Adaptive Gamification for Learning Environments

(Scimago Q1, ATIEF A+)International audienceIn spite of their effectiveness, learning environments often fail to engage users and end up under-used. Many studies show that gamification of learning environments can enhance learners' motivation to use learning environments. However, learners react differently to specific game mechanics and little is known about how to adapt gaming features to learners' profiles. In this paper, we propose a process for adapting gaming features based on a player model. This model is inspired from existing player typologies and types of gamification elements. Our approach is implemented in a learning environment with five different gaming features, and evaluated with 266 participants. The main results of this study show that, amongst the most engaged learners (i.e. learners who use the environment the longest), those with adapted gaming features spend significantly more time in the learning environment. Furthermore, learners with features that are not adapted have a higher level of amotivation. These results support the relevance of adapting gaming features to enhance learners' engagement, and provide cues on means to implement adaptation mechanisms

Does Gamified Educational Systems Change Students’ Learning Behaviors? A Case Study with Postgraduate Students

In the last few years, gamification studies have increased in the field of education and digital technologies, showing different results on the use of gamified educational systems in relation to students’ learning aspects. These studies, however, often keep the focus on quantitative or qualitative approaches directly related to student learning, without considering students’ perceptions of the gamification design and how the gamification design aspects of the system can influence positively the students’ behavior change. Therefore, this study compared a gamified with a non-gamified version of an educational system, through a mixed (quantitative and qualitative) approach to identify if gamified educational systems are better than non-gamified educational systems to provide positive students’ learning behavior change. The results confirmed that the gamified educational system was more effective than the non-gamified system

Simulation Game Concept For AI-Enhanced Teaching Of Advanced Value Stream Analysis and Design

Value stream analysis and design is employed globally by improvement teams within industrial settings to maximize value creation and eliminate waste. For ending methodical time-centricity, research expanded the methodology to incorporate diverse facets like material flow cost accounting, information logistics, and external influence factors. These enhancements, along with increasing data volumes, are prompting a re-evaluation of how professional improvement teams should think and operate. Consequently, a transformation of the pedagogical approach used for educating students and professionals necessitates novel solutions. Conventional teaching methods such as expository lectures are widely considered inadequate in promoting knowledge retention and engagement. So far, existing research has not yet resulted in a solution that can effectively impart the methodological complexity of advanced value stream analysis and design in a motivating and vivid fashion. To address this gap, this paper applies a tailored CRISP gamification framework to develop a simulation game concept. These concept enables AI-enhanced teaching of advanced value stream analysis and design focusing on identification of multi-stage resource-efficient optimization strategies. Through integration of game-based learning with AI a trained reinforcement learning agent can act either competitively or cooperatively, creating a unique form of teaching accounting the aspects personalization, adaptive feedback, content creation, and analysis and assessment

Elaboration and validation of the scale to measure the experience on gamification in education (EGAMEDU)

Nowadays, we talk about the use of gamification in education, an active methodology that consists of the use of mechanics, design or game structures in class. With this type of methodology, the effort is rewarded, which is treated as a motivating tool in class. There is no valid or well-structured instrument to measure gamification properly in education. This research arises from the need to develop and validate an instrument to measure the experience on gamification in educational contexts (EGAMEDU) as a useful tool of diagnosis so that the teaching staff can guide their teaching practice toward the use of this methodology. The sample used for the validation of the questionnaire is composed of 401 participants related to education and gamified experiences. The results show good validity indexes and a factorial structure according to the one proposed in the theoryPeer Reviewe

Turning Users\u27 In-Game Behaviours into Actionable Adaptive Gamification Strategies using the PEAS Framework

Adaptive gamification answers the need to customize engagement strategies because users are motivated by different game elements and mechanics. To better understand these individual preferences, user modelling is vital. However, gameful designers must make many decisions on matching profiling data to actual adaptation strategies, which makes modelling particularly challenging. The lack of a standardized and guided process for adaptive gamification hinders replicability, comparability, and complicates making adaptation dynamic. In this study, we analyzed a persuasive gameful application (Play\&Go) to show how in-game behaviours can be translated into adaptation strategies. We used an existing adaptation framework (PEAS) grounded in the games and gamification literature. Our work demonstrates the suitability of the PEAS model as a shared, standardized method for adaptive gamification and shows how it can guide the process of transforming user behaviours into actionable adaptation strategies

Turning Users' In-Game Behaviours into Actionable Adaptive Gamification Strategies using the PEAS Framework

Adaptive gamification answers the need to customize engagement strategies because users are motivated by different game elements and mechanics. To better understand these individual preferences, user modelling is vital. However, gameful designers must make many decisions on matching profiling data to actual adaptation strategies, which makes modelling particularly challenging. The lack of a standardized and guided process for adaptive gamification hinders replicability, comparability, and complicates making adaptation dynamic. In this study, we analyzed a persuasive gameful application (Play\&Go) to show how in-game behaviours can be translated into adaptation strategies. We used an existing adaptation framework (PEAS) grounded in the games and gamification literature. Our work demonstrates the suitability of the PEAS model as a shared, standardized method for adaptive gamification and shows how it can guide the process of transforming user behaviours into actionable adaptation strategies

Gamified Feedback durch Avatare im Mobile Learning

Viele Arbeitsprozesse in der Industrie werden zunehmend digitalisiert. Diese Entwicklung erfordert neue Kompetenzen, welche im Arbeitsprozess durch Ansätze wie mobile Applikationen erworben werden können. Aufgrund der Informationsfülle im Mobile Learning und den Spezifika solcher Endgeräte kann es zu einer kognitiven Überlastung des Lernenden kommenden, wodurch dieser Lerninhalte nicht mehr aufnehmen kann. Um diesen Herausforderungen zu begegnen, schlagen wir den Einsatz von Gamified Feedback durch Avatare vor, welche als Lehrerergänzung die notwendigen Hilfestellungen und Informationen bereitstellen können. Hierzu wird im Kurzbeitrag eine Studie zur Untersuchung der Wirkungsweise von GamifiedFeedback auf Cognitive Load von Lernenden im Mobile Learning präsentiert

A Review on Gamification in e-learning: Effects and Challenges

Information technology has brought us a great deal of technological advancement, opening up endless possibilities for distance education. E-Learning platforms make it possible to connect people around the globe. Using the various technologies that are available, Gamification enhances the performance of e-learning platforms. Gamification of e-learning platforms helps in providing an engaging learning experience for users of all ages. Applying gamification in a non-gaming environment motivates students and also keeps them engaged in learning. This paper summarizes various game elements such as points, leader boards, badges, provided to the users for better e-learning experience by gamifying the environment and discussing the impact of gamification

Do people's user types change over time? An exploratory study

In recent years, different studies have proposed and validated user models (e.g., Bartle, BrainHex, and Hexad) to represent the different user profiles in games and gamified settings. However, the results of applying these user models in practice (e.g., to personalize gamified systems) are still contradictory. One of the hypotheses for these results is that the user types can change over time (i.e., user types are dynamic). To start to understand whether user types can change over time, we conducted an exploratory study analyzing data from 74 participants to identify if their user type (Achiever, Philanthropist, Socialiser, Free Spirit, Player, and Disruptor) had changed over time (six months). The results indicate that there is a change in the dominant user type of the participants, as well as the average scores in the Hexad sub-scales. These results imply that all the scores should be considered when defining the Hexad's user type and that the user types are dynamic. Our results contribute with practical implications, indicating that the personalization currently made (generally static) may be insufficient to improve the users' experience, requiring user types to be analyzed continuously and personalization to be done dynamically.Comment: 5th International GamiFIN Conference 2021 (GamiFIN 2021), April 7-10, 2021, Finlan

Model Gamifikasi Menggunakan Logika Fuzzy untuk Penentuan Reward Pelanggan pada E-Commerce

Inovasi menggunakan gamifikasi diperlukan untuk menghadapi persaingan antar e-commerce. Gamifikasi berguna untuk meningkatkan pengalaman, menjaga kesetiaan pelanggan, penguatan merk dan melengkapi motivasi pembeli dan melakukan transaksi di e-commerce. Bentuk yang umum dari gamifikasi adalah pemberian reward bagi pelanggan dengan kondisi tertentu. Kondisi ini contohnya adalah lama menjadi pelanggan, besar transaksi, jenis transaksi. Masalah yang terjadi berkaitan dengan pemberian reward kepada pelanggan adalah reward yang tidak sesuai dan monoton atau mudah ditebak sehingga unsur kejutan yang menjadi salah satu elemen penting dari reward menjadi menurun kualitasnya. Penelitian ini bertujuan membentuk model gamifikasi yang tidak monoton menggunakan kecerdasan buatan dengan metode logika fuzzy. Logika fuzzy mampu membentuk perilaku reward yang dinamis sehingga meningkatkan kualitas reward yang diberikan kepada pelanggan. Input yang digunakan untuk menentukan reward adalah banyaknya transaksi, banyak produk dipilih dan total biaya pesanan. Hasil dari penelitian ini, logika fuzzy dapat menghasilkan perilaku reward yang lebih dinamis. Kata kunci: gamifikasi, reward, logika fuzzy, e-commerc