A student’s profile defines the best way a student chooses to learn. It comprises information on student’s characteristics such as background knowledge, learning style preference, goals, personality etc. The foremost challenge that the students experience in learning system is that they are unable to bring back relevant information based on their needs. One of the methods used to obtain the students’ needs is to create a highly efficient student profile, which would represent the true students’ needs. Our contribution consists in modeling a student’s profile based on many important characteristics. In this context, we developed an “SPOnto” ontology to represent a student profile in an adaptive gamified learning system. This ontology will then help the classification of the different types of learners using the machine learning techniques. The present paper epitomizes the implementation of our contribution in a gamified learning environment “Class Quiz” and the assessment of its effectiveness. We created classification models by applying several algorithms and using a dataset encompassing 500 instances.

学生的个人资料定义了学生选择的最佳学习方式。它包括关于学生特征的信息，如背景知识、学习风格偏好、目标、个性等。学生在学习系统中遇到的最大挑战是他们无法根据自己的需要带回相关信息。用于获取学生需求的方法之一是创建高效的学生档案，这将代表真正的学生需求。我们的贡献在于根据许多重要特征对学生的个人资料进行建模。在这种情况下，我们开发了一个“SPOnto”本体来表示自适应游戏化学习系统中的学生档案。然后，该本体将帮助使用机器学习技术对不同类型的学习者进行分类。本文概括了我们在游戏化学习环境“课堂测验”中的贡献的实施及其有效性的评估。我们通过应用多种算法并使用包含 500 个实例的数据集来创建分类模型。