K. Tamura, Tsuyoshi Okamoto, Misato Oi, Atsushi Shimada, Kohei Hatano, M. Yamada, M. Lu, S. Konomi
To improve designs of e-learning materials, it is necessary to know which word or figure a learner felt "difficult" in the materials. In this pilot study, we measured electroencephalography (EEG) and eye gaze data of learners and analyzed to estimate which area they had difficulty to learn. The developed system realized simultaneous measurements of physiological data and subjective evaluations during learning. Using this system, we observed specific EEG activity in difficult pages. Integrating of eye gaze and EEG measurements raised a possibility to determine where a learner felt "difficult" in a page of learning materials. From these results, we could suggest that the multimodal measurements of EEG and eye gaze would lead to effective improvement of learning materials. For future study, more data collection using various materials and learners with different backgrounds is necessary. This study could lead to establishing a method to improve e-learning materials based on learners' mental states.
{"title":"Pilot Study to Estimate \"Difficult\" Area in e-Learning Material by Physiological Measurements","authors":"K. Tamura, Tsuyoshi Okamoto, Misato Oi, Atsushi Shimada, Kohei Hatano, M. Yamada, M. Lu, S. Konomi","doi":"10.1145/3330430.3333648","DOIUrl":"https://doi.org/10.1145/3330430.3333648","url":null,"abstract":"To improve designs of e-learning materials, it is necessary to know which word or figure a learner felt \"difficult\" in the materials. In this pilot study, we measured electroencephalography (EEG) and eye gaze data of learners and analyzed to estimate which area they had difficulty to learn. The developed system realized simultaneous measurements of physiological data and subjective evaluations during learning. Using this system, we observed specific EEG activity in difficult pages. Integrating of eye gaze and EEG measurements raised a possibility to determine where a learner felt \"difficult\" in a page of learning materials. From these results, we could suggest that the multimodal measurements of EEG and eye gaze would lead to effective improvement of learning materials. For future study, more data collection using various materials and learners with different backgrounds is necessary. This study could lead to establishing a method to improve e-learning materials based on learners' mental states.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80237857","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}
Online classes and degree programs continue to grow in popularity, in part due to the increased convenience and accessibility of education that technology has provided in recent years. As online education scales upwards and outwards, there is an increased need to provide students with an engaging and collaborative learning experience. In some online learning environments, student collaboration is perceived to be more difficult than it is in a physical classroom setting due to cultural or geographic distance between students. In particular, online class lectures often lack the collaborative spirit seen in most in-person classroom lectures. To improve upon the online classroom experience, this project first examines the benefits and drawbacks of several in-person and online lecture delivery techniques, then proposes an online lecture platform that allows students to facilitate their own collaborative classrooms on-demand through a semi-synchronous viewing area and chatroom.
{"title":"Synchronous at Scale: Investigation and Implementation of a Semi-Synchronous Online Lecture Platform","authors":"Denise G. Kutnick, David A. Joyner","doi":"10.1145/3330430.3333653","DOIUrl":"https://doi.org/10.1145/3330430.3333653","url":null,"abstract":"Online classes and degree programs continue to grow in popularity, in part due to the increased convenience and accessibility of education that technology has provided in recent years. As online education scales upwards and outwards, there is an increased need to provide students with an engaging and collaborative learning experience. In some online learning environments, student collaboration is perceived to be more difficult than it is in a physical classroom setting due to cultural or geographic distance between students. In particular, online class lectures often lack the collaborative spirit seen in most in-person classroom lectures. To improve upon the online classroom experience, this project first examines the benefits and drawbacks of several in-person and online lecture delivery techniques, then proposes an online lecture platform that allows students to facilitate their own collaborative classrooms on-demand through a semi-synchronous viewing area and chatroom.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"105 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85987990","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}
Scott Hellman, Mark Rosenstein, Andrew Gorman, William Murray, Lee Becker, Alok Baikadi, Jill Budden, P. Foltz
Automated essay scoring (AES) allows writing to be assigned in large courses and can provide instant formative feedback to students. However, creating models for AES can be costly, requiring the collection and human scoring of hundreds of essays. We have developed and are piloting a web-based tool that allows instructors to incrementally score responses to enable AES scoring while minimizing the number of essays the instructors must score. Previous work has shown that techniques from the machine learning subfield of active learning can reduce the amount of training data required to create effective AES models. We extend those results to a less idealized scenario: one driven by the instructor's need to score sets of essays, in which the model is trained iteratively using batch mode active learning. We propose a novel approach inspired by a class of topological methods, but with reduced computational requirements, which we refer to as topological maxima. Using actual student data, we show that batch mode active learning is a practical approach to training AES models. Finally, we discuss implications of using this technology for automated customized scoring of writing across the curriculum.
{"title":"Scaling Up Writing in the Curriculum: Batch Mode Active Learning for Automated Essay Scoring","authors":"Scott Hellman, Mark Rosenstein, Andrew Gorman, William Murray, Lee Becker, Alok Baikadi, Jill Budden, P. Foltz","doi":"10.1145/3330430.3333629","DOIUrl":"https://doi.org/10.1145/3330430.3333629","url":null,"abstract":"Automated essay scoring (AES) allows writing to be assigned in large courses and can provide instant formative feedback to students. However, creating models for AES can be costly, requiring the collection and human scoring of hundreds of essays. We have developed and are piloting a web-based tool that allows instructors to incrementally score responses to enable AES scoring while minimizing the number of essays the instructors must score. Previous work has shown that techniques from the machine learning subfield of active learning can reduce the amount of training data required to create effective AES models. We extend those results to a less idealized scenario: one driven by the instructor's need to score sets of essays, in which the model is trained iteratively using batch mode active learning. We propose a novel approach inspired by a class of topological methods, but with reduced computational requirements, which we refer to as topological maxima. Using actual student data, we show that batch mode active learning is a practical approach to training AES models. Finally, we discuss implications of using this technology for automated customized scoring of writing across the curriculum.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"99 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84015255","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}
Saar Kuzi, W. Cope, D. Ferguson, Chase Geigle, Chengxiang Zhai
Automated assessment of complex assignments is crucial for scaling up learning of complex skills such as critical thinking. To address this challenge, one previous work has applied supervised machine learning to automate the assessment by learning from examples of graded assignments by humans. However, in the previous work, only simple lexical features, such as words or n-grams, have been used. In this paper, we propose to use topics as features for this task, which are more interpretable than those simple lexical features and can also address polysemy and synonymy of lexical semantics. The topics can be learned automatically from the student assignment data by using a probabilistic topic model. We propose and study multiple approaches to construct topical features and to combine topical features with simple lexical features. We evaluate the proposed methods using clinical case assignments performed by veterinary medicine students. The experimental results show that topical features are generally very effective and can substantially improve performance when added on top of the lexical features. However, their effectiveness is highly sensitive to how the topics are constructed and a combination of topics constructed using multiple views of the text data works the best. Our results also show that combining the prediction results of using different types of topical features and of topical and lexical features is more effective than pooling all features together to form a larger feature space.
{"title":"Automatic Assessment of Complex Assignments using Topic Models","authors":"Saar Kuzi, W. Cope, D. Ferguson, Chase Geigle, Chengxiang Zhai","doi":"10.1145/3330430.3333615","DOIUrl":"https://doi.org/10.1145/3330430.3333615","url":null,"abstract":"Automated assessment of complex assignments is crucial for scaling up learning of complex skills such as critical thinking. To address this challenge, one previous work has applied supervised machine learning to automate the assessment by learning from examples of graded assignments by humans. However, in the previous work, only simple lexical features, such as words or n-grams, have been used. In this paper, we propose to use topics as features for this task, which are more interpretable than those simple lexical features and can also address polysemy and synonymy of lexical semantics. The topics can be learned automatically from the student assignment data by using a probabilistic topic model. We propose and study multiple approaches to construct topical features and to combine topical features with simple lexical features. We evaluate the proposed methods using clinical case assignments performed by veterinary medicine students. The experimental results show that topical features are generally very effective and can substantially improve performance when added on top of the lexical features. However, their effectiveness is highly sensitive to how the topics are constructed and a combination of topics constructed using multiple views of the text data works the best. Our results also show that combining the prediction results of using different types of topical features and of topical and lexical features is more effective than pooling all features together to form a larger feature space.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78815858","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}
M. Lu, K. Tamura, Tsuyoshi Okamoto, Misato Oi, Atsushi Shimada, Kohei Hatano, M. Yamada, S. Konomi
Extended learning support systems for all-age education requires inclusive user interface design, especially for elderly users. A dual-tablet user interface with simplified visual layers and more intuitive operations was proposed aiming to reduce the physical and mental loads of elderly learners. An initial prototype with basic functions of viewing learning material was developed based on a cross-platform framework. Two preliminary user experiments participated by elderly volunteers were carried out for formative evaluations, in order to improve the usability of the interface design iteratively. The prototype was modified based on the participants' comments and observation of their operations during the experiments. Additional findings of the elderly users' preference and tendency were discussed for further development.
{"title":"Proposal and Implementation of an Elderly-oriented User Interface for Learning Support Systems","authors":"M. Lu, K. Tamura, Tsuyoshi Okamoto, Misato Oi, Atsushi Shimada, Kohei Hatano, M. Yamada, S. Konomi","doi":"10.1145/3330430.3333650","DOIUrl":"https://doi.org/10.1145/3330430.3333650","url":null,"abstract":"Extended learning support systems for all-age education requires inclusive user interface design, especially for elderly users. A dual-tablet user interface with simplified visual layers and more intuitive operations was proposed aiming to reduce the physical and mental loads of elderly learners. An initial prototype with basic functions of viewing learning material was developed based on a cross-platform framework. Two preliminary user experiments participated by elderly volunteers were carried out for formative evaluations, in order to improve the usability of the interface design iteratively. The prototype was modified based on the participants' comments and observation of their operations during the experiments. Additional findings of the elderly users' preference and tendency were discussed for further development.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"129 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88845147","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}
Denise C. Nacu, P. Upadhyay, Evan Skorepa, Tre Everette, Evelyn Flores, Mighel Jackson, Nichole Pinkard
To address the goal of increasing and broadening participation of youth in STEM fields, a learning ecosystem approach is a promising strategy. Learning analytics can play an important role in such efforts which aim to build learning supports across the diverse spaces in which learning and development occurs, including informal, formal, and online contexts. This paper introduces a city-level learning analytics implementation effort in a developing STEM ecosystem in one mid-sized city. We describe aspects of our design and research approach and challenges that emerge by taking a learning ecosystem perspective of learning and development.
{"title":"Implementing Learning Analytics to Foster a STEM Learning Ecosystem at the City-Level: Emerging Research and Design Challenges","authors":"Denise C. Nacu, P. Upadhyay, Evan Skorepa, Tre Everette, Evelyn Flores, Mighel Jackson, Nichole Pinkard","doi":"10.1145/3330430.3333651","DOIUrl":"https://doi.org/10.1145/3330430.3333651","url":null,"abstract":"To address the goal of increasing and broadening participation of youth in STEM fields, a learning ecosystem approach is a promising strategy. Learning analytics can play an important role in such efforts which aim to build learning supports across the diverse spaces in which learning and development occurs, including informal, formal, and online contexts. This paper introduces a city-level learning analytics implementation effort in a developing STEM ecosystem in one mid-sized city. We describe aspects of our design and research approach and challenges that emerge by taking a learning ecosystem perspective of learning and development.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79187885","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}
Sahiti Labhishetty, Bhavya, Kevin Pei, Assma Boughoula, Chengxiang Zhai
We will demonstrate a prototype system WOSView built based on the vision of the Web of Slides(WOS), which aims to link all the lectures slides so as to facilitate navigation over all the slides. The links can be created at the slide level or at the level of phrases inside a slide, and many types of links can be created. The prototype system we built implements the most basic type of links, which link slides that have similar content and integrates lectures from four different MOOCs. WOSView also supports keyword search, which generates virtual links dynamically. We will demonstrate how the graphical interface of the WOSView enables students to flexibly navigate into slides from different courses and explore related slides using both static and dynamic links and solicit feedback from the community about the vision of WOS.
我们将展示一个基于Web of Slides(WOS)愿景构建的原型系统WOSView，该系统旨在链接所有讲座幻灯片，以便于在所有幻灯片上进行导航。可以在幻灯片级别或幻灯片内的短语级别创建链接，并且可以创建许多类型的链接。我们构建的原型系统实现了最基本的链接类型，它将内容相似的幻灯片链接起来，并整合了来自四个不同mooc的讲座。WOSView还支持关键字搜索，可以动态生成虚拟链接。我们将演示WOSView的图形界面如何使学生能够灵活地导航到不同课程的幻灯片，并使用静态和动态链接探索相关幻灯片，并征求社区对WOS愿景的反馈。
{"title":"WOSView Demo: A Tool to Explore the Web of Slides","authors":"Sahiti Labhishetty, Bhavya, Kevin Pei, Assma Boughoula, Chengxiang Zhai","doi":"10.1145/3330430.3333669","DOIUrl":"https://doi.org/10.1145/3330430.3333669","url":null,"abstract":"We will demonstrate a prototype system WOSView built based on the vision of the Web of Slides(WOS), which aims to link all the lectures slides so as to facilitate navigation over all the slides. The links can be created at the slide level or at the level of phrases inside a slide, and many types of links can be created. The prototype system we built implements the most basic type of links, which link slides that have similar content and integrates lectures from four different MOOCs. WOSView also supports keyword search, which generates virtual links dynamically. We will demonstrate how the graphical interface of the WOSView enables students to flexibly navigate into slides from different courses and explore related slides using both static and dynamic links and solicit feedback from the community about the vision of WOS.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88738357","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}
With Massive Open Online Courses (MOOCs) the number of people having access to higher education increased rapidly. The intentions to enroll for a specific course vary significantly and depend on one's professional or personal learning needs and interests. All learners have in common that they pursue their individual learning objectives. However, predominant MOOC platforms follow a one-size-fits-all approach and primarily aim for completion with certification. Specifically, technical support for goal-oriented and self-regulated learning to date is very limited in this context although both learning strategies are proven to be key factors for students' achievement in large-scale online learning environments. In this first investigation, a concept for the application and technical integration of personalized learning objectives in a MOOC platform is realized and assessed. It is evaluated with a mixed-method approach. First, the learners' acceptance is examined with a multivariate A/B test in two courses. Second, a survey was conducted to gather further feed-back about the perceived usefulness, next to the acceptance. The results show a positive perception by the learners, which paves the way for future research.
{"title":"On the Acceptance and Usefulness of Personalized Learning Objectives in MOOCs","authors":"Tobias Rohloff, Dominic Sauer, C. Meinel","doi":"10.1145/3330430.3333624","DOIUrl":"https://doi.org/10.1145/3330430.3333624","url":null,"abstract":"With Massive Open Online Courses (MOOCs) the number of people having access to higher education increased rapidly. The intentions to enroll for a specific course vary significantly and depend on one's professional or personal learning needs and interests. All learners have in common that they pursue their individual learning objectives. However, predominant MOOC platforms follow a one-size-fits-all approach and primarily aim for completion with certification. Specifically, technical support for goal-oriented and self-regulated learning to date is very limited in this context although both learning strategies are proven to be key factors for students' achievement in large-scale online learning environments. In this first investigation, a concept for the application and technical integration of personalized learning objectives in a MOOC platform is realized and assessed. It is evaluated with a mixed-method approach. First, the learners' acceptance is examined with a multivariate A/B test in two courses. Second, a survey was conducted to gather further feed-back about the perceived usefulness, next to the acceptance. The results show a positive perception by the learners, which paves the way for future research.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89343140","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}
Higher education at scale, such as in the California public post-secondary system, has promoted upward socioeconomic mobility by supporting student transfer from 2-year community colleges to 4-year degree granting universities. Among the barriers to transfer is earning enough credit at 2-year institutions that qualify for the transfer credit required by 4-year degree programs. Defining which course at one institution will count as credit for an equivalent course at another institution is called course articulation, and it is an intractable task when attempting to manually articulate every set of courses at every institution with one another. In this paper, we present a methodology towards making tractable this process of defining and maintaining articulations by leveraging the information contained within historic enrollment patterns and course catalog descriptions. We provide a proof-of-concept analysis using data from a 4-year and 2-year institution to predict articulation pairs between them, produced from machine translation models and validated by a set of 65 institutionally pre-established course-to-course articulations. Finally, we create a report of proposed articulations for consumption by the institutions and close with a discussion of limitations and the challenges to adoption.
{"title":"Data-Assistive Course-to-Course Articulation Using Machine Translation","authors":"Z. Pardos, Hung Chau, Haocheng Zhao","doi":"10.1145/3330430.3333622","DOIUrl":"https://doi.org/10.1145/3330430.3333622","url":null,"abstract":"Higher education at scale, such as in the California public post-secondary system, has promoted upward socioeconomic mobility by supporting student transfer from 2-year community colleges to 4-year degree granting universities. Among the barriers to transfer is earning enough credit at 2-year institutions that qualify for the transfer credit required by 4-year degree programs. Defining which course at one institution will count as credit for an equivalent course at another institution is called course articulation, and it is an intractable task when attempting to manually articulate every set of courses at every institution with one another. In this paper, we present a methodology towards making tractable this process of defining and maintaining articulations by leveraging the information contained within historic enrollment patterns and course catalog descriptions. We provide a proof-of-concept analysis using data from a 4-year and 2-year institution to predict articulation pairs between them, produced from machine translation models and validated by a set of 65 institutionally pre-established course-to-course articulations. Finally, we create a report of proposed articulations for consumption by the institutions and close with a discussion of limitations and the challenges to adoption.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90909765","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}
Despite the fact that anyone can sign up for open online courses, their enrollment patterns reflect the historical underrepresentation of certain sociodemographic groups (e.g. women in STEM disciplines). We theorize that enrollment choices online are shaped by contextual cues that activate stereotypes about numeric representation and climate in brick-and-mortar institutions. A longitudinal matched-pairs experiment with 14 MOOCs (N=29,000) tested this theory by manipulating the presence of a diversity statement on course pages and measuring effects on who enrolls. We found a 3% increase in the proportion of students with lower socioeconomic status. The effect size varied across courses between -0.5 and 7 percentage points. No significant changes in enrollment patterns by gender, age, and national development level occurred. Implications for the use and content of diversity statements and their alternatives are discussed.
{"title":"Can a diversity statement increase diversity in MOOCs?","authors":"René F. Kizilcec, Andrew J. Saltarelli","doi":"10.1145/3330430.3333633","DOIUrl":"https://doi.org/10.1145/3330430.3333633","url":null,"abstract":"Despite the fact that anyone can sign up for open online courses, their enrollment patterns reflect the historical underrepresentation of certain sociodemographic groups (e.g. women in STEM disciplines). We theorize that enrollment choices online are shaped by contextual cues that activate stereotypes about numeric representation and climate in brick-and-mortar institutions. A longitudinal matched-pairs experiment with 14 MOOCs (N=29,000) tested this theory by manipulating the presence of a diversity statement on course pages and measuring effects on who enrolls. We found a 3% increase in the proportion of students with lower socioeconomic status. The effect size varied across courses between -0.5 and 7 percentage points. No significant changes in enrollment patterns by gender, age, and national development level occurred. Implications for the use and content of diversity statements and their alternatives are discussed.","PeriodicalId":20693,"journal":{"name":"Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78114567","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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