Directing All Learners to Course Goal with Enforcement of Discipline Utilizing Persona Motivation

スポンサーリンク

概要

• 論文の詳細を見る

• The paper proposes the PMD method to design an introductory programming practice course plan that is inclusive for all learners and stable throughout a course. To achieve the course plan, the method utilizes personas, each of which represents learners having similar motivation to study programming. The learning of the personas is directed to the course goal with an enforcement resulting from the discipline, which is an integration of effective learning strategies with affective components of the persoans. Under the enforcement, services to facilitate and promote the learning of each persona can be decided, based on motivation components of each persona, motivational effects of the services, and the cycle of self-efficacy. The application of the method on about 500 freshmen in C programming practice course has shown this is a successful approach for designing courses.

著者

• Harada Fumiko

  College Of Information Science And Engineering Ritsumeikan University

• HARADA Fumiko

  College of Information Science and Engineering, Ritsumeikan University

• Shimakawa Hiromitsu

  College of Information Science and Engineering, Ritsumeikan Uni.

• DINH Dong

  Graduate School of Science and Engineering, Ritsumeikan University

• Shimakawa Hiromitsu

  College of Information Science and Engineering, Ritsumeikan Uni

• Dinh Dong

  Graduate School of Science and Engineering, Ritsumeikan Uni

• SHIMAKAWA Hiromitsu

  College of information Science and Engineering

• HARADA Fumiko

  College of information Science and Engineering

関連論文

• Adaptive Fair Resource Allocation for Energy and QoS Trade-Off Management
• Adaptive Fair Sharing Control in Real-Time Systems Using Nonlinear Elastic Task Models(Nonlinear Problems)
• Directing All Learners to Course Goal with Enforcement of Discipline Utilizing Persona Motivation
• Derivation of Learning Style Effectiveness from Portfolio in Programming Education
• Presuming Learner Personas from Portfolios with Non-negative Matrix Factorization
• Non-negative Matrix Factorization to Identify Motivation and Learning Strategies from Portfolio

スポンサーリンク