Exploring long-term behavior patterns in a book recommendation system for reading

阅读(过程) 班级(哲学) 计算机科学 讲故事 理解力 读写能力 数学教育 万维网 多媒体 教育学 心理学 叙述的 人工智能 语言学 哲学 程序设计语言
作者
Tzu Chao Chien,Zhi Hong Chen,Tak Wai Chan
摘要

Introduction Book recommendation between students has the potential to enhance reading interest and ability (Chien, Chen, Ko, Ku, & Chan, 2015). The recommendation process encourages students to share and discuss what they have read, thus helping to create and foster a good reading atmosphere within the class (Larson, 2009). A book recommendation system can provide students with an opportunity to review what they have read by retelling, based on their own individual understanding and perspectives, which can greatly improve their literacy skills, reading comprehension and recollection (Carico, Logan, & Labbo, 2004). However, the benefits of a book recommendation system are reliant upon extensive and frequent student interaction, which requires overcoming the difficulties of organizational complexity and limited interaction. The former relates to the problem of class time allocation. It is difficult for teachers in the classroom to clear space on the agenda for a book recommendation activity and ensure that all students have an equal chance to express their opinions. The latter refers to the time needed in order to reinforce the effect of social interaction. In small class size elementary classrooms, there might not be enough student interaction for peer-to-peer book recommendation. Strategies proposed to overcome these two difficulties include activities designed to reduce the complexity and enhance the efficiency of social interaction, such as book talks, storytelling, and dramas (Pilgreen, 2000; Gardiner, 2005; Atwell, 2007). Although these activities can greatly help to facilitate classroom book recommendation, they still require the teacher to expend a lot of effort on logistical organization, such as setting up tables, group allocation, and maintaining classroom order. Recent developments in information technology however, have opened the door for teachers to provide tech-support support for the development of communication tools and book recommendation systems (Hamilton & Cherniavsky, 2006, Larson, 2008) in the classroom, include message board discussions (Wolsey, Biesenbach-Lucas, & Meloni, 2004), blogs (Huffaker, 2005; Ray, 2006), and social networking systems. With the support of technology, teachers can efficiently plan activities to help students express their opinions to their peers, both in and out of school time (Hancock, 2008). These technology-supported activities can serve as a stage, on which students can express ideas, perspectives, and thoughts to their classmates, and help to foster the development of a learning community for reading and book recommendation (Wolsey, Biesenbach-Lucas, & Meloni, 2004; Larson, 2009). One example is to use potential of technology for promoting the behavior of book recommendation. The MyBookstore system (Chien, Chen, Ko, Ku, & Chan, 2011), which incorporates incentive models into a recommendation system, is designed to help students describe their favorite books and recommend them to their classmates. Although a previous study has demonstrated that such a system can enhance student learning in terms of word usage and reading perception (Chien et al., 2015), little attention was paid to investigating the students' behavior patterns over a long period of time. Investigating student behavior when using such a book recommendation system is critical because not only do the findings enrich our understanding of how an effective system works, but also sheds light on how to stimulate and maintain positive behaviors. The purpose of this study is thus to conduct a long-term empirical study using the My-Bookstore system as an example. In addition, to acquire a more comprehensive understanding of student behavior, we not only analyze the frequency of certain behaviors, but also trace their sequence. In this way, subtle changes in behavior can be revealed, even if the frequencies remain similar. The two research questions to be answered in this study are: (1) What are the frequent behaviors and behavioral patterns of students participating in a book recommendation system? …

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
无言完成签到,获得积分10
2秒前
佚名完成签到,获得积分10
2秒前
TAO完成签到,获得积分10
2秒前
4秒前
xbw发布了新的文献求助10
4秒前
wjh发布了新的文献求助10
4秒前
5秒前
5秒前
5秒前
7秒前
歇儿哒哒完成签到,获得积分10
8秒前
文献完成签到,获得积分10
8秒前
Akim应助hezhouse采纳,获得10
10秒前
11秒前
11秒前
12秒前
Ztf发布了新的文献求助10
12秒前
江睿曦发布了新的文献求助10
12秒前
13秒前
13秒前
14秒前
文献发布了新的文献求助10
14秒前
15秒前
15秒前
16秒前
1234关注了科研通微信公众号
16秒前
chu发布了新的文献求助10
16秒前
长安应助AnhaoY采纳,获得20
16秒前
潞垚发布了新的文献求助10
16秒前
情怀应助wjh采纳,获得10
17秒前
17秒前
19秒前
陶醉若云完成签到,获得积分10
19秒前
墨尘发布了新的文献求助10
20秒前
SciGPT应助文献采纳,获得10
20秒前
Egal完成签到,获得积分10
20秒前
orixero应助细腻的夏波采纳,获得10
21秒前
21秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
A Study of the Model by which Principals’ Leadership Behaviour Influences Student Learning Outcomes in Elementary Schools 1000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7710158
求助须知:如何正确求助?哪些是违规求助? 9267076
关于积分的说明 20062709
捐赠科研通 7286290
什么是DOI,文献DOI怎么找? 3296857
关于科研通互助平台的介绍 2451449
邀请新用户注册赠送积分活动 2303901