LAK21: 11th International Learning Analytics and Knowledge Conference最新文献_第6页

A learning analytic approach to unveiling self-regulatory processes in learning tactics 一种揭示学习策略自我调节过程的学习分析方法

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448211

Yizhou Fan, John Saint, Shaveen Singh, J. Jovanović, D. Gašević

{"title":"A learning analytic approach to unveiling self-regulatory processes in learning tactics","authors":"Yizhou Fan, John Saint, Shaveen Singh, J. Jovanović, D. Gašević","doi":"10.1145/3448139.3448211","DOIUrl":"https://doi.org/10.1145/3448139.3448211","url":null,"abstract":"Investigation of learning tactics and strategies has received increasing attention by the Learning Analytics (LA) community. While previous research efforts have made notable contributions towards identifying and understanding learning tactics from trace data in various blended and online learning settings, there is still a need to deepen our understanding about learning processes that are activated during the enactment of distinct learning tactics. In order to fill this gap, we propose a learning analytic approach to unveiling and comparing self-regulatory processes in learning tactics detected from trace data. Following this approach, we detected four learning tactics (Reading with Quiz Tactic, Assessment and Interaction Tactic, Short Login and Interact Tactic and Focus on Quiz Tactic) as used by 728 learners in an undergrad course. We then theorised and detected five micro-level processes of self-regulated learning (SRL) through an analysis of trace data. We analysed how these micro-level SRL processes were activated during enactment of the four learning tactics in terms of their frequency of occurrence and temporal sequencing. We found significant differences across the four tactics regarding the five micro-level SRL processes based on multivariate analysis of variance and comparison of process models. In summary, the proposed LA approach allows for meaningful interpretation and distinction of learning tactics in terms of the underlying SRL processes. More importantly, this approach shows the potential to overcome the limitations in the interpretation of LA results which stem from the context-specific nature of learning. Specifically, the study has demonstrated how the interpretation of LA results and recommendation of pedagogical interventions can also be provided at the level of learning processes rather than only in terms of a specific course design.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125014368","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: 29

Using Clickstream Data Mining Techniques to Understand and Support First-Generation College Students in an Online Chemistry Course 使用点击流数据挖掘技术来理解和支持第一代大学生在线化学课程

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448169

F. Rodriguez, H. Lee, Teomara Rutherford, Christian Fischer, E. Potma, M. Warschauer

{"title":"Using Clickstream Data Mining Techniques to Understand and Support First-Generation College Students in an Online Chemistry Course","authors":"F. Rodriguez, H. Lee, Teomara Rutherford, Christian Fischer, E. Potma, M. Warschauer","doi":"10.1145/3448139.3448169","DOIUrl":"https://doi.org/10.1145/3448139.3448169","url":null,"abstract":"Although online courses can provide students with a high-quality and flexible learning experience, one of the caveats is that they require high levels of self-regulation. This added hurdle may have negative consequences for first-generation college students. In order to better understand and support students’ self-regulated learning, we examined a fully online Chemistry course with high enrollment (N = 312) and a high percentage of first-generation college students (65.70%). Using students’ lecture video clickstream data, we created two indicators of self-regulated learning: lecture video completion and time management. Performing a k-means clustering on these indicators uncovered four distinct self-regulated learning patterns: (1) Early Planning, (2) Planning, (3) Procrastination, and (4) Low Engagement. Early Planning behaviors were especially important for course success—they consistently predicted higher final course grades, even after controlling for important demographic variables. Interestingly, first-generation college students classified as Early Planners achieved at similar levels as their non-first-generation peers, but first-generation students in the Low Engagement group had the lowest average grades among students. Overall, our results show that self-regulation may be an important skill for determining first-generation students’ STEM achievement, and targeting these skills may serve as a useful way to support their specific learning needs.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130334941","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

Who wins, who learns? Exploring gameful pedagogy as a technique to support student differences 谁赢，谁学习?探索游戏教学法作为一种支持学生差异的技术

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448198

Caitlin Hayward, Kyle Schulz, Barry J. Fishman

引用次数: 2

Developing an In-Application Shared View Metric to Capture Collaborative Learning in a Multi-Platform Astronomy Simulation 开发应用内共享视图度量以捕获多平台天文学模拟中的协作学习

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448156

Morgan Diederich, Jina Kang, Taehyun Kim, Robb Lindgren

{"title":"Developing an In-Application Shared View Metric to Capture Collaborative Learning in a Multi-Platform Astronomy Simulation","authors":"Morgan Diederich, Jina Kang, Taehyun Kim, Robb Lindgren","doi":"10.1145/3448139.3448156","DOIUrl":"https://doi.org/10.1145/3448139.3448156","url":null,"abstract":"There has been recent interest in the design of collaborative learning activities that are distributed across multiple technology devices for students to engage in scientific inquiry. Emerging research has begun to investigate students’ collaborative behaviors across different device types and students’ shared attention by tracking eye gaze, body posture, and their interactions with the digital environment. Using a 3D astronomy simulation that leverages a VR headset and tablet computers, this paper builds on the ideas described in eye-gaze studies by developing and implementing a metric of shared viewing across multiple devices. Preliminary findings suggest that a higher level of shared view could be related to increased conceptual discussion, as well as point to an early-stage pattern of behavior of decreased SV to prompt facilitator intervention to refocus collaborative efforts. We hope this metric will be a promising first step in further understanding and assessing the quality of collaboration across multiple device platforms in a single shared space. This paper provides an in depth look at a highly exploratory stage of a broader research trajectory to establish a robust, effective way to track screen views, including providing resources to teachers when students engage in similar learning environments, and providing insight from log data to understand how students effectively collaborate.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125641703","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

What You Do Predicts How You Do: Prospectively Modeling Student Quiz Performance Using Activity Features in an Online Learning Environment 你做什么预测你怎么做:使用在线学习环境中的活动特征前瞻性建模学生测验表现

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448151

Emily Jensen, Tetsumichi Umada, Nicholas C. Hunkins, Stephen Hutt, A. Huggins-Manley, S. D’Mello

{"title":"What You Do Predicts How You Do: Prospectively Modeling Student Quiz Performance Using Activity Features in an Online Learning Environment","authors":"Emily Jensen, Tetsumichi Umada, Nicholas C. Hunkins, Stephen Hutt, A. Huggins-Manley, S. D’Mello","doi":"10.1145/3448139.3448151","DOIUrl":"https://doi.org/10.1145/3448139.3448151","url":null,"abstract":"Students using online learning environments need to effectively self-regulate their learning. However, with an absence of teacher-provided structure, students often resort to less effective, passive learning strategies versus constructive ones. We consider the potential benefits of interventions that promote retrieval practice – retrieving learned content from memory – which is an effective strategy for learning and retention. The goal is to nudge students towards completing short, formative quizzes when they are likely to succeed on those assessments. Towards this goal, we developed a machine-learning model using data from 32,685 students who used an online mathematics platform over an entire school year to prospectively predict scores on three-item assessments (N = 210,020) from interaction patterns up to 9 minutes before the assessment as well as Item Response Theory (IRT) estimates of student ability and quiz difficulty. These models achieved a student-independent correlation of 0.55 between predicted and actual scores on the assessments and outperformed IRT-only predictions (r = 0.34). Model performance was largely independent of the length of the analyzed window preceding a quiz. We discuss potential for future applications of the models to trigger dynamic interventions that aim to encourage students to engage with formative assessments rather than more passive learning strategies.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126293991","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

Analyzing the Efficacy of ECoach in Supporting Gateway Course Success Through Tailored Support 通过量身定制的支持，分析ECoach在支持门户课程成功中的效果

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448160

Rebecca L. Matz, Kyle Schulz, E. Hanley, Holly Derry, B. Hayward, Benjamin Köster, Caitlin Hayward, Timothy McKay

{"title":"Analyzing the Efficacy of ECoach in Supporting Gateway Course Success Through Tailored Support","authors":"Rebecca L. Matz, Kyle Schulz, E. Hanley, Holly Derry, B. Hayward, Benjamin Köster, Caitlin Hayward, Timothy McKay","doi":"10.1145/3448139.3448160","DOIUrl":"https://doi.org/10.1145/3448139.3448160","url":null,"abstract":"Large courses act as gateways for college students and often have poor outcomes, particularly in STEM fields where the pace of improvement has been glacial. Students encounter barriers to persistence like low grades, competitive cultures, and a lack of motivation and belonging. Tailored technology systems offer one promising path forward. In this observational study, we report on the use of one such system, called ECoach, that provides students resources based on their psychosocial profile, performance metrics, and pattern of ECoach usage. We investigated ECoach efficacy in five courses enrolling 3,599 students using a clustering method to group users by engagement level and subsequent regression analyses. We present results showing significant positive relationships with small effect sizes between ECoach engagement and final course grade as well as grade anomaly, a performance measure that takes into account prior course grades. The courses with the strongest relationship between ECoach engagement and performance offered nominal extra credit incentives yet show improved grades well above this “investment” from instructors. Such small incentives may act as a catalyst that spurs deeper engagement with the platform. The impact of specific ECoach features and areas for future study are discussed.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125861137","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: 10

A Deep Transfer Learning Approach to Modeling Teacher Discourse in the Classroom 教师课堂话语建模的深度迁移学习方法

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448168

Emily Jensen, Samuel L. Pugh, S. D’Mello

{"title":"A Deep Transfer Learning Approach to Modeling Teacher Discourse in the Classroom","authors":"Emily Jensen, Samuel L. Pugh, S. D’Mello","doi":"10.1145/3448139.3448168","DOIUrl":"https://doi.org/10.1145/3448139.3448168","url":null,"abstract":"Teachers, like everyone else, need objective reliable feedback in order to improve their effectiveness. However, developing a system for automated teacher feedback entails many decisions regarding data collection procedures, automated analysis, and presentation of feedback for reflection. We address the latter two questions by comparing two different machine learning approaches to automatically model seven features of teacher discourse (e.g., use of questions, elaborated evaluations). We compared a traditional open-vocabulary approach using n-grams and Random Forest classifiers with a state-of-the-art deep transfer learning approach for natural language processing (BERT). We found a tradeoff between data quantity and accuracy, where deep models had an advantage on larger datasets, but not for smaller datasets, particularly for variables with low incidence rates. We also compared the models based on the level of feedback granularity: utterance-level (e.g., whether an utterance is a question or a statement), class session-level proportions by averaging across utterances (e.g., question incidence score of 48%), and session-level ordinal feedback based on pre-determined thresholds (e.g., question asking score is medium [vs. low or high]) and found that BERT generally provided more accurate feedback at all levels of granularity. Thus, BERT appears to be the most viable approach to providing automatic feedback on teacher discourse provided there is sufficient data to fine tune the model.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132134339","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: 10

Theory-based learning analytics to explore student engagement patterns in a peer review activity 基于理论的学习分析，探索学生在同行评议活动中的参与模式

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448158

Erkan Er, Cristina Villa-Torrano, Y. Dimitriadis, D. Gašević, Miguel L. Bote-Lorenzo, Juan I. Asensio-Pérez, E. Gómez-Sánchez, A. Martínez-Monés

{"title":"Theory-based learning analytics to explore student engagement patterns in a peer review activity","authors":"Erkan Er, Cristina Villa-Torrano, Y. Dimitriadis, D. Gašević, Miguel L. Bote-Lorenzo, Juan I. Asensio-Pérez, E. Gómez-Sánchez, A. Martínez-Monés","doi":"10.1145/3448139.3448158","DOIUrl":"https://doi.org/10.1145/3448139.3448158","url":null,"abstract":"Peer reviews offer many learning benefits. Understanding students’ engagement in them can help design effective practices. Although learning analytics can be effective in generating such insights, its application in peer reviews is scarce. Theory can provide the necessary foundations to inform the design of learning analytics research and the interpretation of its results. In this paper, we followed a theory-based learning analytics approach to identifying students’ engagement patterns in a peer review activity facilitated via a web-based tool called Synergy. Process mining was applied on temporal learning data, traced by Synergy. The theory about peer review helped determine relevant data points and guided the top-down approach employed for their analysis: moving from the global phases to regulation of learning, and then to micro-level actions. The results suggest that theory and learning analytics should mutually relate with each other. Mainly, theory played a critical role in identifying a priori engagement patterns, which provided an informed perspective when interpreting the results. In return, the results of the learning analytics offered critical insights about student behavior that was not expected by the theory (i.e., low levels of co-regulation). The findings provided important implications for refining the grounding theory and its operationalization in Synergy.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130652882","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

Explorations of Designing Spatial Classroom Analytics with Virtual Prototyping 利用虚拟样机设计空间课堂分析的探索

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448192

JiWoong Jang, Jaewook Lee, Vanessa Echeverría, LuEttaMae Lawrence, V. Aleven

{"title":"Explorations of Designing Spatial Classroom Analytics with Virtual Prototyping","authors":"JiWoong Jang, Jaewook Lee, Vanessa Echeverría, LuEttaMae Lawrence, V. Aleven","doi":"10.1145/3448139.3448192","DOIUrl":"https://doi.org/10.1145/3448139.3448192","url":null,"abstract":"Despite the potential of spatial displays for supporting teachers’ classroom orchestration through real-time classroom analytics, the process to design these displays is a challenging and under-explored topic in the learning analytics (LA) community. This paper proposes a mid-fidelity Virtual Prototyping method (VPM), which involves simulating a classroom environment and candidate designs in virtual space to address these challenges. VPM allows for rapid prototyping of spatial features, requires no specialized hardware, and enables teams to conduct remote evaluation sessions. We report observations and findings from an initial exploration with five potential users through a design process utilizing VPM to validate designs for an AR-based spatial display in the context of middle-school orchestration tools. We found that designs created using virtual prototyping sufficiently conveyed a sense of three-dimensionality to address subtle design issues like occlusion and depth perception. We discuss the opportunities and limitations of applying virtual prototyping, particularly its potential to allow for more robust co-design with stakeholders earlier in the design process.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132919295","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: 0

Co-Designing for Privacy, Transparency, and Trust in K-12 Learning Analytics K-12学习分析中隐私、透明度和信任的共同设计

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448145

June Ahn, Fabio Campos, Ha Nguyen, Maria Hays, Janina Morrison

引用次数: 7