Proceedings of the Tenth International Conference on Learning Analytics & Knowledge最新文献

Perceptions and expectations about learning analytics from a brazilian higher education institution 巴西高等教育机构对学习分析的看法与期望

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375478

Taciana Pontual Falcão, R. F. Mello, R. Rodrigues, J. Diniz, Yi-Shan Tsai, D. Gašević

{"title":"Perceptions and expectations about learning analytics from a brazilian higher education institution","authors":"Taciana Pontual Falcão, R. F. Mello, R. Rodrigues, J. Diniz, Yi-Shan Tsai, D. Gašević","doi":"10.1145/3375462.3375478","DOIUrl":"https://doi.org/10.1145/3375462.3375478","url":null,"abstract":"Several tools to support learning processes based on educational data have emerged from research on Learning Analytics (LA) in the last few years. These tools aim to support students and instructors in daily activities, and academic managers in making institutional decisions. Although the adoption of LA tools is spreading, the field still needs to deepen the understanding of the contexts where learning takes place, and of the views of the stakeholders involved in implementing and using these tools. In this sense, the SHEILA framework proposes a set of instruments to perform a detailed analysis of the expectations and needs of different stakeholders in higher education institutions, regarding the adoption of LA. Moreover, there is a lacuna in research on stakeholders' expectations from LA outside the Global North. Therefore, this paper reports on the findings of the application of interviews and focus groups, based on the SHEILA framework, with students and teaching staff from a Brazilian public university, to investigate their perceptions of the potential benefits and risks of using LA in higher education in the country. Findings indicate that there is a high interest in using LA for improving the learning experience, in particular, being able to provide personalized feedback, to adapt teaching practices to students' needs, and to make evidence-based pedagogical decisions. From the analysis of these perspectives, we point to opportunities for using LA in Brazilian higher education.","PeriodicalId":355800,"journal":{"name":"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123756685","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: 17

Applying prerequisite structure inference to adaptive testing 前提结构推理在自适应测试中的应用

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375541

S. Saarinen, Evan Cater, M. Littman

引用次数: 2

How patterns of students dashboard use are related to their achievement and self-regulatory engagement 学生使用仪表板的模式如何与他们的成就和自我监管参与相关

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375472

Fatemeh Salehian Kia, Stephanie D. Teasley, M. Hatala, S. Karabenick, Matthew Kay

{"title":"How patterns of students dashboard use are related to their achievement and self-regulatory engagement","authors":"Fatemeh Salehian Kia, Stephanie D. Teasley, M. Hatala, S. Karabenick, Matthew Kay","doi":"10.1145/3375462.3375472","DOIUrl":"https://doi.org/10.1145/3375462.3375472","url":null,"abstract":"The aim of student-facing dashboards is to support learning by providing students with actionable information and promoting self-regulated learning. We created a new dashboard design aligned with SRL theory, called MyLA, to better understand how students use a learning analytics tool. We conducted sequence analysis on students' interactions with three different visualizations in the dashboard, implemented in a LMS, for a large number of students (860) in ten courses representing different disciplines. To evaluate different students' experiences with the dashboard, we computed chi-squared tests of independence on dashboard users (52%) to find frequent patterns that discriminate students by their differences in academic achievement and self-regulated learning behaviors. The results revealed discriminating patterns in dashboard use among different levels of academic achievement and self-regulated learning, particularly for low achieving students and high self-regulated learners. Our findings highlight the importance of differences in students' experience with a student-facing dashboard, and emphasize that one size does not fit all in the design of learning analytics tools.","PeriodicalId":355800,"journal":{"name":"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130673404","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: 20

Supporting actionable intelligence: reframing the analysis of observed study strategies 支持可操作的情报:重构观察到的学习策略的分析

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375474

J. Jovanović, S. Dawson, Srécko Joksimovíc, George Siemens

{"title":"Supporting actionable intelligence: reframing the analysis of observed study strategies","authors":"J. Jovanović, S. Dawson, Srécko Joksimovíc, George Siemens","doi":"10.1145/3375462.3375474","DOIUrl":"https://doi.org/10.1145/3375462.3375474","url":null,"abstract":"Models and processes developed in learning analytics research are increasing in sophistication and predictive power. However, the ability to translate analytic findings to practice remains problematic. This study aims to address this issue by establishing a model of learner behaviour that is both predictive of student course performance, and easily interpreted by instructors. To achieve this aim, we analysed fine grained trace data (from 3 offerings of an undergraduate online course, N=1068) to establish a comprehensive set of behaviour indicators aligned with the course design. The identified behaviour patterns, which we refer to as observed study strategies, proved to be associated with the student course performance. By examining the observed strategies of high and low performers throughout the course, we identified prototypical pathways associated with course success and failure. The proposed model and approach offers valuable insights for the provision of process-oriented feedback early in the course, and thus can aid learners in developing their capacity to succeed online.","PeriodicalId":355800,"journal":{"name":"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123592404","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

Is faster better?: a study of video playback speed 越快越好吗?:视频播放速度的研究

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375466

David Lang, Guanling Chen, Kathy Mirzaei, A. Paepcke

引用次数: 19

Peeking through the classroom window: a detailed data-driven analysis on the usage of a curriculum integrated math game in authentic classrooms 透过教室的窗户窥视:对真实课堂中课程整合数学游戏使用情况的详细数据驱动分析

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375525

Preya Shabrina, Ruth Okoilu Akintunde, Mehak Maniktala, T. Barnes, Collin Lynch, Teomara Rutherford

引用次数: 3

Learning analytics challenges: trade-offs, methodology, scalability 学习分析的挑战:权衡、方法、可扩展性

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375463

Radek Pelánek

引用次数: 8

Towards automatic content analysis of social presence in transcripts of online discussions 面向在线讨论文本中社会存在的自动内容分析

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375495

Maverick Andre Dionisio Ferreira, V. Rolim, R. F. Mello, R. Lins, Guanliang Chen, D. Gašević

{"title":"Towards automatic content analysis of social presence in transcripts of online discussions","authors":"Maverick Andre Dionisio Ferreira, V. Rolim, R. F. Mello, R. Lins, Guanliang Chen, D. Gašević","doi":"10.1145/3375462.3375495","DOIUrl":"https://doi.org/10.1145/3375462.3375495","url":null,"abstract":"This paper presents an approach to automatic labeling of the content of messages in online discussion according to the categories of social presence. To achieve this goal, the proposed approach is based on a combination of traditional text mining features and word counts extracted with the use of established linguistic frameworks (i.e., LIWC and Coh-metrix). The best performing classifier obtained 0.95 and 0.88 for accuracy and Cohen's kappa, respectively. This paper also provides some theoretical insights into the nature of social presence by looking at the classification features that were most relevant for distinguishing between the different categories. Finally, this study adopted epistemic network analysis to investigate the structural construct validity of the automatic classification approach. Namely, the analysis showed that the epistemic networks produced based on messages manually and automatically coded produced nearly identical results. This finding thus produced evidence of the structural validity of the automatic approach.","PeriodicalId":355800,"journal":{"name":"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116461188","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: 25

Intergroup and interpersonal forum positioning in shared-thread and post-reply networks 群际和人际论坛在分享和回复网络中的定位

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375533

Oleksandra Poquet, J. Jovanović

{"title":"Intergroup and interpersonal forum positioning in shared-thread and post-reply networks","authors":"Oleksandra Poquet, J. Jovanović","doi":"10.1145/3375462.3375533","DOIUrl":"https://doi.org/10.1145/3375462.3375533","url":null,"abstract":"Network analysis has become a major approach for analysing social learning, used to capture learner positioning in online forum networks. LA research investigated the association between positioning in forum networks with academic performance and discourse quality, the latter two serving as proxies for learning. However, the research findings have been inconsistent, in part due to the discrepancies in the adopted approaches to network construction. Yet, it is still unclear how online forum networks should be modelled to assure that the learners' network positioning is properly captured. To address this gap, the current study explored if some existing approaches to network construction may complement each other and thus offer richer insights. In particular, we hypothesised that the post-reply learner network could represent interpersonal positioning, whereas the network based on co-participation in discussion threads could encapsulate intergroup positioning. The study used learner social interaction data from a large edX MOOC forum to examine the relationship between these two kinds of network positioning. The results suggest that intergroup and interpersonal positioning may capture different aspects of social learning, potentially related to different learning outcomes. We find that although interpersonal and intergroup positioning indicators covary, these measures are not congruent for some 37% of forum posters. Network coevolution analysis also reveals an interdependent relationship between the intergroup and interpersonal centrality in a forum network. Co-occurrence of learners in a discussion thread prior to direct exchanges is predictive of a direct post-reply interaction at a later stage of the course, and vice-versa, suggesting that intergroup positioning is a precursor of direct communication. The study contributes to the discussion around the definition of learner forum positioning in learning analytics, and validated approaches towards measuring it.","PeriodicalId":355800,"journal":{"name":"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132079674","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: 15

Prediction of students' assessment readiness in online learning environments: the sequence matters 在线学习环境中学生评估准备的预测:顺序问题

Proceedings of the Tenth International Conference on Learning Analytics & Knowledge Pub Date : 2020-03-23 DOI: 10.1145/3375462.3375468

D. Malekian, J. Bailey, G. Kennedy

{"title":"Prediction of students' assessment readiness in online learning environments: the sequence matters","authors":"D. Malekian, J. Bailey, G. Kennedy","doi":"10.1145/3375462.3375468","DOIUrl":"https://doi.org/10.1145/3375462.3375468","url":null,"abstract":"Online learning environments are now pervasive in higher education. While not exclusively the case, in these environments, there is often modest teacher presence, and students are provided with access to a range of learning, assessment, and support materials. This places pressure on their study skills, including self-regulation. In this context, students may access assessment material without being fully prepared. This may result in limited success and, in turn, raise a significant risk of disengagement. Therefore, if the prediction of students' assessment readiness was possible, it could be used to assist educators or online learning environments to postpone assessment tasks until students were deemed \"ready\". In this study, we employed a range of machine learning techniques with aggregated and sequential representations of students' behaviour in a Massive Open Online Course (MOOC), to predict their readiness for assessment tasks. Based on our results, it was possible to successfully predict students' readiness for assessment tasks, particularly if the sequential aspects of behaviour were represented in the model. Additionally, we used sequential pattern mining to investigate which sequences of behaviour differed between high or low level of performance in assessments. We found that a high level of performance had the most sequences related to viewing and reviewing the lecture materials, whereas a low level of performance had the most sequences related to successive failed submissions for an assessment. Based on the findings, implications for supporting specific behaviours to improve learning in online environments are discussed.","PeriodicalId":355800,"journal":{"name":"Proceedings of the Tenth International Conference on Learning Analytics & Knowledge","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130243234","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: 14