Learning Contents Recommendation Method in Consideration to Match Difficulty and Proficiency

2016 Fiscal Year Final Research Report

• Project/Area Number: 25330364
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Web informatics, Service informatics
• Research Institution: Kochi University
• Principal Investigator: Miyoshi Yasuo 高知大学, 教育研究部自然科学系理学部門, 講師 (20380115)
• Research Collaborator: HAMADA Kazunobu ; TOMITA Hiroki ; FUJISAKI Yuri ; MINAMI Yuki
• Project Period (FY): 2013-04-01 – 2017-03-31
• Keywords: 学習コンテンツ / 難易度推定 / 習熟度推定 / コンテンツ推薦

Outline of Final Research Achievements

I have developed a habit development support system for web learning, it is base for a learning-contents recommendation system. In addition, by trial and error, I have improved precision of the algorithm to estimate learner proficiency and learning-contents difficulty. It is clear that the algorithm is for general purpose but the result is greatly influenced by the learning purpose of the learner, from the result that applied the algorithm to the recipes of Cookpad. This study develops into the development of algorithm to estimate the standard indicating understandability.

Free Research Field

教育工学