Proceedings of the Fifth Annual ACM Conference on Learning at Scale最新文献_第3页

An active viewing framework for video-based learning 基于视频学习的主动观看框架

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231682

Samuel Dodson, Ido Roll, Matthew Fong, Dongwook Yoon, N. M. Harandi, S. Fels

引用次数: 27

An automatic knowledge graph construction system for K-12 education 面向中小学教育的知识图谱自动构建系统

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231698

Penghe Chen, Yu Lu, V. Zheng, Xiyang Chen, Xiaoqing Li

引用次数: 23

Transformative approaches in distance online education: aligning evidence to influence the design of teaching at scale 远程在线教育的变革方法:调整证据以影响大规模教学设计

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3232261

P. McAndrew, S. Anastopoulou, E. Scanlon

引用次数: 1

Multimedia learning principles at scale predict quiz performance 多媒体学习原理在规模上预测测验表现

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231694

Anita B. Delahay, M. Lovett

引用次数: 1

Who downloads online content and why? 谁下载在线内容，为什么?

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231699

Katherine A. Brady, G. Narasimham, D. Fisher

引用次数: 4

Representing and predicting student navigational pathways in online college courses 表示和预测在线大学课程中学生的导航路径

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231702

Renzhe Yu, Daokun Jiang, M. Warschauer

{"title":"Representing and predicting student navigational pathways in online college courses","authors":"Renzhe Yu, Daokun Jiang, M. Warschauer","doi":"10.1145/3231644.3231702","DOIUrl":"https://doi.org/10.1145/3231644.3231702","url":null,"abstract":"Representation and prediction of student navigational pathways, typically based on neural network (NN) methods, have seen their potential of improving instruction and learning under insufficient human knowledge about learner behavior. However, they are prominently studied in MOOCs and less probed within more institutionalized higher education scenarios. This work extends such research to the context of online college courses. Comparing student navigational sequences through course pages to documents in natural language processing, we apply a skip-gram model to learn vector embedding of course pages, and visualize the learnt vectors to understand the extent to which students' learning pathways align with pre-designed course structure. We find that students who get different letter grades in the end exhibit different levels of adherence to designed sequence. Next, we fit the embedded sequences into a long short-term memory architecture and test its ability to predict next page that a student visits given her prior sequence. The highest accuracy reaches 50.8% and largely outperforms the frequency-based baseline of 41.3%. These results show that neural network methods have the potential to help instructors understand students' learning behaviors and facilitate automated instructional support.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74718150","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: 5

The relationship between scientific explanations and the proficiencies of content, inquiry, and writing 科学解释与内容、探究和写作熟练程度之间的关系

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231660

Haiying Li, J. Gobert, Rachel Dickler

引用次数: 1

Information overload and online collaborative learning: insights from agent-based modeling 信息过载和在线协作学习:来自基于代理的建模的见解

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231701

Shimin Zhang

引用次数: 3

The effects of adaptive learning in a massive open online course on learners' skill development 大规模在线开放课程中适应性学习对学习者技能发展的影响

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231651

Y. Rosen, I. Rushkin, Rob Rubin, Liberty Munson, Andrew M. Ang, G. Weber, Glenn Lopez, D. Tingley

{"title":"The effects of adaptive learning in a massive open online course on learners' skill development","authors":"Y. Rosen, I. Rushkin, Rob Rubin, Liberty Munson, Andrew M. Ang, G. Weber, Glenn Lopez, D. Tingley","doi":"10.1145/3231644.3231651","DOIUrl":"https://doi.org/10.1145/3231644.3231651","url":null,"abstract":"We report an experimental implementation of adaptive learning functionality in a self-paced Microsoft MOOC (massive open online course) on edX. In a personalized adaptive system, the learner's progress toward clearly defined goals is continually assessed, the assessment occurs when a student is ready to demonstrate competency, and supporting materials are tailored to the needs of each learner. Despite the promise of adaptive personalized learning, there is a lack of evidence-based instructional design, transparency in many of the models and algorithms used to provide adaptive technology or a framework for rapid experimentation with different models. ALOSI (Adaptive Learning Open Source Initiative) provides open source adaptive learning technology and a common framework to measure learning gains and learner behavior. This study explored the effects of two different strategies for adaptive learning and assessment: Learners were randomly assigned to three groups. In the first adaptive group ALOSI prioritized a strategy of remediation - serving learners items on topics with the least evidence of mastery; in the second adaptive group ALOSI prioritized a strategy of continuity - that is learners would be more likely served items on similar topic in a sequence until mastery is demonstrated. The control group followed the pathways of the course as set out by the instructional designer, with no adaptive algorithms. We found that the implemented adaptivity in assessment, with emphasis on remediation is associated with a substantial increase in learning gains, while producing no big effect on the drop-out. Further research is needed to confirm these findings and explore additional possible effects and implications to course design.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85493414","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: 22

Supporting answerers with feedback in social Q&A 在社交问答中提供反馈以支持答案

Proceedings of the Fifth Annual ACM Conference on Learning at Scale Pub Date : 2018-06-26 DOI: 10.1145/3231644.3231653

John Frens, Erin Walker, Gary Hsieh

引用次数: 5