際際滷shows by User: sbs / http://www.slideshare.net/images/logo.gif 際際滷shows by User: sbs / Wed, 14 Feb 2024 23:53:21 GMT 際際滷Share feed for 際際滷shows by User: sbs The Generative AI System Shock, and some thoughts on Collective Intelligence and Teamwork Analytics /slideshow/the-generative-ai-system-shock-and-some-thoughts-on-collective-intelligence-and-teamwork-analytics/266313206 sbstbl2024-240214235321-f22a2b7f
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]]>
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]]> Wed, 14 Feb 2024 23:53:21 GMT /slideshow/the-generative-ai-system-shock-and-some-thoughts-on-collective-intelligence-and-teamwork-analytics/266313206 sbs@slideshare.net(sbs) The Generative AI System Shock, and some thoughts on Collective Intelligence and Teamwork Analytics sbs 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 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sbstbl2024-240214235321-f22a2b7f-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 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
The Generative AI System Shock, and some thoughts on Collective Intelligence and Teamwork Analytics from Simon Buckingham Shum
]]> 194 0 https://cdn.slidesharecdn.com/ss_thumbnails/sbstbl2024-240214235321-f22a2b7f-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Could Generative AI Augment Reflection, Deliberation and Argumentation? /slideshow/could-generative-ai-augment-reflection-deliberation-and-argumentation/258102512 sbsct2023genai-230529104518-ec02d4fe
Critical Deliberative Democracy Tech Workshop, 11th International Conference on Communities & Technologies ]]>
Critical Deliberative Democracy Tech Workshop, 11th International Conference on Communities & Technologies ]]> Mon, 29 May 2023 10:45:17 GMT /slideshow/could-generative-ai-augment-reflection-deliberation-and-argumentation/258102512 sbs@slideshare.net(sbs) Could Generative AI Augment Reflection, Deliberation and Argumentation? sbs Critical Deliberative Democracy Tech Workshop, 11th International Conference on Communities & Technologies <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sbsct2023genai-230529104518-ec02d4fe-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Critical Deliberative Democracy Tech Workshop, 11th International Conference on Communities &amp; Technologies
Could Generative AI Augment Reflection, Deliberation and Argumentation? from Simon Buckingham Shum
]]> 466 0 https://cdn.slidesharecdn.com/ss_thumbnails/sbsct2023genai-230529104518-ec02d4fe-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Conversational, generative AI as a cognitive tool for critical thinking /slideshow/conversational-generative-ai-as-a-cognitive-tool-for-critical-thinking/257863013 bingedgechatargmaps-230516120525-bd9d4e63
Using GPT-4 (via MS Edge browser) with ArgDown to generate and test Argument Maps from a source text]]>
Using GPT-4 (via MS Edge browser) with ArgDown to generate and test Argument Maps from a source text]]> Tue, 16 May 2023 12:05:25 GMT /slideshow/conversational-generative-ai-as-a-cognitive-tool-for-critical-thinking/257863013 sbs@slideshare.net(sbs) Conversational, generative AI as a cognitive tool for critical thinking sbs Using GPT-4 (via MS Edge browser) with ArgDown 鐃to generate and test Argument Maps from a source text <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bingedgechatargmaps-230516120525-bd9d4e63-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Using GPT-4 (via MS Edge browser) with ArgDown 鐃to generate and test Argument Maps from a source text
Conversational, generative AI as a cognitive tool for critical thinking from Simon Buckingham Shum
]]> 203 0 https://cdn.slidesharecdn.com/ss_thumbnails/bingedgechatargmaps-230516120525-bd9d4e63-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 On the Design of a Writing App offering 24/7 Formative Feedback on Reflective Writing /slideshow/on-the-design-of-a-writing-app-offering-247-formative-feedback-on-reflective-writing/253696772 sbs-unimelbarc-oct22-221019031232-8d1f4890
Seminar, Assessment Research Centre, University of Melbourne]]>
Seminar, Assessment Research Centre, University of Melbourne]]> Wed, 19 Oct 2022 03:12:32 GMT /slideshow/on-the-design-of-a-writing-app-offering-247-formative-feedback-on-reflective-writing/253696772 sbs@slideshare.net(sbs) On the Design of a Writing App offering 24/7 Formative Feedback on Reflective Writing sbs Seminar, Assessment Research Centre, University of Melbourne <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sbs-unimelbarc-oct22-221019031232-8d1f4890-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Seminar, Assessment Research Centre, University of Melbourne
On the Design of a Writing App offering 24/7 Formative Feedback on Reflective Writing from Simon Buckingham Shum
]]> 56 0 https://cdn.slidesharecdn.com/ss_thumbnails/sbs-unimelbarc-oct22-221019031232-8d1f4890-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 SBS_ISLS2022.pdf /slideshow/sbsisls2022pdf/251937213 sbsisls2022-220607132836-16774d3c
際際滷s 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]]>
際際滷s 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]]> Tue, 07 Jun 2022 13:28:36 GMT /slideshow/sbsisls2022pdf/251937213 sbs@slideshare.net(sbs) SBS_ISLS2022.pdf sbs 際際滷s 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 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sbsisls2022-220607132836-16774d3c-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s 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
SBS_ISLS2022.pdf from Simon Buckingham Shum
]]> 132 0 https://cdn.slidesharecdn.com/ss_thumbnails/sbsisls2022-220607132836-16774d3c-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Is The Matter With Things also 鐃whats the matter with Learning Analytics? /slideshow/is-the-matter-with-things-also-whats-the-matter-with-learning-analytics/251414361 lak22polaslidessbs-220324053823
https://simon.buckinghamshum.net/2022/03/the-matter-with-things-and-learning-analytics/]]>
https://simon.buckinghamshum.net/2022/03/the-matter-with-things-and-learning-analytics/]]> Thu, 24 Mar 2022 05:38:23 GMT /slideshow/is-the-matter-with-things-also-whats-the-matter-with-learning-analytics/251414361 sbs@slideshare.net(sbs) Is The Matter With Things also 鐃whats the matter with Learning Analytics? sbs https://simon.buckinghamshum.net/2022/03/the-matter-with-things-and-learning-analytics/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lak22polaslidessbs-220324053823-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> https://simon.buckinghamshum.net/2022/03/the-matter-with-things-and-learning-analytics/
Is The Matter With Things also whats the matter with Learning Analytics? from Simon Buckingham Shum
]]> 178 0 https://cdn.slidesharecdn.com/ss_thumbnails/lak22polaslidessbs-220324053823-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Deliberative Democracy as a strategy 鐃for co-designing university ethics 鐃around analytics and AI in education /slideshow/deliberative-democracy-as-a-strategy-for-codesigning-university-ethics-around-analytics-and-ai-in-education/250786696 aare2021deliberativedemocracyethics-211205222554
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). DMPs 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.]]>
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). DMPs 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.]]> Sun, 05 Dec 2021 22:25:54 GMT /slideshow/deliberative-democracy-as-a-strategy-for-codesigning-university-ethics-around-analytics-and-ai-in-education/250786696 sbs@slideshare.net(sbs) Deliberative Democracy as a strategy 鐃for co-designing university ethics 鐃around analytics and AI in education sbs 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). DMPs 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aare2021deliberativedemocracyethics-211205222554-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 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). DMPs 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&#39;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.
Deliberative Democracy as a strategy for co-designing university ethics around analytics and AI in education from Simon Buckingham Shum
]]> 217 0 https://cdn.slidesharecdn.com/ss_thumbnails/aare2021deliberativedemocracyethics-211205222554-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Knowledge Art or Participatory Improvisational DVN /slideshow/knowledge-art-or-participatory-improvisational-dvn/245420507 knowledgeart-mdsiguestlecture-mar-210331233936
Guest Lecture, UTS Master of Data Science & Innovation36104 Data Visualisation & Narratives (DVN), 31st Mar. 2021 ]]>
Guest Lecture, UTS Master of Data Science & Innovation36104 Data Visualisation & Narratives (DVN), 31st Mar. 2021 ]]> Wed, 31 Mar 2021 23:39:36 GMT /slideshow/knowledge-art-or-participatory-improvisational-dvn/245420507 sbs@slideshare.net(sbs) Knowledge Art or Participatory Improvisational DVN sbs Guest Lecture, UTS Master of Data Science & Innovation鐃36104 Data Visualisation & Narratives (DVN), 31st Mar. 2021 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/knowledgeart-mdsiguestlecture-mar-210331233936-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Guest Lecture, UTS Master of Data Science &amp; Innovation鐃36104 Data Visualisation &amp; Narratives (DVN), 31st Mar. 2021
Knowledge Art or Participatory Improvisational DVN from Simon Buckingham Shum
]]> 230 0 https://cdn.slidesharecdn.com/ss_thumbnails/knowledgeart-mdsiguestlecture-mar-210331233936-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 March 2021 24/7 Instant Feedback on Writing: 鐃Integrating AcaWriter into your Teaching /slideshow/march-2021-247-instant-feedback-on-writing-integrating-acawriter-into-your-teaching/244641083 acawriterlxlabmar2021-210318054532
際際滷s 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 weve 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.]]>
際際滷s 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 weve 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.]]> Thu, 18 Mar 2021 05:45:32 GMT /slideshow/march-2021-247-instant-feedback-on-writing-integrating-acawriter-into-your-teaching/244641083 sbs@slideshare.net(sbs) March 2021 24/7 Instant Feedback on Writing: 鐃Integrating AcaWriter into your Teaching sbs 際際滷s 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 weve 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/acawriterlxlabmar2021-210318054532-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s 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 weve 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 &amp; 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.
March 2021 腦吟 24/7 Instant Feedback on Writing: Integrating AcaWriter into your Teaching from Simon Buckingham Shum
]]> 148 0 https://cdn.slidesharecdn.com/ss_thumbnails/acawriterlxlabmar2021-210318054532-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 ICQE20: Quantitative Ethnography Visualizations as Tools for Thinking /slideshow/icqe20-quantitative-ethnography-visualizations-as-tools-for-thinking/242378542 sbsicqe2020keynote-210207100906
際際滷s 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/ ]]>
際際滷s 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/ ]]> Sun, 07 Feb 2021 10:09:06 GMT /slideshow/icqe20-quantitative-ethnography-visualizations-as-tools-for-thinking/242378542 sbs@slideshare.net(sbs) ICQE20: Quantitative Ethnography Visualizations as Tools for Thinking sbs 際際滷s 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/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sbsicqe2020keynote-210207100906-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s 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/
ICQE20: Quantitative Ethnography Visualizations as Tools for Thinking from Simon Buckingham Shum
]]> 460 0 https://cdn.slidesharecdn.com/ss_thumbnails/sbsicqe2020keynote-210207100906-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 24/7 Instant Feedback on Writing: Integrating AcaWriter into your Teaching /slideshow/247-instant-feedback-on-writing-integrating-acawriter-into-your-teaching/239671577 utsacawriterlxlab2020-201202054029
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 weve 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.]]>
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 weve 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.]]> Wed, 02 Dec 2020 05:40:29 GMT /slideshow/247-instant-feedback-on-writing-integrating-acawriter-into-your-teaching/239671577 sbs@slideshare.net(sbs) 24/7 Instant Feedback on Writing: Integrating AcaWriter into your Teaching sbs 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 weve 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/utsacawriterlxlab2020-201202054029-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 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 weve 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 &amp; 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.
24/7 Instant Feedback on Writing: Integrating AcaWriter into your Teaching from Simon Buckingham Shum
]]> 193 0 https://cdn.slidesharecdn.com/ss_thumbnails/utsacawriterlxlab2020-201202054029-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Argumentation 101 for Learning Analytics PhDs! /slideshow/argumentation-101-for-learning-analytics-phds/238847657 argumentation101forlaphds-201013032252
An introduction to argumentation for UTS:CIC PhD students (with some Learning Analytics examples, but potentially of wider interest to students/researchers)]]>
An introduction to argumentation for UTS:CIC PhD students (with some Learning Analytics examples, but potentially of wider interest to students/researchers)]]> Tue, 13 Oct 2020 03:22:52 GMT /slideshow/argumentation-101-for-learning-analytics-phds/238847657 sbs@slideshare.net(sbs) Argumentation 101 for Learning Analytics PhDs! sbs An introduction to argumentation for UTS:CIC PhD students (with some Learning Analytics examples, but potentially of wider interest to students/researchers) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/argumentation101forlaphds-201013032252-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> An introduction to argumentation for UTS:CIC PhD students (with some Learning Analytics examples, but potentially of wider interest to students/researchers)
Argumentation 101 for Learning Analytics PhDs! from Simon Buckingham Shum
]]> 1748 0 https://cdn.slidesharecdn.com/ss_thumbnails/argumentation101forlaphds-201013032252-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Learning Informatics: AI Analytics Accountability Agency /slideshow/learning-informatics-ai-analytics-accountability-agency/238640773 sbslearninginformaticsumn2020-200925023942
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. Simons career-long fascination with softwares 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 ]]>
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. Simons career-long fascination with softwares 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 ]]> Fri, 25 Sep 2020 02:39:42 GMT /slideshow/learning-informatics-ai-analytics-accountability-agency/238640773 sbs@slideshare.net(sbs) Learning Informatics: AI Analytics Accountability Agency sbs 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. Simons career-long fascination with softwares 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 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sbslearninginformaticsumn2020-200925023942-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 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. Simons career-long fascination with softwares 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
Learning Informatics: AI 腦吟 Analytics 腦吟 Accountability 腦吟 Agency from Simon Buckingham Shum
]]> 603 0 https://cdn.slidesharecdn.com/ss_thumbnails/sbslearninginformaticsumn2020-200925023942-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 AI/Data Analytics (AIDA): Key concepts, examples & risks /slideshow/aidata-analytics-aida-key-concepts-examples-risks/205251436 aidaethics-acossintro-sept2019-191213060117
Despite AIs 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?]]>
Despite AIs 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?]]> Fri, 13 Dec 2019 06:01:17 GMT /slideshow/aidata-analytics-aida-key-concepts-examples-risks/205251436 sbs@slideshare.net(sbs) AI/Data Analytics (AIDA): Key concepts, examples & risks sbs Despite AIs 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? <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aidaethics-acossintro-sept2019-191213060117-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Despite AIs 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?
AI/Data Analytics (AIDA): Key concepts, examples & risks from Simon Buckingham Shum
]]> 423 3 https://cdn.slidesharecdn.com/ss_thumbnails/aidaethics-acossintro-sept2019-191213060117-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Learning Analytics as Educational Knowledge Infrastructure /slideshow/learning-analytics-as-educational-knowledge-infrastructure/161513573 sbssolarwebinaraug2019-190806090837
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 isnt 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.]]>
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 isnt 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.]]> Tue, 06 Aug 2019 09:08:37 GMT /slideshow/learning-analytics-as-educational-knowledge-infrastructure/161513573 sbs@slideshare.net(sbs) Learning Analytics as Educational Knowledge Infrastructure sbs 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 isnt 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sbssolarwebinaraug2019-190806090837-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 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 isnt 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.
Learning Analytics as Educational Knowledge Infrastructure from Simon Buckingham Shum
]]> 749 7 https://cdn.slidesharecdn.com/ss_thumbnails/sbssolarwebinaraug2019-190806090837-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Towards Collaboration Translucence: Giving Meaning to Multimodal Group Data /slideshow/towards-collaboration-translucence-giving-meaning-to-multimodal-group-data/144566918 chi2019collabtransslides-190509095604
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 (CHI19). 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.]]>
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 (CHI19). 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.]]> Thu, 09 May 2019 09:56:04 GMT /slideshow/towards-collaboration-translucence-giving-meaning-to-multimodal-group-data/144566918 sbs@slideshare.net(sbs) Towards Collaboration Translucence: Giving Meaning to Multimodal Group Data sbs 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 (CHI19). 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/chi2019collabtransslides-190509095604-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 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 (CHI19). 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.
Towards Collaboration Translucence: Giving Meaning to Multimodal Group Data from Simon Buckingham Shum
]]> 561 5 https://cdn.slidesharecdn.com/ss_thumbnails/chi2019collabtransslides-190509095604-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Knowledge Art - MDSI Guest Lecture - 1st May 2019 /slideshow/knowledge-art-mdsi-guest-lecture-1st-may-2019/143062172 mdsiknowledgeartmay2019-190501095917
Introductory briefing accompanied by open educational resources at http://simon.buckinghamshum.net/2016/05/knowledge-art-learning-resources/]]>
Introductory briefing accompanied by open educational resources at http://simon.buckinghamshum.net/2016/05/knowledge-art-learning-resources/]]> Wed, 01 May 2019 09:59:17 GMT /slideshow/knowledge-art-mdsi-guest-lecture-1st-may-2019/143062172 sbs@slideshare.net(sbs) Knowledge Art - MDSI Guest Lecture - 1st May 2019 sbs Introductory briefing accompanied by open educational resources at http://simon.buckinghamshum.net/2016/05/knowledge-art-learning-resources/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mdsiknowledgeartmay2019-190501095917-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Introductory briefing accompanied by open educational resources at http://simon.buckinghamshum.net/2016/05/knowledge-art-learning-resources/
Knowledge Art - MDSI Guest Lecture - 1st May 2019 from Simon Buckingham Shum
]]> 475 5 https://cdn.slidesharecdn.com/ss_thumbnails/mdsiknowledgeartmay2019-190501095917-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 UX/LX for PLSA: Workshop Welcome /slideshow/uxlx-for-plsa-workshop-welcome/133614162 ux-lx-intro-utscic-2019-190227214902
https://utscic.edu.au/event/plsa-ux-lx-workshop]]>
https://utscic.edu.au/event/plsa-ux-lx-workshop]]> Wed, 27 Feb 2019 21:49:02 GMT /slideshow/uxlx-for-plsa-workshop-welcome/133614162 sbs@slideshare.net(sbs) UX/LX for PLSA: Workshop Welcome sbs https://utscic.edu.au/event/plsa-ux-lx-workshop <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ux-lx-intro-utscic-2019-190227214902-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> https://utscic.edu.au/event/plsa-ux-lx-workshop
UX/LX for PLSA: Workshop Welcome from Simon Buckingham Shum
]]> 515 3 https://cdn.slidesharecdn.com/ss_thumbnails/ux-lx-intro-utscic-2019-190227214902-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Educational Data Scientists: A Scarce Breed /slideshow/educational-data-scientists-a-scarce-breed/112067656 lak13-panel-slides-180829063559
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. ]]>
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. ]]> Wed, 29 Aug 2018 06:35:59 GMT /slideshow/educational-data-scientists-a-scarce-breed/112067656 sbs@slideshare.net(sbs) Educational Data Scientists: A Scarce Breed sbs 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lak13-panel-slides-180829063559-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Panel held at LAK13: 3rd International Conference on Learning Analytics &amp; 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.
Educational Data Scientists: A Scarce Breed from Simon Buckingham Shum
]]> 426 5 https://cdn.slidesharecdn.com/ss_thumbnails/lak13-panel-slides-180829063559-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Transitioning Educations Knowledge Infrastructure ICLS 2018 /slideshow/transitioning-educations-knowledge-infrastructure-icls-2018/103351534 transitioningeducationsknowledgeinfrastructureicls2018-180627222923
Keynote Address, International Conference of the Learning Sciences, London Festival of Learning Transitioning Educations 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 Pasteurs 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.]]>
Keynote Address, International Conference of the Learning Sciences, London Festival of Learning Transitioning Educations 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 Pasteurs 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.]]> Wed, 27 Jun 2018 22:29:23 GMT /slideshow/transitioning-educations-knowledge-infrastructure-icls-2018/103351534 sbs@slideshare.net(sbs) Transitioning Educations Knowledge Infrastructure ICLS 2018 sbs Keynote Address, International Conference of the Learning Sciences, London Festival of Learning Transitioning Educations 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 Pasteurs 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/transitioningeducationsknowledgeinfrastructureicls2018-180627222923-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Keynote Address, International Conference of the Learning Sciences, London Festival of Learning Transitioning Educations 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 Pasteurs 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.
Transitioning Educations Knowledge Infrastructure ICLS 2018 from Simon Buckingham Shum
]]> 1241 6 https://cdn.slidesharecdn.com/ss_thumbnails/transitioningeducationsknowledgeinfrastructureicls2018-180627222923-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-sbs-48x48.jpg?cb=1707954757 Following Doug Engelbart, it's all about "Augmenting Human Intellect" to tackle sociotechnical complexity: http://simon.buckinghamshum.net + http://utscic.edu.au simon.buckinghamshum.net https://cdn.slidesharecdn.com/ss_thumbnails/sbstbl2024-240214235321-f22a2b7f-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/the-generative-ai-system-shock-and-some-thoughts-on-collective-intelligence-and-teamwork-analytics/266313206 The Generative AI Syst... https://cdn.slidesharecdn.com/ss_thumbnails/sbsct2023genai-230529104518-ec02d4fe-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/could-generative-ai-augment-reflection-deliberation-and-argumentation/258102512 Could Generative AI Au... https://cdn.slidesharecdn.com/ss_thumbnails/bingedgechatargmaps-230516120525-bd9d4e63-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/conversational-generative-ai-as-a-cognitive-tool-for-critical-thinking/257863013 Conversational, genera...