Teaching as a fractal: from experience to model

被引:1
作者
Compan-Rosique, Patricia [1 ]
Molina-Carmona, Rafael [1 ]
Satorre-Cuerda, Rosana [1 ]
Llorens-Largo, Faraon [1 ]
机构
[1] Univ Alicante, Dept Comp Sci & Artificial Intelligence, Alicante, Spain
来源
EDUCATION IN THE KNOWLEDGE SOCIETY | 2015年 / 16卷 / 04期
关键词
motivation; evaluation; active learning; instructional design; task-based learning; fractal;
D O I
10.14201/eks20151643246
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
The aim of this work is to improve students' learning by designing a teaching model that seeks to increase student motivation to acquire new knowledge. To design the model, the methodology is based on the study of the students' opinion on several aspects we think importantly affect the quality of teaching (such as the overcrowded classrooms, time intended for the subject or type of classroom where classes are taught), and on our experience when performing several experimental activities in the classroom (for instance, peer reviews and oral presentations). Besides the feedback from the students, it is essential to rely on the experience and reflections of lecturers who have been teaching the subject several years. This way we could detect several key aspects that, in our opinion, must be considered when designing a teaching proposal: motivation, assessment, progressiveness and autonomy. As a result we have obtained a teaching model based on instructional design as well as on the principles of fractal geometry, in the sense that different levels of abstraction for the various training activities are presented and the activities are self-similar, that is, they are decomposed again and again. At each level, an activity decomposes into a lower level tasks and their corresponding evaluation. With this model the immediate feedback and the student motivation are encouraged. We are convinced that a greater motivation will suppose an increase in the student's working time and in their performance. Although the study has been done on a subject, the results are fully generalizable to other subjects.
引用
收藏
页码:32 / 46
页数:15
相关论文
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