Proceedings of the 8th International Conference on Learning Analytics and Knowledge最新文献_第3页

Analytics-enabled teaching as design: reconceptualisation and call for research 作为设计的分析教学:重新概念化和对研究的呼吁

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170390

Sakinah S. J. Alhadad, K. Thompson, Simon Knight, Melinda J. Lewis, J. Lodge

{"title":"Analytics-enabled teaching as design: reconceptualisation and call for research","authors":"Sakinah S. J. Alhadad, K. Thompson, Simon Knight, Melinda J. Lewis, J. Lodge","doi":"10.1145/3170358.3170390","DOIUrl":"https://doi.org/10.1145/3170358.3170390","url":null,"abstract":"As a human-centred educational practice and field of research, learning analytics must account for key stakeholders in teaching and learning. The focus of this paper is on the role of institutions to support teachers to incorporate learning analytics into their practice by understanding the confluence of internal and external factors that influence what they do. In this paper, we reconceptualise `teaching as design' for `analytics-enabled teaching as design' to shape this discussion to allow for the consideration of external factors, such as professional learning or ethical considerations of student data, as well as personal considerations, such as data literacy and teacher beliefs and identities. In order to address the real-world challenges of progressing teachers' efficacy and capacity toward analytics-enabled teaching as design, we have placed the teacher - as a cognitive, social, and emotional being - at the center. In so doing, we discuss potential directions towards research for practice in elucidating underpinning factors of teacher inquiry in the process of authentic design.","PeriodicalId":437369,"journal":{"name":"Proceedings of the 8th International Conference on Learning Analytics and Knowledge","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134245085","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

Epistemic network analysis of students' longer written assignments as formative/summative evaluation 作为形成性/总结性评价的学生较长书面作业的认知网络分析

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170414

Simon Skov Fougt, Amanda Siebert-Evenstone, Brendan R. Eagan, Sara Tabatabai, Morten Misfeldt

引用次数: 12

Coenrollment networks and their relationship to grades in undergraduate education 本科共同招生网络及其与成绩的关系

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170373

Josh Gardner, Christopher A. Brooks

{"title":"Coenrollment networks and their relationship to grades in undergraduate education","authors":"Josh Gardner, Christopher A. Brooks","doi":"10.1145/3170358.3170373","DOIUrl":"https://doi.org/10.1145/3170358.3170373","url":null,"abstract":"In this paper, we evaluate the complete undergraduate coenrollment network over a decade of education at a large American public university. We provide descriptive properties of the network, demonstrating that the coenrollment networks evaluated follow power-law degree distributions similar to many other large-scale networks; that they reveal strong performance-based assortativity; and that network-based features can significantly improve GPA-based student performance predictors. We then implement a network-based, multi-view classification model to predict students' final course grades. In particular, we adapt a structural modeling approach from [19, 34], whereby we model the university-wide undergraduate coenrollment network as an undirected graph. We compare the performance of our predictor to traditional methods used for grade prediction in undergraduate university courses, and demonstrate that a multi-view ensembling approach outperforms both prior \"flat\" and network-based models for grade prediction across several classification metrics. These findings demonstrate the usefulness of combining diverse approaches in models of student success, and demonstrate specific network-based modeling strategies which are likely to be most effective for grade prediction.","PeriodicalId":437369,"journal":{"name":"Proceedings of the 8th International Conference on Learning Analytics and Knowledge","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123469951","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

Data-driven generation of rubric criteria from an educational programming environment 从教育编程环境中生成数据驱动的标题标准

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170399

Nicholas Diana, Michael Eagle, John C. Stamper, Shuchi Grover, M. Bienkowski, Satabdi Basu

引用次数: 9

Driving data storytelling from learning design 从学习设计中推动数据叙事

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170380

Vanessa Echeverría, Roberto Martínez Maldonado, Roger Granda, K. Chiluiza, C. Conati, S. B. Shum

引用次数: 45

The classroom as a dashboard: co-designing wearable cognitive augmentation for K-12 teachers 教室作为仪表盘:为K-12教师共同设计可穿戴认知增强设备

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170377

Kenneth Holstein, Gena Hong, Mera Tegene, B. McLaren, V. Aleven

{"title":"The classroom as a dashboard: co-designing wearable cognitive augmentation for K-12 teachers","authors":"Kenneth Holstein, Gena Hong, Mera Tegene, B. McLaren, V. Aleven","doi":"10.1145/3170358.3170377","DOIUrl":"https://doi.org/10.1145/3170358.3170377","url":null,"abstract":"When used in classrooms, personalized learning software allows students to work at their own pace, while freeing up the teacher to spend more time working one-on-one with students. Yet such personalized classrooms also pose unique challenges for teachers, who are tasked with monitoring classes working on divergent activities, and prioritizing help-giving in the face of limited time. This paper reports on the co-design, implementation, and evaluation of a wearable classroom orchestration tool for K-12 teachers: mixed-reality smart glasses that augment teachers' realtime perceptions of their students' learning, metacognition, and behavior, while students work with personalized learning software. The main contributions are: (1) the first exploration of the use of smart glasses to support orchestration of personalized classrooms, yielding design findings that may inform future work on real-time orchestration tools; (2) Replay Enactments: a new prototyping method for real-time orchestration tools; and (3) an in-lab evaluation and classroom pilot using a prototype of teacher smart glasses (Lumilo), with early findings suggesting that Lumilo can direct teachers' time to students who may need it most.","PeriodicalId":437369,"journal":{"name":"Proceedings of the 8th International Conference on Learning Analytics and Knowledge","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128028183","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: 79

Multi-institutional positioning test feedback dashboard for aspiring students: lessons learnt from a case study in flanders 面向有志学生的多机构定位测试反馈仪表板:从佛兰德斯案例研究中吸取的教训

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170419

Tom Broos, K. Verbert, G. Langie, C. Soom, T. Laet

{"title":"Multi-institutional positioning test feedback dashboard for aspiring students: lessons learnt from a case study in flanders","authors":"Tom Broos, K. Verbert, G. Langie, C. Soom, T. Laet","doi":"10.1145/3170358.3170419","DOIUrl":"https://doi.org/10.1145/3170358.3170419","url":null,"abstract":"Our work focuses on a multi-institutional implementation and evaluation of a Learning Analytics Dashboards (LAD) at scale, providing feedback to N=337 aspiring STEM (science, technology, engineering and mathematics) students participating in a region-wide positioning test before entering the study program. Study advisors were closely involved in the design and evaluation of the dashboard. The multi-institutional context of our case study requires careful consideration of external stakeholders and data ownership and portability issues, which gives shape to the technical design of the LAD. Our approach confirms students as active agents with data ownership, using an anonymous feedback code to access the LAD and to enable students to share their data with institutions at their discretion. Other distinguishing features of the LAD are the support for active content contribution by study advisors and LATEX type-setting of question item feedback to enhance visual recognizability. We present our lessons learnt from a first iteration in production.","PeriodicalId":437369,"journal":{"name":"Proceedings of the 8th International Conference on Learning Analytics and Knowledge","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127132495","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

An application of participatory action research in advising-focused learning analytics 参与式行动研究在以咨询为中心的学习分析中的应用

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170387

S. Fiorini, A. Sewell, Mathew Bumbalough, Pallavi Chauhan, Linda Shepard, George Rehrey, D. Groth

引用次数: 5

Classroom size, activity and attendance: scaling up drivers of learning space occupation 教室规模、活动和出勤率:扩大学习空间占用的驱动因素

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170401

Amelia Brennan, Christina Peace, Pablo Munguia

引用次数: 7

A generalized classifier to identify online learning tool disengagement at scale 一种广义分类器来识别在线学习工具的大规模脱离

Proceedings of the 8th International Conference on Learning Analytics and Knowledge Pub Date : 2018-03-07 DOI: 10.1145/3170358.3170370

Jacqueline L. Feild, N. Lewkow, Sean Burns, Karen Gebhardt

{"title":"A generalized classifier to identify online learning tool disengagement at scale","authors":"Jacqueline L. Feild, N. Lewkow, Sean Burns, Karen Gebhardt","doi":"10.1145/3170358.3170370","DOIUrl":"https://doi.org/10.1145/3170358.3170370","url":null,"abstract":"Student success, a major focus in higher education, in part, requires students to remain actively engaged in the required coursework. Identifying student disengagement, when a student stops completing coursework, at scale has been a continuing challenge for higher education due to the heterogeneity of traditional college courses. This research uses data from Connect by McGraw-Hill Education, a widely used online learning tool, to build a classifier to identify learning tool disengagement at scale. This classifier was trained and tested on four years of historical data, representing 4.5 million students in 175,000 courses, across 256 disciplines. Results show that the classifier is effective in identifying disengagement within the online learning tool against baselines, across time, and within and across disciplines. The classifier was also effective in identifying students at risk of disengaging from Connect and then earning unsuccessful grades in a pilot course for which the assignments in Connect were worth a relatively small portion of the overall course grade. Because Connect is widely used, this classifier is positioned to be a good tool for instructors and institutions to identify students at risk for disengagement from coursework. Instructors and institutions can use this information to design and implement interventions to improve engagement and improve student success at the institution in key courses.","PeriodicalId":437369,"journal":{"name":"Proceedings of the 8th International Conference on Learning Analytics and Knowledge","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131310310","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: 9