Kirsty Kitto, Simon Buckingham Shum, and Andrew Gibson. (2018). Embracing Imperfection in Learning Analytics. In Proceedings of LAK18: International Conference on Learning Analytics and Knowledge, March 5–9, 2018, Sydney, NSW, Australia, pp.451-460. (ACM, New York, NY, USA). https://doi.org/10.1145/3170358.3170413
Open Access: http://simon.buckinghamshum.net/2018/01/embracing-imperfection-in-learning-analytics
Abstract: Learning Analytics (LA) sits at the confluence of many contributing disciplines, which brings the risk of hidden assumptions inherited from those fields. Here, we consider a hidden assumption derived from computer science, namely, that improving computational accuracy in classification is always a worthy goal. We demonstrate that this assumption is unlikely to hold in some important educational contexts, and argue that embracing computational “imperfection” can improve outcomes for those scenarios. Specifically, we show that learner-facing approaches aimed at “learning how to learn” require more holistic validation strategies. We consider what information must be provided in order to reasonably evaluate algorithmic tools in LA, to facilitate transparency and realistic performance comparisons.
CLARAfying project: http://utscic.edu.au/projects/uts-projects/science-learning-power
Developing Resilient Agency in Learning: use of CLARA for first year science students with coaching support
A work in progress briefing for the UTS First Year Experience Forum, Sept 2015
CLARAfying project: http://utscic.edu.au/projects/uts-projects/science-learning-power
Developing Resilient Agency in Learning: use of CLARA for first year science students with coaching support
A work in progress briefing for the UTS First Year Experience Forum, Sept 2015
What are systems and how does this apply to school leadership Ruth Deakin Crick
A presentation about systems thinking and its application to school leadership. With thanks to Patrick Godfrey and David Blockley from the Systems Centre at Bristol.
Teaching, Assessment and Learning Analytics: Time to Question AssumptionsSimon Buckingham Shum
Presented by the Assessment Research Centre
and the Melbourne Centre for the Study of Higher Education
Teaching, Assessment and Learning Analytics: Time to Question Assumptions
Simon Buckingham Shum
Professor of Learning Informatics, and Director of the Connected Intelligence Centre (CIC)
University of Technology Sydney
When: 11.30 -12.30 pm, Wed. 13 Sep 2017
Where: Frank Tate Room, Level 9, 100 Leicester St, Carlton
This will be a non-technical talk accessible to a broad range of educational practitioners and researchers, designed to provoke a conversation that provides time to question assumptions. The field of Learning Analytics sits at the convergence of two fields: Learning (including learning technology, educational research and learning/assessment sciences) and Analytics (statistics; visualisation; computer science; data science; AI). Many would add Human-Computer Interaction (e.g. participatory design; user experience; usability evaluation) as a differentiator from related fields such as Educational Data Mining, since the Learning Analytics community attracts many with a concern for the sociotechnical implications of designing and embedding analytics in educational organisations.
Learning Analytics is viewed by many educators with the same suspicion they reserve for AI or “learning management systems”. While in some cases this is justified, I will question other assumptions with some learning analytics examples which can serve as objects for us to think with. I am curious to know what connections/questions arise when these are shared..
Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, where he was appointed in August 2014 to direct the new Connected Intelligence Centre. Previously he was Professor of Learning Informatics and an Associate Director at The UK Open University’s Knowledge Media Institute. He is active in the field of Learning Analytics as a co-founder and former Vice President of the Society for Learning Analytics Research, and Program Co-Chair of LAK18, the International Learning Analytics and Knowledge Conference. Previously he co-founded the Compendium Institute and Learning Emergence networks. Simon brings a Human-Centred Informatics (HCI) approach to his work, with a background in Psychology (BSc, York), Ergonomics (MSc, London) and HCI Design Argumentation (PhD, York). He co-edited Visualizing Argumentation (2003) followed by Knowledge Cartography (2008, 2nd Edn. 2014), and with Al Selvin, wrote Constructing Knowledge Art (2015). He was recently appointed as a Fellow of The RSA. http://Simon.BuckinghamShum.net
Keynote Address, International Conference of the Learning Sciences, London Festival of Learning
Transitioning Education’s Knowledge Infrastructure:
Shaping Design or Shouting from the Touchline?
Abstract: Bit by bit, a data-intensive substrate for education is being designed, plumbed in and switched on, powered by digital data from an expanding sensor array, data science and artificial intelligence. The configurations of educational institutions, technologies, scientific practices, ethics policies and companies can be usefully framed as the emergence of a new “knowledge infrastructure” (Paul Edwards).
The idea that we may be transitioning into significantly new ways of knowing – about learning and learners – is both exciting and daunting, because new knowledge infrastructures redefine roles and redistribute power, raising many important questions. For instance, assuming that we want to shape this infrastructure, how do we engage with the teams designing the platforms our schools and universities may be using next year? Who owns the data and algorithms, and in what senses can an analytics/AI-powered learning system be ‘accountable’? How do we empower all stakeholders to engage in the design process? Since digital infrastructure fades quickly into the background, how can researchers, educators and learners engage with it mindfully? If we want to work in “Pasteur’s Quadrant” (Donald Stokes), we must go beyond learning analytics that answer research questions, to deliver valued services to frontline educational users: but how are universities accelerating the analytics innovation to infrastructure transition?
Wrestling with these questions, the learning analytics community has evolved since its first international conference in 2011, at the intersection of learning and data science, and an explicit concern with those human factors, at many scales, that make or break the design and adoption of new educational tools. We are forging open source platforms, links with commercial providers, and collaborations with the diverse disciplines that feed into educational data science. In the context of ICLS, our dialogue with the learning sciences must continue to deepen to ensure that together we influence this knowledge infrastructure to advance the interests of all stakeholders, including learners, educators, researchers and leaders.
Speaking from the perspective of leading an institutional analytics innovation centre, I hope that our experiences designing code, competencies and culture for learning analytics sheds helpful light on these questions.
Learning.Analytics for Learning.Futures?
Simon Buckingham Shum and Ruth Deakin Crick
Centre for Connected Intelligence, UTS
The social, technical and political challenges we face as a society demand new ways of thinking and working which are collaborative, holistic and resilient. As we unpack what these words mean, the implications for a university – indeed any learning organisation – run deep. At the core of the paradigm shift we see the need for learners (at all levels) to take increasing responsibility for their learning in authentic contexts: to become resilient agents of their own learning trajectories; to think holistically and to make sense of complex data. Far from being solely ‘graduate attributes’, the same qualities are needed by us: if we can’t model these qualities ourselves, we can’t teach them; if we can’t assess them authentically, we have no evidence base and we can’t provide formative feedback. This line of argument shapes how CIC is conceiving learning analytics (computer-supported tools to help learners and educators gather, analyse, visualise and act on learners’ data) and collective intelligence (networking tools to build a learning community’s evidence-base). In this talk we will give glimpses of these approaches in action, we’ll hear from learners and educators on what this paradigm shift feels like, and through several activities, we invite you to imagine how we can collaborate to test these concepts across UTS, as we move into Learning.Futures.
STEM education is about creating a student-centered, inquiry-based classroom where students discover the natural (and real-world) connection between science, technology, engineering, and math. As educators, it is our job to keep the flame of curiosity burning bright in our students in our classrooms and throughout their lives.
This webinar will explore the most effective strategies for Inquiry-Based Instruction with a focus on how STEM education connects to the Common Core State Standards.
You will learn:
Strategies for implementing inquiry-based instruction with an emphasis on critical thinking skills.
Effective ways to apply STEM competencies to impact lesson planning and assessment with a focus on increasing real-world application of content knowledge.
How STEM education connects to the instructional shifts embedded in the Common Core State Standards.
Crafting Hackerspaces with Moodle and Mahara: The Potential of Creation based...Jingjing Lin
Associated keynote talk can be found on YouTube: https://www.youtube.com/watch?v=slIITVfOhXg&t=1433s
On February 18, 2022, I delivered a rather interesting and important talk online to a group of 60ish educators, researchers, and practitioners on teaching with Moodle in MoodleMoot Japan 2022. If the following keywords interest you, you should not miss this video: ontology, epistemology, psychology, educational paradigms, learning theories, and pedagogy. This video also for the first time introduces an original untested learning theory called by me "creation-based learning (CBL)". I embrace the learning paradigms of #constructivism and #connectivism. I also am a strong fan of constructionism. I hope CBL will be one step further to promote active learning online. In this video, I also raised the idea of "sustainable learning behaviors" and raised the attention of the public towards sustainable learning behaviors of creating, maintaining, recycling, renewing, and sharing knowledge using networked digital technologies.
Tesla T-Pack Instructional Design Model in Virtual Reality for Deeper Learnin...2dimpaian
The presentation is related to the Instructional Design of the TESLA project; an innovative instructional design constitutes the basis of the Palestinian Universities Curriculum redesign to incorporate Virtual Reality Environments in the Higher Education teaching and learning practice.
In general, TESLA project will enable Palestinian HEIs to offer higher capabilities in translating some major key-concept into a dynamic and a fully interactive VR component.
Due to the special geopolitical context of Palestinian territories and restrictions imposed by the occupation, the virtual reality will offer students, researcher and academic staff in Palestinian universities the ability to conduct research in simulated virtual labs and avoiding on the same time mobility issues, access to material, lack of specialized laboratories, and the expensive character of such experiences.
On the other hand, virtual reality will be expanded in this project to include the instruction of GIS courses by a common learning management system using maps and built-in GIS tools which enable students to perform tests and simulate real-life conditions in an instructional evaluated context.
The main characteristics of the VR project will tend to offer better service then consolidate multiple functions into one tool, decreasing need for supplies and equipment, empowerment of users, improved interface, increased customizability, increased longevity, increased productivity, reduced user effort, reduced environmental impact, and finally saving of money.
Aims and Objectives
❖ Concrete aims
● Involving Palestinian HEI's in Research Movement related to Virtual Reality in Europe.
● Encourage Palestinian researchers and academics to have an interest in topics related to Ergonomics, Cognitive Psychology, and Human Impact.
● Reduce the cost of material related to experimentation and mobility issues.
● Reduce risks by offering simulated controlled environment and immersive learning experience.
● Involving Palestinian 3D Modellers and Programmers into the VR development process.
❖ Concrete Objectives
● Setting-up a common VR development framework throughout Palestinian HEI’s providing excellence in term of instructional design, development, and exploitation of services.
● Designing, piloting, and evaluating first courses which integrate the VR concept.
● Creating an international research network about VR integration into instructional technologies.
● Implementing immersive learning experience into technical courses with a high - level of abstraction like topography, criminology, and geography.
REFERENCE
TESLA / ERASMUS+ PROJECT
http://www.tesla-vr.net/index.php/en/index.php
International Journal of Humanities and Social Science Invention (IJHSSI)inventionjournals
is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
What is Heutagogy? And And how can we use it to help develop self-determined ...Lisa Marie Blaschke
Today's employees must readily adapt to quickly changing and complex work environments, and employers are looking to educational institutions to produce employment-ready students who will hit the ground running. Learning to learn has become an overarching theme, and as a result, interest in the theory of heutagogy, or the study of self-determined learning, is on the rise. This webinar would provide an overview of the theory as well as research- and practice-based examples of how we can help guide our students along the pedagogy-andragogy-heutagogy (PAH) continuum to become more self-determined learners.
Social and Cognitive Presence in Virtual Learning Environments Terry Anderson
Reviews and speculates on further development of the Community of Inquiry model (communitiesofinquiry.com) developed in Alberta by Randy Garrison, Terry Anderson, Walter Archer and Liam Rourke. This project developed theory and tools to measure teaching, cognitive and social presence in online environments
What are systems and how does this apply to school leadership Ruth Deakin Crick
A presentation about systems thinking and its application to school leadership. With thanks to Patrick Godfrey and David Blockley from the Systems Centre at Bristol.
Teaching, Assessment and Learning Analytics: Time to Question AssumptionsSimon Buckingham Shum
Presented by the Assessment Research Centre
and the Melbourne Centre for the Study of Higher Education
Teaching, Assessment and Learning Analytics: Time to Question Assumptions
Simon Buckingham Shum
Professor of Learning Informatics, and Director of the Connected Intelligence Centre (CIC)
University of Technology Sydney
When: 11.30 -12.30 pm, Wed. 13 Sep 2017
Where: Frank Tate Room, Level 9, 100 Leicester St, Carlton
This will be a non-technical talk accessible to a broad range of educational practitioners and researchers, designed to provoke a conversation that provides time to question assumptions. The field of Learning Analytics sits at the convergence of two fields: Learning (including learning technology, educational research and learning/assessment sciences) and Analytics (statistics; visualisation; computer science; data science; AI). Many would add Human-Computer Interaction (e.g. participatory design; user experience; usability evaluation) as a differentiator from related fields such as Educational Data Mining, since the Learning Analytics community attracts many with a concern for the sociotechnical implications of designing and embedding analytics in educational organisations.
Learning Analytics is viewed by many educators with the same suspicion they reserve for AI or “learning management systems”. While in some cases this is justified, I will question other assumptions with some learning analytics examples which can serve as objects for us to think with. I am curious to know what connections/questions arise when these are shared..
Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, where he was appointed in August 2014 to direct the new Connected Intelligence Centre. Previously he was Professor of Learning Informatics and an Associate Director at The UK Open University’s Knowledge Media Institute. He is active in the field of Learning Analytics as a co-founder and former Vice President of the Society for Learning Analytics Research, and Program Co-Chair of LAK18, the International Learning Analytics and Knowledge Conference. Previously he co-founded the Compendium Institute and Learning Emergence networks. Simon brings a Human-Centred Informatics (HCI) approach to his work, with a background in Psychology (BSc, York), Ergonomics (MSc, London) and HCI Design Argumentation (PhD, York). He co-edited Visualizing Argumentation (2003) followed by Knowledge Cartography (2008, 2nd Edn. 2014), and with Al Selvin, wrote Constructing Knowledge Art (2015). He was recently appointed as a Fellow of The RSA. http://Simon.BuckinghamShum.net
Keynote Address, International Conference of the Learning Sciences, London Festival of Learning
Transitioning Education’s Knowledge Infrastructure:
Shaping Design or Shouting from the Touchline?
Abstract: Bit by bit, a data-intensive substrate for education is being designed, plumbed in and switched on, powered by digital data from an expanding sensor array, data science and artificial intelligence. The configurations of educational institutions, technologies, scientific practices, ethics policies and companies can be usefully framed as the emergence of a new “knowledge infrastructure” (Paul Edwards).
The idea that we may be transitioning into significantly new ways of knowing – about learning and learners – is both exciting and daunting, because new knowledge infrastructures redefine roles and redistribute power, raising many important questions. For instance, assuming that we want to shape this infrastructure, how do we engage with the teams designing the platforms our schools and universities may be using next year? Who owns the data and algorithms, and in what senses can an analytics/AI-powered learning system be ‘accountable’? How do we empower all stakeholders to engage in the design process? Since digital infrastructure fades quickly into the background, how can researchers, educators and learners engage with it mindfully? If we want to work in “Pasteur’s Quadrant” (Donald Stokes), we must go beyond learning analytics that answer research questions, to deliver valued services to frontline educational users: but how are universities accelerating the analytics innovation to infrastructure transition?
Wrestling with these questions, the learning analytics community has evolved since its first international conference in 2011, at the intersection of learning and data science, and an explicit concern with those human factors, at many scales, that make or break the design and adoption of new educational tools. We are forging open source platforms, links with commercial providers, and collaborations with the diverse disciplines that feed into educational data science. In the context of ICLS, our dialogue with the learning sciences must continue to deepen to ensure that together we influence this knowledge infrastructure to advance the interests of all stakeholders, including learners, educators, researchers and leaders.
Speaking from the perspective of leading an institutional analytics innovation centre, I hope that our experiences designing code, competencies and culture for learning analytics sheds helpful light on these questions.
Learning.Analytics for Learning.Futures?
Simon Buckingham Shum and Ruth Deakin Crick
Centre for Connected Intelligence, UTS
The social, technical and political challenges we face as a society demand new ways of thinking and working which are collaborative, holistic and resilient. As we unpack what these words mean, the implications for a university – indeed any learning organisation – run deep. At the core of the paradigm shift we see the need for learners (at all levels) to take increasing responsibility for their learning in authentic contexts: to become resilient agents of their own learning trajectories; to think holistically and to make sense of complex data. Far from being solely ‘graduate attributes’, the same qualities are needed by us: if we can’t model these qualities ourselves, we can’t teach them; if we can’t assess them authentically, we have no evidence base and we can’t provide formative feedback. This line of argument shapes how CIC is conceiving learning analytics (computer-supported tools to help learners and educators gather, analyse, visualise and act on learners’ data) and collective intelligence (networking tools to build a learning community’s evidence-base). In this talk we will give glimpses of these approaches in action, we’ll hear from learners and educators on what this paradigm shift feels like, and through several activities, we invite you to imagine how we can collaborate to test these concepts across UTS, as we move into Learning.Futures.
STEM education is about creating a student-centered, inquiry-based classroom where students discover the natural (and real-world) connection between science, technology, engineering, and math. As educators, it is our job to keep the flame of curiosity burning bright in our students in our classrooms and throughout their lives.
This webinar will explore the most effective strategies for Inquiry-Based Instruction with a focus on how STEM education connects to the Common Core State Standards.
You will learn:
Strategies for implementing inquiry-based instruction with an emphasis on critical thinking skills.
Effective ways to apply STEM competencies to impact lesson planning and assessment with a focus on increasing real-world application of content knowledge.
How STEM education connects to the instructional shifts embedded in the Common Core State Standards.
Crafting Hackerspaces with Moodle and Mahara: The Potential of Creation based...Jingjing Lin
Associated keynote talk can be found on YouTube: https://www.youtube.com/watch?v=slIITVfOhXg&t=1433s
On February 18, 2022, I delivered a rather interesting and important talk online to a group of 60ish educators, researchers, and practitioners on teaching with Moodle in MoodleMoot Japan 2022. If the following keywords interest you, you should not miss this video: ontology, epistemology, psychology, educational paradigms, learning theories, and pedagogy. This video also for the first time introduces an original untested learning theory called by me "creation-based learning (CBL)". I embrace the learning paradigms of #constructivism and #connectivism. I also am a strong fan of constructionism. I hope CBL will be one step further to promote active learning online. In this video, I also raised the idea of "sustainable learning behaviors" and raised the attention of the public towards sustainable learning behaviors of creating, maintaining, recycling, renewing, and sharing knowledge using networked digital technologies.
Tesla T-Pack Instructional Design Model in Virtual Reality for Deeper Learnin...2dimpaian
The presentation is related to the Instructional Design of the TESLA project; an innovative instructional design constitutes the basis of the Palestinian Universities Curriculum redesign to incorporate Virtual Reality Environments in the Higher Education teaching and learning practice.
In general, TESLA project will enable Palestinian HEIs to offer higher capabilities in translating some major key-concept into a dynamic and a fully interactive VR component.
Due to the special geopolitical context of Palestinian territories and restrictions imposed by the occupation, the virtual reality will offer students, researcher and academic staff in Palestinian universities the ability to conduct research in simulated virtual labs and avoiding on the same time mobility issues, access to material, lack of specialized laboratories, and the expensive character of such experiences.
On the other hand, virtual reality will be expanded in this project to include the instruction of GIS courses by a common learning management system using maps and built-in GIS tools which enable students to perform tests and simulate real-life conditions in an instructional evaluated context.
The main characteristics of the VR project will tend to offer better service then consolidate multiple functions into one tool, decreasing need for supplies and equipment, empowerment of users, improved interface, increased customizability, increased longevity, increased productivity, reduced user effort, reduced environmental impact, and finally saving of money.
Aims and Objectives
❖ Concrete aims
● Involving Palestinian HEI's in Research Movement related to Virtual Reality in Europe.
● Encourage Palestinian researchers and academics to have an interest in topics related to Ergonomics, Cognitive Psychology, and Human Impact.
● Reduce the cost of material related to experimentation and mobility issues.
● Reduce risks by offering simulated controlled environment and immersive learning experience.
● Involving Palestinian 3D Modellers and Programmers into the VR development process.
❖ Concrete Objectives
● Setting-up a common VR development framework throughout Palestinian HEI’s providing excellence in term of instructional design, development, and exploitation of services.
● Designing, piloting, and evaluating first courses which integrate the VR concept.
● Creating an international research network about VR integration into instructional technologies.
● Implementing immersive learning experience into technical courses with a high - level of abstraction like topography, criminology, and geography.
REFERENCE
TESLA / ERASMUS+ PROJECT
http://www.tesla-vr.net/index.php/en/index.php
International Journal of Humanities and Social Science Invention (IJHSSI)inventionjournals
is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
What is Heutagogy? And And how can we use it to help develop self-determined ...Lisa Marie Blaschke
Today's employees must readily adapt to quickly changing and complex work environments, and employers are looking to educational institutions to produce employment-ready students who will hit the ground running. Learning to learn has become an overarching theme, and as a result, interest in the theory of heutagogy, or the study of self-determined learning, is on the rise. This webinar would provide an overview of the theory as well as research- and practice-based examples of how we can help guide our students along the pedagogy-andragogy-heutagogy (PAH) continuum to become more self-determined learners.
Social and Cognitive Presence in Virtual Learning Environments Terry Anderson
Reviews and speculates on further development of the Community of Inquiry model (communitiesofinquiry.com) developed in Alberta by Randy Garrison, Terry Anderson, Walter Archer and Liam Rourke. This project developed theory and tools to measure teaching, cognitive and social presence in online environments
The Generative AI System Shock, and some thoughts on Collective Intelligence ...Simon Buckingham Shum
Keynote Address: Team-based Learning Collaborative Asia Pacific Community (TBLC-APC) Symposium (“Impact of emerging technologies on learning strategies”) 8-9 February 2024, Sydney https://tbl.sydney.edu.au
Slides from my contribution to the panel convened by Jeremy Roschelle at the International Society for the Learning Sciences: Engaging Learning Scientists in Policy Challenges: AI and the Future of Learning
Deliberative Democracy as a strategy for co-designing university ethics aro...Simon Buckingham Shum
Buckingham Shum, S. (2021). Deliberative Democracy as a strategy for co-designing university ethics around analytics and AI in education. AARE2021: Australian Association for Research in Education, 28 Nov. – 2 Dec. 2021
Deliberative Democracy as a Strategy for Co-designing University Ethics Around Analytics and AI in Education
Simon Buckingham Shum
Connected Intelligence Centre, University of Technology Sydney
Universities can see an increasing range of student and staff activity as it becomes digitally visible in their platform ecosystems. The fields of Learning Analytics and AI in Education have demonstrated the significant benefits that ethically responsible, pedagogically informed analysis of student activity data can bring, but such services are only possible because they are undeniably a form of “surveillance”, raising legitimate questions about how the use of such tools should be governed.
Our prior work has drawn on the rich concepts and methods developed in human-centred system design, and participatory/co-design, to design, deploy and validate practical tools that give a voice to non-technical stakeholders (e.g. educators; students) in shaping such systems. We are now expanding the depth and breadth of engagement that we seek, looking to the Deliberative Democracy movement for inspiration. This is a response to the crisis in confidence in how typical democratic systems engage citizens in decision making. A hallmark is the convening of a Deliberative Mini-Public (DMP) which may work at different scales (organisation; community; region; nation) and can take diverse forms (e.g. Citizens’ Juries; Citizens’ Assemblies; Consensus Conferences; Planning Cells; Deliberative Polls). DMP’s combination of stratified random sampling to ensure authentic representation, neutrally facilitated workshops, balanced expert briefings, and real support from organisational leaders, has been shown to cultivate high quality dialogue in sometimes highly conflicted settings, leading to a strong sense of ownership of the DMP's final outputs (e.g. policy recommendations).
This symposium contribution will describe how the DMP model is informing university-wide consultation on the ethical principles that should govern the use of analytics and AI around teaching and learning data.
March 2021 • 24/7 Instant Feedback on Writing: Integrating AcaWriter into yo...Simon Buckingham Shum
Slides accompanying the monthly UTS educator briefing https://cic.uts.edu.au/events/24-7-instant-feedback-on-writing-integrating-acawriter-into-your-teaching-18-march/
What difference could instant feedback on draft writing make to your students? Over the last 5 years the Connected Intelligence Centre has been developing and piloting an automated feedback tool for academic writing (AcaWriter), working closely with academics across several faculties. The research portal documents how educators and students engage with this kind of AI, and what we’ve learnt about integrating it into teaching and assessment.
In May, AcaWriter was launched to all students along with an information portal. Now we want to start upskilling academics, tutors and learning technologists, in a monthly session to give you the chance to learn about AcaWriter, and specifically, good practices for integrating it into your subject. CIC can support you, and we hope you may be interested in co-designing publishable research.
AcaWriter handles several different ‘genres’ of writing, including reflective writing (e.g. a Reflective Essay; Reflective Blogs/Journals on internships/work-placements) and analytical writing (e.g. Argumentative Essays; Research Abstracts & Introductions). This briefing will demo AcaWriter, and show it can be embedded in student activities. We hope this sparks ideas for your own teaching, which we can discuss in more detail.
ICQE20: Quantitative Ethnography Visualizations as Tools for ThinkingSimon Buckingham Shum
Slides for this keynote talk to the 2nd International Conference on Quantitative Ethnography
http://simon.buckinghamshum.net/2021/02/icqe2020-keynote-qe-viz-as-tools-for-thinking/
24/7 Instant Feedback on Writing: Integrating AcaWriter into your TeachingSimon Buckingham Shum
https://cic.uts.edu.au/events/24-7-instant-feedback-on-writing-integrating-acawriter-into-your-teaching-2-dec/
What difference could instant feedback on draft writing make to your students? Over the last 5 years the Connected Intelligence Centre has been developing and piloting an automated feedback tool for academic writing (AcaWriter), working closely with academics across several faculties. The research portal documents how educators and students engage with this kind of AI, and what we’ve learnt about integrating it into teaching and assessment.
In May, AcaWriter was launched to all students along with an information portal. Now we want to start upskilling academics, tutors and learning technologists, in a monthly session to give you the chance to learn about AcaWriter, and specifically, good practices for integrating it into your subject. CIC can support you, and we hope you may be interested in co-designing publishable research.
AcaWriter handles several different ‘genres’ of writing, including reflective writing (e.g. a Reflective Essay; Reflective Blogs/Journals on internships/work-placements) and analytical writing (e.g. Argumentative Essays; Research Abstracts & Introductions).
This briefing will demo AcaWriter, and show it can be embedded in student activities. We hope this sparks ideas for your own teaching, which we can discuss in more detail.
An introduction to argumentation for UTS:CIC PhD students (with some Learning Analytics examples, but potentially of wider interest to students/researchers)
Webinar: Learning Informatics Lab, University of Minnesota
Replay the talk: https://youtu.be/dcJZeDIMr2I
Learning Informatics
AI • Analytics • Accountability • Agency
Simon Buckingham Shum
Professor of Learning Informatics
Director, Connected Intelligence Centre
University of Technology Sydney
Abstract:
“Health Informatics”. “Urban Informatics”. “Social Informatics”. Informatics offers systemic ways of analyzing and designing the interaction of natural and artificial information processing systems. In the context of education, I will describe some Learning Informatics lenses and practices which we have developed for co-designing analytics and AI with educators and students. We have a particular focus on closing the feedback loop to equip learners with competencies to navigate a complex, uncertain future, such as critical thinking, professional reflection and teamwork. En route, we will touch on how we build educators’ trust in novel tools, our design philosophy of “embracing imperfection” in machine intelligence, and the ways that these infrastructures embody values. Speaking from the perspective of leading an institutional innovation centre in learning analytics, I hope that our experiences spark productive reflection around as the UMN Learning Informatics Lab builds its program.
Biography:
Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, where he serves as inaugural director of the Connected Intelligence Centre. CIC is a transdisciplinary innovation centre, using analytics to provide new insights for university teams, with particular expertise in educational data science. Simon’s career-long fascination with software’s ability to make thinking visible has seen him active in communities including Computer-Supported Cooperative Work, Hypertext, Design Rationale, Scholarly Publishing, Semantic Web, Computational Argumentation, Educational Technology and Learning Analytics. The challenge of visualizing contested knowledge has produced several books: Visualizing Argumentation, Knowledge Cartography, and Constructing Knowledge Art. He has been active over the last decade in shaping the field of Learning Analytics, co-founding the Society for Learning Analytics Research, and catalyzing several strands: Social Learning Analytics, Discourse Analytics, Dispositional Analytics and Writing Analytics. http://Simon.BuckinghamShum.net
Despite AI’s potential for beneficial use, it creates important risks for Australians. AI, big data, and AI-informed decision making can cause exclusion, discrimination, skill loss, and economic impact; and can affect privacy, security of critical infrastructure and social well-being. What types of technology raise particular human rights concerns? Which human rights are particularly implicated?
Abstract: The emerging configuration of educational institutions, technologies, scientific practices, ethics policies and companies can be usefully framed as the emergence of a new “knowledge infrastructure” (Paul Edwards). The idea that we may be transitioning into significantly new ways of knowing – about learning and learners, teaching and teachers – is both exciting and daunting, because new knowledge infrastructures redefine roles and redistribute power, raising many important questions. What should we see when open the black box powering analytics? How do we empower all stakeholders to engage in the design process? Since digital infrastructure fades quickly into the background, how can researchers, educators and learners engage with it mindfully? This isn’t just interesting to ponder academically: your school or university will be buying products that are being designed now. Or perhaps educational institutions should take control, building and sharing their own open source tools? How are universities accelerating the transition from analytics innovation to infrastructure? Speaking from the perspective of leading an institutional innovation centre in learning analytics, I hope that our experiences designing code, competencies and culture for learning analytics sheds helpful light on these questions.
Towards Collaboration Translucence: Giving Meaning to Multimodal Group DataSimon Buckingham Shum
Vanessa Echeverria, Roberto Martinez-Maldonado, and Simon Buck- ingham Shum.. 2019. Towards Collaboration Translucence: Giving Meaning to Multimodal Group Data. In Proceedings of ACM CHI conference (CHI’19). ACM, New York, NY, USA, Paper 39, 16 pages. https://doi.org/10.1145/3290605.3300269
Collocated, face-to-face teamwork remains a pervasive mode of working, which is hard to replicate online. Team members’ embodied, multimodal interaction with each other and artefacts has been studied by researchers, but due to its complexity, has remained opaque to automated analysis. However, the ready availability of sensors makes it increasingly affordable to instrument work spaces to study teamwork and groupwork. The possibility of visualising key aspects of a collaboration has huge potential for both academic and professional learning, but a frontline challenge is the enrichment of quantitative data streams with the qualitative insights needed to make sense of them. In response, we introduce the concept of collaboration translucence, an approach to make visible selected features of group activity. This is grounded both theoretically (in the physical, epistemic, social and affective dimensions of group activity), and contextually (using domain-specific concepts). We illustrate the approach from the automated analysis of healthcare simulations to train nurses, generating four visual proxies that fuse multimodal data into higher order patterns.
Panel held at LAK13: 3rd International Conference on Learning Analytics & Knowledge
http://simon.buckinghamshum.net/2013/03/lak13-edu-data-scientists-scarce-breed
Educational Data Scientists: A Scarce Breed
The Educational Data Scientist is currently a poorly understood, rarely sighted breed. Reports vary: some are known to be largely nocturnal, solitary creatures, while others have been reported to display highly social behaviour in broad daylight. What are their primary habits? How do they see the world? What ecological niches do they occupy now, and will predicted seismic shifts transform the landscape in their favour? What survival skills do they need when running into other breeds? Will their numbers grow, and how might they evolve? In this panel, the conference will hear and debate not only broad perspectives on the terrain, but will have been exposed to some real life specimens, and caught glimpses of the future ecosystem.
Opening to the inaugural workshop on Learning Analytics in Schools held at LAK18: International Conference on Learning Analytics & Knowledge, Sydney. http://lak18.solaresearch.org
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
6. 6
Scheffel, M., Drachsler, H., Stoyanov, S., Specht, M.: Quality Indicators for Learning Analytics. Educational Technology &
Society 17(4), 117–132 (2014)
Scheffel, M. (2017). The Evaluation Framework for Learning Analytics.
7. 7
Scheffel, M., Drachsler, H., Stoyanov, S., Specht, M.: Quality Indicators for Learning Analytics. Educational Technology &
Society 17(4), 117–132 (2014)
Scheffel, M. (2017). The Evaluation Framework for Learning Analytics.
8. does LA help learning?
While EDM aims to improve learning outcomes, its
“emphasis on the ‘educational’ aspect of educational data
mining has been scarce. . . One reason for this is the
inclination of researchers to evaluate EDM research
primarily for model fits and predictive accuracy rather than
for plausibility, interpretability, and generalizable insights.”
8
9. does LA help learning?
While EDM aims to improve learning outcomes, its
“emphasis on the ‘educational’ aspect of educational data
mining has been scarce. . . One reason for this is the
inclination of researchers to evaluate EDM research
primarily for model fits and predictive accuracy rather than
for plausibility, interpretability, and generalizable insights.”
9
Ran Liu and Kenneth R Koedinger. 2017. Closing the loop: Automated data-driven cognitive model discoveries lead
to improved instruction and learning gains. JEDM-Journal of Educational Data Mining 9, 1 (2017), 25–41.
14. 14
Should the distributed intelligence of the whole
system’s performance (humans + technology) be the
output measure?
Or, should we also be concerned with the effects on
human performance when stripped of the technology?
Gavriel Salomon, David N Perkins, and Tamar Globerson. 1991. Partners in
cognition: Extending human intelligence with intelligent technologies. Educational
researcher 20, 3 (1991), 2–9.
15. learning to learn
15
“equipping students with knowledge, skills, and
dispositions that prepare them for lifelong
learning, in a complex and uncertain world”
“Creativity, critical thinking, agency, curiosity, and an
ability to tolerate uncertainty...”
arguably the purpose of analytics-powered pedagogy in such
contexts is to provoke productive reflection on one’s
strengths and weaknesses — these are higher order
competencies, into which a machine can have limited insight
Buckingham Shum, S. and Deakin Crick, R. (2016). Learning analytics for 21st century competencies.
Journal of Learning Analytics, 3, (2), 6–21.
16. authentic learning: vital but challenging for LA
16
wicked problems: how do we provide LA
when there is no correct answer?
transformed perspective: the sense that a
learner makes of their experience, or a shift in
worldview, which by definition is not accessible to
the machine, but to which a machine might have
partial access
socially and psychologically complex
performance: scenarios where the outcome is
emergent in nature, a function of many drivers
that result in unpredictable and/or unique
outcomes, often because social interaction is
central to the process
analytics in such contexts will
in principle have a high degree
of imperfection!
18. 18
Turpin, Scholer (2006). User performance versus precision
measures for simple search tasks. In Proceedings of the 29th
annual international ACM SIGIR conference on Research and
development in information retrieval (pp. 11-18). ACM.
a cautionary tale
from information
retrieval
19. 19
are we measuring what we value?
or merely valuing what we can
measure?
Gordon Wells and Guy Claxton. 2008. Learning for life in the 21st century: Sociocultural
perspectives on the future of education. John Wiley & Sons.
21. cognitive presence
https://plus.google.com/u/0/+StefanPSchmid/posts/4wrUbFzFwpJ
“extent to which the participants in any particular
configuration of a community of inquiry are able to
construct meaning through sustained communication.”
Triggering
Exploration
Integration
Resolution
Garrison, Anderson, Archer (2001) Critical thinking, cognitive presence,
and computer conferencing in distance education. American journal of
distance education, 15(1):7–23
22. Kovanović, Joksimović, Waters, Gašević, Kitto, Hatala, Siemens (2016).
Towards automated content analysis of discussion transcripts: a cognitive
presence case. In Proceedings of the Sixth International Conference on
Learning Analytics & Knowledge (LAK '16). ACM, New York, NY, USA, 15-24.
we can use machine
learning to classify
discussion forum text
using this construct
24. how accurate does it have to be?
data was unbalanced (solved using boosting)
▪ is it overfitted for one “type” of learning scenario?
▪ how accurate will it be if used in another context?
▪ how different does a situation have to be before we retrain?
how are we going to use it?
▪ who sees the classifications?
▪ what happens if the classifier is wrong?
24
27. A very strong reflection from most recent trial?
27
In Week 2 I was very aspirational about the role I wanted to play; ‘I would like my profile
to be professional, respectful, organised, connected and visible. I aim to be an active
participant within “reflection and critical discourse that is the core dynamic of a
community of inquiry”. I achieved my aim of being an active participant as I made over
75 comments on my peers’ posts, averaging over 5 per week. However I feel I did not
participate fully in all 4 phases of the cognitive presence in the Practical [sic] Inquiry
Model; triggering event, exploration, integration and resolution – despite
having sentence openers taped next to my computer! Triggering events and some
exploration were met by sharing an interesting article relevant to a post I had read and
also asking some questions, but I felt a lot of my posts were agreeing with and
complimenting upon the erudite musings of my peers. I was definitely wary of
confronting differing ideas and promoting a critical discourse. This participation in all
cognitive phases needs improving so the sentence openers will remain up! [score=4]
Kirsty Kitto, Mandy Lupton, Kate Davis, and Zak Waters. 2017. Designing for student-facing learning analytics.
Australian Journal of Educational Technology, 33, 5 (2017), 152–168.
29. the Navajo rug
In a Navajo rug there is always an
imperfection woven into the corner. And
interestingly enough, it's where “the Spirit
moves in and out of the rug.” The pattern
is perfect and then there's one part of it
that clearly looks like a mistake …
Perfection is not the elimination of
imperfection. That's our Western either/or,
need-to-control thinking. Perfection,
rather, is the ability to incorporate
imperfection!
29
http://exhibitions.kelsey.lsa.umich.edu/less-than-perfect/navajo.php
Breathing Under Water: Spirituality and the 12 Steps,
by Richard Rohr
30. the Navajo rug
In a Navajo rug there is always an
imperfection woven into the corner. And
interestingly enough, it's where “the Spirit
moves in and out of the rug.” The pattern
is perfect and then there's one part of it
that clearly looks like a mistake …
Perfection is not the elimination of
imperfection. That's our Western either/or,
need-to-control thinking. Perfection,
rather, is the ability to incorporate
imperfection!
30
http://exhibitions.kelsey.lsa.umich.edu/less-than-perfect/navajo.php
Breathing Under Water: Spirituality and the 12 Steps,
by Richard Rohr
31. 31
active learning squared (AL2)
the student trains the classifier...
...while it is training the student…
Kirsty Kitto, Mandy Lupton, Kate Davis, and Zak Waters. 2017. Designing for student-facing learning analytics.
Australian Journal of Educational Technology, 33, 5 (2017), 152–168.
35. 35
LAK17 Best Paper / Academic Writing Analytics: https://utscic.edu.au/tools/awa
see the paper for second example of imperfection:
automated formative feedback on reflective writing
37. embracing imperfection
37
so imperfection in our LA tools opens up new opportunities
▪ teachable moments
▪ intelligence augmentation
▪ mindful engagement with automated feedback
▪ learning to challenge computational decisions
▪ accelerates presence of more advanced LA in
education
but to get to this point we need to ensure that mature LA tools
are evaluated holistically!
38. as machine intelligence
reduces, we can increase
human agency (and learning)
through good LD
38
Gavriel Salomon, David N Perkins, and Tamar Globerson.
1991. Partners in cognition: Extending human intelligence
with intelligent technologies. Educational researcher 20, 3
(1991), 2–9.
“nonautomatic, effortful and thus
metacognitively guided processes”
40. towards comprehensive evaluation for LA
mature student facing LA (that aims to help students learn how
to learn) needs to be evaluated across a range of criteria
in the paper we explore:
1. Learning design
2. Model
3. Feedback
4. Sensemaking/gain
5. Accuracy
40
41. applying this to AL2
41
Learning design: this learning design aims to teach (i) data literacy (i.e. that
ML can be wrong) and (ii) a basic educational construct
Model: dual process model of cognition
Feedback: automatic classifications are appended to student comments and
presented in a new display
Sensemaking/gain: The interface allows the student to (i) change the
classification of their post, (ii), highlight components of the post that they feel
are indicative of the classification they have chosen, (iii) leave a comment
about why they chose that classification.
Accuracy: to date - very low in pilot trials (30.2%!)
42. conclusions
42
▪ perfect accuracy in LA is unlikely to be possible in a wide
range of authentic learning scenarios…
▪ … nor is it always desirable — embracing imperfection
opens up new possibilities for teachable moments!
▪ imperfection is sometimes a feature not a bug
Alexander Johmann: https://www.flickr.com/photos/alexander_johmann/78028029