LAK21: 11th International Learning Analytics and Knowledge Conference最新文献_第2页

A Teacher-facing Learning Analytics Dashboard for Process-oriented Feedback in Online Learning 面向教师的学习分析仪表板，用于在线学习过程导向的反馈

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448187

Raphael A. Dourado, R. Rodrigues, Nivan Ferreira, R. F. Mello, A. S. Gomes, K. Verbert

引用次数: 14

Investigating the Well-being Impacts of Educational Technologies Supported by Learning Analytics: An application of the initial phase of IEEE P7010 recommended practice to a set of cases 调查由学习分析支持的教育技术对福祉的影响:将IEEE P7010推荐实践的初始阶段应用于一组案例

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448165

Eyad Hakami, Davinia Hernández Leo

{"title":"Investigating the Well-being Impacts of Educational Technologies Supported by Learning Analytics: An application of the initial phase of IEEE P7010 recommended practice to a set of cases","authors":"Eyad Hakami, Davinia Hernández Leo","doi":"10.1145/3448139.3448165","DOIUrl":"https://doi.org/10.1145/3448139.3448165","url":null,"abstract":"The accelerated adoption of digital technologies by people and communities results in a close relation between, on one hand, the state of individual and societal well-being and, on the other hand, the state of the digital technologies that underpin our life experiences. The ethical concerns and questions about the impact of such technologies on human well-being become more crucial when data analytics and intelligent competences are integrated. To investigate how learning technologies could impact human well-being considering the promising and concerning roles of learning analytics, we apply the initial phase of the recently produced IEEE P7010 Well-being Impact Assessment, a methodology and a set of metrics, to allow the digital well-being of a set of educational technologies to be more comprehensively tackled and evaluated. We posit that the use of IEEE P7010 well-being metrics could help identify where educational technologies supported by learning analytics would increase or decrease well-being, providing new routes to future technological innovation in Learning Analytics research.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"8 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":"132573977","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

Investigating Student Reflection during Game-Based Learning in Middle Grades Science 初中科学游戏学习中学生反思的调查研究

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448166

Daniel Carpenter, Elizabeth B. Cloude, Jonathan P. Rowe, R. Azevedo, James C. Lester

{"title":"Investigating Student Reflection during Game-Based Learning in Middle Grades Science","authors":"Daniel Carpenter, Elizabeth B. Cloude, Jonathan P. Rowe, R. Azevedo, James C. Lester","doi":"10.1145/3448139.3448166","DOIUrl":"https://doi.org/10.1145/3448139.3448166","url":null,"abstract":"Reflection plays a critical role in learning by encouraging students to contemplate their knowledge and previous learning experiences to inform their future actions and higher-order thinking, such as reasoning and problem solving. Reflection is particularly important in inquiry-driven learning scenarios where students have the freedom to set goals and regulate their own learning. However, despite the importance of reflection in learning, there are significant theoretical, methodological, and analytical challenges posed by measuring, modeling, and supporting reflection. This paper presents results from a classroom study to investigate middle-school students’ reflection during inquiry-driven learning with Crystal Island, a game-based learning environment for middle-school microbiology. To collect evidence of reflection during game-based learning, we used embedded reflection prompts to elicit written reflections during students’ interactions with Crystal Island. Results from analysis of data from 105 students highlight relationships between features of students’ reflections and learning outcomes related to both science content knowledge and problem solving. We consider implications for building adaptive support in game-based learning environments to foster deep reflection and enhance learning, and we identify key features in students’ problem-solving actions and reflections that are predictive of reflection depth. These findings present a foundation for providing adaptive support for reflection during game-based learning.","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":"131994190","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

Transforming Everyday Information into Practical Analytics with Crowdsourced Assessment Tasks 通过众包评估任务将日常信息转化为实用分析

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448146

June Ahn, Ha Nguyen, Fabio Campos, William Young

{"title":"Transforming Everyday Information into Practical Analytics with Crowdsourced Assessment Tasks","authors":"June Ahn, Ha Nguyen, Fabio Campos, William Young","doi":"10.1145/3448139.3448146","DOIUrl":"https://doi.org/10.1145/3448139.3448146","url":null,"abstract":"Educators use a wide variety of data to inform their practices. Examples of these data include forms of information that are commonplace in schools, such as student work and paper-based artifacts. One limitation in these situations is that there are less efficient ways to process such everyday varieties of information into analytics that are more usable and practical for educators. To explore how to address this constraint, we describe two sets of design experiments that utilize crowdsourced tasks for scoring open-ended assessments. Developing crowdsourced systems and their resulting analytics introduced a variety of challenges, such as attending to the expertise and learning of the crowd. In this paper, we describe the potential efficacy of design decisions such as screening the crowd, providing multimedia instruction, and asking the crowd to explain their answers. We also explore the potential of crowdsourcing as a learning opportunity for those participating in the collective tasks. Our work offers key design implications for leveraging crowdsourcing to process educational data in ways that are relevant to educators, while offering learning experiences for the crowd.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"97 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":"125044145","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

Skills Matter: Modeling the relationship between decision making processes and collaborative problem-solving skills during Hidden Profile Tasks 技能问题:在隐藏配置文件任务中建模决策过程和协作解决问题技能之间的关系

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448180

Yiwen Lin, Nia Dowell, Andrew Godfrey

{"title":"Skills Matter: Modeling the relationship between decision making processes and collaborative problem-solving skills during Hidden Profile Tasks","authors":"Yiwen Lin, Nia Dowell, Andrew Godfrey","doi":"10.1145/3448139.3448180","DOIUrl":"https://doi.org/10.1145/3448139.3448180","url":null,"abstract":"Collaborative problem-solving (CPS) is one of the most essential 21st century skills for success across educational and professional settings. The hidden-profile paradigm is one of the most prominent avenues of studying group decision making and underlying issues in information sharing. Previous research on the hidden-profile paradigm has primarily focused on static constructs (e.g., group size, group expertise), or on the information itself (whether certain pieces of information is being shared). In the current study, we propose a lens on individual and group’s collaborative problem-solving skills, to explore the relationships between dynamic discourse processes and decision making in a distributed information environment. Specifically, we sought to examine CPS skills in association with decision change and productive decision-making. Our results suggest that while sharing information has significantly positive association with decision change and effective decision-making, other aspects of social processes appear to be negatively correlated with these outcomes. Cognitive CPS skills, however, exhibit a strong positive relationship with making a (productive) change in students final decisions. We also find that these results are more pronounced at the group level, particularly with cognitive CPS skills. Our study shed lights on a more nuanced picture of how social and cognitive CPS interactions are related to effective information sharing and decision making in collaborative problem-solving interactions.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"37 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":"128305589","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

Exploring Metrics for the Analysis of Code Submissions in an Introductory Data Science Course 在数据科学入门课程中探索代码提交分析的度量

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448209

Huy A. Nguyen, Michelle Lim, Steven Moore, Eric Nyberg, M. Sakr, John C. Stamper

{"title":"Exploring Metrics for the Analysis of Code Submissions in an Introductory Data Science Course","authors":"Huy A. Nguyen, Michelle Lim, Steven Moore, Eric Nyberg, M. Sakr, John C. Stamper","doi":"10.1145/3448139.3448209","DOIUrl":"https://doi.org/10.1145/3448139.3448209","url":null,"abstract":"While data science education has gained increased recognition in both academic institutions and industry, there has been a lack of research on automated coding assessment for novice students. Our work presents a first step in this direction, by leveraging the coding metrics from traditional software engineering (Halstead Volume and Cyclomatic Complexity) in combination with those that reflect a data science project’s learning objectives (number of library calls and number of common library calls with the solution code). Through these metrics, we examined the code submissions of 97 students across two semesters of an introductory data science course. Our results indicated that the metrics can identify cases where students had overly complicated codes and would benefit from scaffolding feedback. The number of library calls, in particular, was also a significant predictor of changes in submission score and submission runtime, which highlights the distinctive nature of data science programming. We conclude with suggestions for extending our analyses towards more actionable intervention strategies, for example by tracking the fine-grained submission grading outputs throughout a student’s submission history, to better model and support them in their data science learning process.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"1 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":"128803491","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

Which one’s more work? Predicting effective credit hours between courses 哪个更费力?预测课程之间的有效学分

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448204

Shruthi Chockkalingam, Run Yu, Z. Pardos

{"title":"Which one’s more work? Predicting effective credit hours between courses","authors":"Shruthi Chockkalingam, Run Yu, Z. Pardos","doi":"10.1145/3448139.3448204","DOIUrl":"https://doi.org/10.1145/3448139.3448204","url":null,"abstract":"University students select courses for an upcoming term in part based on expected workload. Course credit hours is often the only metric given by the institution relevant to how much work a course will be and does not serve as a precise estimate due to the lack of granularity of the metric which can lead to student under or overestimation. We define a novel task of predicting relative effective course credit hours, or time load; essentially, determining which courses take more time than others. For this task, we draw from institutional data sources including course catalog descriptions, student enrollment histories and ratings from a popular course rating website. To validate this work, we design a personalized survey for university students to collect ground truth labels, presenting them with pairs of courses they had taken and asking which course took more time per week on average. We evaluate which sources of data using which machine representation techniques provide the best prediction of these course time load ratings. We establish a benchmark accuracy of 0.71 on this novel task and find skip-grams applied to enrollment data (i.e., course2vec), not catalog descriptions, to be most useful in predicting the time demands of a course.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"4 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":"129062319","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

Validity and Reliability of Student Models for Problem-Solving Activities 学生解决问题活动模式的效度与信度

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448140

Tomáš Effenberger, Radek Pelánek

引用次数: 3

How Did You Get that A? Selectivity’s Role in Rising Undergraduate Grades at a Large Public University 你是怎么得A的?在一所大型公立大学，选择性在提高本科成绩中的作用

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448199

A. Evrard, Kyle Schulz, Caitlin Hayward

{"title":"How Did You Get that A? Selectivity’s Role in Rising Undergraduate Grades at a Large Public University","authors":"A. Evrard, Kyle Schulz, Caitlin Hayward","doi":"10.1145/3448139.3448199","DOIUrl":"https://doi.org/10.1145/3448139.3448199","url":null,"abstract":"For nearly a century, pre-college standardized test scores and undergraduate letter grades have been de facto industry standard measures of achievement in US higher education. We examine a sample of millions of grades and a half million pre-college test scores earned by undergraduates between 2006 and 2019 at a large public research university that became increasingly selective, in terms of test scores of matriculated students, over that time. A persistent, moderate correlation between test score and grades within the period motivates us to employ a simple importance sampling model to address the question, “How much is increased selectivity driving up campus grades?”. Of the overall 0.213 rise in mean undergraduate grade points over the thirteen-year period, we find that nearly half, 0.098 ± 0.004, can be ascribed to increased selectivity. The fraction is higher, nearly 70%, in engineering, business and natural science subjects. Removing selectivity’s influence to surface curricular-related grade inflation within academic domains, we find a factor four range, from a low of ∼ 0.05 in business and engineering to a high of 0.18 in the humanities, over the thirteen year period.","PeriodicalId":108600,"journal":{"name":"LAK21: 11th International Learning Analytics and Knowledge Conference","volume":"5 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":"126880350","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

Combining Data-Driven Models and Expert Knowledge for Personalized Support to Foster Computational Thinking Skills 结合数据驱动的模型和个性化支持的专家知识，以培养计算思维技能

LAK21: 11th International Learning Analytics and Knowledge Conference Pub Date : 2021-04-12 DOI: 10.1145/3448139.3448175

Sébastien Lallé, Ö. Yalçın, C. Conati

引用次数: 2