=Paper=
{{Paper
|id=Vol-1573/Paper_5_BCSS2016
|storemode=property
|title=Measuring Computer Literacy without Questionnaires
|pdfUrl=https://ceur-ws.org/Vol-1573/Paper_5_BCSS2016.pdf
|volume=Vol-1573
|authors=Roeland H.P. Kegel,Roel J. Wieringa
|dblpUrl=https://dblp.org/rec/conf/persuasive/KegelW16
}}
==Measuring Computer Literacy without Questionnaires==
https://ceur-ws.org/Vol-1573/Paper_5_BCSS2016.pdf
61 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Measuring Computer Literacy without Questionnaires
Measuring Computer Literacy without Questionnaires
Roeland H.P. Kegel, and Roel J. Wieringa
University of Twente, Enschede, The Netherlands
r.h.p.kegel@utwente.nl
Abstract. Behavior Change Support Systems (BCSS) benefit from understand-
ing the user: a user profile can help select the right way to formulate an argu-
ment, selecting the right tone, format and content. Part of such a profile is an
adequate representation of the computer literacy of a user. Unfortunately, com-
puter literacy is commonly measured by asking the user to fill in a question-
naire. This an obstacle to the adoption of a BCSS, and as such is not a good
way to build a model of a user's computer literacy. In this paper we describe the
setup of a series of experiments intended to identify indicators that can be
measured automatically and that correlate well with a relevant concept of com-
puter literacy.
Keywords: Persuasive Technology, Computer Literacy, Behavior Change Sup-
port Systems
1 Introduction
The concept of using the computer as a means to persuade users originated from the
90s, with Captology, or Computers as Persuasive Technologies coined as a term in a
special interest group meeting in CHI '97 [3]. Since then, both computer technologies
and applications have evolved to the point where computers play an ever greater role
in our lives. Many elements that contribute to the persuasiveness of a system have
been examined and identified: Oinas-Kukkonen and Harjumaa have presented an
overview of specific methods by which a persuasive systems may be designed [7],
containing both a way to analyse the context of a persuasive system, as well as tech-
niques to use when implementing it.
A persuasive system with the intent to change attitudes or behaviour conveys mes-
sages designed to influence the user in some way. Whether the intent is to change an
attitude, behaviour, or just to garner short-term compliance, these messages use per-
suasive techniques designed to influence users, explicitly or implicitly, to affect a
change in their view or behaviour. To do so, it is important to understand the user:
certain persuasive techniques can backfire when applied to the wrong person (for
example, using Cialdini's Authority principle [2] may cause an adverse reaction if the
person is not well-disposed towards accepting advice from authority figures). To un-
derstand a user, systems can use persuasive profiles, using past observations about the
user to adapt the means they use when communicating. Kaptein has called such sys-
62 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Measuring Computer Literacy without Questionnaires
tems Adaptive-means Persuasive Systems [4]. Beyond online shopping preferences,
however, Kaptein does not give an implementation in this paper.
1.1 Goal
We propose a system for measuring theoretical construct of computer literacy in an
automated fashion, based on published definitions of these measurements in existing
literature. Computer literacy influences a user’s perception of technology, as well as
the user’s comprehension of any computer related message. This can influence the
persuasiveness of a system: communicating on the wrong technical level, or with the
wrong medium (such as written text, or a virtual agent) can cause an adverse reaction.
In the context of the Personal Information Security Assistant (PISA) project, we aim
to implement a system to measure computer literacy, with the goal of using these
measurements to tailor interactions with the user, which should improve the persua-
sive power of the system. In this workshop paper, we restrict ourselves to the descrip-
tion of experiments to correlate automated measurements of Computer Literacy to
more traditional measurement by questionnaire. These experiments aim to answer the
following research questions:
• RQ1: How can we translate mental constructs to automated measurements based
on user observation?
• RQ2: How can we compare such automated measurements to existing measure-
ment methods?
Answering these research question allows us to answer the following research ques-
tion as a part of future work:
• RQ3: Can we use these measured mental constructs to construct a persuasive pro-
file, improving the persuasive power of a system?
1.2 Defining Computer Literacy
A comprehensive overview of literacies including a discussion about computer litera-
cy has been published by Bawden [1]. In order to update this overview, we first per-
formed a thorough literature study, examining the exact nature of computer literacy as
it occurs within existing literature [5]. This study includes a more detailed look at how
computer literacy is measured in practice, as well as how it is defined in theory. For
this study, 189 documents using computer literacy or related concepts were consulted
and a list of 371 concepts related to computer literacy was created based on these
documents. After several refinement steps, these concepts were organised in a tree
diagram denoting the functional decomposition of computer literacy into measurable
elements. This diagram was constructed by performing a manual categorization of
concepts and subsequently validated by subjecting it to an inter-rater agreement pro-
cess between three researchers. While this diagram is too large to show in this docu-
ment, it is available upon request from the authors.
63 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Measuring Computer Literacy without Questionnaires
Computer literacy contains several dimensions within literature. Throughout our
literature review, we find the five most important dimensions of computer literacy to
be the following, based on their frequency of occurrence within literature:
• Skills: The skills associated with computers. This includes basic computer opera-
tion skills such as knowing how to use a keyboard and mouse, but can also contain
more advanced concepts such as programming skills.
• Knowledge: Knowledge of the characteristics, capabilities and context of the
computer. This includes general computer terminology and software concepts, but
also the social and ethical context in with computers reside.
• Attitude: The collection of Cognitive, Behavioural and Affective attitudes that a
person can have towards computers. This includes well covered concepts such as
computer anxiety, but also computer interest and beliefs about computers.
• Experience: The measure of time and frequency a person uses a computer. It is
assumed that time spent using the computer leads to associated knowledge and
skills.
• Information: Argued by some to be "distinct but interrelated" [6] with computer
literacy, information literacy (the skill in sourcing, processing and communicating
information) is frequently measured alongside computer literacy. Most, if not all
applications of computers involve the manipulation of information and so it is in-
cluded as a dimension of computer literacy.
There are no elements common to all definitions and/or measurements of computer
literacy that we reviewed. However, the Computer Skills and Computer Knowledge
dimensions are present in most of the consulted documents, and we regard these as
the central elements of computer literacy.
2 Measuring Computer Literacy
The PISA is personal assistant designed as a BCSS for Privacy and Security, aiming
to change behaviours and attitudes relating to personal information management and
personal security. In this context, measuring Computer Literacy serves a dual pur-
pose: it a) allows for communication with the user on a technically appropriate level,
and b) helps in the assessment of the risks a user is subject to such as phishing and
viruses. We have implemented a system that can collect measurements related to
computer literacy described in section 1.2. These measurements include elements
such as browsing behaviour, typing speed and installation activity. Our goal is now to
investigate if systematic relations exist between these measurements on the one hand,
and CL as measured by a questionnaire, on the other. To the extent that these relations
exist, we can replace the measurement of computer literacy by questionnaire with the
measurement of computer literacy by our software.
Of the five dimensions of computer literacy listed in section 1.2, elements of the
Computer Skills, Experience and Information dimensions are measured by our sys-
tem. It is unsurprising that Skills, Experience and Information lend themselves to
64 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Measuring Computer Literacy without Questionnaires
automated observation, as these dimensions come the closest to observable actions.
Computer Knowledge and Computer Attitude, on the on the other hand, are theoretical
constructs within the mind of the user rather than actions observable by the computer,
and we expect these to correlate less well with our automated measurements.
Figure 1 shows a fragment of the larger diagram which describes how computer
literacy is measured. This fragment contains all of the elements of computer literacy
that our system can collect. This diagram uses the same functional decomposition
approach to describe how the concepts are related. The colours indicate whether the
concept is a Theoretical Construct (shades of grey), or a Variable containing an oper-
ationalized measurement. The numbers next to the diagram indicate how often the
concept occurs within the 189 documents investigated over the course of the preced-
ing literature review [5].
The experiment detailed below aims to investigate how well such a subset of relat-
ed concepts measures computer literacy compared to the existing practice of using
questionnaires.
Computer
Literacy
74
Computer Internet
16 Surfing Skill
41
Experience
Computer Use Search
17 Engines
8
Frequency
Internet Surfing Internet
9 Activity Type
5
Frequency
Computer Availability
Skills
36 of IT facilities
6
Application Gaming Availability of
Specific Skills
26 Frequency
4 Computers
9
Basic Computer Keyboard Computer
Operation Skills
12 Skills
7 12
at Home
Digital Security Privacy
Skills
7 4 Computer
5
Skills at Work
Computer
Maintenance Skills
4
Fig. 1. An exerpt from the larger computer literacy measurements diagram, showing the meas-
urements of computer Literacy collected by our system.
2.1 Experimental Setup
To validate the system, a two week test is planned. Before this time, subjects will
install the experimental system on the computers that they use for their daily work
and private life, capturing information about the elements shown in Figure 1. Internet
browsing information is captured using browser plugins that cooperate with the exper-
imental system. The system itself measures typing speed, active and focused applica-
tions and installed software. All gathered data will be anonymized and sent to a cen-
65 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Measuring Computer Literacy without Questionnaires
tral server using a pre-generated pseudonym as identifier. Alongside this, a question-
naire will be handed to the subjects that will incorporate questions taken from exist-
ing, validated computer literacy questionnaires. This questionnaire will contain ques-
tions clustered along the same dimensions as were found in existing literature, with
additional questions for the dimensions that are measured through the experimental
system. This questionnaire will be validated in a separate experiment. The question-
naires are sent and stored using the same pseudonym, linking the experimental system
and the questionnaire for comparison purposes while preserving anonymity.
The data gathered by the experimental systems will then be compared to the data
gathered by the questionnaires distributed at the start of the experiment. We are cur-
rently planning to then perform a cluster analysis along the dimensions of computer
literacy. Since this comparison is a non-trivial task however, the details of this analy-
sis are currently still under consideration and beyond the scope of this article.
Should this approach prove effective, we speculate that a similar literature analysis
could then be performed to measure other theoretical concepts. This would allow for
the usage of cognitive models in persuasive profiles in a novel, real-time manner,
improving the detail of persuasion profiles and, by extension, the persuasive power of
a system.
Acknowledgments
The PISA project is sponsored by NWO and KPN under contract 628.001.001.
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