International Conference on Learning Analytics and Knowledge最新文献_第4页

Probing Actionability in Learning Analytics: The Role of Routines, Timing, and Pathways 探究学习分析中的可操作性：常规、时间和路径的作用

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636914

Yeonji Jung, Alyssa Friend Wise

引用次数: 0

Learner Modeling and Recommendation of Learning Resources using Personal Knowledge Graphs 利用个人知识图谱为学习者建模并推荐学习资源

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636881

Qurat Ul Ain, Mohamed Amine Chatti, Paul Arthur Meteng Kamdem, R. Alatrash, Shoeb Joarder, Clara Siepmann

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What Fairness Metrics Can Really Tell You: A Case Study in the Educational Domain 公平指标能真正告诉你什么？教育领域的案例研究

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636873

Lea Cohausz, Jakob Kappenberger, Heiner Stuckenschmidt

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Exploring Confusion and Frustration as Non-linear Dynamical Systems 探索作为非线性动力系统的困惑与挫折

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636875

Elizabeth B. Cloude, Anabil Munshi, J. M. A. Andres, Jaclyn L. Ocumpaugh, Ryan S. Baker, Gautam Biswas

{"title":"Exploring Confusion and Frustration as Non-linear Dynamical Systems","authors":"Elizabeth B. Cloude, Anabil Munshi, J. M. A. Andres, Jaclyn L. Ocumpaugh, Ryan S. Baker, Gautam Biswas","doi":"10.1145/3636555.3636875","DOIUrl":"https://doi.org/10.1145/3636555.3636875","url":null,"abstract":"Numerous studies aim to enhance learning in digital environments throughemotionally-sensitiveinterventions. TheD’MelloandGraesser (2012) model of affect dynamics hypothesizes that when a learner encounters confusion, the degree to which it is prolonged (and transitions into frustration) or resolved, significantly affects their learning outcomes in digital environments. However, studies yield inconclusive results regarding relations between confusion, frustration, and learning. More research is needed to explore how confusion and frustration manifest during learning and its relation to outcomes. We go beyond past work looking at the rate, duration, and transitions of confusion and frustration by treating these affective states as non-linear dynamical systems consisting of expressive and behavioral components. We examined the frequency and recurrence of facial expressions associated with basic emotions (as automatically labeled by AffDex, a standard tool for analyzing emotions with video data) during confused and frustrated states (as automatically labeled with BROMP-based detectors applied to students’ interaction data). We compare these co-occurring patterns to learning outcomes (pre-tests, post-tests, and learning gains) within a digital learning environment, Betty’s Brain. Results showed that the frequency and recurrence rate of basic emotions expressed during confusion and frustration are complex and remain incompletely understood. Specifically, we show that confusion and frustration have different relationships with learning outcomes, depending on which basic emotion expressions they co-occur with. Implications of this study open avenues for better understanding these emotions as complex and non-linear dynamical systems, in the long-term enabling personalized feedback and emotional support within digital learning environments that enhance learning outcomes.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":" 3","pages":"241-252"},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140390678","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

The Effect of Assistance on Gamers: Assessing The Impact of On-Demand Hints & Feedback Availability on Learning for Students Who Game the System 帮助对游戏者的影响：评估按需提示和反馈对游戏系统学生学习的影响

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636904

Kirk P. Vanacore, Ashish Gurung, Adam Sales, Neil T. Heffernan

引用次数: 0

Which Planning Tactics Predict Online Course Completion? 哪些计划策略能预测在线课程的完成情况？

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636891

J. Cho, Yan Tao, Michael Yeomans, Dustin Tingley, René F. Kizilcec

{"title":"Which Planning Tactics Predict Online Course Completion?","authors":"J. Cho, Yan Tao, Michael Yeomans, Dustin Tingley, René F. Kizilcec","doi":"10.1145/3636555.3636891","DOIUrl":"https://doi.org/10.1145/3636555.3636891","url":null,"abstract":"Planning is a self-regulated learning strategy and widely used behavior change technique that can help learners achieve academic goals (e.g., pass an exam, apply to college, or complete an online course). Numerous studies have tested the effects of planning interventions, but few have examined the content of learners’ plans and how it relates to their academic outcomes. Building on a large-scale intervention study, we conducted a qualitative content analysis of 650 learner plans sampled from 15 massive open online courses (MOOCs). We identified a number of planning tactics , compared their prevalence, and examined which ones significantly predict course progress and completion using regression analyses. We found that learners whose plans specify a time of day (e.g., morning, afternoon, night) are significantly more likely to complete a MOOC, but only 25% of the learners in our sample used this tactic. The high degree of variation in the effectiveness of planning tactics may contribute to mixed intervention findings in scale-up studies. Models of plan effectiveness can be used to provide feedback on the quality of learners’ plans and encourage them to use effective tactics to achieve their learning goals.","PeriodicalId":162301,"journal":{"name":"International Conference on Learning Analytics and Knowledge","volume":" 11","pages":"360-370"},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140389838","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

Unveiling Goods and Bads: A Critical Analysis of Machine Learning Predictions of Standardized Test Performance in Early Childhood Education 揭开好坏的面纱：对机器学习预测幼儿教育标准化测试成绩的批判性分析

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636920

Lin Li, Namrata Srivastava, Jia Rong, Gina Pianta, Raju Varanasi, D. Gašević, Guanliang Chen

引用次数: 0

Epistemic Network Analysis for End-users: Closing the Loop in the Context of Multimodal Analytics for Collaborative Team Learning 最终用户的认识论网络分析：在团队协作学习的多模态分析背景下实现闭环

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636855

Linxuan Zhao, Vanessa Echeverría, Z. Swiecki, Lixiang Yan, Riordan Alfredo, Xinyu Li, D. Gašević, Roberto Martínez-Maldonado

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Multiple Choice vs. Fill-In Problems: The Trade-off Between Scalability and Learning 多选题与填空题：可扩展性与学习之间的权衡

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636908

Ashish Gurung, Kirk P. Vanacore, Andrew A. Mcreynolds, Korinn S. Ostrow, Eamon Worden, Adam Sales, Neil T. Heffernan

引用次数: 0

Kattis vs ChatGPT: Assessment and Evaluation of Programming Tasks in the Age of Artificial Intelligence Kattis vs ChatGPT：人工智能时代编程任务的评估与评价

International Conference on Learning Analytics and Knowledge Pub Date : 2024-03-18 DOI: 10.1145/3636555.3636882

Nora Dunder, Saga Lundborg, Jacqueline Wong, Olga Viberg

引用次数: 1