Ranilson O. Araújo Paiva
Seiji Isotani
ABSTRACT
In this work we present a way to classify students from a gamified online learning environment according to their interactions, and to use the results to create and recommend "missions" - a gamification element that contains challenging tasks to keep students engaged - that focus on: (1) the students' most common interactions, (2) the students' least common interactions (to balance their online behavior), and (3) more than one type of interaction at the same time. The classification approach was systematically applied, following the Pedagogical Recommendation Process. It's main objective was to assist teachers creating personalized missions. We applied a questionnaire to compare the new approach (classification according to patterns in interactions) to the existing one (a report showing some actions students took in the environment). In the results, the classification approach provided a better way to evaluate the students, regarding the three missions' focus.
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Index Terms
- Improving pedagogical recommendations by classifying students according to their interactional behavior in a gamified learning environment
Recommendations
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Reviews
Stewart Mark Godwin
Online learning participation continues to grow across the US, with over 7.1 million students enrolled in at least one course. Based on this fact and the changing educational paradigm, the authors present a method to classify online students using a gaming approach that has four categories: collaborative, gamification, pedagogical, and social. Each category represents a particular type of online persona with specific interactions and interests. Using the pedagogical recommendation process (PRP), the paper describes a case study that classifies students based on how they interact with the learning environment. By using the data from a real online learning environment called MeuTutor, the authors engaged the PRP steps to classify students and then create content to suit these groups. Whilst the conclusions did achieve the initial objectives, there is limited application for the results. The authors do acknowledge the need for future studies, and I would suggest the practical outcomes from this research could be considered by educators. Therefore, I would recommend this paper as a general source of information for teachers who are involved with online learning environments. Online Computing Reviews Service
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