the relations among user issues,
technological possibilities, and
overall dynamics of the interaction.
• Even without providing detailed
understanding, such experiences
can pinpoint the limitations of a
technology, such as the need for a
clear visual field between the sensor and a user’s hands, the influence of lighting on the performance
of the sensor, the delay caused by
the processing of data, and some
indirect consequences, such as the
user fatigue when the interaction is
prolonged. In early phases, this can
lead the student to create solutions
that overcome these limitations,
such as clever positioning of the
sensors, adding lighting elements,
and making the interaction sessions
short enough to avoid user fatigue.
In our educational framework,
this direct experience of exploring
computing technologies is a starting point of the learning process,
enabling students to come up with
an understanding of computation
by reflecting on their experiences.
• Figure 1. In this
example a transparency of a
window changes
in response to the
estimated intensity
of hand motion. A
motion detector is
used to control the
transparency of the
image representing
the window.
Background
Experiential learning is a guided
process of questioning, investigat-
ing, reflecting, and conceptualizing
based on direct experiences. In
this learning process, the learner
is actively engaged, has freedom to
choose, and directly experiences
the consequences of their actions.
There are several models of the
experiential learning process,
including Kolb’s cyclical learn-
ing process [ 2], Schön’s reflective
practice model [ 1], Joplin’s action-
reflection cycle [ 3], Kesselheim’s
learning process [ 4], and Dewey’s
three-stage process of learning
[ 5]. Though there are differences
among these models, the nature of
experiential learning is fairly well
understood and agreed upon, and
all experiential learning models
share the following elements [ 6]:
• actions that create an experi-
ence,
• reflections on the action and
experience,
• abstractions drawn from the
reflections, and
• application of abstractions to a
new experience.
The Framework
We have begun to develop a
framework for teaching advanced
computing concepts based on the
experiential learning paradigm.
With our framework we wanted to
enable industrial design students
to experience the design of systems
that employ advanced computing
technologies, such as speech- and
camera-based sensors, or Web ser-
vices, and to learn from that experi-
ence. More specifically, we had the
following goals:
• To empower students to explore
computing technologies without
intensive programming. Most of
our students are not programmers,
and creating systems that employ
advanced computing technology
using conventional programming
languages is beyond their reach.
• To increase students’ awareness
of the possibilities, limitations,
and complexity of computing systems. Many of our students are
not aware of the availability and
opportunities of emerging computing technologies, and they often
have unrealistic expectations about
technologies and their complexity.
Having in mind these goals and
the discussion about the previous
work, we adopted several guiding
principles for development of our
framework:
May + June 2012
