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Running Head: EVALUATION OF SPHERO ON DIFFERENT AGE GROUPS 1

Evaluation of Sphero Among Different Age Groups

Marian Baldonado

University of California Santa Cruz


Abstract

This paper investigates the underlying motivations, strengths, and weaknesses on the use

of Sphero the robotic ball by people of different age groups. This study uses a focus group for

explorative purposes that covers difficulties, ease, changes, and personal investment into Sphero

and combines qualitative and quantitative analyses. This aims to include the older population in

the design discussions surrounding. This study revealed that the older population preferred

salient haptic feedback and design aesthetics with practical functions while the younger

population preferred more diversity in the actions that Sphero could accomplish.


1. Introduction

Sphero is a robotic sphere designed with the intent to facilitate Connected Play.

Designers of Sphero claim that Connected Play is the connection formed between humans

that is mediated by robots, which encourages interactions with both human-human and

human-robot. Sphero differs from traditional purposes of robots because it extends outside of

industrial zones into the domestic front. Some the basic functions of Sphero include rolling,

changing colors, location sensing, accessibility with Bluetooth devices, and programmability.

Even though the company’s target user demographic is children 8 to 14 years old, and robot

enthusiasts, Co-founder Adam Wilson also boasts about the educational factor that Sphero

provides in early teaching of programming [1; 2]. Despite the high expectations surrounding

Sphero, the assessment of the developer’s claims need not only be tested with the target

demographic but also the indirect stakeholders that Sphero affects in the domestic household:

parents, grandparents, older children.

Social robots in the domestic sphere are advancing from a novel idea to a rapidly iterating

field. According to Frennert, Eftring and Östlund, the perseverance of the older population

drives a subsection of assistive robotics research. Unfortunately, the older population may

only be represented in the design process through a developer’s image of them as users [3].

The issue with the development of social robots today is that older groups of people are

purposely ignored or stereotyped, yet are centered as main consumers[3]. How can

developer’s and companies embed solutions based on the preferences, needs, and wants of an

older generation if they are left out of discussion?

2. The study


The purpose of this pilot focus group is to both assess the claims of the designers of Sphero

and to explore the use case, strengths, and improvements identified by an older demographic

compared to the younger demographic. This study combines qualitative and quantitative analysis

on the answers given and the scales measured in the post-question interviews. Qualitatively,

semi-structured post-interview discussion questions and recorded behaviors and exclamations

during the use of Sphero were analyzed. Quantitatively, performance scores on ColorGrab

application with Sphero, recommendation ratings, and market and personal investment

predictions were statistically analyzed.

2.1 Participants

There were two focus group sessions, comprised of 4 people each, with 50% in the less

than 20 years old range and the other 50% above 20 years old (See Table 1).

Session 1 Session 2

Persons under 20 2 2

Persons over 20 2 2

Table 1 : Breakdown of age groups and number of participants in each session.

The participants were recruited via convenience sample with the first session conducted with my

family and the second session with my housemates—all participants are naïve users of Sphero.

Because of the convenient sample, I was able to conduct the sessions in the living space of the

participants (See Figure 1).


Fig. 1: Picture of Session 1 playing ColorGrab with Sphero.

3. Qualitative analysis- Focus group discussion

The Qualitative measures are analyzed through recorded discussion and play behavior

during the basic functions of Sphero on the Sphero application, ColorGrab, and the post-

interview.

3.1 Problems

The participants under 20 years old identified that: the main problem is the lack of color

feedback (See Figure 2). 100% of participants in the younger age range agreed that Sphero

needed more difference between yellow-green and purple-blue. Older persons identified

problems with controls and instructions, the extraneous bulk of color and buttons, feedback when

settings change, the need for a tutorial, and possible interactions with pet (See Figure 3).


Fig. 2: Problem rates of persons under 20 years old. Includes what they mentioned and percentage of

people that mentioned it.

Fig. 3: Problem rates of persons over 20 years old. Includes what they mentioned and percentage of



3.2 Easy

The participants under 20 years old identified that the easiest part of using Sphero is the

controls and holistically understanding the capabilities of Sphero (See Figure 4). Older persons

identified that the easiest part of Sphero are the direct interactions with grabbing Sphero and the

direct feedback from pressing buttons (See Figure 5).

Fig. 4: Easy rates of persons under 20 years old. Includes what they mentioned and percentage of people

that mentioned it.


Fig. 5: Easy rates of persons under 20 years old. Includes what they mentioned and percentage of people

that mentioned it.

3.3 Concerns

The participants under 20 years old identified that the main concern is the lack purpose

for Sphero in group settings. 100% of participants in the younger age range agreed that Sphero

needed an aim (See Figure 6). Older persons identified concerns with Sphero being

unimpressive, constantly getting stuck, gets lost often, and gets dirty often (See Figure 7).


Fig. 6: Concern rates of persons under 20 years old. Includes what they mentioned and percentage of


Fig. 7: Concern rates of persons under 20 years old. Includes what they mentioned and percentage

of people that mentioned it.

3.4 Desired features


The main recommendations that participants under 20 years old wanted to change are the

ability for Sphero to jump, talk, play music, and record ground movement (with a camera). Older

participants desired a camera to record ground movement also, the ability to talk, play music,

change the skin of Sphero, and create a more dynamic and stable redesign so that it doesn’t look

like it can break easily.

Fig. 8: Desired features rates of persons under 20 years old. Includes what they mentioned and percentage



Fig. 9: Desired features rates of persons under 20 years old. Includes what they mentioned and percentage


4. Quantitative analysis- ColorGrab performance

The Quantitative measures analyzed where extracted from the post-interview questions

that asked about recommendations to a friend, the difference between market price and personal

investment predictions, and the ColorGrab performance. The recommendations were measured

with a 5 point Likert scale with 1 = Very much not recommend, 2 = Not recommend, 3 =

Neutral, 4 = Recommend, and 5 = Very much recommend. The participant’s prediction on the

market price of Sphero was subtracted from what the participants would have paid for Sphero;

the difference was used in the statistical analysis. Finally, the ColorGrab performance was taken

from the scores of all the participants after playing ColorGrab.


All three quantitative measures were analyzed via t-test with a 95% confidence interval

comparing the younger aged group with the older age group. I found that there was no significant

difference between the younger age group and the older age group for the Sphero

recommendation, t (6) = 2.236, p > 0.05 p = 0.067 n.s. Similarly, there was no significant

difference between the younger age group and the older age group for the difference in market

price prediction and the personal investment, t (6) = -.778, p > 0.05 p = 0.466 n.s. There was

significant difference in the performance on ColorGrab between the younger age group and the

older age group, t (6) = 3.225, p < 0.05 p = 0.018 s.

Fig. 10: Scatterplot for performance in ColorGrab of all participants from both age groups. t(6) =3.225, p < 0.05, p = 0.018

5. Discussion and Conclusion

Older participants expressed more problems, ease of use, concerns, and desired features

with Sphero that ranged from aesthetic and functionality violations than the younger participants.

For example, for the concerns, the older population took into account personal procedures of

when Sphero needs to be cleaned or found while younger participants focused on more engaging


missions to master. The development of programming features that the developers included takes

into account those that prefer a challenge and personal accomplishment with Sphero, but lacks

the naïve need for tutorials or autonomy for when lost or dirtied. These extensive concerns could

be because of the exclusion or lack of participation of elder groups in the developmental process

in the creation of Sphero [4]. Negligence of a demographic may influence the people’s

acceptance of domestic robots [3]. If indirect users of Sphero are left out of the conversation in

the creation of the system that is supposed to increase connected play within a household, then

how can that system reflect and address the needs of those who are indirectly using Sphero? This

exclusion significantly widens the gap in performance between those in the younger age group

and the older age group when using Sphero. As seen in Figure 10, those who are older did

significantly worse than those who were younger in ColorGrab because of lack of color

discrepancy. This affects investments and experience with Sphero and other robotic innovations,

so we need to bridge this gap in order to be accepted by both groups of people.

All in all we need to include and take into account the problems, concerns, and solutions

of older groups to avoid omitting risk violations. Some actionable recommendations for Sphero

are for aesthetic to change outer shell so that it doesn’t get dirty easily and make the base of

Sphero a sturdier material. For functionality, there needs to be explicit feedback when colors and

task change, add a tutorial in the beginning that can be skipped, change the inverted controls to

direct controls, and possibly include an accessory that is a sensor return for when Sphero is out

of sight.


References

[1] https://techcrunch.com/2013/08/14/sphero-2-0-is-twice-as-fast-agile-and-awesome/

[2] http://mashable.com/2014/01/05/sphero-2b/#BM6Q0C0TYiqE

[3] Frennert, S., Eftring, H., & Östlund, B. (2013). What Older People Expect of Robots: A

Mixed Methods Approach. Social Robotics Lecture Notes in Computer Science, 19-29.

doi:10.1007/978-3-319-02675-6_3

[4] Frennert, S., & Östlund, B. (2014). Review: Seven Matters of Concern of Social Robots and

Older People. International Journal of Social Robotics, 6(2), 299-310. doi:10.1007/s12369-013-

0225-8

http://mashable.com/2014/01/05/sphero-2b/#BM6Q0C0TYiqE

https://techcrunch.com/2013/08/14/sphero-2-0-is-twice-as-fast-agile-and-awesome/

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