LAK22: 12th International Learning Analytics and Knowledge Conference最新文献

Tracking Individuals in Classroom Videos via Post-processing OpenPose Data 通过后处理OpenPose数据跟踪课堂视频中的个人

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506888

Paul Hur, Nigel Bosch

{"title":"Tracking Individuals in Classroom Videos via Post-processing OpenPose Data","authors":"Paul Hur, Nigel Bosch","doi":"10.1145/3506860.3506888","DOIUrl":"https://doi.org/10.1145/3506860.3506888","url":null,"abstract":"Analyzing classroom video data provides valuable insights about the interactions between students and teachers, albeit often through time-consuming qualitative coding or the use of bespoke sensors to record individual movement information. We explore measuring classroom posture and movement in secondary classroom video data through computer vision methods (especially OpenPose), and introduce a simple but effective approach to automatically track movement via post-processing of OpenPose output data. Analysis of 67 videos of mathematics classes from middle school and high school levels highlighted the challenges associated with analyzing movement in typical classroom videos: occlusion from low camera angles, difficulty detecting lower body movement due to sitting, and the close proximity of students to one another and their teachers. Despite these challenges, our approach tracked person IDs across classroom videos for 93.0% of detected individuals. The tracking results were manually verified through randomly sampling 240 instances, which revealed notable OpenPose tracking inconsistencies. Finally, we discuss the implications for supporting more scalability of video data classroom movement analysis, and future potential explorations.","PeriodicalId":185465,"journal":{"name":"LAK22: 12th International Learning Analytics and Knowledge Conference","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124729210","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: 5

Towards an Automatic Approach for Assessing Program Competencies 迈向评估项目能力的自动方法

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506875

Xinyuan Chang, Bingxin Wang, Bowen Hui

{"title":"Towards an Automatic Approach for Assessing Program Competencies","authors":"Xinyuan Chang, Bingxin Wang, Bowen Hui","doi":"10.1145/3506860.3506875","DOIUrl":"https://doi.org/10.1145/3506860.3506875","url":null,"abstract":"Skills analysis is an interdisciplinary area that studies labor market trends and provides recommendations for developing educational standards and re-skilling efforts. We leverage techniques in this area to develop a scalable approach that identifies and evaluates educational competencies. In this work, we developed a skills extraction algorithm that uses natural language processing and machine learning techniques. We evaluated our algorithm on a labeled dataset and found its performance to be competitive with state-of-the-art methods. Using this algorithm, we analyzed student skills, university course syllabi, and online job postings. Our cross-sector analysis provides an initial landscape of skill needs for specific job titles. Additionally, we conducted a within-sector analysis based on programming jobs, computer science curriculum, and undergraduate students. Our findings suggest that students have a variety of hard skills and soft skills, but they are not necessarily the ones that employers want. The data also suggests these courses teach skills that are somewhat different from industry needs, and there is a lack of emphasis on soft skills. These results provide an initial assessment of the program competencies for a computer science program. Future work includes more data gathering, improving the algorithm, and applying our method to assess additional educational programs.","PeriodicalId":185465,"journal":{"name":"LAK22: 12th International Learning Analytics and Knowledge Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116520376","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

Towards a Pragmatic and Theory-Driven Framework for Multimodal Collaboration Feedback 面向多模式协作反馈的实用和理论驱动框架

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506898

M. Boothe, Collin Yu, Armanda Lewis, X. Ochoa

引用次数: 3

Grade 5 Students’ Elective Replay After Experiencing Failures in Learning Fractions in an Educational Game: When Does Replay After Failures Benefit Learning? 五年级学生在教育游戏中学习分数失败后的重玩:失败后的重玩在什么情况下有利于学习?

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506873

Qian Zhang, Teomara Rutherford

{"title":"Grade 5 Students’ Elective Replay After Experiencing Failures in Learning Fractions in an Educational Game: When Does Replay After Failures Benefit Learning?","authors":"Qian Zhang, Teomara Rutherford","doi":"10.1145/3506860.3506873","DOIUrl":"https://doi.org/10.1145/3506860.3506873","url":null,"abstract":"Despite theoretical benefits of replayability in educational games, empirical studies have found mixed evidence about the effects of replaying a previously passed game (i.e., elective replay) on students’ learning. Particularly, we know little about behavioral features of students’ elective replay process after experiencing failures (i.e., interruptive elective replay) and the relationships between these features and learning outcomes. In this study, we analyzed 5th graders’ log data from an educational game, ST Math, when they studied fractions—one of the most important but challenging math topics. We systematically constructed interruptive elective replay features by following students’ sequential behaviors after failing a game and investigated the relationships between these features and students’ post-test performance, after taking into account pretest performance and in-game performance. Descriptive statistics of the features we constructed revealed individual differences in the elective replay process after failures in terms of when to start replaying, what to replay, and how to replay. Moreover, a Bayesian multi-model linear regression showed that interruptive elective replay after failures might be beneficial for students if they chose to replay previously passed games when failing at a higher, more difficult level in the current game and if they passed the replayed games.","PeriodicalId":185465,"journal":{"name":"LAK22: 12th International Learning Analytics and Knowledge Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133566125","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 Review of Learning Analytics Dashboard Research in Higher Education: Implications for Justice, Equity, Diversity, and Inclusion 高等教育学习分析仪表板研究综述:对公正、公平、多样性和包容性的影响

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506900

K. Williamson, René F. Kizilcec

{"title":"A Review of Learning Analytics Dashboard Research in Higher Education: Implications for Justice, Equity, Diversity, and Inclusion","authors":"K. Williamson, René F. Kizilcec","doi":"10.1145/3506860.3506900","DOIUrl":"https://doi.org/10.1145/3506860.3506900","url":null,"abstract":"Learning analytics dashboards (LADs) are becoming more prevalent in higher education to help students, faculty, and staff make data-informed decisions. Despite extensive research on the design and implementation of LADs, few studies have investigated their relation to justice, equity, diversity, and inclusion (JEDI). Excluding these issues in LAD research limits the potential benefits of LADs generally and risks reinforcing long-standing inequities in education. We conducted a critical literature review, identifying 45 relevant papers to answer three research questions: how is LAD research improving JEDI, ii. how might it maintain or exacerbate inequitable outcomes, and iii. what opportunities exist in this space to improve JEDI in higher education. Using thematic analysis, we identified four common themes: (1) participant identities and researcher positionality, (2) surveillance concerns, (3) implicit pedagogies, and (4) software development resources. While we found very few studies directly addressing or mentioning JEDI concepts, we used these themes to explore ways researchers could consider JEDI in their studies. Our investigation highlights several opportunities to intentionally incorporate JEDI into LAD research by sharing software resources and conducting cross-border collaborations, better incorporating user needs, and centering considerations of justice in LAD efforts to improve historical inequities.","PeriodicalId":185465,"journal":{"name":"LAK22: 12th International Learning Analytics and Knowledge Conference","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125992785","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: 20

Generating and Evaluating Collective Concept Maps 生成和评估集体概念图

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506918

Riordan Brennan, Debbie Perouli

引用次数: 1

Detecting Impasse During Collaborative Problem Solving with Multimodal Learning Analytics 利用多模态学习分析发现协作问题解决中的僵局

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506865

Yingbo Ma, M. Celepkolu, K. Boyer

{"title":"Detecting Impasse During Collaborative Problem Solving with Multimodal Learning Analytics","authors":"Yingbo Ma, M. Celepkolu, K. Boyer","doi":"10.1145/3506860.3506865","DOIUrl":"https://doi.org/10.1145/3506860.3506865","url":null,"abstract":"Collaborative problem solving has numerous benefits for learners, such as improving higher-level reasoning and developing critical thinking. While learners engage in collaborative activities, they often experience impasse, a potentially brief encounter with differing opinions or insufficient ideas to progress. Impasses provide valuable opportunities for learners to critically discuss the problem and re-evaluate their existing knowledge. Yet, despite the increasing research efforts on developing multimodal modeling techniques to analyze collaborative problem solving, there is limited research on detecting impasse in collaboration. This paper investigates multimodal detection of impasse by analyzing 46 middle school learners’ collaborative dialogue—including speech and facial behaviors—during a coding task. We found that the semantics and speaker information in the linguistic modality, the pitch variation in the audio modality, and the facial muscle movements in the video modality are the most significant unimodal indicators of impasse. We also trained several multimodal models and found that combining indicators from these three modalities provided the best impasse detection performance. To the best of our knowledge, this work is the first to explore multimodal modeling of impasse during the collaborative problem solving process. This line of research contributes to the development of real-time adaptive support for collaboration.","PeriodicalId":185465,"journal":{"name":"LAK22: 12th International Learning Analytics and Knowledge Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129957789","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

FairEd: A Systematic Fairness Analysis Approach Applied in a Higher Educational Context 公平:高等教育环境下的系统公平分析方法

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506902

Jonathan Vasquez Verdugo, Xavier Gitiaux, Cesar Ortega, H. Rangwala

{"title":"FairEd: A Systematic Fairness Analysis Approach Applied in a Higher Educational Context","authors":"Jonathan Vasquez Verdugo, Xavier Gitiaux, Cesar Ortega, H. Rangwala","doi":"10.1145/3506860.3506902","DOIUrl":"https://doi.org/10.1145/3506860.3506902","url":null,"abstract":"Higher education institutions increasingly rely on machine learning models. However, a growing body of evidence shows that these algorithms may not serve underprivileged communities well and at times discriminate against them. This is all the more concerning in education as negative outcomes have long-term implications. We propose a systematic process for framing, detecting, documenting, and reporting unfairness risks. The systematic approach’s outcomes are merged into a framework named FairEd, which would help decision-makers to understand unfairness risks along the environmental and analytical fairness dimension. The tool allows to decide (i) whether the dataset contains risks of unfairness; (ii) how the models could perform along many fairness dimensions; (iii) whether potentially unfair outcomes can be mitigated without degrading performance. The systematic approach is applied to a Chilean University case study, where a predicting student dropout model is aimed to build. First, we capture the nuances of the Chilean context where unfairness emerges along income lines and demographic groups. Second, we highlight the benefit of reporting unfairness risks along a diverse set of metrics to shed light on potential discrimination. Third, we find that measuring the cost of fairness is an important quantity to report on when doing the model selection.","PeriodicalId":185465,"journal":{"name":"LAK22: 12th International Learning Analytics and Knowledge Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130532510","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

Do Speech-Based Collaboration Analytics Generalize Across Task Contexts? 基于语音的协作分析是否可以跨任务上下文进行推广?

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506894

Samuel L. Pugh, A. Rao, Angela E. B. Stewart, S. D’Mello

{"title":"Do Speech-Based Collaboration Analytics Generalize Across Task Contexts?","authors":"Samuel L. Pugh, A. Rao, Angela E. B. Stewart, S. D’Mello","doi":"10.1145/3506860.3506894","DOIUrl":"https://doi.org/10.1145/3506860.3506894","url":null,"abstract":"We investigated the generalizability of language-based analytics models across two collaborative problem solving (CPS) tasks: an educational physics game and a block programming challenge. We analyzed a dataset of 95 triads (N=285) who used videoconferencing to collaborate on both tasks for an hour. We trained supervised natural language processing classifiers on automatic speech recognition transcripts to predict the human-coded CPS facets (skills) of constructing shared knowledge, negotiation / coordination, and maintaining team function. We tested three methods for representing collaborative discourse: (1) deep transfer learning (using BERT), (2) n-grams (counts of words/phrases), and (3) word categories (using the Linguistic Inquiry Word Count [LIWC] dictionary). We found that the BERT and LIWC methods generalized across tasks with only a small degradation in performance (Transfer Ratio of .93 with 1 indicating perfect transfer), while the n-grams had limited generalizability (Transfer Ratio of .86), suggesting overfitting to task-specific language. We discuss the implications of our findings for deploying language-based collaboration analytics in authentic educational environments.","PeriodicalId":185465,"journal":{"name":"LAK22: 12th International Learning Analytics and Knowledge Conference","volume":"377 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126721636","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

Uncovering Associations Between Cognitive Presence and Speech Acts: A Network-Based Approach 认知在场和言语行为之间的关联:基于网络的方法

LAK22: 12th International Learning Analytics and Knowledge Conference Pub Date : 2022-03-21 DOI: 10.1145/3506860.3506908

Sehrish Iqbal, Z. Swiecki, Srécko Joksimovíc, R. F. Mello, N. Aljohani, Saeed-Ul Hassan, D. Gašević

引用次数: 1