Proceedings of the 2nd International Conference on Learning Analytics and Knowledge最新文献_第2页

Monitoring student progress through their written "point of originality" 通过学生写的“原创性点”来监控他们的进步

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330653

J. Larusson, B. White

{"title":"Monitoring student progress through their written \"point of originality\"","authors":"J. Larusson, B. White","doi":"10.1145/2330601.2330653","DOIUrl":"https://doi.org/10.1145/2330601.2330653","url":null,"abstract":"This paper describes a new method for the objective evaluation of student work through the identification of original content in writing assignments. Using WordNet as a lexical reference, this process allows instructors to track how key phrases are employed and evolve over the course of a student's writing, and to automatically visualize the point at which the student's language first demonstrates original thought, phrased in their own, original words. The paper presents a case study where the analysis method was evaluated by analyzing co-blogging data from a reading and writing intensive undergraduate course. The evidence shows that the tool can be predictive of students' writing in a manner that correlates with their progress in the course and engagement in the technology-mediated activity. By visualizing otherwise subjective information in a way that is objectively intelligible, the goal is to provide educators with the ability to monitor student investment in concepts from the course syllabus, and to extend or modify the boundaries of the syllabus in anticipation of pre-existing knowledge or trends in interest. A tool of this sort can be of value particularly in larger gateway courses, where the sheer size of the class makes the ongoing evaluation of student progress a daunting if not otherwise impossible task.","PeriodicalId":311750,"journal":{"name":"Proceedings of the 2nd International Conference on Learning Analytics and Knowledge","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124468512","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: 11

Mining academic data to improve college student retention: an open source perspective 挖掘学术数据以提高大学生保留率:一个开源的视角

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330637

E. Lauría, Joshua D. Baron, Mallika Devireddy, V. Sundararaju, Sandeep M. Jayaprakash

引用次数: 83

Where learning analytics meets learning design 学习分析与学习设计在哪里相遇

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330609

Lori Lockyer, S. Dawson

引用次数: 26

Student success system: risk analytics and data visualization using ensembles of predictive models 学生成功系统:使用预测模型集合的风险分析和数据可视化

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330641

Alfred Essa, H. Ayad

{"title":"Student success system: risk analytics and data visualization using ensembles of predictive models","authors":"Alfred Essa, H. Ayad","doi":"10.1145/2330601.2330641","DOIUrl":"https://doi.org/10.1145/2330601.2330641","url":null,"abstract":"We propose a novel design of a Student Success System (S3), a holistic analytical system for identifying and treating at-risk students. S3 synthesizes several strands of risk analytics: the use of predictive models to identify academically at-risk students, the creation of data visualizations for reaching diagnostic insights, and the application of a case-based approach for managing interventions. Such a system poses numerous design, implementation, and research challenges. In this paper we discuss a core research challenge for designing early warning systems such as S3. We then propose our approach for meeting that challenge. A practical implementation of an student risk early warning system, utilizing predictive models, must meet two design criteria: a) the methodology for generating predictive models must be flexible to allow generalization from one context to another; b) the underlying mechanism of prediction should be easily interpretable by practitioners whose end goal is to design meaningful interventions on behalf of students. Our proposed solution applies an ensemble method for predictive modeling using a strategy of decomposition. Decomposition provides a flexible technique for generating and generalizing predictive models across different contexts. Decomposition into interpretable semantic units, when coupled with data visualizations and case management tools, allows practitioners, such as instructors and advisors, to build a bridge between prediction and intervention.","PeriodicalId":311750,"journal":{"name":"Proceedings of the 2nd International Conference on Learning Analytics and Knowledge","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129594166","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: 101

Using an instructional expert to mediate the locus of control in adaptive e-learning systems 运用教学专家调解自适应电子学习系统的控制点

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330626

Christopher A. Brooks, J. Greer, C. Gutwin

引用次数: 4

Learning analytics: challenges, paradoxes and opportunities for mega open distance learning institutions 学习分析:大型远程开放教育机构的挑战、悖论和机遇

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330635

P. Prinsloo, Sharon Slade, F. Galpin

{"title":"Learning analytics: challenges, paradoxes and opportunities for mega open distance learning institutions","authors":"P. Prinsloo, Sharon Slade, F. Galpin","doi":"10.1145/2330601.2330635","DOIUrl":"https://doi.org/10.1145/2330601.2330635","url":null,"abstract":"Despite all the research on student retention and success since the first conceptual mappings of student success e.g. Spady [12], there have not been equal impacts on the rates of both student success and retention. To realise the potential of learning analytics to impact on student retention and success, mega open distance learning (ODL) institutions face a number of challenges, paradoxes and opportunities. For the purpose of this paper we critique a 'closed' view of learning analytics as focusing only on data produced by students' interactions with institutions of higher learning. Students are not the only actors in their learning journeys and it would seem crucial that learning analytics also includes the impacts of all stakeholders on students' learning journeys in order to increase the success of students' learning. As such the notion of 'Thirdspace' as used by cultural, postmodern and identity theorists provide a useful heuristic to map the challenges and opportunities, but also the paradoxes of learning analytics and its potential impact on student success and retention. This paper explores some of these challenges, paradoxes and opportunities with reference to two mega ODL institutions namely the Open University in the UK (OU) and the University of South Africa (Unisa). Although these two institutions share a number of characteristics, there are also some major and important differences between them. We explore some of the shared challenges, paradoxes and opportunities learning analytics offer in the context of these two institutions.","PeriodicalId":311750,"journal":{"name":"Proceedings of the 2nd International Conference on Learning Analytics and Knowledge","volume":"2003 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114129427","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: 33

Sherpa: increasing student success with a recommendation engine 夏尔巴:通过推荐引擎提高学生的成功率

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330625

Robert Bramucci, J. Gaston

引用次数: 22

Learn-B: a social analytics-enabled tool for self-regulated workplace learning Learn-B:一个社会分析支持的工具，用于自我调节的工作场所学习

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330632

Melody Siadaty, D. Gašević, J. Jovanović, Nikola Milikić, Z. Jeremic, Liaqat Ali, Aleksandar Giljanovic, M. Hatala

引用次数: 25

Bridging the gap from knowledge to action: putting analytics in the hands of academic advisors 弥合从知识到行动的差距:将分析交到学术顾问手中

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330647

Steven Lonn, Andrew E. Krumm, R. J. Waddington, Stephanie D. Teasley

引用次数: 47

Predicting failure: a case study in co-blogging 预测失败:合作博客的案例研究

Proceedings of the 2nd International Conference on Learning Analytics and Knowledge Pub Date : 2012-04-29 DOI: 10.1145/2330601.2330665

Bjorn Levi Gunnarsson, R. Alterman

引用次数: 16