A user-transaction-based recommendation strategy for an educational digital library

被引：0
作者：
Gerd Kortemeyer
Stefan Dröschler
机构：
[1] ETH Zurich,Educational Development and Technology (LET)
[2] ETH Zurich,Department of Computer Science
来源：
International Journal on Digital Libraries | 2021年 / 22卷
关键词：
Digital library; Recommender system; Learning objects; Collaborative filtering;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The automated recommendation of content resources to learners is one of the most promising functions of educational digital libraries. Underlying strategies should take the individual progress of the learner into account to provide appropriate recommendations that are meaningful to the learner. If presented with appropriate assistance, learners will more likely engage in productive learning strategies, such as reading up on concepts and accessing preparatory materials, and refrain from unproductive behavior, such as guessing on or copying of homework. In this exploratory case study, we are analyzing transactional data within an educational digital library of online physics homework problems and learning content. The sequence of events starting with a learner failing to solve a particular problem, interacting with other online resources, and then succeeding on that same problem is used to identify potentially helpful resources for future learners. It was found that these “success stories” indeed allow for providing recommendations with acceptable accuracy, which, when implemented, may lead to more productive learning paths.
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收藏
页码：147 / 157
页数：10
相关论文
共 113 条
  • [1] Adomavicius G(2005)Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions IEEE Trans. Knowl. Data Eng. 17 734-749
  • [2] Tuzhilin A(1991)A guide to introductory physics teaching Am. J. Phys. 59 189-190
  • [3] Arons AB(2016)Research-paper recommender systems: a literature survey Int. J. Digit. Libr. 17 305-338
  • [4] Gould H(2009)Collaborative filtering adapted to recommender systems of e-learning Knowl.-Based Syst. 22 261-265
  • [5] Gould M(2001)Online homework: does it make a difference? Phys. Teacher 39 293-296
  • [6] Beel J(2006)Towards flexible learning object metadata Int. J. Contin. Eng Educ. Life Long Learn. 16 50-63
  • [7] Gipp B(2008)Intelligent web-based learning system with personalized learning path guidance Comput. Educ. 51 787-814
  • [8] Langer S(2004)Using an online homework system enhances students’ learning of physics concepts in an introductory physics course Am. J. Phys. 72 1447-1453
  • [9] Breitinger C(2013)Report and recommendations on multimedia materials for teaching and learning electricity and magnetism Eur. J. Phys. 34 L47-423
  • [10] Bobadilla J(2008)Personal recommender systems for learners in lifelong learning networks: the requirements, techniques and model Int. J. Learn. Technol. 3 404-60
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