Toward a Meta-design Method for Learning Games

Marne Bertrand

1 a

, Muratet Mathieu

2,3 b

and Sehaba Karim

4 c

ICAR UMR 5191, Universit

e Lumi

ere Lyon 2, France

Sorbonne Universit

e, CNRS, LIP6, F-75005 Paris, France

INS HEA, 92150 Suresnes, France

Universit

e de Lyon, CNRS. Universit

e Lyon 2, LIRIS, UMR5205, F-69676, France

Keywords:

Serious Games, Meta-design, Computational Thinking, Authoring Tools.

Abstract:

To support the appropriation of serious learning games by teachers, we are studying design methods that

focus on both design and use phases: meta-design methods. Our objective is to propose models and tools

for designing levels and scenarios for Blockly Maze and to provide the teacher with monitoring indicators

allowing him/her to appropriate and adapt the game according to the observed uses. In this article, we detail

the ﬁrst contributions of this study based on qualitative data: analysis of the game Blockly Maze and interviews

with two teachers. First results draw three main needs: level design tool, scenario design tool and monitoring

tool. Beyond these needs we introduce underlying models of each of them and future works.

1 INTRODUCTION

Learning games offer signiﬁcant beneﬁts over tradi-

tional teaching tools (Freitas, 2006; Prensky, 2004).

Indeed, many authors consider learning games as

promising, especially to increase learner engagement

(Bouvier et al., 2014) and motivation (Garris et al.,

2002; Malone and Lepper, 2005), others are more

interested in modeling and evaluating player experi-

ence (Kiili, 2005; Sweetser and Wyeth, 2005) or in

using learning games to promote a more construc-

tivist learning (Bogost, 2007; Marne, 2019; Ryan

et al., 2012). However, their adoption, especially by

teachers, remains scarce (Li, 2018; Sardone, 2018).

To foster the adoption of learning games by teachers,

we work on the hypothesis that a participatory design

method such as meta-design might be suitable.

Meta-design is an advanced participatory design

method, in which the design process is centred on

the end users (“owners of problems”). However, end

users must continue to have the means to design dur-

ing the artefact use phase (Fischer and Herrmann,

2011). This is made possible, among other things,

by the underdesign that Fischer et al. (Fischer et al.,

2004) deﬁne as:

https://orcid.org/0000-0002-4953-9360

https://orcid.org/0000-0001-6101-5132

https://orcid.org/0000-0002-6541-1877

“[. . . ] underdesign aims to provide social and

technical instruments for the owners of prob-

lems to create the solutions [of their problems]

themselves at use time.”

Our work questions this approach in the context

of the use of serious games by teachers as owners of

problems.

The work presented in this paper reports the be-

ginning of a project on this topic. We focused our

study on the teaching of computational thinking, and

the implementation of a meta-design approach for

learning games. This project aims to exploit an ex-

isting learning game and to study to what extent it

is possible for teachers to “appropriate” it (underde-

sign). We investigated how allowing them to mod-

ify its content according to their pedagogical needs

and observed or intended uses. We chose Blockly

Maze

(BM), among other things, because it is well-

tested and free software. Indeed, inspired by Scratch

(Resnick et al., 2009), BM has been reused in many

derivative works. For instance, the Hour of Code

Algorea

, and more than 400 derivatives on the forge

Github

. The fact that the source code is available,

Blockly Maze is a learning game developed by Google:

https://blockly.games/maze consulted on 2021/02/03

https://code.org/ consulted on 2021/02/03

https://algorea.org/ consulted on 2021/02/03

https://github.com/google/blockly-

370

Bertrand, M., Mathieu, M. and Karim, S.

Toward a Meta-design Method for Learning Games.

DOI: 10.5220/0010530203700376

In Proceedings of the 13th International Conference on Computer Supported Education (CSEDU 2021) - Volume 2, pages 370-376

ISBN: 978-989-758-502-9

freely reusable, and widely tested has particularly in-

terested us to design and evaluate methods and tools

allowing meta-design and underdesign for this learn-

ing game.

The limits of the original Google version of

Blockly Maze are the same limits as those found in

many other learning games: (1) limited number of

levels, Blockly Maze offers 10 levels covering a few

programming skills; (2) non-modiﬁable scenario,

the course of these 10 levels is a linear sequence that

the teacher cannot modify; (3) the players’ activity

is not recorded, hence the teacher cannot retrieve any

trace of the learners’ performance. For these reasons,

it is difﬁcult for the teacher to understand the practices

and difﬁculties of the learners and thus to appropriate

and adapt the learning game to the pedagogical con-

text.

Our goal is to provide tools and methods enabling

teachers, more or less comfortable with teaching com-

puter science, to use Blockly Maze, to build their

own sequences of levels corresponding to their needs,

to build levels that complement those available, and

to follow the learners’ activity to better understand

their use and thus adapt learning. Therefore, our ulti-

mate goal is to build a meta-design context based on

a generic model for the design and development of

levels.

Our ﬁrst step is the deconstruction of Blockly

Maze, both on a conceptual perspective and on a soft-

ware one. Thus, we intend to develop explicit models

of the levels and their educational content. This paper

describes this ﬁrst part of our work.

In the ﬁrst part of the paper, we present Blockly

Maze and the scientiﬁc issues we are studying, as they

emerge from the different obstacles arising from the

literature and the practice of teaching computational

thinking. In the second part, we present our method-

ological context and our choices. Finally, before con-

cluding, we present our ﬁrst results in the third part.

2 INTRODUCING BLOCKLY

MAZE AND OUR SCIENTIFIC

PROBLEMS

In order to work on meta-design, we chose an open

source learning game (source code available, freely

reusable, and modiﬁable). We chose Blockly Maze

because of the popularity of the Blockly engine,

but also because of the wide adoption of Blockly

Maze (BM) by many organizations such as the Hour

of Code or Algorea. The concept of this learning

games/network/members consulted on 2021/02/03

Figure 1: Screenshot of Blockly Maze showing block pro-

gramming to guide the avatar toward the exit.

game developed by Google is to teach programming

through the guidance of an automatic avatar in a maze

(see ﬁgure 1). The guidance is done by program-

ming with blocks of instructions, inspired by Scratch

(Resnick et al., 2009).

However, the original BM from Google only

offers 10 levels. They train to the use in-

structions sequences, conditions (if/else), loops

(repeat/until), including nested ones, and basic al-

gorithmic (left-hand method). This is rather limited

considering the various needs of teaching computa-

tional thinking (Brunet et al., 2020; Vandevelde and

Fluckiger, 2020). Thus, many derived works (forks)

and learning games similar to BM have emerged, of-

fering numerous other levels. We mentioned the Hour

of Code, which offers a large selection of additional

levels dealing with multiple aspects of computational

thinking distributed in several “courses”. The “Hour

of Code” has a wide choice of scenarios (combining

other types of learning games than BM), which means

that, for a teacher, an informed choice of the resource

or course to use requires a global vision of the avail-

able options, and therefore also requires a signiﬁcant

amount of time to grip the whole platform. We also

mentioned Algor

ea (L

eonard, 2020), it offers learning

games that are close to BM (although, apparently on

a different code base). Like the Hour of Code, these

learning games are provided with a variety of other

educational resources, structured to prepare a French

programming competition: Algor

ea. The learning

games provided are puzzles that can be solved with

blocks like in Blockly (in addition to the Python code

and Scratch blocks). Nevertheless, only a few of them

use a maze as puzzle. Those maze games only focus

on a few aspects of computational thinking: instruc-

tion sequences, function calls, simple or nested loops,

conditional instructions. The learning games based

on block programming which address more complex

notions are not based on maze puzzles.

In any case, it seems difﬁcult for a teacher, who

is familiar with these three resources, to build a cur-

riculum for his or her learners by picking out what is

Toward a Meta-design Method for Learning Games

371

Figure 2: Screenshot of a sample Blockly Maze scenario provided by APPLiq.

needed for them. Moreover, the resources are not de-

signed for this kind of ﬂexibility, but rather to be used

in the form of indivisible sequences of several levels.

Given these limitations, our problem is therefore

to provide teachers with the proper tools and methods

to be able to appropriate BM. On the one hand, by

giving them the opportunity to understand how BM

works and how it is structured (instrumentation), and,

on the other hand, by enabling them to adapt, mod-

ify, remix BM and its levels (instrumentalisation and

meta-design) (Rabardel, 2003).

To foster appropriation of BM by teachers through

mastery and adaptation, we relied mainly on the meta-

study of Dermeval et al. (Dermeval et al., 2018) to

explore available authoring tools. Our goal was to

ﬁnd out which ones could be used to adapt the lev-

els or the succession of levels of BM. However, BM

is not intended to work with such tools. In our inves-

tigations, beyond this meta-study, we only found the

authoring tool APPLiq which can be used to adapt a

BM scenario, as it has already been tested with it by

its author (Marne and Labat, 2014; Marne, 2014).

APPLiq enables teachers/users to prepare and

provide learners/players with a succession of levels

(called activities) in a learning game, taking into ac-

count the pre-requisite and worked on pedagogical

objectives at each of these stages. This succession

of levels is not necessarily linear (see ﬁgure 2), and

may therefore depend on the actions and performance

of the learner/player (objectives worked on or not

worked on during the activities).

Nevertheless, APPLiq has several limitations. In

the context of our study, the most important limitation

is that this authoring tool only allows the adaptation

of the levels order. Therefore, while it enables teach-

ers/users to change the sequence and order of the lev-

els, they cannot change the BM levels themselves. In

APPLiq, one can add new levels in the description of

the model of a speciﬁc learning game. However, it

is the concern of the user who makes this modiﬁca-

tion to make the necessary adaptations to the learning

game itself. Indeed, in MoPPLiq (Marne and Labat,

2014), APPLiq’s underlying scenario model, the ac-

tivities (levels) are modelled as black boxes.

In addition, the author of APPLiq provides a mod-

iﬁed version of BM working with his authoring tool.

But the latter is derived from a version of BM released

by Google in 2012. Since then, BM has changed a lot,

and these very profound adaptations would have to be

made again.

In our particular situation, choosing APPLiq as a

tool enabling teachers to adapt BM implies, on the

one hand, providing a major update of BM and, on

the other hand, providing another authoring tool that

allows adaptation of levels.

For this work of learning games modelling and

development of authoring tools for teachers, our

approach is a design-based collaborative research

(Sanchez et al., 2017). We describe the three main

axes of this research in the next section.

3 APPROACH AND

METHODOLOGY

Our goal is to provide tools and methods inspired

by meta-design that allow teachers to master Blocky

Maze in order to design, use and adapt levels and sce-

narios that meet their pedagogical needs in the ﬁeld

of computer science teaching.

To achieve this goal, our approach is to involve

teachers in order to discuss and conceptualize com-

putational thinking for pedagogical purposes in the

form of a concept map (see ﬁgure 3). To co-design

this map

, we chose to conduct qualitative interviews

with two teachers instead of quantitative survey based

on questionnaire. The ﬁrst teacher is an experienced

mathematics teacher who teaches hospitalized sec-

ondary school children, and the other is the director

of children’s education at the same hospital.

The co-design of this map was, above all, the

main discursive tool we used to address many of the

main pedagogical issues of the teachers we worked

with. The map is therefore not intended to model

See the complete concept map (in French): https:

//mycore.core-cloud.net/index.php/s/NsntsseDxGUILM4/

download.

CSEDU 2021 - 13th International Conference on Computer Supported Education

372

Figure 3: Overview of our approach.

computational thinking in an exhaustive or consen-

sual way. Rather, it allows us to understand the ap-

proaches taken by the teachers in constructing lev-

els/scenarios and to identify possible difﬁculties they

might be experiencing. Thus, we were less interested

in the actual map itself than in discussing its content.

The summary of the interviews carried out with

each teacher regarding the conceptual map allowed us

to pinpoint:

• The concepts taught and the teaching methodol-

ogy adopted by them.

• The relevance of storytelling and games to foster

learning.

• The need to adapt the BM levels to, among other

things, adjust statements’ wording, blocks used,

dialogues, and add features (variables, timers,

etc.).

• The need for pedagogical monitoring indicators

enabling teachers to measure the progress of their

learners and identify their appropriation of the

concepts studied.

• The need for meta-design indicators that make

it easier for teachers to adapt and update lev-

els/scenarios according to the uses observed.

The ﬁrst study resulted in specifying three main

directions that bring together the main features of a

set of authoring tools dedicated to meta-design: (1)

Level design tool: this tool will allow the teacher to

implement new levels or to reuse existing levels fol-

lowing a simple and intuitive model and methodol-

ogy. Therefore, for each level, the aims are to be able

to (re)deﬁne the mazes themselves, the list of blocks

made available to the learner, the dialogues and the

conditions for triggering them, as well as other con-

straints: number of blocks available, time limits for

resolution, blocks already set, etc.; (2) Scenario de-

sign tool: this tool should enable the teacher to de-

ﬁne the sequence of the levels and the conditions for

triggering them. It should allow the teacher to de-

ﬁne a succession of speciﬁc levels for each learner

according to his or her performance; (3) Monitor-

ing tools: this tool should allow the teacher to col-

lect data related to interactions between the learner

and the levels/scenarios and to calculate indicators on

learning and the quality of teaching resources. These

are high-level indicators such as success rates, levels

completed or not, completion times, or more speciﬁ-

cally the number of blocks used, the number of help

messages displayed, etc.

In the next section, we present our work and its

results in each of these three directions.

4 FIRST WORK AND RESULTS

Following this meta-design approach, we have con-

ceptually deconstructed BM in order to develop three

models presented in the subsections.

4.1 Level Model

Interviews with teachers about the design of the con-

cept map showed us that the BM levels, as they cur-

rently exist, were not sufﬁcient enough to meet the

needs (theirs, those of their colleagues) for teaching

computational thinking. We worked with them to dis-

cuss possible improvements and to establish a model

of BM levels, both on a conceptual standpoint and

within the source code itself.

Modelling BM levels was done in two steps: (1)

isolation of all the components of the BM source

code related to the description of levels, within a very

monolithic program (a single ﬁle) where these com-

ponents are spread over many functions and objects;

(2) Conceptualization of the level source code in the

form of a UML model (see ﬁgure 4).

The main features of this BM level model are, on

the one hand, the maze, the starting conditions (ori-

Toward a Meta-design Method for Learning Games

373

Figure 4: UML model for Blockly Maze levels.

entation, number of blocks available, etc.) which are

modelled as simple variables. On the other hand, the

message system (helpMessages) for players based on

their actions. This system is much more complex and

needs to be modelled with both a conditions system

and an event (trigger) system.

To contribute to verify this model, we have suc-

cessfully described again all the ten BM levels by in-

stantiating them in JSON ﬁles. Furthermore, we have

signiﬁcantly reworked BM’s source code so it is now

able to read these JSON ﬁles. In addition, we are

preparing a pull request to be submitted to BM devel-

opers (Google), so that all potential users can easily

make new levels written with JSON.

Our ﬁrst experiments with the teachers show that

we can work with them to write new levels with the

JSON model. The weakness of this approach is the

design of the help messages, which is still very com-

plex. Therefore, the next step in our work is to build

an authoring tool that generates these JSON ﬁles, and

helps to set up help messages for players.

The tiniest possible scale of the changes that

teachers might consider is the levels. We also intend

to allow the teachers to modify learning games on a

bigger scale: the sequence of levels (scenario).

4.2 Scenario Model

Our interviews conﬁrm the teachers’ need to be able

to organize a progression through the different levels

according to their speciﬁc teaching context.

For this purpose, APPLiq seems relevant (Marne

and Labat, 2014). It is based on an XML model of

the scenario (MoPPLiq) in which the levels (activi-

ties) are considered as black boxes, meant to let the

players work on some speciﬁc sets of pedagogical and

Figure 5: MoPPLiq Entity-Relationship Diagram (Marne

and Labat, 2014).

playful objectives. Each activity can have several out-

put states depending on the set of objectives effec-

tively worked on. Each activity can also have several

input states restricting the possibilities of connecting

the activity to the rest of the scenario according to a

set of prerequisite objectives. The scenario is there-

fore described as a sequence of all the desired output

state/input state links (see ﬁgures 2 and 5).

When refactoring BM’s source code to be able to

load levels described with JSON, we also used the

API provided by APPliq’s author (Marne, 2014) to

embed the ability to load MoPPLiq models.

However, we are facing several issues: (1) The

new levels designed with the JSON model must also

be described (modelled) within APPLiq. Therefore,

we think that we should allow our level authoring

tool to communicate with APPLiq to prevent teach-

ers from having to describe their levels twice and ac-

cording to different approaches (BM JSON, on the

one hand, and MoPPLiq on the other hand); (2) AP-

PLiq enables teachers to build a scenario that adapts

to the learner’s performance according to the “worked

on” pedagogical objectives described with the output

states. However, in our BM level model, the complex

assessment of what is or is not worked on is not im-

plemented. We consider adapting our model and its

conditions and trigger system (currently related to the

help messages) to measure whether the objectives are

being worked on; (3) APPLiq provides a static sce-

nario. Therefore, adaptation to the performances of

learners is pre-designed. We are studying the possibil-

ity of modifying APPLiq to beneﬁt from the results of

a monitoring system such as the one we have started

to model.

CSEDU 2021 - 13th International Conference on Computer Supported Education

374

4.3 Monitoring Model

Based on discussions with the teachers, we also iden-

tiﬁed the need for a tracking and monitoring sys-

tem. Its purpose is to identify whether the levels and

scenarios designed meet teachers’ needs after one or

more play sessions by the learners.

We decided to use a version of xAPI adapted to se-

rious games (Serrano-Laguna et al., 2017) as a basis

for our tracking system. xAPI allows deﬁning indi-

cators (statements speciﬁed with triplets actor verb

object) which are stored in a Learning Record Store

(LRS).

We identiﬁed two different levels of monitor-

ing: monitoring within the level, and monitoring be-

tween the levels. With the teachers help, we de-

signed statements they felt relevant: the time taken

to complete the levels (Actor initialized level,

Actor exited level); the completion of the lev-

els (Actor completed level, Actor unlocked

level); the use of external support (Actor

unfocused game Windows, Actor focused game

Windows); the number of blocks used and the num-

ber of tests of their program ran by the learner (Actor

interacted blocks, Actor executed program).

We are currently implementing this xAPI monitor-

ing system in BM’s source code.

To conclude, thanks to the work carried out with

the teachers who accompanied us, we were able to

model three signiﬁcant aspects of BM: the levels, the

scenario and the monitoring.

5 CONCLUSIONS AND FUTURE

WORK

To foster adoption and appropriation of learning

games we planned to rely on the meta-design ap-

proach (Fischer and Herrmann, 2011), and we fo-

cused on learning games for computational thinking

such as Blockly Maze (BM). Meta-design goal is to

enable teachers to act as designers of learning games

both at the initial design stage and in the use stage.

In this paper, we have presented a description of

our work in progress. The work is focused on the

deconstruction of BM, both from a conceptual and a

software standpoint. Our objective is to obtain, with

the help of participating teachers, explicit models of

the levels and the educational contents. This work

was required to provide an underdesigned (Fischer

et al., 2004) version of BM. This means a usable,

“turnkey” BM, but above all a learning game that of-

fers the main features required to provide an effec-

tive and facilitated instrumental genesis for teachers

(Rabardel, 2003).

In collaboration with the teachers involved as con-

tributors, we experimented a research method based

on the design of a concept map related to a teach-

ing ﬁeld (computational thinking). The map’s design

brought to light many issues related to their teaching

as well as the needs around BM.

Based on these needs, and always in collaboration

with the teachers, we developed three models describ-

ing BM. Then, we implemented them in a new ver-

sion of BM, which we will submit to its authors (pull

request). The Level Model, implemented in JSON,

proved to be able to describe all the current BM lev-

els, as well as to be used to design new ones with

teachers. For the Scenario Model, we choose MoP-

PLiq and APPLiq and plan to evolve them to answer

our research questions (Marne and Labat, 2014). We

have started work on a Monitoring Model based on

xAPI.

The research reported in this paper was severely

limited by the COVID-19 pandemic, which prevented

us from working with as many teachers as we would

have liked. Therefore, our current and future work

consists of collaborating with more teachers in (1) de-

veloping levels to enrich and test our model of BM

levels; (2) improving and experimenting with the sce-

nario design and adaptation; and (3) implementing the

monitoring of learners to allow teachers to validate

their BM adaptations.

ACKNOWLEDGEMENTS

The authors would like to acknowledge The Univer-

sity Lumi

ere Lyon 2 for the APPI 2020 Grant.

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