Physics Education
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Never far from shore: productive patterns in
physics students’ use of the digital learning
environment Algodoo
To cite this article: Elias Euler et al 2020 Phys. Educ. 55 045015
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PA P E R
Phys. Educ. 55 (2020) 045015 (8pp) iopscience.org/ped
Never far from shore:
productive patterns in
physics students’ use of
the digital learning
environment Algodoo
Elias Euler1, Christopher Prytz2 and Bor Gregorcic1
1
Department of Physics and Astronomy, Uppsala University, Box 516, 75120
Uppsala, Sweden
2
Rydbekianska gymnasiet, Skolgatan 5, 72215 V¨asterås, Sweden
E-mail: elias.euler@physics.uu.se
Abstract
In this paper, we present three types of activity that we have observed during
students’ free exploration of a software called Algodoo, which allows
students to explore a range of physics phenomena within the same digital
learning environment. We discuss how, by responding to any of the three
activity types we identify in the students’ use of Algodoo, physics teachers
can springboard into a range of relevant physics discussions while supporting
and valuing student agency and divergent thinking. Thus, while one might
not expect students’ undirected use of a digital tool such as Algodoo to be
particularly worthwhile for the physics classroom, we highlight how students
are never ‘far from the shore’ of a productive physics discussion.
Keywords: Algodoo, grounded theory, digital learning environment, exploration,
testing, engineering, creativity
1. Introduction
With regards to digital learning environments
in physics education, on one hand there are
software that focus on specific phenomena, e.g.
Original content from this work may be used
under the terms of the Creative Commons
Attribution 4.0 licence. Any further distribution of this work
must maintain attribution to the author(s) and the title of the
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PhET simulations [1], Physlets [2], QuVis animations
[3], and, on the other hand, software that
function more as creative arenas within which
many phenomena can be explored, e.g. Algodoo
[4], Interactive Physics [5], and Fizika [6].
We refer to the former category of phenomenaspecific
digital learning environments as ‘constrained’
and the latter as ‘less-constrained’ [7],
owing to the degree to which those environments
are designed to ‘productively constrain’ [8]
students’ behavior (see also [9–11]). While both
1361-6552/20/045015+8$33.00 1 © 2020 The Author(s). Published by IOP Publishing Ltd
E Euler et al
constrained and less-constrained digital learning
environments have unique affordances for supporting
physics students’ learning, constrained
software has received significantly more attention
from developers and physics education researchers
in recent decades. In this paper, we present
our findings for some of the ways in which one
less-constrained digital learning environment—
specifically, Algodoo—can be productive for the
physics classroom, specifically when students are
allowed to freely explore within the software for
themselves.
Given the relative open-endedness of lessconstrained
software such as Algodoo, a physics
teacher who includes this type of digital learning
environment in their repertoire of curricular
materials can choose to implement the software
in a range of ways. At one extreme, a teacher can
use Algodoo as a means for students to engage
with specific physics content in directed tasks. In
this approach, students can use Algodoo to explore
a range of physics topics, from projectile motion
[12] to Kepler’s laws [13], kinetic gas theory [14],
and the refraction of light [15], all within the same
digital learning environment. This topic-specific
use of a less-constrained software more closely
resembles the productively controlled approach
behind many constrained physics learning software
mentioned above3
.
At the opposite extreme, a physics teacher can
choose to take a more student-directed approach:
that is, a teacher can refrain from selecting specific
topics, allowing students to explore the software
for themselves and responding to the students’
exploration at opportune points. Such a
student-directed approach may intuitively seem
too unfocused to be worthwhile for the teaching
and learning of physics. However, we have found
that students’ self-directed exploration within the
less-constrained software, Algodoo, has several
unique, if unanticipated, affordances for physics
education [7].
3 While there is a resemblance between a topically-focused use
of less-constrained software and the typical use of constrained
software, it should be pointed out that in the case of the former,
many of the constraints are imposed by the teacher rather than
through the imposed limitations of the software itself.
In this paper, we describe three types of activities
identified while observing students’ selfdirected
use of Algodoo and explain how each
activity type has the potential to be productively
leveraged by a physics teacher. Among other
things, we show that, by allowing students to
creatively explore within tool-rich physics environments
such as Algodoo, physics teachers can
springboard into a range of relevant discussions
while supporting and valuing the agency and
divergent thinking of students.
2. Three types of student activity in
Algodoo
The three activity types we present in this paper
were identified based on the analysis of video
recordings of seven pairs of university physics students
as they used Algodoo for the first time4
.
Through the use of a grounded theory method
[16], the video recordings were iteratively viewed,
transcripts were generated, student behavior was
coded in successively larger chunks, and, ultimately,
three categories of activity were identified.
Below, we present each of these activity
types, along with their potential relevance for the
teaching and learning of physics.
2.1. Activity type 1: exploration of the
software fundamentals
During the first activity type, which we call
exploration of the software fundamentals, students
investigate the tools and functions of Algodoo.
This activity type is characterized by students
familiarizing themselves with Algodoo’s
buttons, toolbars, and drop-down menus (see
figure 1) in order to develop a sense for the
basics of how the software is operated. Students’
exploration of the software fundamentals tends
to be (outwardly) chaotic, exemplified by the
students shifting their focus between the many
features housed in Algodoo. Especially when
students are new users of Algodoo, this activity
type is the behavior which physics teachers
4 The activity types presented in this paper were originally
identified in Prytz’s master’s thesis [28]. For those interested,
a full discussion of the data and methodology can be found
there.
July 2020 2 Phys. Educ. 55 (2020) 045015
Never far from shore:
Figure 1. Two examples of the Edit drop-down menus that students tend to familiarize themselves with in Algodoo
during the first activity type, exploration of the software fundamentals. On the left, the Edit menu is shown open
to the Material submenu, where students can vary the density, mass, coefficient of friction, etc for the object(s)
selected. On the right, the Edit menu is shown open to the Springs submenu, where students can vary the spring
constant, viscous damping parameter, and target length of the selected spring(s).
should expect to see chronologically first. Additionally,
due to the high number of features made
available in Algodoo, students frequently return
to this activity type throughout their exploration
as they discover new functionalities of the
software.
Students’ exploration of the software fundamentals
can be productive for the physics teacher
insofar as students naturally uncover new physics
parameters. While students ‘poke around’ in
the Algodoo software, they interact with the buttons
and sliders corresponding to various parameters
that are relevant to the discipline of physics
(e.g. restitution, damping, speed/velocity, gravity,
kinetic energy, and so on). Depending on
the students’ familiarity with the formalisms of
physics, the parameters encountered in Algodoo
will be more or less recognizable to the
students. A physics teacher can notice which
parameters seem to be less-recognized by students
and encourage those students to further
investigate those parameters unfamiliar to them.
For example, elsewhere we have analyzed how
two students came across the slider labelled
‘Damping’ within the editing menu for springs
(figure 1, right) and were guided by researchers to
make sense of the behavior of damped/undamped
springs [7].
2.2. Activity type 2: testing and contrasting
In the second activity type, which we call testing
and contrasting, students explore how well
the physics engine of Algodoo matches the real
world. Students tend to construct classic physics
scenarios within the software to ensure that
the software behaves as it should (e.g. dropping
two objects from the same height to ‘demonstrate’
the acceleration due to gravity) or they
create simple tests to determine if the software
allows for certain complexities of physics interactions
(e.g. dropping a square onto a thin rectangle
given the material preset of ‘glass’ to see if glass
objects shatter in Algodoo5
, figure 2). In general,
we have found that students engage in testing and
5 Algodoo allows the user to assign material presets such as
glass, wood, steel, etc, to objects, which correspond to certain
configurations of the objects’ density, friction properties, restitution,
and refractive index.
July 2020 3 Phys. Educ. 55 (2020) 045015
E Euler et al
Figure 2. A screenshot of an observed testing and contrasting activity in Algodoo—recreated by the authors for
clarity in this publication—where two students tried to shatter a thin rectangle made with the ‘glass’ material preset
(shown in light blue laying horizontally on top of two support rectangles) with another, massive object (the gold
square at the top of the screen). After running the simulation, the students concluded that Algodoo does not allow
the breaking of objects.
contrasting to check ‘how far’ they can go within
the software.
For the physics teacher, testing and contrasting
activities can be productive in that they can
be leveraged to highlight the role of modeling in
physics [17, 18]. For example, in the case shown
in figure 2 involving the ‘glass’ rectangle, a physics
teacher could interject to ask students about
whether the Algodoo software is still a valid environment
for exploring physics phenomena. Previous
research findings have highlighted that software
such as Algodoo have the potential to be a
resource for entry-level physics modeling [4, 19],
where the intuitive interface allows students to
examine dynamic models of physical phenomena
without a prerequisite proficiency in programming.
Beyond supporting discussions of physics
modeling, students’ testing and contrasting activities
can serve as the backdrop for introductory
discussions around the use of computer simulations
in modern science [20].
2.3. Activity type 3: engineering
In the third activity type, which we refer to
as engineering, students tend to prototype
machines/setups in the pursuit of self-determined
goals within Algodoo. For example, some students
constructed a simple car and, after getting their
car rolling, created obstacles such as a small hill
for the car to traverse (figure 3). In doing so, these
students were motivated to explore the role of
friction, torque, etc, in the context of a car climbing
a hill. In many cases, the students’ impetus to
construct machines comes during their noticing a
specific feature of Algodoo in their exploration of
the software fundamentals (activity type 1). After
finding Algodoo’s ‘thruster’ tool, for instance,
students might quickly transition into building a
rocket. We have found a salient feature of engineering
activities is students’ modification of their
machines in pursuit of their self-determined goal.
In this way, students’ engineering activities seem
July 2020 4 Phys. Educ. 55 (2020) 045015
Never far from shore:
Figure 3. A screenshot of the kind of machine typically created by students in Algodoo—again, recreated by the
authors for this publication—as they engage in the third activity type, engineering. A simple car consisting of a
rectangular ‘body’ and two circular ‘wheels’ (fitted with motor-driven axels) drives up an angular obstacle also
created by the students. In achieving the goal of driving their simple car up and over this obstacle, students engage
with the coefficient of friction of the wheels/ramp and the torques applied to the motor-driven axels, among other
things.
to involve iterative loops wherein they design,
test, and challenge various prototypes.
Students’ engineering activities are potentially
useful for the physics classroom in that
they often entail students working in ways that
resemble pedagogically-sought-after scientific
practices [21]. More precisely, during the prototyping
typical in engineering activities, students
often design tests for achieving self-determined
goals, evaluate the outcome of their tests, and iteratively
revise their constructions to accommodate
those outcomes. This sequence of reasoning may
constitute what Gregorcic et al [22] describe as
the ‘seed[s] of scientific practices’—or perhaps
in our case, the seeds of engineering practices. A
teacher can take advantage of students’ engineering
tasks by prompting students to reflect on their
prototyping process, which may subsequently be
turned into a discussion of the characteristics of
scientific and engineering practices more broadly
[23, 24]. Alternatively, since Algodoo allows for
the ‘zooming in on’ and the ‘unpacking of’ the
various parts within a construction, teachers can
utilize students’ machines/setups as the focus for
further inquiry. For example, when a pair of students
engineered a way to lodge an arrow into
a ‘sponge’ in Algodoo, researchers were able to
utilize the students’ success in meeting their goal
as the basis for a discussion on how non-rigid
bodies are modeled in the software [7].
3. Summary of implications for teaching
When allowed to explore software such as Algodoo
in a self-directed manner, students are likely
to engage in some combination of the three activity
types detailed above, each of which can be
potentially productive for the teaching and learning
of physics in their own way (table 1). A teacher
who allows students to engage in this kind of
activity can choose to build upon students’ exploration
[25] during any of the three activity types
July 2020 5 Phys. Educ. 55 (2020) 045015
E Euler et al
Table 1. A summary of the three activity types we identified in students’ use of Algodoo without a specific prompt.
Activity type Explanation
Productiveness for the physics
classroom
Exploration of the software
fundamentals
Students develop a sense for the tools
and functions of the software environ-
ment
Students can naturally uncover relevant
physics parameters
Testing and contrasting Students explore how the software’s
physics engine compares with the real
world
Can serve as a backdrop for discussions
about physics modeling and the use of
computers in science
Engineering Students create machines/setups and
pursue self-determined goals
Students’ engagement in science- and
engineering-like practices may be
unpacked for further discussion; students’
creations can be taken up as the
focus for further inquiry
in order to guide the students’ attention to the
type of discussion that the teacher wants. Building
from the first activity type, students’ exploration
of the software fundamentals, a teacher can
encourage students to explore the meaning of various
parameters as they are uncovered in the software
interface. With students’ testing and contrasting,
the second activity type, a teacher can
springboard into entry-level discussions on the
role of modeling in physics and the function of
computer modeling in scientific inquiry. Finally,
from the third activity type, students’ engineering,
teachers can take on students’ creations for discussions
around scientific practices and/or as inspiration
for more topic-specific discussions of particular
phenomena. Among other things, allowing
students to explore less-constrained physics software
such as Algodoo in a self-directed manner
can signal to those students that their creativity,
divergent thinking, and, ultimately, agency [26] is
valuable to the process of learning—and doing—
physics.
3.1. Additional considerations for teachers
encouraging students to explore Algodoo
While we have so far used this paper to highlight
ways in which students’ use Algodoo can be productive
for the physics classroom, it is worth mentioning
some potential challenges physics teachers
might face when encouraging an entire class
of students to ‘freely explore’ less-constrained
digital learning environments. First, in larger
classes it may be difficult to manage multiple
groups of students that may be headed in divergent,
often unrelated, directions. In our experience,
we have found that a single teacher, who
is familiar with the software, can manage classes
on the scale of 20–30 students (in groups of 2–
3). Alternatively, teachers can encourage students
to explore Algodoo as homework or within a labstyle
setting where student-teacher ratios tend to
be smaller.
A second challenge that physics teachers
might face when implementing Algodoo in their
classroom is that allowing students to ‘mess
about’ in such digital learning environments
simply takes more time to reach certain learning
goals when compared to more pointed discussions/lectures
of desired topics. Our recommendation
regarding this concern is that teachers
consider incorporating student-directed use
of Algodoo into their toolbox of active learning
approaches and, ultimately, decide for themselves
what balance to strike in the pacing of content
goals.
Finally, since every student group will, by
design of such a teaching approach, end up engaging
in different activities and pursing their own
goals, a third challenge teachers might face when
incorporating Algodoo in their classrooms is that
there is a loss of a single shared experience for
students. In response to this last challenge, we
recommend that teachers intermittently pull the
full class together for a discussion around a particular
group’s work. This may help all of the students
reflect on the nature of their own work and
may encourage them to generalize some of their
July 2020 6 Phys. Educ. 55 (2020) 045015
Never far from shore:
productive ideas across the various contexts that
appear in other students’ work [27].
4. Conclusion
Regardless of whether students are ‘poking
around’ in Algodoo’s menus, checking the boundaries
of the software’s physics engine, or creating
machines to meet their own goals, physics teachers
can be assured that students’ self-directed
exploration of less-constrained digital learning
environments is a near neighbor of a worthwhile
physics discussion. Thus, as long as the interested
physics teacher is willing to build upon the
divergent activity of students engaging with lessconstrained
digital learning environments such as
Algodoo, their students will likely never be ‘far
from the shore’ of productive physics discussions.
Acknowledgment
This project was funded in part through the
Swedish VR Grant No. 2016-04113.
ORCID iD
Elias Euler  https://orcid.org/0000-0003-0526-
3005
Received 26 February 2020
Accepted for publication 26 March 2020
https://doi.org/10.1088/1361-6552/ab83e7
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Elias Euler earned a bachelor’s
degree in physics from the University
of Colorado Boulder in 2015. He
is currently a PhD candidate in the
Division for Physics Education
Research at Uppsala University in
Sweden, where he researches the use
of digital tools in the teaching and
learning of physics.
Christopher Prytz graduated from
Uppsala University in the summer
of 2019 with a Degree of Master
of Science in Upper Secondary
Education. Currently, he is practicing
his interest in physics education
research as a working teacher
in physics and mathematics at a
Swedish gymnasium, Rudbeckianska
gymnasiet, in V¨asterås.
Bor Gregorcic gained his PhD in
physics education from the University
of Ljubljana in Slovenia. He is
currently working as a post-doctoral
researcher at the Department of
Physics and Astronomy, Division
for Physics Education Research at
Uppsala University in Sweden. His
interests revolve around computersupported
collaborative learning in
physics.
July 2020 8 Phys. Educ. 55 (2020) 045015