAD behavior.
Due to the non-verbal nature of MADs communication, the impact of human interpretation on MAD
training service needs cannot be avoided. However, as exemplified above, ACI researchers could develop
inclusive RE approaches aimed at mitigating human impact on MADs through the deployment of technologies
that better support humans elicitation and interpretation of MAD stakeholder specifications. Thus, we suggest
that technological applications such as the ones described above should be further investigated.
7 Conclusions
The findings of a recent pilot study suggest that eliciting and meeting the needs of MADs in training are impacted
by employees’ ability to accurately, clearly and explicitly interpret their behavior and thus determine if and with
whom a dog is placed within a partnership. Lack of accuracy, clarity and explicitness could potentially lead to
flawed assessments and thus to inappropriate decisions for a dogs future. Further research into how technology
might support accurate human interpretation could lead to the development of RE approaches and toolkits that
support more accessible requirements elicitation techniques, helping researchers and practitioners meet the needs
of non-verbal users such as MADs.
7.0.1 Acknowledgments
This research was conducted with the informed consent of all the participants and ethics approval granted by
The Open University. Funding: This work was supported by the Petplan Charitable Trusts sponsorship of the
doctoral research project Dog-Smart Homes: Portable Controls Optimized for Mobility Assistance Dogs. I would
particularly like to thank all Dogs for Good staff who participated in this research, without whose cooperation
this project would not have been possible.
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