J. Learn. Anal.最新文献_第6页

A Learning Analytics Approach to Monitoring the Quality of Online One-to-One Tutoring 监测在线一对一辅导质量的学习分析方法

J. Learn. Anal. Pub Date : 2021-10-25 DOI: 10.35542/osf.io/qfh7z

M. Cukurova, Madiha Khan-Galaria, E. Millán, R. Luckin

{"title":"A Learning Analytics Approach to Monitoring the Quality of Online One-to-One Tutoring","authors":"M. Cukurova, Madiha Khan-Galaria, E. Millán, R. Luckin","doi":"10.35542/osf.io/qfh7z","DOIUrl":"https://doi.org/10.35542/osf.io/qfh7z","url":null,"abstract":"One-to-one online tutoring provided by human tutors can improve students’ learning outcomes. However, monitoring the quality of such tutoring is a significant challenge. In this paper, we propose a learning analytics approach for monitoring online one-to-one tutoring quality. The approach analyses teacher behaviours and classifies tutoring sessions into those that are effective and those that are not effective. More specifically, we use sequential behaviour pattern mining to analyse tutoring sessions using the CM-SPAM algorithm and classify tutoring sessions into effective and less effective using the J-48 and JRIP decision tree classifiers. To show the feasibility of the approach, we analysed data from 2250 minutes of online one-to-one primary Maths tutoring sessions with 44 tutors from 8 schools. The results showed that the approach can classify tutors’ effectiveness with high accuracy (F measures of 0.89 and 0.98 were achieved). The results also showed that effective tutors present significantly more frequent hint provision and proactive planning behaviours than their less effective colleagues in these online one-to-one sessions. Furthermore, effective tutors sequence their monitoring actions with appropriate pauses and initiations of students’ self-correction behaviours. We conclude that the proposed approach is feasible to monitor the quality of online one-to-one primary Maths tutoring sessions.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116892088","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: 7

More Than Figures on Your Laptop: (Dis)trustful Implementation of Learning Analytics 不仅仅是笔记本电脑上的数字:学习分析的可信实现

J. Learn. Anal. Pub Date : 2021-10-13 DOI: 10.18608/jla.2021.7379

Yi-Shan Tsai, A. Whitelock-Wainwright, D. Gašević

引用次数: 14

Are We Living In LA (P)LA Land? Reporting on the Practice of 30 STEM Tutors in their Use of a Learning Analytics Implementation at the Open University 我们生活在洛杉矶吗?报告30名STEM导师在开放大学使用学习分析实施的实践

J. Learn. Anal. Pub Date : 2021-10-01 DOI: 10.18608/jla.2021.7261

Tom Olney, S. Walker, Carlton Wood, Anactoria Clarke

{"title":"Are We Living In LA (P)LA Land? Reporting on the Practice of 30 STEM Tutors in their Use of a Learning Analytics Implementation at the Open University","authors":"Tom Olney, S. Walker, Carlton Wood, Anactoria Clarke","doi":"10.18608/jla.2021.7261","DOIUrl":"https://doi.org/10.18608/jla.2021.7261","url":null,"abstract":"Most higher education institutions view their increasing use of learning analytics as having significant potential to improve student academic achievement, retention outcomes, and learning and teaching practice but the realization of this potential remains stubbornly elusive. While there is an abundance of published research on the creation of visualizations, dashboards, and predictive models, there has been little work done to explore the impact of learning analytics on the actual practice of teachers. Through the lens of social informatics (an approach that views the users of technologies as active social actors whose technological practices constitute a wider socio-technical system) this qualitative study reports on an investigation into the practice of 30 tutors in the STEM faculty at Europe’s largest distance learning organization, The Open University UK (OU). When asked to incorporate learning analytics (including predictive learning analytics) contained in the Early Alert Indicator (EAI) dashboard during the 2017–2018 academic year into their practice, we found that tutors interacted with this dashboard in certain unanticipated ways and developed three identifiable “shadow practices”.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125338671","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: 4

Can Strategic Behaviour Facilitate Confusion Resolution? The Interplay Between Confusion and Metacognitive Strategies in Betty's Brain 策略行为能促进解决困惑吗?贝蒂大脑中混淆与元认知策略的相互作用

J. Learn. Anal. Pub Date : 2021-10-01 DOI: 10.18608/jla.2021.7161

Yingbin Zhang, L. Paquette, R. Baker, Jaclyn L. Ocumpaugh, Nigel Bosch, Gautam, Biswas, Anabil Munshi

引用次数: 3

Analyzing and Visualizing Learning Data: A System Designer's Perspective 分析和可视化学习数据:系统设计师的视角

J. Learn. Anal. Pub Date : 2021-09-03 DOI: 10.18608/jla.2021.7345

Radek Pelánek

引用次数: 6

De-identification is Insufficient to Protect Student Privacy, or - What Can a Field Trip Reveal? 去身份识别不足以保护学生隐私，或者——实地考察能揭示什么?

J. Learn. Anal. Pub Date : 2021-09-03 DOI: 10.18608/jla.2021.7353

Elad Yacobson, Orly Fuhrman, S. Hershkovitz, Giora Alexandron

引用次数: 7

ADA for IBL: Lessons Learned in Aligning Learning Design and Analytics for Inquiry-Based Learning Orchestration 面向IBL的ADA:为基于查询的学习编排调整学习设计和分析的经验教训

J. Learn. Anal. Pub Date : 2021-09-03 DOI: 10.18608/jla.2021.7357

M. Rodríguez-Triana, L. Prieto, Y. Dimitriadis, T. Jong, D. Gillet

{"title":"ADA for IBL: Lessons Learned in Aligning Learning Design and Analytics for Inquiry-Based Learning Orchestration","authors":"M. Rodríguez-Triana, L. Prieto, Y. Dimitriadis, T. Jong, D. Gillet","doi":"10.18608/jla.2021.7357","DOIUrl":"https://doi.org/10.18608/jla.2021.7357","url":null,"abstract":"Orchestrating technology-enhanced learning is a difficult task, especially in demanding pedagogical approaches like inquiry-based learning (IBL). To foster effective teacher adoption, both the complexity of designing IBL activities and the uncertainty about the student learning path during enactment need to be addressed. Previous research suggests that aligning learning design and learning analytics can be an effective way to provide such orchestration support. This paper reports on a design-based research (DBR) project to explore teachers’ orchestration needs in Go-Lab (a technological ecosystem for IBL used by thousands of primary and secondary school teachers around the world), and on how solutions that align learning design and analytics can fulfill such needs. The analysis of data from multiple events (including surveys, case studies, workshops with teachers, and platform usage analyses) led to a catalogue of IBL orchestration needs that can be tackled by aligning learning design and analytics, as well as a list of guidelines for technology development aiming to support IBL orchestration. These two contributions can support the creation of future learning analytics–enhanced IBL environments that are both pedagogically grounded and usable by teachers in authentic settings.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124511912","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: 6

How Teacher Characteristics Relate to How Teachers Use Dashboards: Results From Two Case Studies in K-12 教师特征与教师如何使用仪表板的关系:来自K-12两个案例研究的结果

J. Learn. Anal. Pub Date : 2021-09-03 DOI: 10.18608/jla.2021.7325

A. V. Leeuwen, C. K. Campen, I. Molenaar, N. Rummel

{"title":"How Teacher Characteristics Relate to How Teachers Use Dashboards: Results From Two Case Studies in K-12","authors":"A. V. Leeuwen, C. K. Campen, I. Molenaar, N. Rummel","doi":"10.18608/jla.2021.7325","DOIUrl":"https://doi.org/10.18608/jla.2021.7325","url":null,"abstract":"Teacher dashboards are a specific form of analytics in which visual displays provide teachers with information about their students; for example, concerning student progress and performance on tasks during lessons or lectures. In the present paper, we focus on the role of teacher dashboards in the context of teacher decision-making in K–12 education. There is large variation in teacher dashboard use in the classroom, which could be explained by teacher characteristics. Therefore, we investigate the role of teacher characteristics — such as experience, age, gender, and self-efficacy — in how teachers use dashboards. More specifically, we present two case studies to understand how diversity in teacher dashboard use is related to teacher characteristics. Surprisingly, in both case studies, teacher characteristics were not associated with dashboard use. Based on our findings, we propose an initial framework to understand what contributes to diversity of dashboard use. This framework might support future research to attribute diversity in dashboard use. This paper should be seen as a first step in examining the role of teacher characteristics in dashboard use in K–12 education.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117102684","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

Learning Analytics for Primary and Secondary Schools 《中小学学习分析》

J. Learn. Anal. Pub Date : 2021-09-03 DOI: 10.18608/jla.2021.7543

Vitomir Kovanovíc, Claudia Mazziotti, J. Lodge

引用次数: 19

Game-Based Learning Analytics for Supporting Adolescents' Reflection 支持青少年反思的游戏学习分析

J. Learn. Anal. Pub Date : 2021-09-03 DOI: 10.18608/jla.2021.7371

Elizabeth B. Cloude, Daniel Carpenter, Daryn A. Dever, R. Azevedo, James C. Lester

{"title":"Game-Based Learning Analytics for Supporting Adolescents' Reflection","authors":"Elizabeth B. Cloude, Daniel Carpenter, Daryn A. Dever, R. Azevedo, James C. Lester","doi":"10.18608/jla.2021.7371","DOIUrl":"https://doi.org/10.18608/jla.2021.7371","url":null,"abstract":"Reflection is critical for adolescents’ problem solving and learning in game-based learning environments (GBLEs). Yet challenges exist in the literature because most studies lack a theoretical perspective and clear operational definition to inform how and when reflection should be scaffolded during game-based learning. In this paper, we address these issues by studying the quantity and quality of 120 adolescents’ written reflections and their relation to their learning and problem solving with Crystal Island, a GBLE. Specifically, we (1) define reflection and how it relates to skill and knowledge acquisition; (2) review studies examining reflection and its relation to problem solving and learning with emerging technologies; and (3) provide direction for building reflection prompts into GBLEs that are aligned with the learning goals built into the learning session (e.g., learn about microbiology versus successfully solve a problem) to maximize adolescents’ reflection, learning, and performance. Overall, our findings emphasize how important it is to examine not only the quantity of reflection but also the depth of written reflection as it relates to specific learning goals. We discuss the implications of using game-learning analytics to guide instructional decision making in the classroom.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129305966","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: 13