Learning Style Gamification Model: Gamification in E-Learning Based on Students’ Learning Styles

Zaric, Nadja; Šćepanović, Snežana; Schroeder, Ulrik

doi:10.21125/iceri.2018.2068

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…In any case, it would be convenient to make a specific study of the player profile of engineering students in Latin America, to confirm whether their player profile is the one that the literature attributes to the student body in general and thus demonstrate the observed gap. Given that the effectiveness of gamified didactic situations is conditioned on the adequacy of the student's player profile [84], this raises the need on the part of the professor to adapt the design of their situations to player profiles different from their own [57, 69].…”

Section: Discussionmentioning

confidence: 99%

“…In part, the above gap can be explained by the age difference between professors and their students [71]. Those who design game-based didactic situations naturally tend to strengthen the presence of the player profile that is most in line with their own, so professors should reflect on their own player profile and strive to design gamified situations suitable for player profiles F I G U R E 2 Bartle's classification of player profiles different from their own [22,57,58,69,75,84]. In this article, a first exploration of the player profile of the engineering professors is carried out, from the perspective that they themselves have in this regard, to lay the groundwork for establishing the main differences with the player profiles of the students, more abundantly studied in the literature.…”

Section: Player Profiles Of Engineering Students and Engineering Prof...mentioning

confidence: 99%

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Player profiles for game‐based applications in engineering education

Vergara

Antón‐Sancho

Fernández‐Arias

2022

Comp Applic In Engineering

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The use of digital learning environments in higher education has led to design methodological strategies, like gamification, adapted to computer‐based learning. The effectiveness of gamification depends on the adaptation of the methodology to the player's profile. Four types of player profiles (Explorer, Killer, Socialized, and Achiever) are established according to the Bartle classification. In this article, quantitative research is carried out on the player profile and the one considered best for learning engineering professors. Sociological and academic aspects that influence player profile choices are also identified. A descriptive and inferential analysis of the answers given by a population of 532 engineering professors —who attended a training course on gamification in digital environments—to a survey designed by the authors was carried out. The results reveal that most engineering professors are Explorers and this is also the player profile considered best for learning, although there is a gap between the own player profile and the choice of the most effective one. The player profile shown here to be the most frequent among engineering professors differs from that attributed to students in the literature, which is Achiever. Gaps by gender, age, teaching experience, and university tenure are also identified. Universities are recommended to strengthen professor training to design personalized game‐based computing environments and to cater to differences due to several sociological and academic aspects.

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Section: Discussionmentioning

confidence: 99%

Section: Player Profiles Of Engineering Students and Engineering Prof...mentioning

confidence: 99%

Player profiles for game‐based applications in engineering education

Vergara

Antón‐Sancho

Fernández‐Arias

2022

Comp Applic In Engineering

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“…In order to influence the various types of learners and learning styles, the Felder-Silverman Learning Style Model (FSLSM) has been used to identify students' learning styles and propose corresponding learning methods. This model was selected since the FSLSM combines major learning models such as Kolb, Myers-Briggs and Pask [25]. Several adapted learning components have been proposed and documented in Table 1 to satisfy each learning style.…”

Section: B Analysis Of Learning Styles and Learning Modelsmentioning

confidence: 99%

A Mobile Application for Learning Enterprise Resource Planning

Dhondee,

Surjoo,

Cadersaib

2022

JTEC

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With the growing demand for Enterprise Resource Planning (ERP) literate graduates in the professional world, ERP education is an imperative aspect that has been integrated into universities. However, for many higher education institutions, the affordability of a commercial ERP system for courses is not practical. On the other hand, students struggle to grasp the concept of business processes and enterprise systems. They have difficulties in fully understanding the interrelationship of various ERP modules, especially new ERP features such as Business Intelligence (BI) and Business Analytics (BA), in meeting the holistic organisational objectives. This struggle was reinforced by the COVID -19 pandemic, which forced courses to be moved from face-to-face to online platforms. In this paper, a gamified mobile learning approach for ERP learning has been proposed and implemented to enhance ERP knowledge retention, improve the availability of ERP learning material, and expose new ERP features. The mobile application, named LearnES, consists of the application of gamification and adapted learning components based on various learning models. A research model with hypotheses was developed to test the outcomes of the solution, and the application was evaluated through a mixed survey-based approach. Following the evaluation, participants manifested a favourable attitude towards learning ERP through the mobile application.

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