Presentation by Dr Jason Zagami to the QSITE2015 conference on 24 September 2015 at Townsville, Queensland.
Zagami, J. (2015, September) Teaching the Technologies learning area using a thinking skills approach. Presentation presented to QSITE2015 conference, Townsville, Queensland, Australia. http://www.slideshare.net/j.zagami/teaching-the-technologies-learning-area-using-a-thinking-skills-approach
The Technologies learning area provides an opportunity to develop in students five distinct but complementary ways of thinking about and understanding the world: Systems Thinking, Design Thinking, Computational Thinking, Futures Thinking, and Strategic Thinking. This session will explore approaches to teaching the Technologies learning area through problem-solving activities that develop these thinking approaches.
Teaching the Technologies learning area using a thinking skills approachJason Zagami
Presentation to the Digital Technologies 2015 EdTechSA on 16 July 2015
The Technologies learning area provides an opportunity to develop in students five distinct but complementary ways of thinking about and understanding the world: Systems Thinking, Design Thinking, Computational Thinking, Futures Thinking, and Strategic Thinking. This session will explore approaches to teaching the Technologies learning area through problem-solving activities that develop these thinking approaches.
Taking the Elevator: Reflections on the PhD journey, DMU keynote May 2016Dr. Crispin Coombs
Keynote presentation by Dr Crispin Coombs at Research Conference for Doctoral and Early Career Researchers, 10 May 2016, DeMontfort University, Leicester
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
UCL joint Institute of Education (London Knowledge Lab) & UCL Interaction Centre seminar, 20th April 2016. Replay: https://youtu.be/0t0IWvcO-Uo
Algorithmic Accountability & Learning Analytics
Simon Buckingham Shum
Connected Intelligence Centre, University of Technology Sydney
ABSTRACT. As algorithms pervade societal life, they are moving from the preserve of computer science to becoming the object of far wider academic and media attention. Many are now asking how the behaviour of algorithms can be made “accountable”. But why are they “opaque” and to whom? As this vital discussion unfolds in relation to Big Data in general, the Learning Analytics community must articulate what would count as meaningful questions and satisfactory answers in educational contexts. In this talk, I propose different lenses that we can bring to bear on a given learning analytics tool, to ask what it would mean for it to be accountable, and to whom. From a Human-Centred Informatics perspective, it turns out that algorithmic accountability may be the wrong focus.
BIO. Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, which he joined in August 2014 to direct the new Connected Intelligence Centre. Prior to that he was at The Open University’s Knowledge Media Institute 1995-2014. He brings a Human-Centred Informatics (HCI) approach to his work, with a background in Psychology (BSc, York), Ergonomics (MSc, London) and HCI (PhD, York) where he worked with Rank Xerox Cambridge EuroPARC on Design Rationale. He co-edited Visualizing Argumentation (2003) followed by Knowledge Cartography (2008, 2nd Edn. 2014), and with Al Selvin wrote Constructing Knowledge Art (2015). He is active in the emerging field of Learning Analytics and is a co-founder of the Society for Learning Analytics Research, Compendium Institute and Learning Emergence network.
Teaching the Technologies learning area using a thinking skills approachJason Zagami
Presentation to the Digital Technologies 2015 EdTechSA on 16 July 2015
The Technologies learning area provides an opportunity to develop in students five distinct but complementary ways of thinking about and understanding the world: Systems Thinking, Design Thinking, Computational Thinking, Futures Thinking, and Strategic Thinking. This session will explore approaches to teaching the Technologies learning area through problem-solving activities that develop these thinking approaches.
Taking the Elevator: Reflections on the PhD journey, DMU keynote May 2016Dr. Crispin Coombs
Keynote presentation by Dr Crispin Coombs at Research Conference for Doctoral and Early Career Researchers, 10 May 2016, DeMontfort University, Leicester
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
UCL joint Institute of Education (London Knowledge Lab) & UCL Interaction Centre seminar, 20th April 2016. Replay: https://youtu.be/0t0IWvcO-Uo
Algorithmic Accountability & Learning Analytics
Simon Buckingham Shum
Connected Intelligence Centre, University of Technology Sydney
ABSTRACT. As algorithms pervade societal life, they are moving from the preserve of computer science to becoming the object of far wider academic and media attention. Many are now asking how the behaviour of algorithms can be made “accountable”. But why are they “opaque” and to whom? As this vital discussion unfolds in relation to Big Data in general, the Learning Analytics community must articulate what would count as meaningful questions and satisfactory answers in educational contexts. In this talk, I propose different lenses that we can bring to bear on a given learning analytics tool, to ask what it would mean for it to be accountable, and to whom. From a Human-Centred Informatics perspective, it turns out that algorithmic accountability may be the wrong focus.
BIO. Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, which he joined in August 2014 to direct the new Connected Intelligence Centre. Prior to that he was at The Open University’s Knowledge Media Institute 1995-2014. He brings a Human-Centred Informatics (HCI) approach to his work, with a background in Psychology (BSc, York), Ergonomics (MSc, London) and HCI (PhD, York) where he worked with Rank Xerox Cambridge EuroPARC on Design Rationale. He co-edited Visualizing Argumentation (2003) followed by Knowledge Cartography (2008, 2nd Edn. 2014), and with Al Selvin wrote Constructing Knowledge Art (2015). He is active in the emerging field of Learning Analytics and is a co-founder of the Society for Learning Analytics Research, Compendium Institute and Learning Emergence network.
Driving Digital Transformation in Higher Education. 2020 EDUCAUSE Horizon Reporteraser Juan José Calderón
Driving Digital Transformation in Higher Education . 2020 EDUCAUSE Horizon Report™ | Teaching and Learning Edition. D. Christopher Brooks, EDUCAUSE
Mark McCormack, EDUCAUSE
June 2020
This report profiles key trends and emerging technologies and practices shaping the future of teaching and learning and envisions a number of scenarios and implications for that future. It is based on the perspectives and expertise of a global panel of leaders from across the higher education landscape.
Why Watson Won: A cognitive perspectiveJames Hendler
In this talk, we present how the Watson program, IBM's famous Jeopardy playing computer, works (based on papers published by IBM), we look at some aspects of potential scoring approaches, and we examine how Watson compares to several well known systems and some preliminary thoughts on using it in future artificial intelligence and cognitive science approaches.
Systemic Learning Analytics Symposium, October 10th 2013Adam Cooper
Slides for the talk "Barriers and Pitfalls to Systemic Learning Analytics" by Adam Cooper, Cetis, for the online Systemic Learning Analytics Symposium, organised by George Siements and held on October 10th 2013.
Related blog post at: http://blogs.cetis.ac.uk/adam/2013/10/31/policy-and-strategy-for-systemic-deployment-of-learning-analytics-barriers-and-potential-pitfalls/
See http://blogs.cetis.ac.uk/adam/2013/10/31/policy-and-strategy-for-systemic-deployment-of-learning-analytics-barriers-and-potential-pitfalls/ for an extended blog post on the subject.
A talk presented at IBM's "Academy of Technology" exploring, in brief, what the research community has to learn from Watson (and the techniques derived therefrom) and some new research ideas that can be explored therefrom. All known proprietary information from either IBM or RPI has been removed from the original talk.
Towards Contested Collective Intelligence
Simon Buckingham Shum, Director Connected Intelligence Centre, University of Technology Sydney
This talk is to open up a dialogue with the important work of the SWARM project. I’ll introduce the key ideas that have shaped my work on interactive software tools to make thinking visible, shareable and contestable, some of the design prototypes, and some of the lessons we’ve learnt en route.
Computational Thinking: Why It is Important for All StudentsNAFCareerAcads
Given the importance of computing and computer science in most career paths, computational thinking must be a part of every curriculum. This session explores
how computational thinking is related to computer science and information technology and how it might affect K-12 education. Participants will look at curricula examples and learn about new resources produced by a joint ISTE/
CSTA NSF group.
Presenter: Joe Kmoch, Milwaukee Public Schools
The Future of AI: Going BeyondDeep Learning, Watson, and the Semantic WebJames Hendler
These slides, based on a presentation at distinguished lecture at IBM Almaden in March, 2017 explore some of the challenges to machine learning and some recent work. It is a newer version of the slides originally presented at IJCAI 2016.
Email is broken and it's time to fix it. Or is it that we've broken email, and it's time we fix ourselves?
This presentation examines the problem of information and email overload from a research perspective, and presents a synthesis of different approaches we could take to start to resolve the issue.
Prepared for my final masters capstone presentation. Not meant to be entirely read or understood without accompanying narration. See my website at http://www.joshualyman.com/ for more on the topic of information and email overload.
Booz Allen's experts define the science and art of Data Science in the ground breaking The Field Guide to Data Science. The work unlocks the potential data provides in improving every aspect of our lives by explaining how to ask the right questions from data.
From Jisc's student experience experts group meeting in Birmingham on 21 April 2016.
https://www.jisc.ac.uk/events/student-experience-experts-group-meeting-20-apr-2016
Hiring data scientists and deploying Hadoop is not enough. Your company needs a data driven culture, based on values such as honesty, democracy, creativity and strategy. Your company also needs good data engineering and good experimentation practices.
Driving Digital Transformation in Higher Education. 2020 EDUCAUSE Horizon Reporteraser Juan José Calderón
Driving Digital Transformation in Higher Education . 2020 EDUCAUSE Horizon Report™ | Teaching and Learning Edition. D. Christopher Brooks, EDUCAUSE
Mark McCormack, EDUCAUSE
June 2020
This report profiles key trends and emerging technologies and practices shaping the future of teaching and learning and envisions a number of scenarios and implications for that future. It is based on the perspectives and expertise of a global panel of leaders from across the higher education landscape.
Why Watson Won: A cognitive perspectiveJames Hendler
In this talk, we present how the Watson program, IBM's famous Jeopardy playing computer, works (based on papers published by IBM), we look at some aspects of potential scoring approaches, and we examine how Watson compares to several well known systems and some preliminary thoughts on using it in future artificial intelligence and cognitive science approaches.
Systemic Learning Analytics Symposium, October 10th 2013Adam Cooper
Slides for the talk "Barriers and Pitfalls to Systemic Learning Analytics" by Adam Cooper, Cetis, for the online Systemic Learning Analytics Symposium, organised by George Siements and held on October 10th 2013.
Related blog post at: http://blogs.cetis.ac.uk/adam/2013/10/31/policy-and-strategy-for-systemic-deployment-of-learning-analytics-barriers-and-potential-pitfalls/
See http://blogs.cetis.ac.uk/adam/2013/10/31/policy-and-strategy-for-systemic-deployment-of-learning-analytics-barriers-and-potential-pitfalls/ for an extended blog post on the subject.
A talk presented at IBM's "Academy of Technology" exploring, in brief, what the research community has to learn from Watson (and the techniques derived therefrom) and some new research ideas that can be explored therefrom. All known proprietary information from either IBM or RPI has been removed from the original talk.
Towards Contested Collective Intelligence
Simon Buckingham Shum, Director Connected Intelligence Centre, University of Technology Sydney
This talk is to open up a dialogue with the important work of the SWARM project. I’ll introduce the key ideas that have shaped my work on interactive software tools to make thinking visible, shareable and contestable, some of the design prototypes, and some of the lessons we’ve learnt en route.
Computational Thinking: Why It is Important for All StudentsNAFCareerAcads
Given the importance of computing and computer science in most career paths, computational thinking must be a part of every curriculum. This session explores
how computational thinking is related to computer science and information technology and how it might affect K-12 education. Participants will look at curricula examples and learn about new resources produced by a joint ISTE/
CSTA NSF group.
Presenter: Joe Kmoch, Milwaukee Public Schools
The Future of AI: Going BeyondDeep Learning, Watson, and the Semantic WebJames Hendler
These slides, based on a presentation at distinguished lecture at IBM Almaden in March, 2017 explore some of the challenges to machine learning and some recent work. It is a newer version of the slides originally presented at IJCAI 2016.
Email is broken and it's time to fix it. Or is it that we've broken email, and it's time we fix ourselves?
This presentation examines the problem of information and email overload from a research perspective, and presents a synthesis of different approaches we could take to start to resolve the issue.
Prepared for my final masters capstone presentation. Not meant to be entirely read or understood without accompanying narration. See my website at http://www.joshualyman.com/ for more on the topic of information and email overload.
Booz Allen's experts define the science and art of Data Science in the ground breaking The Field Guide to Data Science. The work unlocks the potential data provides in improving every aspect of our lives by explaining how to ask the right questions from data.
From Jisc's student experience experts group meeting in Birmingham on 21 April 2016.
https://www.jisc.ac.uk/events/student-experience-experts-group-meeting-20-apr-2016
Hiring data scientists and deploying Hadoop is not enough. Your company needs a data driven culture, based on values such as honesty, democracy, creativity and strategy. Your company also needs good data engineering and good experimentation practices.
Chris Soderquist presentation at the 2016 Science of HOPE
Description:
This session will introduce participants to a powerful approach to orchestrating useful learning across difficult boundaries using system dynamics. Through real world examples and interactive exercises, participants will learn how system dynamics can help them gain far more useful leverage when addressing complex, adaptive challenges. Participants will also see how this approach was used in a project funded by the Foundation for Healthy Generations to guide strategic decisions in Washington (and other states) for building community capacity and resilience.
Respond to the below discussion questionsDo the following w.docxcarlstromcurtis
Respond to the below discussion questions:
Do the following when responding:
Read the discussions.
Provide substantive comments by
- contributing new, relevant information from course readings, Web sites, or other sources;
- building on the remarks or questions of others; or
sharing practical examples of key concepts from your professional or personal experiences
- Respond to feedback on your posting and provide feedback to other students on their ideas.
Make sure your writing is
- clear, concise, and organized;
- demonstrates ethical scholarship in accurate representation and attribution of sources; and
- displays accurate spelling, grammar, and punctuation.
Discussion #1
How does systems thinking apply to an organization’s culture, goals, and structures?
First, one of the greatest aspects of our country is the ability to provide opportunity; one of the saddest part of our country is when that opportunity forgets its original mission, serving others. I make these arguments for this post this week because I ask my fellow peers: how does system thinking (ST) create a space that hinders and destroys its’ original goal? Well, let me first begin by examining the recent closure of over sixty-three Sam Club stores in the United States on Friday, January 12, 2018. According to CNBC, “Walmart is taking prudent steps to prepare for the next generation of retail warfare” (Thomas and Wells, 2018). However, what Walmart fails to the report is the number of employees who went to work yesterday and with no warning, lost their jobs! Whose best interest is at heart? The employee or the stakeholders?
Secondly, I would argue that organizational culture produces an organizational climate; in terms of communication, basically, how communication interactions are positively or negatively carried in a culture, they can have an incredible impact on the climate. An organizational climate can be reciprocal and can clearly influence a culture – look again, at Walmart Sam Club store closings. Thus, I posit this question: what does the leader have an ability to execute? Next, how well can they sell that vision?
According to our text, authors, Uhl-Bien, Schermerhorn, and Osborn (2014) elucidate, “one of the most accepted conclusions of scientific research to date is that there is no single best way to handle people and the situations that develop as they work together in organizations” Uhl-Bien., et.al, 2014). Thus, for the staff at Walmart the transformation process was ignored and employees (and yes, some stakeholders) were deeply affected by the lack of transparency executed by ST in a clear and evidently broken system. Sadly, socioeconomic class plays a vital role in a lot of decision making for larger corporations in terms of whom they decided to provide goods and services to consumers.
How are the stakeholders in an organization interconnected and interrelated?
Stakeholders in organization are interconnected and interrelated becaus ...
2022-10-25 Smidig Meetup - from Silos to System.pdfSmidigkonferansen
FROM SILOS TO SYSTEM: BUILDING AND MANAGING ORGANIZATIONS AS SYNCHRONISED NETWORKS FOR THE AGE OF COMPLEXITY
Dr. Domenico Lepore will talk about shifting organizations from silos to systems that are fit for the age of complexity.
1308 226 PMDESIGNING QUALITATIVE RESEARCH PROPOSALSPage.docxmoggdede
1/3/08 2:26 PMDESIGNING QUALITATIVE RESEARCH PROPOSALS
Page 1 of 3file:///Users/joannelarson/Desktop/Current/Courses/ED%20507/Readi…rchives/DESIGNING%20QUALITATIVE%20RESEARCH%20PROPOSALS.webarchive
DESIGNING QUALITATIVE RESEARCH PROPOSALS
Some simple suggestions
Ethnographic or qualitative studies are always to some degree emergent: they're dances in which the
researchers follow the leads of the participants. Still, you've got to have some idea of what kind of dance
event it is (a masked ball or a rave) before you can proceeed. You need, in other words, a clear picture of
the issues and questions you want to investigate, some idea of how you're going to go about investigating
them, but also a readiness to improvise and revise. Ideally, you work out designs with colleagues and
advisors (including participants), but there are also some standard features, forms, and cautions that can be
suggested (the numbered components below are taken from the chapter titles in Joe Maxwell's Qualitative
Research Design: An interactive approach. Thousand Oaks, CA: Sage, 1996, the best available text on
design that I'm aware of (which isn't to say that I agree with all of it). The rest, e.g., my suggestions on
framing research questions, are my own, though it should go without saying that these are simply ways of
thinking that I've absorbed ideas from others over the years.).
1) What's the topic, the focal process you're interested in? What are the goals of the study? Why
do you want to conduct it? Why is it worthwhile?
Qualitative studies are ways of learning about how processes and events unfold. They are usually not useful
for asking questions about the distribution or variance of taken-for-granted-entities. So, a goal for an
ethnographic study might entail examining some taken-for-granted or ignored process that seems important
or central to some vital institution. It might involve questioning familiar categories (asking how they come
to be, for example). And so forth.
2) What is the context for the study? What are the theories, or the research literatures, or the
policy positions you anticipate drawing on, challenging, or addressing, through your research?
Bear in mind that "contexts" are not given in the phenomena or settings you study: in other words, your
research is a wau of creating or defining what counts as a context: you're crafting representations of people,
things, events within certain frames - either ones you've choosen, or the participants have choosen, or ones
promoted by governments, disciplines, organizations (and of course, the processes of contextualization and
framing should be topics of inquiry). My own preference is to recognize layers - or perhaps it would be
better to simply say "alternative" frames - of context. Multiply possible connections. Many theories are
better than one.
3) Research Questions: what do you want to get smart about? What are you presently ignorant
about?
These questions should be how questions, they shoul ...
Zagami, J. (2016, October). Digital Solutions Response. Presentation at the accessIT - ACS Qld State Conference 2016, Brisbane, Australia. Retrieved from http://www.slideshare.net/j.zagami/digital-solutions-response
Zagami, J. & Becker, S. (2016, September). ACCE Leadership Forum Summary. Presentation at the Australian Council for Computers in Education Conference, Brisbane, Australia.
Zagami, J. & Becker, S. (2016, September). ACCE Leadership Forum. Forum conducted at the Australian Council for Computers in Education Conference, Brisbane, Australia.
Horizon Report K12: What are the trends, challenges and developments in techn...Jason Zagami
Zagami, J. (2016, June) Horizon Report K12: What are the trends, challenges and developments in technology. Keynote presentation presented to Digital Technologies Summit 2016: Initial Teacher Education, Brisbane, Queensland, Australia. https://www.griffith.edu.au/conference/digital-technologies-summit-2016
Trends, challenges and developments in technologies that will influence the f...Jason Zagami
Keynote presentation by Dr Jason Zagami to the ASLA conference on 29 September 2015 at Brisbane, Queensland.
Zagami, J. (2015, September) Trends, challenges and developments in technologies that will influence the future of libraries. Keynote presentation presented to ASLA conference, Brisbane, Queensland, Australia. http://www.slideshare.net/j.zagami/trends-challenges-and-developments-in-technologies-that-will-influence-the-future-of-libraries
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
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.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
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.
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.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
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.
15. Digital systems:
the components of digital
systems: hardware,
software and networks and
their use
Representation of data:
how data are represented
and structured symbolically
Knowledge and Understanding
Design and
Technologies
Digital
Technologies
Creating Solutions
Technologies and society:
the use, development and
impact of technologies in
people’s lives
Technologies contexts:
technologies and design
across a range of
technologies contexts
26. Once a new technology rolls over you, if you’re not part of the
steamroller, you’re part of the road
Stewart Brand
27. We live in a society exquisitely dependent on science and
technology and yet have cleverly arranged things so that
almost no one understands science and technology. That’s a
clear prescription for disaster
Carl Sagan
28. It has become appallingly obvious that our technology has
exceeded our humanity
Albert Einstein
30. Global Warming
Armed Conflicts
Food Scarcity
Clean Water
Ageing Population
Obesity
Overpopulation
Alternative Energy
Education
Health Care
Epidemics
Housing and Shelter
Big Problems
33. Systems Thinking makes it possible to analyse
and understand complex phenomena
Systems Thinking
34. Instead of isolating smaller and smaller parts of the
system being studied, systems thinking works by
expanding its view to consider larger and larger
numbers of interactions as an issue is being studied
Systems Thinking
35. Thinking consists of two activities: constructing mental
models and then simulating them in order to draw
conclusions and make decisions
Barry Richmond
36. Understanding the concept of a tree requires more
information than is available through sensory experience
alone. It’s built on past experiences and knowledge.
38. The image of the world around us, which we carry in our
head, is just a model. Nobody in his head imagines all the
world… they have only selected concepts, and relationships
between them, and uses those to represent the real system
Jay Forrester
39.
40. The problems we have created in the world today will not be
solved by the level of thinking that created them
Albert Einstein
41. We are limited in our capacity to form and reform mental
models. Systems modelling allows us to move from “what” to
“what if” and make our thinking visible
The basic building blocks of dynamic models are stocks, flows,
and loops
43. A supermarket can be seen as any of the following kinds of
systems, depending on the perspective:
a "profit making system" … from the perspective of management and owners
a "distribution system“… from the perspective of the suppliers
an "employment system“… from the perspective of employees
a "materials supply system“… from the perspective of customers
an "entertainment system“… from the perspective of loiterers
a "social system" …from the perspective of local residents
a "dating system" …from the perspective of single customers
44. Students need learn to identify the properties of the
various subsystems they explore, for example of a bicycle,
and examine how they relate to the whole.
Children tend to think of the properties of a system as
belonging to individual parts of it rather than as arising
from the interaction of the parts. A system property that
arises from interaction of parts is therefore a difficult idea.
45. Students should already know that if something consists
of many parts, the parts usually influence one another.
Also they should be aware that something may not work as
well (or at all) if a part of it is missing, broken, worn out,
mismatched, or misconnected.
47. Students can learn about the
choices and constraints that
go into the design of a
bicycle system. Depending
on whether the bicycle is
intended for racing,
mountain roads, or touring,
influences its design and
such choices as the type of
tires, frame and materials,
and drives and gears.
48. In addition, accommodating one constraint can often lead
to conflict with others. For example, the lightest material
may not be the strongest, or the most efficient shape may
not be the safest or the most aesthetically pleasing.
Therefore, every design problem lends itself to many
alternative solutions, depending on what values people
place on the various constraints.
60. As you are reading, look for key words such as:
change transform revolution becoming more rose went up increased
got higher grew/growth gained less fell went down decreased went
lower declined lost
Write down one or more quotes in each box. Circle key words of change
and underline what you think is changing. Draw a line graph of how the
quote shows change over time. Explain why the change occurs.
Identifying Change Over Time in Text
Quotes from book Change over time
Why this might be
occurring
82. A feedback loop is formed when changes in a stock affect the flows
into or out of that same stock
Balancing feedback loops are stability seeking and try to keep a
stock at a certain level or within a certain range
Reinforcing feedback loops occur when a system element has the
ability to reproduce itself or grow at a constant fraction of itself
Loops
87. Symbols
A converter holds
information or
relationships that
affect the rate of
the flows, or that
affect the content
of another
converter
A connector
indicates that
changes in one
element cause
changes in another
element; only
changes a stock by
going through an
accompanying
flow
A flow represents actions or
processes; transports “stuff”,
concrete or abstract, that
directly adds to or takes away
from accumulation in a stock;
the verbs in the system
A stock represents
an accumulation,
concrete or
abstract, that
increases or
decreases over
time; the nouns in
the system
109. Computational Thinking
The curriculum is designed so that students will develop and use
increasingly sophisticated computational thinking skills, and
processes, techniques and digital systems to create solutions to
address specific problems, opportunities or needs.
110. Computational Thinking
Computational thinking is a process of recognising aspects of
computation in the world and being able to think logically,
algorithmically, recursively and abstractly. Students will also
apply procedural techniques and processing skills when
creating, communicating and sharing ideas and information, and
managing projects.
119. Digital systems
The digital systems concept focuses on the components of
digital systems: hardware and software (computer architecture
and the operating system), and networks and the internet
(wireless, mobile and wired networks and protocols).
120. Abstraction
Abstraction, which underpins all content, particularly the
content descriptions relating to the concepts of data
representation and specification, algorithms and
implementation
121. Abstraction
Abstraction involves hiding details of an idea, problem or
solution that are not relevant, to focus on a manageable number
of aspects. Abstraction is a natural part of communication:
people rarely communicate every detail, because many details
are not relevant in a given context. The idea of abstraction can be
acquired from an early age. For example, when students are
asked how to make toast for breakfast, they do not mention all
steps explicitly, assuming that the listener is an intelligent
implementer of the abstract instructions.
122. Abstraction
Central to managing the complexity of information systems is
the ability to ‘temporarily ignore’ the internal details of the
subcomponents of larger specifications, algorithms, systems or
interactions. In digital systems, everything must be broken down
into simple instructions.
124. Data collection
Data collection describes the numerical, categorical and textual
facts measured, collected or calculated as the basis for creating
information and its binary representation in digital systems.
125. Data representation
Data representation describes how data are represented and
structured symbolically for storage and communication, by
people and in digital systems
127. Specification (descriptions and techniques), algorithms
(following and describing) and implementation (translating and
programming)
Specification, algorithms and
implementation
128. Specification
Specification describes the process of defining and
communicating a problem precisely and clearly. For example,
explaining the need to direct a robot to move in a particular way.
129. Algorithms
An algorithm is a precise description of the steps and decisions
needed to solve a problem. Algorithms will need to be tested
before the final solution can be implemented. Anyone who has
followed or given instructions, or navigated using directions, has
used an algorithm.
132. Interactions and impacts
The interactions and impacts concepts focus on all aspects of
human interaction with and through information systems, and
the enormous potential for positive and negative economic,
environmental and social impacts enabled by these systems.
Interactions and impacts are addressed in the processes and
production skills strand.
133. Interactions
Interactions refers to all human interactions with information
systems, especially user interfaces and experiences, and
human–human interactions including communication and
collaboration facilitated by digital systems.
134. Impacts
Impacts describes analysing and predicting the extent to which
personal, economic, environmental and social needs are met
through existing and emerging digital technologies; and
appreciating the transformative potential of digital technologies
in people’s lives.
145. Design Thinking
Use of strategies for understanding design problems and
opportunities, visualising and generating creative and
innovative ideas, and analysing and evaluating those ideas that
best meet the criteria for success and planning.
146. Design Process
Creating a product, environment or service
• investigating the problem
• generating a solution
• producing a solution
• evaluating the solution
• collaborating on and managing this
process
156. • conceptualise more just and sustainable human and
planetary futures.
• develop knowledge and skills in exploring probable
and preferred futures.
• understand the dynamics and influence that human,
social and ecological systems have on alternative
futures.
• conscientise responsibility and action on the part of
students toward creating better futures.
Futures Thinking
166. Managing Projects and
Collaboration
plan (with teacher support) simple steps and follow
directions to complete their own projects or manage
their own role within team projects.
responsibility for specific roles within a project with
increasing levels of collaboration and team work.
manage projects, with support from peers and teachers.
fully manage projects and teams. They use digital tools
to support their project management. They coordinate
teams and collaborate with others locally and globally.
F - 2
3-6
9-10
7-8
188. Project is the teachers, with
students following directions
to support the creative ideas
of the teacher
Common Unit Problems
189. There is no opportunity for
students to be creative and
design their own solutions
Common Unit Problems
190. There is no demonstration of
the iterative nature of the
design cycle, using what was
learnt from evaluation to
inform further investigation,
generation and production
Common Unit Problems
191. It is an ICT unit that supports
the learning of another
learning area
Common Unit Problems
192. Evaluation is little more than
reflection, with no criteria or
possibility of failure
Common Unit Problems