J. Learn. Anal.最新文献_第4页

Insights of Instructors and Advisors into an Early Prediction Model for Non-Thriving Students 教师和顾问对不成功学生早期预测模型的见解

J. Learn. Anal. Pub Date : 2022-06-21 DOI: 10.18608/jla.2022.7509

A. Hershkovitz, A. Ambrose

引用次数: 3

Analyzing Students' Problem-Solving Sequences: A Human-in-the-Loop Approach 分析学生解决问题的顺序:人在循环的方法

J. Learn. Anal. Pub Date : 2022-06-04 DOI: 10.18608/jla.2022.7465

Erica Kleinman, Murtuza N. Shergadwala, Magy Seif El-Nasr, Zhaoqing Teng, Jennifer Villareale, Andy Bryant, Jichen Zhu

引用次数: 2

Learning Analytics on the African Continent: An Emerging Research Focus and Practice 学习分析在非洲大陆:一个新兴的研究焦点和实践

J. Learn. Anal. Pub Date : 2022-06-04 DOI: 10.18608/jla.2022.7539

P. Prinsloo, Rogers Kaliisa

{"title":"Learning Analytics on the African Continent: An Emerging Research Focus and Practice","authors":"P. Prinsloo, Rogers Kaliisa","doi":"10.18608/jla.2022.7539","DOIUrl":"https://doi.org/10.18608/jla.2022.7539","url":null,"abstract":"While learning analytics (LA) has been highlighted as a field aiming to address systemic equity and quality issues within educational systems between and within regions, to date, its adoption is predominantly in the Global North. Since the Society for Learning Analytics Research (SoLAR) aspires to be international in reach and relevance, and to increase the diversity and inclusivity of the SoLAR community, it is pertinent to look at learning analytics use in higher education institutions in Africa. This paper reports the first scoping review of research in the field of LA conducted on the African continent. The coding and analysis show that LA research is still in its infancy on the African continent with only 15 studies, overwhelmingly from South Africa. The study also revealed several challenges, such as limited technical support and access to LMSs, the limited visibility of African scholars at SoLAR events and publication venues, and the limited focus on interventions that involve stakeholders. The article concludes with several propositions and provocations to advance the adoption of LA in Africa and open up space for critical conversations about the potential of learning analytics in contexts with characteristics different than those found in the Global North.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125637617","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: 2

When Do Learners Study?: An Analysis of the Time-of-Day and Weekday-Weekend Usage Patterns of Learning Management Systems from Mobile and Computers in Blended Learning 学习者什么时候学习?混合学习中移动和计算机学习管理系统的时间-工作日-周末使用模式分析

J. Learn. Anal. Pub Date : 2022-05-26 DOI: 10.18608/jla.2022.6697

Varshita Sher, M. Hatala, D. Gašević

{"title":"When Do Learners Study?: An Analysis of the Time-of-Day and Weekday-Weekend Usage Patterns of Learning Management Systems from Mobile and Computers in Blended Learning","authors":"Varshita Sher, M. Hatala, D. Gašević","doi":"10.18608/jla.2022.6697","DOIUrl":"https://doi.org/10.18608/jla.2022.6697","url":null,"abstract":"Recent advances in smart devices and online technologies have facilitated the emergence of ubiquitous learning environments for participating in different learning activities. This poses an interesting question about modality access, i.e., what students are using each platform for and at what time of day. In this paper, we present a log-based exploratory study on learning management system (LMS) use comparing three different modalities—computer, mobile, and tablet—based on the aspect of time. Our objective is to better understand how and to what extent learning sessions via mobiles and tablets occur at different times throughout the day compared to computer sessions. The complexity of the question is further intensified because learners rarely use a single modality for their learning activities but rather prefer a combination of two or more. Thus, we check the associations between patterns of modality usage and time of day as opposed to the counts of modality usage and time of day. The results indicate that computer-dominant learners are similar to limited-computer learners in terms of their session-time distribution, while intensive learners show completely different patterns. For all students, sessions on mobile devices are more frequent in the afternoon, while the proportion of computer sessions was higher at night. On comparison of these time-of-day preferences with respect to modalities on weekdays and weekends, they were found consistent for computer-dominant and limited-computer learners only. We demonstrate the implication of this research for enhancing contextual profiling and subsequently improving the personalization of learning systems such that personalized notification systems can be integrated with LMSs to deliver notifications to students at appropriate times.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134142740","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: 3

A Partnership-Based Approach to Operationalizing Learning Behaviours Using Event Data 基于伙伴关系的使用事件数据操作学习行为的方法

J. Learn. Anal. Pub Date : 2022-05-25 DOI: 10.18608/jla.2022.6751

Andrew E. Krumm, H. Everson, J. Neisler

引用次数: 3

Developing a Code of Practice for Using Data in Wellbeing Support 制定在福利支持中使用数据的行为准则

J. Learn. Anal. Pub Date : 2022-05-22 DOI: 10.18608/jla.2022.7533

A. Cormack, D. Reeve

{"title":"Developing a Code of Practice for Using Data in Wellbeing Support","authors":"A. Cormack, D. Reeve","doi":"10.18608/jla.2022.7533","DOIUrl":"https://doi.org/10.18608/jla.2022.7533","url":null,"abstract":"With student and staff wellbeing a growing concern, several authors have asked whether existing data might help institutions provide better support. By analogy with the established field of Learning Analytics, this might involve identifying causes of stress, improving access to information for those who need it, suggesting options, providing rapid feedback, even early warning of problems. But just investigating the possibility of such uses can create significant risks for individuals: feelings of creepiness or surveillance making wellbeing worse, inappropriate data visibility destroying trust, assessments or interventions becoming self-fulfilling prophecies. To help institutions decide whether and how to explore this area, and to reassure individuals that this is being done safely, we propose a Wellbeing Analytics Code of Practice. This starts from an existing Learning Analytics Code, confirms that its concerns and mitigations remain relevant, and adds additional safeguards and tools for the wellbeing context. These are derived from a detailed analysis of European and UK data protection law, extracting all rules and safeguards mentioned in relation to health data. We also develop context-specific tools for managing risk and evaluating data sources. Early feedback suggests that these documents will indeed increase confidence that this important area can be safely explored.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128054133","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: 1

The Curious Case of Centrality Measures: A Large-Scale Empirical Investigation 中心性测度的奇特案例:一项大规模实证调查

J. Learn. Anal. Pub Date : 2022-03-11 DOI: 10.18608/jla.2022.7415

Mohammed Saqr, Sonsoles López-Pernas

{"title":"The Curious Case of Centrality Measures: A Large-Scale Empirical Investigation","authors":"Mohammed Saqr, Sonsoles López-Pernas","doi":"10.18608/jla.2022.7415","DOIUrl":"https://doi.org/10.18608/jla.2022.7415","url":null,"abstract":"There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by single-course case studies that have yielded inconclusive results regarding the consistency and suitability of centrality measures as indicators of academic achievement. Therefore, large-scale studies are needed to overcome the multiple limitations of existing research (limited datasets, selective and reporting bias, as well as limited statistical power). This study aims to empirically test and verify the role of centrality measures as indicators of success in collaborative learning. For this purpose, we attempted to reproduce the most commonly used centrality measures in the literature in all the courses of an institution over five years of education. The study included a large dataset (n=3,277) consisting of 69 course offerings, with similar pedagogical underpinnings, using meta-analysis as a method to pool the results of different courses. Our results show that degree and eigenvector centrality measures can be a consistent indicator of performance in collaborative settings. Betweenness and closeness centralities yielded uncertain predictive intervals and were less likely to replicate. Our results have shown moderate levels of heterogeneity, indicating some diversity of the results comparable to single laboratory replication studies.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127040258","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

Exploring the Utility of Social-Network-Derived Collaborative Opportunity Temperature Readings for Informing Design and Research of Large-Group Immersive Learning Environments 探索社会网络衍生的协作机会温度读数对大群体沉浸式学习环境的设计和研究的实用性

J. Learn. Anal. Pub Date : 2022-03-11 DOI: 10.18608/jla.2022.7419

Aditi Mallavarapu, L. Lyons, S. Uzzo

{"title":"Exploring the Utility of Social-Network-Derived Collaborative Opportunity Temperature Readings for Informing Design and Research of Large-Group Immersive Learning Environments","authors":"Aditi Mallavarapu, L. Lyons, S. Uzzo","doi":"10.18608/jla.2022.7419","DOIUrl":"https://doi.org/10.18608/jla.2022.7419","url":null,"abstract":"Large-group (n > 8) co-located collaboration has not been adequately studied because it demands different conceptual framings than those used to study small-group collaboration, while also posing pragmatic constraints on data collection. Working within these pragmatic constraints, we use video data to devise an indicator of the current possibilities for learner collaboration during large-group co-located interactions. We borrow conceptualizations from proxemics and social network analysis to construct collaborative opportunity networks, allowing us to define the concept of collaborative opportunity temperature (COT) readings: a “snapshot” of the current configuration of the different social subgroup structures within a large group, indicating emergent opportunities for collaboration (via talk or shared action) due to proximity. Using a case study of two groups of people (n = 11, n = 12) who interacted with a multi-user museum exhibit, we outline the processes of deriving COT. We show how to quickly detect differences in subgroup configurations that may result from educational interventions and how COT can triangulate with and complement other forms of data (audio transcripts and activity logs) during lengthier analyses. We also outline how COT readings can be used to supply formative feedback on social engagement to learners and be adapted to other learning environments.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125566274","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

Networks in Learning Analytics: Where Theory, Methodology, and Practice Intersect 学习分析中的网络:理论、方法和实践的交集

J. Learn. Anal. Pub Date : 2022-03-11 DOI: 10.18608/jla.2022.7697

Bodong Chen, Oleksandra Poquet

{"title":"Networks in Learning Analytics: Where Theory, Methodology, and Practice Intersect","authors":"Bodong Chen, Oleksandra Poquet","doi":"10.18608/jla.2022.7697","DOIUrl":"https://doi.org/10.18608/jla.2022.7697","url":null,"abstract":"Network analysis has contributed to the emergence of learning analytics. In this editorial, we briefly introduce network science as a field and situate it within learning analytics. Drawing on the Learning Analytics Cycle, we highlight that effective application of network science methods in learning analytics involves critical considerations of learning processes, data, methods and metrics, and interventions, as well as ethics and value systems surrounding these areas. Careful work must meaningfully situate network methods and interventions within the theoretical assumptions explaining learning, as well as within pedagogical and technological factors shaping learning processes. The five empirical papers in the special section demonstrate diverse applications of network analysis, and the invited commentaries from cognitive network science and physics education research further discuss potential synergies between learning analytics and other sister fields with a shared interest in leveraging network science. We conclude by discussing opportunities to strengthen the rigour of network-based learning analytics projects, expand current work into nascent areas, and achieve more impact by holistically addressing the full cycle of learning analytics.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129739474","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

How the Monitoring Events of Individual Students Are Associated With Phases of Regulation: A Network Analysis Approach 个别学生的监控事件如何与监管阶段相关联:网络分析方法

J. Learn. Anal. Pub Date : 2022-03-11 DOI: 10.18608/jla.2022.7429

Jonna Malmberg, Mohammed Saqr, H. Järvenoja, Sanna Järvelä

{"title":"How the Monitoring Events of Individual Students Are Associated With Phases of Regulation: A Network Analysis Approach","authors":"Jonna Malmberg, Mohammed Saqr, H. Järvenoja, Sanna Järvelä","doi":"10.18608/jla.2022.7429","DOIUrl":"https://doi.org/10.18608/jla.2022.7429","url":null,"abstract":"The current study uses a within-person temporal and sequential analysis to understand individual learning processes as part of collaborative learning. Contemporary perspectives of self-regulated learning acknowledge monitoring as a crucial mechanism for each phase of the regulated learning cycle, but little is known about the function of the monitoring of these phases by individual students in groups and the role of motivation in this process. This study addresses this gap by investigating how monitoring coexists temporally and progresses sequentially during collaborative learning. Twelve high school students participated in an advanced physics course and collaborated in groups of three for twenty 90-minute learning sessions. Each student’s monitoring events were first identified from the videotaped sessions and then associated with the regulation phase. In addition, the ways in which students acknowledged each monitoring event were coded. The results showed that cyclical phases of regulation do not coexist. However, when we examined temporal and sequential aspects of monitoring, the results showed that the monitoring of motivation predicts the monitoring of task definition, leading to task enactment. The results suggest that motivation is embedded in regulation phases. The current study sheds light on idiographic methods that have implications for individual learning analytics.","PeriodicalId":145357,"journal":{"name":"J. Learn. Anal.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130691058","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