Journal of Learning Letters最新文献

Human-centred learning analytics: Four challenges in realising the potential 以人为本的学习分析:实现潜力的四大挑战

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453/fizj7007

Roberto Martínez-Maldonado

{"title":"Human-centred learning analytics: Four challenges in realising the potential","authors":"Roberto Martínez-Maldonado","doi":"10.59453/fizj7007","DOIUrl":"https://doi.org/10.59453/fizj7007","url":null,"abstract":"The notion of Human-Centred Learning Analytics (HCLA) is gaining traction as educators and learning analytics (LA) researchers recognise the need to align analytics and artificial intelligence (AI) technologies with specific educational contexts. This has led an increasing number of researchers to adopt approaches, such as co-design and participatory design, to include educators and students as active participants in the LA design process. However, some experts contend that HCLA must go beyond stakeholder participation by also focusing on the safety, reliability, and trustworthiness of the analytics, and balancing human control and algorithmic automation. While the adoption of human-centred design (HCD) approaches promises considerable benefits, implementing these practices in data-intensive educational systems may not be straightforward. This paper emphasises the critical need to address specific ethical, technical, and methodological challenges tied to educational and data contexts, in order to effectively apply HCD in the creation of LA systems. We delve into four key challenges in this context: i) ensuring representative participation; ii) considering expertise and lived experiences in LA design; iii) balancing stakeholder input with technological innovation; and iv) navigating power dynamics and decision-making processes. LIFT Learning: Engage further with the author and the challenges faced when adopting human-centered approaches in learning analytics at the companion LIFT Learning site. The author will be hosting a live webinar on Tuesday 12 September 2023 at 6-7pm AEST (8-9am UTC). Visit the LIFT Learning site at https://apps.lift.c3l.ai/learning/course/coursev1:LEARNINGLETTERS+0106+2023 to sign up for your free ticket to this event. If you are unable to attend the webinar live, then the recording will be made available on this same site shortly afterwards.","PeriodicalId":430337,"journal":{"name":"Journal of Learning Letters","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124035772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synthetic Data Generator for Student Data Serving Learning Analytics: A Comparative Study 为学习分析服务的学生数据合成数据生成器:比较研究

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453//khzw9006

Chen Zhan, Oscar Blessed Deho, Xuwei Zhang, Srécko Joksimovíc, M. de Laat

{"title":"Synthetic Data Generator for Student Data Serving Learning Analytics: A Comparative Study","authors":"Chen Zhan, Oscar Blessed Deho, Xuwei Zhang, Srécko Joksimovíc, M. de Laat","doi":"10.59453//khzw9006","DOIUrl":"https://doi.org/10.59453//khzw9006","url":null,"abstract":"The ongoing digital transformation in the education sector has led to an increased focus on the adoption of Learning Analytics (LA) techniques. LA collects and uses students’ data to gain insights about students’ learning and guide interventions and feedback. Despite a great potential for improving teaching and learning, the use of LA has also raised important questions about the privacy and ethical implications of collecting and using student data. Despite recent efforts to tackle these challenges through the implementation of privacy-preserving approaches and the proposal of ethical guidelines and policies, there remains an insufficiency in ensuring the full protection of student privacy and well-being. Therefore, as a solution to privacy and ethical concerns in LA, there is a high demand for synthetic data generators that can learn from realistic data to generate synthetic data that closely resembles the original data. This paper aims to examine existing synthetic data generators from the broader community in terms of their performances with student data, as well as the capabilities of serving LA models. A comparative study is conducted by applying a set of different synthetic data generators in Synthetic Data Vault (SDV), an open-sourced synthetic data generation ecosystem of libraries, to real-world student data from a university. We report the efficiencies of different generators and the qualities of generated synthetic datasets regarding their statistical properties against realistic data. Furthermore, we test the compatibility between synthetic data generators and LA models by fitting generated synthetic datasets into common-used LA models. By aligning with the ground truth (realistic data), we evaluated the performances of LA models trained by synthetic datasets as indicators of their capability of serving LA models.","PeriodicalId":430337,"journal":{"name":"Journal of Learning Letters","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130366196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Workplace Logic Model: A method to address authentic work problems through workplace learning actions 工作场所逻辑模型:一种通过工作场所学习行动解决真实工作问题的方法

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453/eyev8004

A. Littlejohn, Koula Charitonos, Fereshte Goshtasbpour, S. Dawadi, R. McMullan

引用次数: 0

Learning Letters: Why a new journal? 学习信函:为什么要创办一份新期刊?

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453/nlsl7954

George Siemens, M. de Laat, Florence Gabriel, Negin Mirriahi

引用次数: 0

Data management of AI-powered education technologies: Challenges and opportunities 人工智能教育技术的数据管理:挑战与机遇

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453//xlud7002

Hassan Khosravi, Shazia Sadiq, S. Amer-Yahia

引用次数: 1

Human-Centred Learning Analytics: Opportunities and Challenges 以人为本的学习分析:机遇与挑战

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453//fizj7007

Roberto Martínez-Maldonado

{"title":"Human-Centred Learning Analytics: Opportunities and Challenges","authors":"Roberto Martínez-Maldonado","doi":"10.59453//fizj7007","DOIUrl":"https://doi.org/10.59453//fizj7007","url":null,"abstract":"The notion of Human-Centered Learning Analytics (HCLA) is gaining traction as educators and learning analytics (LA) researchers recognise the need to align artificial intelligence (AI) technologies with particular educational contexts. This has led an increasing number of researchers to adopt participatory approaches, such as co-design and participatory design, to involve educators and students in the design and development of LA systems. However, some experts contend that HCLA must go beyond stakeholder involvement and prioritize safety, reliability, trustworthiness, and finding a balance between human control and AI automation. Drawing from recent research in the field and the author’s first-hand experiences in conducting HCLA research, this paper discusses opportunities and challenges associated with HCLA. This paper highlights that the adoption of human-centred design approaches can help develop LA systems that align with pedagogical intentions by enabling dialogue among stakeholders and leveraging their expertise and lived experiences. The paper also highlights the crucial need to address ethical, technical, and methodological challenges specific to educational and data contexts for effectively applying human-centred design in the development of learning analytics systems. The paper concludes with recommendations for future research and practice, emphasising the importance of defining the scope of HCLA and continuing collaboration among LA researchers, practitioners, learning scientists, and educational stakeholders to advance the development of HCLA to support meaningful and effective learning experiences.","PeriodicalId":430337,"journal":{"name":"Journal of Learning Letters","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124901397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

“Belonging Analytics”: A Proposal “归属分析”:一个建议

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453//eaxa8005

Lisa-Angelique Lim, S. Buckingham Shum, P. Felten, Jennifer Uno

{"title":"“Belonging Analytics”: A Proposal","authors":"Lisa-Angelique Lim, S. Buckingham Shum, P. Felten, Jennifer Uno","doi":"10.59453//eaxa8005","DOIUrl":"https://doi.org/10.59453//eaxa8005","url":null,"abstract":"It is well-established that a student’s sense of belonging is associated with successful transition into higher education, along with a raft of positive outcomes including enhanced learning, well-being, and attainment for all students. The importance of belonging was further heightened by the Covid-19 pandemic, as the increased shift to online learning highlighted the challenges of monitoring and supporting student belonging in online settings. A significant challenge lies in the contested nature of belonging, as well as its complexity – students’ experience of belonging is both dynamic and contextual. In creating a new agenda connecting the fields of belonging and learning analytics, we propose the idea of “belonging analytics” to address the challenge of tracking students’ belonging. We present the emerging landscape of belonging by discussing how the advancements in the learning analytics field indicate great potential for the field to explore how digital trace data, narratives, textual data, or a combination, could be harnessed to gain insights into the ongoing experience of belonging, and consequently, to support belonging. We conclude with a set of open questions to interested researchers, to advance the field of belonging analytics.","PeriodicalId":430337,"journal":{"name":"Journal of Learning Letters","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123484863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

First 100 days of ChatGPT at Australian Universities An analysis of policy landscape and media discussions about the role of AI in Higher Education 对人工智能在高等教育中的作用的政策格局和媒体讨论的分析

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453/jmtn6001

S. Fowler, Malgorzata Korolkiewicz, Rebecca Marrone

{"title":"First 100 days of ChatGPT at Australian Universities An analysis of policy landscape and media discussions about the role of AI in Higher Education","authors":"S. Fowler, Malgorzata Korolkiewicz, Rebecca Marrone","doi":"10.59453/jmtn6001","DOIUrl":"https://doi.org/10.59453/jmtn6001","url":null,"abstract":"Based on the experience of the first 100 days of ChatGPT integration, the article discusses the potential impact of large language models (LLMs) on the Australian university sector. Using a content analysis of websites and quotes from university spokespeople in the media, the authors note that despite the potential benefits of LLMs in transforming teaching and learning, early media coverage has mainly focused on obstacles to adoption. The authors argue that the lack of official recommendations for Artificial Intelligence (AI) implementation has further impeded progress. Several recommendations for successful AI integration in higher education are proposed to address these challenges. These include developing a clear AI strategy that aligns with institutional goals, investing in infrastructure and staff training, and establishing guidelines for the ethical and transparent use of AI. The importance of involving all stakeholders in the decision-making process to ensure successful adoption is also stressed. The article offers valuable insights for policymakers and university leaders interested in harnessing the potential of AI to improve the quality of education and enhance the student experience.","PeriodicalId":430337,"journal":{"name":"Journal of Learning Letters","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127704644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward a Categorization of Indicators for Assessment Analytics 迈向评估分析指标的分类

Journal of Learning Letters Pub Date : 1900-01-01 DOI: 10.59453/cctb2003

Dirk Ifenthaler, Joana Heil, Samuel Greiff

引用次数: 0