IWMW 2002: How I Learned To Stop Worrying And Love The E-StrategyIWMW
Workshop session at IWMW 2002 on " How I Learned To Stop Worrying And Love The E-Strategy" facilitated by Tracey Stanley
http://www.ukoln.ac.uk/web-focus/events/workshops/webmaster-2002/materials/stanley/
Leveraging Flat Files from the Canvas LMS Data Portal at K-StateShalin Hai-Jew
A lot of data are created in an LMS instance, and much of this can be analyzed for insight. In 2016, Instructure, the makers of Canvas, made their LMS data available to their customers through a data portal (updated monthly). This portal enables access to a number of flat files related to that particular instance. This presentation showcases how this big data was analyzed on a regular laptop with basic office software, to summarize Kansas State University’s use of the LMS. Methods for analysis include the following: basic descriptive statistics, survival analysis, computational linguistic analysis, and others.
The results are reported out with both numbers and data visualizations, including classic pie charts, line graphs, bar charts, mixed-charts, word clouds, and others. The findings provide some insights about how to approach the data, how to use a data dictionary, and other methods for extracting the data for awareness and practical decision-making. This work also is suggestive of next steps for more advanced analysis (using the flat files in a SQL database).
More information about this may be accessed at http://scalar.usc.edu/works/c2c-digital-magazine-spring--summer-2017/wrangling-big-data-in-a-small-tech-ecosystem.
When digital learning objects (DLOs) were initially conceptualized, based on object-oriented programming, there were initial high hopes that people could build learning objects that were re-usable by others. DLOs have come a long way in the past few decades, and many are available for free on various repositories, referatories, digital libraries, and other sources. In a recent research project, the presenter explored what features of DLOs make them adoptable for online learning and created a ten-element model for DLO adoption. The reality is that adoption of DLOs is not cost-free and not effort-free. The ten elements include the following categories:
Pedagogical Value
Learner Engagement
Presentational Features
Legal Considerations
Technological Features
Instructor (Adopter) Control
Applicability to the Respective Learning Contexts (Local Conditions)
Local Costs to Deploy
Labeling and Documentation, Contributor and Informational Source Crediting
Global Transferability and Adoptability
She then analyzed her decades of work in instructional design in higher education (and private industry) to see what features were addressed in the respective funded DLOs. She found discrepancies between what makes DLOs adoptable and what is built and suggests some practical ways to close those gaps with techniques and technologies, in order to further support and propel the “digital learning object economy”.
The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...Shalin Hai-Jew
The presenter will introduce the K-State LMS data portal and introduce some available insights from there and focus on one particular facet of this big data--the third-party apps that K-State faculty, admin, and staff have activated and what that says about how we're using Canvas.
Canvas LMS data portal for the Kansas State University instance
A data dictionary: Version 1.16.2 (https://portal.inshosteddata.com/docs)
Data extraction and processing
What it can tell us: (un)available data and information
Activated third-party tools in K-State Online Canvas LMS instance
Some caveats
What this says about what K-Staters (early adopters) are using
Practical applications of this third-party app activation data
Adding value to LMS data portal data
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
IWMW 2002: How I Learned To Stop Worrying And Love The E-StrategyIWMW
Workshop session at IWMW 2002 on " How I Learned To Stop Worrying And Love The E-Strategy" facilitated by Tracey Stanley
http://www.ukoln.ac.uk/web-focus/events/workshops/webmaster-2002/materials/stanley/
Leveraging Flat Files from the Canvas LMS Data Portal at K-StateShalin Hai-Jew
A lot of data are created in an LMS instance, and much of this can be analyzed for insight. In 2016, Instructure, the makers of Canvas, made their LMS data available to their customers through a data portal (updated monthly). This portal enables access to a number of flat files related to that particular instance. This presentation showcases how this big data was analyzed on a regular laptop with basic office software, to summarize Kansas State University’s use of the LMS. Methods for analysis include the following: basic descriptive statistics, survival analysis, computational linguistic analysis, and others.
The results are reported out with both numbers and data visualizations, including classic pie charts, line graphs, bar charts, mixed-charts, word clouds, and others. The findings provide some insights about how to approach the data, how to use a data dictionary, and other methods for extracting the data for awareness and practical decision-making. This work also is suggestive of next steps for more advanced analysis (using the flat files in a SQL database).
More information about this may be accessed at http://scalar.usc.edu/works/c2c-digital-magazine-spring--summer-2017/wrangling-big-data-in-a-small-tech-ecosystem.
When digital learning objects (DLOs) were initially conceptualized, based on object-oriented programming, there were initial high hopes that people could build learning objects that were re-usable by others. DLOs have come a long way in the past few decades, and many are available for free on various repositories, referatories, digital libraries, and other sources. In a recent research project, the presenter explored what features of DLOs make them adoptable for online learning and created a ten-element model for DLO adoption. The reality is that adoption of DLOs is not cost-free and not effort-free. The ten elements include the following categories:
Pedagogical Value
Learner Engagement
Presentational Features
Legal Considerations
Technological Features
Instructor (Adopter) Control
Applicability to the Respective Learning Contexts (Local Conditions)
Local Costs to Deploy
Labeling and Documentation, Contributor and Informational Source Crediting
Global Transferability and Adoptability
She then analyzed her decades of work in instructional design in higher education (and private industry) to see what features were addressed in the respective funded DLOs. She found discrepancies between what makes DLOs adoptable and what is built and suggests some practical ways to close those gaps with techniques and technologies, in order to further support and propel the “digital learning object economy”.
The K-State Online Canvas LMS Data Portal and Five Years of Activated Third-P...Shalin Hai-Jew
The presenter will introduce the K-State LMS data portal and introduce some available insights from there and focus on one particular facet of this big data--the third-party apps that K-State faculty, admin, and staff have activated and what that says about how we're using Canvas.
Canvas LMS data portal for the Kansas State University instance
A data dictionary: Version 1.16.2 (https://portal.inshosteddata.com/docs)
Data extraction and processing
What it can tell us: (un)available data and information
Activated third-party tools in K-State Online Canvas LMS instance
Some caveats
What this says about what K-Staters (early adopters) are using
Practical applications of this third-party app activation data
Adding value to LMS data portal data
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
Moodle and Drupal are fully customizable platforms, Paradiso offers you a tailored solution according to your needs. Learn more here:
http://www.paradisosolutions.com/moodle/customization
Call Paradiso Solutions now at +1 800 513 5902 to talk with a Moodle Drupal expert today, you can also email us at Sales@paradisosolutions.com
http://www.paradisosolutions.com
In this session I have shown the possibilities that Drupal offers to interact with other enterprise systems like Microsoft Sharepoint, Salesforce or SAP.
As many of you may wonder "why to do this", I want to show some real use cases where Drupal works as an intranet framework, a content marketing portal or a enterprise commerce site - integrated with other enterprise tools to share content, processes and customer interaction.
How to Make Awesome SlideShares: Tips & TricksSlideShare
Turbocharge your online presence with SlideShare. We provide the best tips and tricks for succeeding on SlideShare. Get ideas for what to upload, tips for designing your deck and more.
Ascilite webinar series: http://www.ascilite.org.au/index.php?p=news_detail&item=240
A slightly different version of the Macquarie University keynote at http://www.slideshare.net/sbs/our-learning-analytics-are-our-pedagogy
I swapped out more general critiques of big data, for more detail on Dispositional and Discourse Learning Analytics
Keynote Address, Expanding Horizons 2012, Macquarie University
http://staff.mq.edu.au/teaching/workshops_programs/expanding_horizons
"Learning Analytics": unprecedented data sets and live data streams about learners, with computational power to help make sense of it all, and new breeds of staff who can talk predictive models, pedagogy and ethics. This means rather different things to different people: unprecedented opportunity to study, benchmark and improve educational practice, at scales from countries and institutions, to departments, individual teachers and learners. "Benchmarking" may trigger dystopic visions of dumbed down proxies for 'real teaching and learning', but an emu response is no good. For educational institutions, our calling is to raise the quality of debate, shape external and internal policy, and engage with the companies and open communities developing the future infrastructure. How we deploy these new tools rests critically on assessment regimes, what can be logged and measured with integrity, and what we think it means to deliver education that equips citizens for a complex, uncertain world.
Technical Challenges for Realizing Learning AnalyticsRalf Klamma
Technical Challenges for Realizing Learning Analytics
Learntec 2015, January 28, 2015, Karlsruhe, Germany,
Ralf Klamma
Advanced Community Informations Systems (ACIS) Group
RWTH Aachen University
STLHE 2015 - From Mobile Access to Multi-device Learning Ecologies: A Case StudyPaul Hibbitts
As mobile access is turning into primary access, many universities and organizations find themselves constantly challenged to keep up with student expectations. At the same time, we have moved further into an age of networked information and students have easier access to better quality educational resources outside of university than ever before. Faced with these opportunities, university instructor and software interaction designer Paul Hibbitts has pushed the boundaries of his multi-device course companions in order to improve learner experience and better support an open and ever-evolving learning ecology.
In the current digital era, education system has witness tremendous growth in data storage and efficient retrieval. Many Institutes have very huge databases which may be of terabytes of knowledge and information. The complexity of the data is an important issue as educational data consists of structural as well as non-structural type which includes various text editors like node pad, word, PDF files, images, video, etc. The problem lies in proper storage and correct retrieval of this information. Different types of learning platform like Moodle have implemented to integrate the requirement of educators, administrators and learner. Although this type of platforms are indeed a great support of educators, still mining of the large data is required to uncover various interesting patterns and facts for decision making process for the benefits of the students. In this research work, different data mining classification models are applied to analyse and predict students’ feedback based on their Moodle usage data. The models described in this paper surely assist the educators, decision maker, mentors to early engage with the issues as address by students. In this research, real data from a semester has been experimented and evaluated. To achieve the better classification models, discretization and weight adjustment techniques have also been applied as part of the pre – processing steps. Finally, we conclude that for efficient decision making with the student’s feedback the classifier model must be appropriate in terms of accuracy and other important evaluation measures. Our experiments also shows that by using weight adjustment techniques like information gain and support vector machines improves the performance of classification models.
In the current digital era, education system has witness tremendous growth in data storage and efficient retrieval. Many Institutes have very huge databases which may be of terabytes of knowledge and information. The complexity of the data is an important issue as educational data consists of structural as well as non-structural type which includes various text editors like node pad, word, PDF files, images, video, etc. The problem lies in proper storage and correct retrieval of this information. Different types of learning platform like Moodle have implemented to integrate the requirement of educators, administrators and learner. Although this type of platforms are indeed a great support of educators, still mining of the large data is required to uncover various interesting patterns and facts for decision making process for the
benefits of the students.
Moodle and Drupal are fully customizable platforms, Paradiso offers you a tailored solution according to your needs. Learn more here:
http://www.paradisosolutions.com/moodle/customization
Call Paradiso Solutions now at +1 800 513 5902 to talk with a Moodle Drupal expert today, you can also email us at Sales@paradisosolutions.com
http://www.paradisosolutions.com
In this session I have shown the possibilities that Drupal offers to interact with other enterprise systems like Microsoft Sharepoint, Salesforce or SAP.
As many of you may wonder "why to do this", I want to show some real use cases where Drupal works as an intranet framework, a content marketing portal or a enterprise commerce site - integrated with other enterprise tools to share content, processes and customer interaction.
How to Make Awesome SlideShares: Tips & TricksSlideShare
Turbocharge your online presence with SlideShare. We provide the best tips and tricks for succeeding on SlideShare. Get ideas for what to upload, tips for designing your deck and more.
Ascilite webinar series: http://www.ascilite.org.au/index.php?p=news_detail&item=240
A slightly different version of the Macquarie University keynote at http://www.slideshare.net/sbs/our-learning-analytics-are-our-pedagogy
I swapped out more general critiques of big data, for more detail on Dispositional and Discourse Learning Analytics
Keynote Address, Expanding Horizons 2012, Macquarie University
http://staff.mq.edu.au/teaching/workshops_programs/expanding_horizons
"Learning Analytics": unprecedented data sets and live data streams about learners, with computational power to help make sense of it all, and new breeds of staff who can talk predictive models, pedagogy and ethics. This means rather different things to different people: unprecedented opportunity to study, benchmark and improve educational practice, at scales from countries and institutions, to departments, individual teachers and learners. "Benchmarking" may trigger dystopic visions of dumbed down proxies for 'real teaching and learning', but an emu response is no good. For educational institutions, our calling is to raise the quality of debate, shape external and internal policy, and engage with the companies and open communities developing the future infrastructure. How we deploy these new tools rests critically on assessment regimes, what can be logged and measured with integrity, and what we think it means to deliver education that equips citizens for a complex, uncertain world.
Technical Challenges for Realizing Learning AnalyticsRalf Klamma
Technical Challenges for Realizing Learning Analytics
Learntec 2015, January 28, 2015, Karlsruhe, Germany,
Ralf Klamma
Advanced Community Informations Systems (ACIS) Group
RWTH Aachen University
STLHE 2015 - From Mobile Access to Multi-device Learning Ecologies: A Case StudyPaul Hibbitts
As mobile access is turning into primary access, many universities and organizations find themselves constantly challenged to keep up with student expectations. At the same time, we have moved further into an age of networked information and students have easier access to better quality educational resources outside of university than ever before. Faced with these opportunities, university instructor and software interaction designer Paul Hibbitts has pushed the boundaries of his multi-device course companions in order to improve learner experience and better support an open and ever-evolving learning ecology.
In the current digital era, education system has witness tremendous growth in data storage and efficient retrieval. Many Institutes have very huge databases which may be of terabytes of knowledge and information. The complexity of the data is an important issue as educational data consists of structural as well as non-structural type which includes various text editors like node pad, word, PDF files, images, video, etc. The problem lies in proper storage and correct retrieval of this information. Different types of learning platform like Moodle have implemented to integrate the requirement of educators, administrators and learner. Although this type of platforms are indeed a great support of educators, still mining of the large data is required to uncover various interesting patterns and facts for decision making process for the benefits of the students. In this research work, different data mining classification models are applied to analyse and predict students’ feedback based on their Moodle usage data. The models described in this paper surely assist the educators, decision maker, mentors to early engage with the issues as address by students. In this research, real data from a semester has been experimented and evaluated. To achieve the better classification models, discretization and weight adjustment techniques have also been applied as part of the pre – processing steps. Finally, we conclude that for efficient decision making with the student’s feedback the classifier model must be appropriate in terms of accuracy and other important evaluation measures. Our experiments also shows that by using weight adjustment techniques like information gain and support vector machines improves the performance of classification models.
In the current digital era, education system has witness tremendous growth in data storage and efficient retrieval. Many Institutes have very huge databases which may be of terabytes of knowledge and information. The complexity of the data is an important issue as educational data consists of structural as well as non-structural type which includes various text editors like node pad, word, PDF files, images, video, etc. The problem lies in proper storage and correct retrieval of this information. Different types of learning platform like Moodle have implemented to integrate the requirement of educators, administrators and learner. Although this type of platforms are indeed a great support of educators, still mining of the large data is required to uncover various interesting patterns and facts for decision making process for the
benefits of the students.
Learning analytics and Moodle: So much we could measure, but what do we want to measure? A presentation to the USQ Math and Sciences Community of Practice May 2013
Slides used to support workshop at Association of Learning Technology Conference. ALT-C 2009.
These slides are released under Creative Commons Attribution Non-Commercial Share Alike to respect copyright of images used and acknowledged within the presentation.
Moodle in the Classroom: An "in the tenches" perspectiveNetSpot Pty Ltd
Presented at the Moodle Research Conference in Sousse, Tunsia - 4-5 October 2013. The full paper can be viewed at http://research.moodle.net/mod/data/view.php?d=7&rid=130.
Integrating Blackboard Collaborate 12 and MoodleNetSpot Pty Ltd
Integration Capabilities
Increase the capacity of your Learning Management System (LMS) to connect and engage
For Educators
Schedule web conferencing sessions
List live sessions and recordings as content objects in course information and assignments
Pre-load content
Integrated grading
For Students
Single login for LMS and Collaborate
Attend sessions
View recordings
Presentation by Kim Edgar and Mark Drechsler at the 2012 School Moodlemoot in Brisbane covering the existing rubric grading forms in Moodle 2.2 and the current NetSpot development work to redevelop the Assignment module for Moodle 2.3.
A short overview of simple course design concepts using Moodle, presented by Mark Drechsler at the 2012 Murdoch Teaching & Learning Forum (http://www.murdoch.edu.au/Teaching-and-Learning-Forum/)
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
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.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
2. What do we mean by ‘analytics’?
How can we classify different kinds of analytics?
What are the challenges we face in the LMS?
What is happening in the Moodle project (and
beyond) in relation to analytics?
This session
3. “…exploring the unique types of data that come from
educational settings, and using those methods to better
understand students.”
A broad definition
Source: Wikipedia entry on Educational Data Mining
6. Type Level/object Who benefits?
Learning
Analytics
Course level Learners, Academics
Faculty level Learners, Academics
Academic
Analytics
Institutional Administrators, Funders,
Marketing
Regional Funders, Administrators
National and
international
National governments,
Educational authorities
Multiple perspectives
Source: http://www.educause.edu/ero/article/penetrating-fog-analytics-learning-and-education
Penetrating the Fog: Analytics in Learning and Education – Phillip Long & George Siemens
7. Type Level/object Who benefits?
Learning
Analytics
Course level Learners, Academics
Faculty level Learners, Academics
Academic
Analytics
Institutional Administrators, Funders,
Marketing
Regional Funders, Administrators
National and
international
National governments,
Educational authorities
Multiple perspectives
Target Consumer
Source: http://www.educause.edu/ero/article/penetrating-fog-analytics-learning-and-education
Penetrating the Fog: Analytics in Learning and Education – Phillip Long & George Siemens
11. One extreme: LMS only data analysis
Simple to implement
Losing ‘market share’ of data over time leading to lower
reliability of analysis
Other extreme: Learning ecosystem
Complex – needs open standards model and external
repository
The holy grail of educational analytics?
Analytics Scope
12.
13. One extreme: Manual analysis
Run reports, analyse data, take actions
Other extreme: Automated analysis
Automated analysis against known metrics
Alerts & notifications to consumers
Analytics automation
20. Only one part of the story
Lecture capture? Library systems?
Virtual classroom? Social learning?
Logs in Moodle are good, but not
comprehensive
‘LMS only’ analysis problems
21. Data gets big(gish)
‘Typical’ Moodle uni generates
between 50,000,000 and
100,000,000 log records in a year
LMS only analysis problems
23. Solution part 1: abstraction
Log
store
Adapted from http://docs.moodle.org/dev/Logging_2
Log data
24. What they are saying:
SOLAR: “Development of a common language for
data exchange*” – first item on their roadmap
IMS: “The … ‘holy grail’ of data interoperability
is an agreed upon “learning/progress map” that
all tools and assessments could populate.**”
Solution part 2 - standards
* source: http://solaresearch.org/OpenLearningAnalytics.pdf
** source: http://www.imsglobal.org/blog/?p=258
25. Increase amount of data gathered in Moodle’s logs to
support more in-depth analytics.
Solution part 3 – more data!