Proceedings of the Second (2015) ACM Conference on Learning @ Scale最新文献_第4页

Feature Factory: Crowd Sourced Feature Discovery 功能工厂:众包功能发现

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2728696

K. Veeramachaneni, Kiarash Adl, Una-May O’Reilly

引用次数: 6

Structure and messaging techniques for online peer learning systems that increase stickiness 增加粘性的在线同伴学习系统的结构和消息传递技术

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2724676

Yasmine Kotturi, Chinmay Kulkarni, Michael S. Bernstein, Scott R. Klemmer

{"title":"Structure and messaging techniques for online peer learning systems that increase stickiness","authors":"Yasmine Kotturi, Chinmay Kulkarni, Michael S. Bernstein, Scott R. Klemmer","doi":"10.1145/2724660.2724676","DOIUrl":"https://doi.org/10.1145/2724660.2724676","url":null,"abstract":"When students work with peers, they learn more actively, build richer knowledge structures, and connect material to their lives. However, not every peer learning experience online sees successful adoption. This paper articulates and addresses three adoption challenges for global-scale peer learning. First, peer interactions struggle to bootstrap critical mass. However, class incentives can signal importance and spur initial usage. Second, online classes have limited peer visibility and awareness, so students often feel alone even when surrounded by peers. We find that highlighting interdependence and strengthening norms can mitigate this issue. Third, teachers can readily access \"big\" aggregate data but not \"thick\" contextual data that helps build intuitions, so software should guide teachers' scaffolding of peer interactions. We illustrate these challenges through studying 8,500 students' usage of two peer learning platforms, Talkabout and PeerStudio. This paper measures efficacy through sign-up and participation rates and the structure and duration of student interactions.","PeriodicalId":20664,"journal":{"name":"Proceedings of the Second (2015) ACM Conference on Learning @ Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75488208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 41

Designing MOOCs as Interactive Places for Collaborative Learning 设计mooc作为协作学习的互动场所

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2728689

Saijing Zheng, M. Rosson, Patrick C. Shih, John Millar Carroll

引用次数: 28

Identifying Content-Related Threads in MOOC Discussion Forums 在MOOC论坛中识别与内容相关的线索

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2728679

Yi Cui, A. Wise

引用次数: 44

Technology-Enhanced Learning: Evidence-based Improvement 技术增强学习:循证改进

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2728664

E. Scanlon, T. O'Shea, P. McAndrew

引用次数: 11

Source Effects in Online Education 网络教育中的源效应

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2728671

Nakull Gupta, J. O'Neill, A. Cross, Edward Cutrell, W. Thies

引用次数: 2

Towards Detecting Wheel-Spinning: Future Failure in Mastery Learning 对车轮旋转的检测:掌握学习的未来失败

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2724673

Yue Gong, J. Beck

引用次数: 27

A Playful Game Changer: Fostering Student Retention in Online Education with Social Gamification 一个有趣的游戏改变者:通过社交游戏化促进在线教育中的学生留存率

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2724665

Markus Krause, M. Mogalle, Henning Pohl, J. Williams

引用次数: 126

Alumni & Tenured Participants in MOOCs: Analysis of Two Years of MOOC Discussion Channel Activity MOOC的校友与终身教职参与者:两年MOOC讨论频道活动分析

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2724671

Matti Nelimarkka, Arto Vihavainen

引用次数: 16

The Prediction of Student First Response Using Prerequisite Skills 运用先决技能预测学生第一反应

Proceedings of the Second (2015) ACM Conference on Learning @ Scale Pub Date : 2015-03-14 DOI: 10.1145/2724660.2724675

Anthony F. Botelho, Hao Wan, N. Heffernan

{"title":"The Prediction of Student First Response Using Prerequisite Skills","authors":"Anthony F. Botelho, Hao Wan, N. Heffernan","doi":"10.1145/2724660.2724675","DOIUrl":"https://doi.org/10.1145/2724660.2724675","url":null,"abstract":"A large amount of research in the field of educational data analytics has focused primarily on student next problem correctness. Although the prediction of such information is useful in assessing current student performance, it is better for teachers and instructors to place attention on student knowledge over a longer period of time. Several researchers have articulated that it is important to predict aspects that are more meaningful, inspiring our work here to utilize the large amounts of student data available to derive more substantial predictions over student knowledge. Our goal in this paper is to utilize prerequisite information to better predict student knowledge quantitatively as a subsequent skill is begun. Learning systems like ASSISTments and Khan Academy already record such prerequisite information, and can therefore be used to construct a method of prediction as described in this paper. Using these inter-skill relationships, our method estimates students' initial knowledge based on performance on each prerequisite skill. We compare our method with the standard Knowledge Tracing (KT) model and majority class in terms of the predictive accuracy of students' first responses on subsequent skills. Our results support our method as a viable means of representing student prerequisite knowledge in a subsequent skill, leading to results that outperform the majority class and that are comparably superior to KT by providing more definitive student knowledge estimates without sacrificing predictive accuracy.","PeriodicalId":20664,"journal":{"name":"Proceedings of the Second (2015) ACM Conference on Learning @ Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83000372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21