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International Conference on Learning Analytics and Knowledge最新文献

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Deconstructing disengagement: analyzing learner subpopulations in massive open online courses 解构脱离:分析大规模开放在线课程中的学习者亚群
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460330
René F. Kizilcec, C. Piech, Emily Schneider
{"title":"Deconstructing disengagement: analyzing learner subpopulations in massive open online courses","authors":"René F. Kizilcec, C. Piech, Emily Schneider","doi":"10.1145/2460296.2460330","DOIUrl":"https://doi.org/10.1145/2460296.2460330","url":null,"abstract":"As MOOCs grow in popularity, the relatively low completion rates of learners has been a central criticism. This focus on completion rates, however, reflects a monolithic view of disengagement that does not allow MOOC designers to target interventions or develop adaptive course features for particular subpopulations of learners. To address this, we present a simple, scalable, and informative classification method that identifies a small number of longitudinal engagement trajectories in MOOCs. Learners are classified based on their patterns of interaction with video lectures and assessments, the primary features of most MOOCs to date.\u0000 In an analysis of three computer science MOOCs, the classifier consistently identifies four prototypical trajectories of engagement. The most notable of these is the learners who stay engaged through the course without taking assessments. These trajectories are also a useful framework for the comparison of learner engagement between different course structures or instructional approaches. We compare learners in each trajectory and course across demographics, forum participation, video access, and reports of overall experience. These results inform a discussion of future interventions, research, and design directions for MOOCs. Potential improvements to the classification mechanism are also discussed, including the introduction of more fine-grained analytics.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117335679","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: 1058
Open academic analytics initiative: initial research findings 开放学术分析计划:初步研究成果
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460325
E. Lauría, Erik W. Moody, Sandeep M. Jayaprakash, Nagamani Jonnalagadda, Joshua D. Baron
{"title":"Open academic analytics initiative: initial research findings","authors":"E. Lauría, Erik W. Moody, Sandeep M. Jayaprakash, Nagamani Jonnalagadda, Joshua D. Baron","doi":"10.1145/2460296.2460325","DOIUrl":"https://doi.org/10.1145/2460296.2460325","url":null,"abstract":"This paper describes the results on research work performed by the Open Academic Analytics Initiative, an on-going research project aimed at developing an early detection system of college students at academic risk, using data mining models trained using student personal and demographic data, as well as course management data. We report initial findings on the predictive performance of those models, their portability across pilot programs in different institutions and the results of interventions applied on those pilots.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128910761","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: 42
Analysis of collaborative writing processes using revision maps and probabilistic topic models 使用修订图和概率主题模型分析协作写作过程
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460307
Vilaythong Southavilay, K. Yacef, P. Reimann, R. Calvo
{"title":"Analysis of collaborative writing processes using revision maps and probabilistic topic models","authors":"Vilaythong Southavilay, K. Yacef, P. Reimann, R. Calvo","doi":"10.1145/2460296.2460307","DOIUrl":"https://doi.org/10.1145/2460296.2460307","url":null,"abstract":"The use of cloud computing writing tools, such as Google Docs, by students to write collaboratively provides unprecedented data about the progress of writing. This data can be exploited to gain insights on how learners' collaborative activities, ideas and concepts are developed during the process of writing. Ultimately, it can also be used to provide support to improve the quality of the written documents and the writing skills of learners involved. In this paper, we propose three visualisation approaches and their underlying techniques for analysing writing processes used in a document written by a group of authors: (1) the revision map, which summarises the text edits made at the paragraph level, over the time of writing. (2) the topic evolution chart, which uses probabilistic topic models, especially Latent Dirichlet Allocation (LDA) and its extension, DiffLDA, to extract topics and follow their evolution during the writing process. (3) the topic-based collaboration network, which allows a deeper analysis of topics in relation to author contribution and collaboration, using our novel algorithm DiffATM in conjunction with a DiffLDA-related technique. These models are evaluated to examine whether these automatically discovered topics accurately describe the evolution of writing processes. We illustrate how these visualisations are used with real documents written by groups of graduate students.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122033016","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: 75
An evaluation of policy frameworks for addressing ethical considerations in learning analytics 在学习分析中解决伦理问题的政策框架的评估
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460344
P. Prinsloo, Sharon Slade
{"title":"An evaluation of policy frameworks for addressing ethical considerations in learning analytics","authors":"P. Prinsloo, Sharon Slade","doi":"10.1145/2460296.2460344","DOIUrl":"https://doi.org/10.1145/2460296.2460344","url":null,"abstract":"Higher education institutions have collected and analysed student data for years, with their focus largely on reporting and management needs. A range of institutional policies exist which broadly set out the purposes for which data will be used and how data will be protected. The growing advent of learning analytics has seen the uses to which student data is put expanding rapidly. Generally though the policies setting out institutional use of student data have not kept pace with this change.\u0000 Institutional policy frameworks should provide not only an enabling environment for the optimal and ethical harvesting and use of data, but also clarify: who benefits and under what conditions, establish conditions for consent and the de-identification of data, and address issues of vulnerability and harm. A directed content analysis of the policy frameworks of two large distance education institutions shows that current policy frameworks do not facilitate the provision of an enabling environment for learning analytics to fulfil its promise.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126644690","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: 75
Formative assessment and learning analytics 形成性评估和学习分析
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460337
Dirk T. Tempelaar, A. Heck, H. Cuypers, H. V. D. Kooij, E. V. D. Vrie
{"title":"Formative assessment and learning analytics","authors":"Dirk T. Tempelaar, A. Heck, H. Cuypers, H. V. D. Kooij, E. V. D. Vrie","doi":"10.1145/2460296.2460337","DOIUrl":"https://doi.org/10.1145/2460296.2460337","url":null,"abstract":"Learning analytics seeks to enhance the learning process through systematic measurements of learning related data, and informing learners and teachers of the results of these measurements, so as to support the control of the learning process. Learning analytics has various sources of information, two main types being intentional and learner activity related metadata [1]. This contribution aims to provide a practical application of Shum and Crick's theoretical framework [1] of a learning analytics infrastructure that combines learning dispositions data with data extracted from computer-based, formative assessments. The latter data component is derived from one of the educational projects of ONBETWIST, part of the SURF program 'Testing and Test Driven Learning'.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"453 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127611773","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: 70
Epistemology, pedagogy, assessment and learning analytics 认识论，教育学，评估和学习分析
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460312
Simon Knight, S. B. Shum, K. Littleton
{"title":"Epistemology, pedagogy, assessment and learning analytics","authors":"Simon Knight, S. B. Shum, K. Littleton","doi":"10.1145/2460296.2460312","DOIUrl":"https://doi.org/10.1145/2460296.2460312","url":null,"abstract":"There is a well-established literature examining the relationships between epistemology (the nature of knowledge), pedagogy (the nature of learning and teaching), and assessment. Learning Analytics (LA) is a new assessment technology and should engage with this literature since it has implications for when and why different LA tools might be deployed. This paper discusses these issues, relating them to an example construct, epistemic beliefs -- beliefs about the nature of knowledge -- for which analytics grounded in pragmatic, sociocultural theory might be well placed to explore. This example is particularly interesting given the role of epistemic beliefs in the everyday knowledge judgements students make in their information processing. Traditional psychological approaches to measuring epistemic beliefs have parallels with high stakes testing regimes; this paper outlines an alternative LA for epistemic beliefs which might be readily applied to other areas of interest. Such sociocultural approaches afford opportunity for engaging LA directly in high quality pedagogy.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132733487","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
An evaluation of learning analytics to identify exploratory dialogue in online discussions 学习分析的评估，以确定在线讨论中的探索性对话
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460313
Rebecca Ferguson, Zhongyu Wei, Yulan He, S. B. Shum
{"title":"An evaluation of learning analytics to identify exploratory dialogue in online discussions","authors":"Rebecca Ferguson, Zhongyu Wei, Yulan He, S. B. Shum","doi":"10.1145/2460296.2460313","DOIUrl":"https://doi.org/10.1145/2460296.2460313","url":null,"abstract":"Social learning analytics are concerned with the process of knowledge construction as learners build knowledge together in their social and cultural environments. One of the most important tools employed during this process is language. In this paper we take exploratory dialogue, a joint form of co-reasoning, to be an external indicator that learning is taking place. Using techniques developed within the field of computational linguistics, we build on previous work using cue phrases to identify exploratory dialogue within online discussion. Automatic detection of this type of dialogue is framed as a binary classification task that labels each contribution to an online discussion as exploratory or non-exploratory. We describe the development of a self-training framework that employs discourse features and topical features for classification by integrating both cue-phrase matching and k-nearest neighbour classification. Experiments with a corpus constructed from the archive of a two-day online conference show that our proposed framework outperforms other approaches. A classifier developed using the self-training framework is able to make useful distinctions between the learning dialogue taking place at different times within an online conference as well as between the contributions of individual participants.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130301598","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: 46
Nanogenetic learning analytics: illuminating student learning pathways in an online fraction game 纳米遗传学习分析:在一个在线分数游戏中照亮学生的学习路径
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460328
Taylor Martin, Ani Aghababyan, Jay Pfaffman, J. Olsen, Stephanie Baker Peacock, Philip Janisiewicz, R. Phillips, C. Smith
{"title":"Nanogenetic learning analytics: illuminating student learning pathways in an online fraction game","authors":"Taylor Martin, Ani Aghababyan, Jay Pfaffman, J. Olsen, Stephanie Baker Peacock, Philip Janisiewicz, R. Phillips, C. Smith","doi":"10.1145/2460296.2460328","DOIUrl":"https://doi.org/10.1145/2460296.2460328","url":null,"abstract":"A working understanding of fractions is critical to student success in high school and college math. Therefore, an understanding of the learning pathways that lead students to this working understanding is important for educators to provide optimal learning environments for their students. We propose the use of microgenetic analysis techniques including data mining and visualizations to inform our understanding of the process by which students learn fractions in an online game environment. These techniques help identify important variables and classification algorithms to group students by their learning trajectories.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124547272","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: 18
Aggregating social and usage datasets for learning analytics: data-oriented challenges 为学习分析聚合社会和使用数据集:面向数据的挑战
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460345
K. Niemann, M. Wolpers, Giannis Stoitsis, Georgios Chinis, N. Manouselis
{"title":"Aggregating social and usage datasets for learning analytics: data-oriented challenges","authors":"K. Niemann, M. Wolpers, Giannis Stoitsis, Georgios Chinis, N. Manouselis","doi":"10.1145/2460296.2460345","DOIUrl":"https://doi.org/10.1145/2460296.2460345","url":null,"abstract":"Recent work has studied real-life social and usage datasets from educational applications, highlighting the opportunity to combine or merge them. It is expected that being able to put together different datasets from various applications will make it possible to support learning analytics of a much larger scale and across different contexts. We examine how this can be achieved from a practical perspective by carrying out a study that focuses on three real datasets. More specifically, we combine social data that has been collected from the users of three learning portals and reflect on how they should be handled. We start by studying the data types and formats that these portals use to represent and store social and usage data. Then we develop crosswalks between the different schemas, so that merged versions of the source datasets may be created. The results of this bottom-up, hands-on investigation reveal several interesting issues that need to be overcome before aggregated sets of social and usage data can be actually used to support learning analytics research or services.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128339153","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: 18
What can we learn from Facebook activity?: using social learning analytics to observe new media literacy skills 我们能从Facebook的活动中学到什么?:使用社会学习分析观察新媒体素养技能
International Conference on Learning Analytics and Knowledge Pub Date : 2013-04-08 DOI: 10.1145/2460296.2460323
June Ahn
{"title":"What can we learn from Facebook activity?: using social learning analytics to observe new media literacy skills","authors":"June Ahn","doi":"10.1145/2460296.2460323","DOIUrl":"https://doi.org/10.1145/2460296.2460323","url":null,"abstract":"Social media platforms such as Facebook are now a ubiquitous part of everyday life for many people. New media scholars posit that the participatory culture encouraged by social media gives rise to new forms of literacy skills that are vital to learning. However, there have been few attempts to use analytics to understand the new media literacy skills that may be embedded in an individual's participation in social media. In this paper, I collect raw activity data that was shared by an exploratory sample of Facebook users. I then utilize factor analysis and regression models to show how (a) Facebook members' online activity coalesce into distinct categories of social media behavior and (b) how these participatory behaviors correlate with and predict measures of new media literacy skills. The study demonstrates the use of analytics to understand the literacies embedded in people's social media activity. The implications speak to the potential of social learning analytics to identify and predict new media literacy skills from data streams in social media platforms.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131991536","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: 44
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