Immediate, individualized feedback on their code helps students learning to program. However, even in short, focused exercises in active learning, teachers do not have much time to write feedback. In addition, only looking at a student's final code hides a lot of the students' learning and discovering process. We created a glanceable code history visualization that enables teachers to view a student's entire coding history quickly and efficiently. A preliminary user study shows that this visualization captures previously unseen information that allows teachers to give students better grades and give students longer feedback and better feedback that focuses not just on their final code, but all their code in between.
{"title":"Glanceable code history: visualizing student code for better instructor feedback","authors":"C. Cassidy, Max Goldman, Rob Miller","doi":"10.1145/3231644.3231680","DOIUrl":"https://doi.org/10.1145/3231644.3231680","url":null,"abstract":"Immediate, individualized feedback on their code helps students learning to program. However, even in short, focused exercises in active learning, teachers do not have much time to write feedback. In addition, only looking at a student's final code hides a lot of the students' learning and discovering process. We created a glanceable code history visualization that enables teachers to view a student's entire coding history quickly and efficiently. A preliminary user study shows that this visualization captures previously unseen information that allows teachers to give students better grades and give students longer feedback and better feedback that focuses not just on their final code, but all their code in between.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87850200","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}
Y. A. Kolchinski, S. Ruan, Dan Schwartz, E. Brunskill
In tutoring software, targeting feedback to students' natural-language inputs is a promising avenue for making the software more effective. As a case study, we built such a system using Natural Language Processing (NLP) to provide adaptive feedback to students in an online learning task. We found that the NLP targeting mechanism, relative to more traditional multiple-choice targeting, was able to provide optimal feedback from fewer student interactions and generalize to previously unseen prompts.
{"title":"Adaptive natural-language targeting for student feedback","authors":"Y. A. Kolchinski, S. Ruan, Dan Schwartz, E. Brunskill","doi":"10.1145/3231644.3231684","DOIUrl":"https://doi.org/10.1145/3231644.3231684","url":null,"abstract":"In tutoring software, targeting feedback to students' natural-language inputs is a promising avenue for making the software more effective. As a case study, we built such a system using Natural Language Processing (NLP) to provide adaptive feedback to students in an online learning task. We found that the NLP targeting mechanism, relative to more traditional multiple-choice targeting, was able to provide optimal feedback from fewer student interactions and generalize to previously unseen prompts.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75815204","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}
Living in an information era where various online learning contents are rapidly available, students often learn with a combination of multiple learning tasks. In this work we explore the possibilities of using optimization theory to find the optimal trade-off between the time invested in two different completing learning tasks for each individual student. We show that the problem can be formulated as a linear programming problem, which can be efficiently solved to determine the optimal amount of time for each task. We also report our ongoing attempts to apply this theory to our Facebook Messenger chatbot software that can optimize the trade-off between learning and self-assessing in form of MCQs on the chatbot platform.
{"title":"Pilot study on optimal task scheduling in learning","authors":"Lin Ling, Chee-Wei Tan","doi":"10.1145/3231644.3231677","DOIUrl":"https://doi.org/10.1145/3231644.3231677","url":null,"abstract":"Living in an information era where various online learning contents are rapidly available, students often learn with a combination of multiple learning tasks. In this work we explore the possibilities of using optimization theory to find the optimal trade-off between the time invested in two different completing learning tasks for each individual student. We show that the problem can be formulated as a linear programming problem, which can be efficiently solved to determine the optimal amount of time for each task. We also report our ongoing attempts to apply this theory to our Facebook Messenger chatbot software that can optimize the trade-off between learning and self-assessing in form of MCQs on the chatbot platform.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74646823","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}
In four years, the Georgia Tech Online MS in CS (OMSCS) program has grown from 200 students to over 6000. Despite early evidence of success, there is a need to evaluate the program's effectiveness. In this paper, we focus on trends from Fall 2014 to Fall 2017 in the on-campus and online sections of one OMSCS course, Knowledge-Based Artificial-Intelligence (KBAI). We leverage sentiment analysis and readability assessments to quantify the evolving quality of discourse on the online forum discussions of the various sections. The research was conducted as a longitudinal study, and aims to evaluate the success of the KBAI course by comparing trends between residential and online sections. Despite slight downward trends in online discourse quality and sentiment polarity, our results suggest that the growing OMSCS program has been successful in replicating the quality of learning experienced by on-campus students in the KBAI course.
{"title":"Longitudinal trends in sentiment polarity and readability of an online masters of computer science course","authors":"Ida Camacho, Ashok K. Goel","doi":"10.1145/3231644.3231679","DOIUrl":"https://doi.org/10.1145/3231644.3231679","url":null,"abstract":"In four years, the Georgia Tech Online MS in CS (OMSCS) program has grown from 200 students to over 6000. Despite early evidence of success, there is a need to evaluate the program's effectiveness. In this paper, we focus on trends from Fall 2014 to Fall 2017 in the on-campus and online sections of one OMSCS course, Knowledge-Based Artificial-Intelligence (KBAI). We leverage sentiment analysis and readability assessments to quantify the evolving quality of discourse on the online forum discussions of the various sections. The research was conducted as a longitudinal study, and aims to evaluate the success of the KBAI course by comparing trends between residential and online sections. Despite slight downward trends in online discourse quality and sentiment polarity, our results suggest that the growing OMSCS program has been successful in replicating the quality of learning experienced by on-campus students in the KBAI course.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76852474","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}
"WebLinux" is a web app tool providing a standard Linux OS and an IDE in the browser, including a terminal, a code editor and a file browser. It provides a client-side and offline Linux OS environment based on a Javascript emulated processor. By avoiding the use of a Virtual Machine or any Linux server, Weblinux enables learners to directly start experimenting with the Linux OS without installing any software. The tool is entirely client-side which makes it extremely scalable and easy to deploy within a large community of online learners.
{"title":"WebLinux","authors":"R. Sharrock, Lawrence Angrave, Ella Hamonic","doi":"10.1145/3231644.3231703","DOIUrl":"https://doi.org/10.1145/3231644.3231703","url":null,"abstract":"\"WebLinux\" is a web app tool providing a standard Linux OS and an IDE in the browser, including a terminal, a code editor and a file browser. It provides a client-side and offline Linux OS environment based on a Javascript emulated processor. By avoiding the use of a Virtual Machine or any Linux server, Weblinux enables learners to directly start experimenting with the Linux OS without installing any software. The tool is entirely client-side which makes it extremely scalable and easy to deploy within a large community of online learners.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82019247","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}
Engagement and motivation are particularly important in optional learning environments, like educational games and massive open online courses. Providing some aspects of autonomy and choice to the student can yield significant benefits to learner motivation and persistence; yet there is also evidence that unsupported learners may not always automatically choose to allocate their learning time to pedagogical activities that are most known to be as associated with better learning outcomes. We investigated the impact of choice on student engagement and learning in a Massive Open Online Course (MOOC) on introductory statistics and probability. We compared conditions in which students are given free choice over the practice problems completed to conditions in which students receive a full set of practice activities or no practice activities before completing a post-test. In all cases students were free to navigate to other sections of the course at any time. In one of the two topic sections that included personalized practice activities we found that students performed better in the condition in which they were prompted to complete all practice activities. Though more students in this condition dropped out before reaching the post-test, many more students completed the full set of practice activities in this section than those who did in the free choice condition. These results are still quite preliminary but suggest that providing a default encouraged opt in procedure can encourage students to do more problems than they would otherwise, and that doing such additional problems can yield learning gains.
{"title":"Exploring the impact of the default option on student engagement and performance in a statistics MOOC","authors":"E. Brunskill, D. Zimmaro, Candace Thille","doi":"10.1145/3231644.3231692","DOIUrl":"https://doi.org/10.1145/3231644.3231692","url":null,"abstract":"Engagement and motivation are particularly important in optional learning environments, like educational games and massive open online courses. Providing some aspects of autonomy and choice to the student can yield significant benefits to learner motivation and persistence; yet there is also evidence that unsupported learners may not always automatically choose to allocate their learning time to pedagogical activities that are most known to be as associated with better learning outcomes. We investigated the impact of choice on student engagement and learning in a Massive Open Online Course (MOOC) on introductory statistics and probability. We compared conditions in which students are given free choice over the practice problems completed to conditions in which students receive a full set of practice activities or no practice activities before completing a post-test. In all cases students were free to navigate to other sections of the course at any time. In one of the two topic sections that included personalized practice activities we found that students performed better in the condition in which they were prompted to complete all practice activities. Though more students in this condition dropped out before reaching the post-test, many more students completed the full set of practice activities in this section than those who did in the free choice condition. These results are still quite preliminary but suggest that providing a default encouraged opt in procedure can encourage students to do more problems than they would otherwise, and that doing such additional problems can yield learning gains.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82966909","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}
{"title":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","authors":"","doi":"10.1145/3231644","DOIUrl":"https://doi.org/10.1145/3231644","url":null,"abstract":"","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91239940","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}
Visual models of scientific concepts drawn by students afford expanded opportunities for showing their understanding beyond textual descriptions, but also introduce other elements characterized by artistic creativity and complexity. In this paper, we describe a standardized framework for evaluation of scientific visual models by human raters. This framework attempts to disentangle the interaction between the scientific modeling skills and artistic skills of representing real objects of students, and potentially provides a fair and valid way to assess understanding of scientific concepts e.g. structure and properties of Matter. Additionally, we report ongoing efforts to build automated assessment models based on the evaluation framework. Preliminary findings suggest the promise of such an automated approach.
{"title":"Toward large-scale automated scoring of scientific visual models","authors":"C. W. Leong, Lei Liu, Rutuja Ubale, L. Chen","doi":"10.1145/3231644.3231681","DOIUrl":"https://doi.org/10.1145/3231644.3231681","url":null,"abstract":"Visual models of scientific concepts drawn by students afford expanded opportunities for showing their understanding beyond textual descriptions, but also introduce other elements characterized by artistic creativity and complexity. In this paper, we describe a standardized framework for evaluation of scientific visual models by human raters. This framework attempts to disentangle the interaction between the scientific modeling skills and artistic skills of representing real objects of students, and potentially provides a fair and valid way to assess understanding of scientific concepts e.g. structure and properties of Matter. Additionally, we report ongoing efforts to build automated assessment models based on the evaluation framework. Preliminary findings suggest the promise of such an automated approach.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90703207","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}
R. W. Crues, Nigel Bosch, M. Perry, Lawrence Angrave, Najmuddin Shaik, S. Bhat
Massive open online courses (MOOCs) continue to see increasing enrollment and adoption by universities, although they are still not fully understood and could perhaps be significantly improved. For example, little is known about the relationships between the ways in which students choose to use MOOCs (e.g., sampling lecture videos, discussing topics with fellow students) and their overall level of engagement with the course, although these relationships are likely key to effective course implementation. In this paper we propose a multilevel definition of student engagement with MOOCs and explore the connections between engagement and students' behaviors across five unique courses. We modeled engagement using ordinal penalized logistic regression with the least absolute shrinkage and selection operator (LASSO), and found several predictors of engagement that were consistent across courses. In particular, we found that discussion activities (e.g., viewing forum posts) were positively related to engagement, whereas other types of student behaviors (e.g., attempting quizzes) were consistently related to less engagement with the course. Finally, we discuss implications of unexpected findings that replicated across courses, future work to explore these implications, and relevance of our findings for MOOC course design.
{"title":"Refocusing the lens on engagement in MOOCs","authors":"R. W. Crues, Nigel Bosch, M. Perry, Lawrence Angrave, Najmuddin Shaik, S. Bhat","doi":"10.1145/3231644.3231658","DOIUrl":"https://doi.org/10.1145/3231644.3231658","url":null,"abstract":"Massive open online courses (MOOCs) continue to see increasing enrollment and adoption by universities, although they are still not fully understood and could perhaps be significantly improved. For example, little is known about the relationships between the ways in which students choose to use MOOCs (e.g., sampling lecture videos, discussing topics with fellow students) and their overall level of engagement with the course, although these relationships are likely key to effective course implementation. In this paper we propose a multilevel definition of student engagement with MOOCs and explore the connections between engagement and students' behaviors across five unique courses. We modeled engagement using ordinal penalized logistic regression with the least absolute shrinkage and selection operator (LASSO), and found several predictors of engagement that were consistent across courses. In particular, we found that discussion activities (e.g., viewing forum posts) were positively related to engagement, whereas other types of student behaviors (e.g., attempting quizzes) were consistently related to less engagement with the course. Finally, we discuss implications of unexpected findings that replicated across courses, future work to explore these implications, and relevance of our findings for MOOC course design.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83452564","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}
Given that both computer scientists and educational researchers publish on the topic of massive open online courses (MOOCs), the research community should analyze how these disciplines approach the same topic. In order to promote productive dialogue within the community, we report on a bib-liometrics study of the growing MOOC literature and examine the potential interdisciplinarity of this research space. Drawing from 3,380 bibliographic items retrieved from Scopus, we conducted descriptive analyses on publication years, publication sources, disciplinary categories of publication sources, frequent keywords, leading authors, and cited references. We applied bibliographic coupling and network analysis to further investigate clusters of research topics in the MOOC literature. We found balanced representation of education and computer science within most topic clusters. However, integration could be further improved on, for example, by enhancing communication between the disciplines and broadening the scope of methods in specific studies.
{"title":"The potential of interdisciplinary in MOOC research: how do education and computer science intersect?","authors":"Kristine Lund, Bodong Chen, Sebastian Grauwin","doi":"10.1145/3231644.3231661","DOIUrl":"https://doi.org/10.1145/3231644.3231661","url":null,"abstract":"Given that both computer scientists and educational researchers publish on the topic of massive open online courses (MOOCs), the research community should analyze how these disciplines approach the same topic. In order to promote productive dialogue within the community, we report on a bib-liometrics study of the growing MOOC literature and examine the potential interdisciplinarity of this research space. Drawing from 3,380 bibliographic items retrieved from Scopus, we conducted descriptive analyses on publication years, publication sources, disciplinary categories of publication sources, frequent keywords, leading authors, and cited references. We applied bibliographic coupling and network analysis to further investigate clusters of research topics in the MOOC literature. We found balanced representation of education and computer science within most topic clusters. However, integration could be further improved on, for example, by enhancing communication between the disciplines and broadening the scope of methods in specific studies.","PeriodicalId":20634,"journal":{"name":"Proceedings of the Fifth Annual ACM Conference on Learning at Scale","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83943105","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}
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