Learning Through Game Design - Is This Deep Learning?

Abstract

This study investigated how the creation of games for learning with specific learning goals could contribute to the development of students lower- and higher-order thinking skills. The results confirmed the hypothesis that the depth and complexity of the students’ learning and game design processes when developing games for learning influenced how deep learning processes the student-game designers experienced as they implemented academic knowledge and learning opportunities into their analogue games.

Full text

Learning Through Game Design
- Is This Deep Learning?
Charlotte Lærke Weitze
Digital & Creative Learning Lab
Ulstrupparken 11
3000 Helsingør
Denmark
Phone: +45 29921792
clw@digitalcreativelearninglab.dk
Keywords
GBL, Learning Through Game Design, Higher-Order Thinking Skills.
INTRODUCTION
Game-Based Learning (GBL) provides new and powerful ways of learning (Connolly
et al., 2012; Gee 2003; Squire, 2011). But the efficacy of the GBL environment
depends on how it is designed (Plass, Homer, Kinzer, 2015). To qualify GBL it is
important to focus on studying the cognitive-consequences and value added as well as
explore how theoretically driven design decisions may influence situated learning
outcomes for the students (Clark, Tanner-Smith & Killingswort, 2016).
Currently GBL is extended from students learning specific subject matters by playing
games to students learning through designing games (Earp, 2015; Whitton, 2014).
This leads to a new focus on how we may support students’ deep learning processes
as they learn by creating games for learning.
The hypothesis in this abstract is that the depth and complexity of the students’
learning and game design processes when developing games for learning will
influence how deep learning processes the student-game designers will experience as
they implement academic knowledge and learning opportunities into their games
(Weitze, 2016). Previous studies investigated how to qualify the process of learning
through design of games for learning. That is, the process where students implement
academic content into games to learn about specific subject matters, while the players
of these games also have an opportunity to reach specific learning goals. (Weitze,
2016, 2017).
This abstract initiates the investigation of how the creation of games for learning with
specific learning goals can contribute to the development of students lower- and
higher-order thinking skills. The various ascending levels of cognitive complexity
involves the students ability to remember, understand, apply, analyze, evaluate and be
creative within a specific area of a subject matter (Anderson & Krathwohl, 2001) as
well as their ability to reflect and think critically. The aim for the article following
this abstract is to create learning and design principles for students and teachers
learning through game design, with the purpose to enhance the students’ deep
learning processes (Biggs & Tang, 2011), critical thinking and reflection processes.
METHOD AND RESEARCH DESIGN
In this design-based research project (Plomp, 2013; Reimann, 2011) 120 highschool
students participated in an six hour, one-day workshop. They formed groups and
created 30 board games. By playing these games their fellow students could learn
about, reflect on and critically analyse aspects about energy sources and CO2
emission. The learning goals for the students learning games e.g. were: 1) Which
Proceedings of DiGRA 2019
© 2019 Weitze.C.L. & Digital Games Research Association DiGRA. Personal and educational
classroom use of this paper is allowed, commercial use requires specific permission from the author.

energy sources emit the most CO2? 2) What advantages and disadvantages does
different energy sources have in relation to: the climate, the environment, the
economy, and in terms of availability. In addition to the researcher two teachers were
deeply involved in the development and debriefing of the workshop.
This extended abstract is based on an empirical analysis of: a) observations of the
students in the workshop, b) the game-play of ten games, and c) the students selfmade
videos showing how these games should be played and explaining the principles
behind. Therefore results may be subject to change when the remaining data e.g. the
semistructured interviews with the teachers (conducted before, during and after the
workshop) are analyzed in depth.
RESULTS
The creative process of developing a game for learning was more comprehensive than
playing commercial game for learning, as the students worked from a highly
problem-based and constructionist learning approach. When analyzing the data there
were many examples of students developing lower-order thinking skills
(remembering, understanding, applying); e.g. in the process of creating subject matter
relevant narratives for their board games and when elaborating questions and answers
for quiz games. Here students collected, understood, discussed and collaboratively
developed and chose these narratives, questions and answers.
An even more interesting part of the students’ learning processes involved the
students development of higher-order thinking skills (analyzing, evaluating and being
creative) as they created rules, game and learning mechanics for their games.
In games the learning mechanics and game mechanics may overlap. The game
mechanics are the things that the player interact with and can do in the game. While
learning mechanics more specifically can be defined as: “the mechanics and
interactions intended to support players in learning the target learning
outcomes” (Clark, Tanner-Smith & Killingswort, 2016, p. 101).
The following is one example of how students had developed learning mechanics and
rules inside their game, and in this process showed signs of applying, analyzing,
evaluating and being creative developing higher-order thinking skills regarding their
subject matter.
In this game example (Energy-Island) students were inspired by a settlers game
board. When throwing a dice the players would land on a random spot in the game
and depending on which of the six different (polluting or green) energy sources they
ended up being closest to, they would gain a) x amount of energy, and b) x amount of
CO2. The idea was to get as much energy as possible, and as little CO2 as possible.
Students thus created rules that would teach the player what energy sources would
emit the least CO2 and create the most energy, the ideal (= the winner) was a green
society. There was one catch - if you were placed next to nuclear power there was a
chance you were killed, though this energy source was high in energy and low in
pollution.
In order to create these rules, game and learning mechanics, the students had to
investigate the various energy sources. They also analyzed how much energy these
sources created compared to each other, and connected this to how much CO2 the
sources emitted compared to each other. Then the students evaluated those
informations and created a gameplay, so players of the game could learn how energy
production and CO2 emission were connected within an energy source as well as
between energy sources.
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When analyzing and comparing the more superficial and quiz based games with the
more advanced games, as in the example above, the result was that the students
designing the more advanced games had more comprehensive learning outcomes as
well as a deeper understanding of the subject matter, coving a larger part of the
learning goals.
In the talk other examples will be elaborated, as will the teachers role in qualifying
the complexity of what the students taught in their games and thereby learned though
building these games.
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