Today, the rapid growth of publicly available data reinforces the need for public understanding of statistics and data interpretation. These skills are important for data-based decision making at individual-level or even at societallevel. However, statistics have been accused as a complex educational topic. In the meantime, although gamification notes positive outcomes in education, regarding students' engagement, statistical literacy is sparsely mentioned as an examining context in the respective literature. This study makes the picture more coherent, conducting a review about the adoption of gamification in statistical literacy (N=257 studies). In general, the results are in favor of the use of gamification in statistics education. The few mentioned negative outcomes warn for further attention on its design and integration. Besides having a variety of statistical topics mentioned, lifelong learning is slightly investigated. Only half of the reviewed body of the literature presents empirical data, and narrative and board games are mainly used. Further research is proposed about the design of gamification, touching more topics of statistics and examining various motivational affordances, especially in lifelong learning.
The information age that we live in, is characterized by an exponential growth of
production, storage and analysis of data. Data can provide useful insights in terms of
decision-making and raise social awareness by providing a data-based worldview.
Consequently, citizens need to be engaged in data interpretation and basic statistics skills. In
this context, the dissemination of statistical literacy is a challenge for teachers,
researchers and practitioners [
Gamification is defined as the integration of motivational affordances into services
to create gameful experience [
In this study, we aim to review and synthesize the literature that uses gamification in education of statistics, forecasting and data literacy regarding the taught subjects, the educational level, the used motivational affordances, and the target audience. Based on the behavioral and psychological outcomes, this study identifies gaps in literature, giving further recommendations in order to support public engagement in the important topic of statistics, data literacy and forecasting education. 2
Our study follows the guidelines for an effective literature review [
The literature searches were conducted in the Scopus database and in the Association for Information Systems (AIS) Electronic Library. We chose these databases, because they index context of thousands publishers including rigorous databases, namely: IEEE, ACM and Springer. The search for literature in the Scopus database was conducted using the following search query: TITLE-ABS-KEY (((((predict*) OR (forecast*) OR (statistic*) OR (data)) W/1 (education OR literacy OR teaching OR (learn* W/3 outcome) OR (learn* W/3 student) OR ("learning effect") OR ("learning result*") OR ("learning objectives") OR ("learning aim") OR ("learning goals"))) AND (((game) OR (gamif*))))).
This search is composed of three main parts. Since this review focuses on statistics and forecasting education, firstly, we framed the specific context using the terms: “predict*, forecast*, statistic*, data” in combination with terms relevant to the educational process. Secondly, the part “game” OR “gamif*” was used to include games, gamebased learning and gamification. Finally, the search fields were defined as title, abstract and keywords. The search was limited to English and to conference papers, articles, articles in papers, reviews and book chapters. We followed a similar procedure in the AISeL database.
The literature search was conducted on 10/2019 and resulted in a total of 257 papers. Applying the inclusion and exclusion criteria (section 2.2), upon titles and abstracts, we concluded to 61 candidate papers. Finally, going through the full papers and applying the same criteria, we concluded to a set of 49 papers (articles: 55.10%, book chapters: 4.08%, conference papers: 44.90%). There is an increase in published papers, during the last years and the list of all papers is available: https://tinyurl.com/y4agt26z. 2.2
The inclusion criteria should reflect the purpose of this study in order to conclude to
the appropriate studies. Thus, the reviewed papers had to: (i) describe a game, a
gamified activity, or motivational affordances in the educational context relative to statistics
or forecasting or data literacy (ii) contribute to this educational field (iii) include an
abstract. In addition, we excluded papers which aim to improve forecasting accuracy in
terms of machine learning algorithms or games' score predictions in sports, without any
educational contribution. No further training was used, since the review screening was
conducted by one author.
Initially, our analysis focuses on the current state of the art. We present the specific
subjects of courses, the respective target audience and the system used by the reviewed
studies, which mention gamification interventions. Then, the reported motivational
affordances and psychological and behavioral outcomes are identified and presented.
Finally, the reviewed studies are categorized based on their reported impact. In the
following analysis, we use bold to indicate the highest value, and italic for the second
highest. Furthermore, for the sake of consistency, we use the same terminology as the
research of [
Teachers in a various subjects of statistics have used gamification to equip their
audience with proper statistical background, as presented in Table 1. Gamification has been
mainly used in introductory statistics courses, probably aiming to motivate students,
due to the complexity that these courses entail [
Table 2 demonstrates the examined outcomes, based on reviewed studies. The
psychological outcomes regarding the perceived effect of gamified experience on
participants are examined [
Table 3 lists the analysis methods of reviewed studies based on their results' frequency.
The majority of them –solution, experience and validation papers [
A variety of motivational affordances has been used in many subjects of statistics,
ranging from introductory to advanced topics [
Overall, based on the frequency of the examined variables –motivational
affordances, core systems, subjects, target audience– along with the reported outcomes,
gamification is gaining a stronger position in the field of statistics education. Not only
most of the studies present positive outcomes, but also the variety of the used
motivational affordances is spread in a plethora of systems and subjects of statistics, even in
the most complex topics. These findings are encouraging for the use of gamification in
statistics education, as it seems to have the potential to motivate a wide audience
regarding this topic, promoting a data-based worldview [
Based on our analysis, a few gaps have been identified, giving direction for further
research in the design of gamification, and the target audience. Since statistical literacy
is necessary in order to interpret the data and get useful insights, gamification research
should further employ and evaluate the use of gamification strategies, through
controlled experimental research method (i.e. achievement-related affordances, which have
been mostly used in education with great results [
Although, the present study follows guidelines for a systematic literature review, the backward and forward step would benefit it. Our results are limited to the specific searches. However, this study focuses on the effectiveness of gamification in teaching statistics in a multidisciplinary ground and not generally on the use of gamification in education.
This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement ID 840809.