Learning Analytics of Online Instructional Design during COVID-19: Experience...MohammadDeniAkbar1
Emergency remote online learning is a natural response by education providers to ensure program sustainability whilst educators and students adapt to this change through time. The instructional design of these courses has also been adapted but limited learning analytics-based studies are available. This paper presents a case study on the instructional design and learning analytics in an online learning course entitled Data Analytics conducted at Telkom University. The course content, activity and assessment structure are discussed as well as the data analytics tools functions provided in the learning management platform used. Additional learning analytics case study is reported on the student’s response and experience.
This document summarizes a workshop on linking learning analytics, learning design, and MOOCs. It discusses how learning analytics can provide actionable intelligence for learners and educators. Group activities involved analyzing MOOCs to identify learning outcomes, assessments, and how analytics could support learning. The document suggests learning design tools like templates, planners, and maps can help identify useful analytics and frame analytics questions. The goal is to use analytics to facilitate learning, identify struggles, engagement, and address problems by starting with pedagogy.
EMMA Summer School - M. Laanpere, O. Firssova - Elaborating your MOOC approac...EUmoocs
The principles and techniques of the task-centered instructional design will be introduced and practiced in the hands-on group work that involves creating, sequencing and validating authentic instructional tasks. A special focus will be on mapping the instructional tasks in MOOC to facts, concepts, procedures and rules identified in the course objectves, as well as scaffolding the learning through well-designed course assignments and learning resources.
This presentation was given during the EMMA Summer School, that took place in Ischia (Italy) on 4-11 July 2015.
More info on the website: http://project.europeanmoocs.eu/project/get-involved/summer-school/
Follow our MOOCs: http://platform.europeanmoocs.eu/MOOCs
Design and deliver your MOOC with EMMA: http://project.europeanmoocs.eu/project/get-involved/become-an-emma-mooc-provider/
Presentation given at SCONUL 2014, the summer conference of The Society of College, National and University Libraries, Glasgow, June 2014. The presentation focuses on frequently asked questions (FAQs) about learning analytics, with the emphasis on the role and perspective of libraries in this area.
Workshop run at the European Conference for e-Learning 2015 (ECEL 2015) at the University of Hertfordshire, UK. The workshop included an introduction of both learning analytics and learning design, as well as an exploration of how these could be employed in MOOCs. Some of the group work was focused on the Agincourt MOOC run by the University of Southampton on the FutureLearn platform.
The ethics of MOOC research: why we should involve learnersRebecca Ferguson
Presentation given by Rebecca Ferguson at the FutureLearn Academic Network (FLAN) meeting at the University of Southampton, UK, on 2 December 2015. #flnetwork
(My) Key Concepts for Online Learning Design (2021)John MacMillan
Presentation slides from the 2021 Jisc ConnectMore session on online learning design. The presentation covered planning, resource design, and presence.
EMMA Summer School - C. Padron-Napoles - Choosing a MOOC approach that meets ...EUmoocs
This workshop will give a good opportunity to participants to get acquainted with the main concepts taken into account in the different existing MOOC approaches from pedagogical, technical and market perspectives. This hands-on session will allow participants to establish proper mappings between learning objectives and the choices for designing and developing their MOOC considering learning, human and budgetary resources. At the end of the workshop, participants will have a better overview of how their MOOCs would look like from the design perspective and initial plans for their implementation would be prepared.
This presentation was given during the EMMA Summer School, that took place in Ischia (Italy) on 4-11 July 2015.
More info on the website: http://project.europeanmoocs.eu/project/get-involved/summer-school/
Follow our MOOCs: http://platform.europeanmoocs.eu/MOOCs
Design and deliver your MOOC with EMMA: http://project.europeanmoocs.eu/project/get-involved/become-an-emma-mooc-provider/
Learning Analytics of Online Instructional Design during COVID-19: Experience...MohammadDeniAkbar1
Emergency remote online learning is a natural response by education providers to ensure program sustainability whilst educators and students adapt to this change through time. The instructional design of these courses has also been adapted but limited learning analytics-based studies are available. This paper presents a case study on the instructional design and learning analytics in an online learning course entitled Data Analytics conducted at Telkom University. The course content, activity and assessment structure are discussed as well as the data analytics tools functions provided in the learning management platform used. Additional learning analytics case study is reported on the student’s response and experience.
This document summarizes a workshop on linking learning analytics, learning design, and MOOCs. It discusses how learning analytics can provide actionable intelligence for learners and educators. Group activities involved analyzing MOOCs to identify learning outcomes, assessments, and how analytics could support learning. The document suggests learning design tools like templates, planners, and maps can help identify useful analytics and frame analytics questions. The goal is to use analytics to facilitate learning, identify struggles, engagement, and address problems by starting with pedagogy.
EMMA Summer School - M. Laanpere, O. Firssova - Elaborating your MOOC approac...EUmoocs
The principles and techniques of the task-centered instructional design will be introduced and practiced in the hands-on group work that involves creating, sequencing and validating authentic instructional tasks. A special focus will be on mapping the instructional tasks in MOOC to facts, concepts, procedures and rules identified in the course objectves, as well as scaffolding the learning through well-designed course assignments and learning resources.
This presentation was given during the EMMA Summer School, that took place in Ischia (Italy) on 4-11 July 2015.
More info on the website: http://project.europeanmoocs.eu/project/get-involved/summer-school/
Follow our MOOCs: http://platform.europeanmoocs.eu/MOOCs
Design and deliver your MOOC with EMMA: http://project.europeanmoocs.eu/project/get-involved/become-an-emma-mooc-provider/
Presentation given at SCONUL 2014, the summer conference of The Society of College, National and University Libraries, Glasgow, June 2014. The presentation focuses on frequently asked questions (FAQs) about learning analytics, with the emphasis on the role and perspective of libraries in this area.
Workshop run at the European Conference for e-Learning 2015 (ECEL 2015) at the University of Hertfordshire, UK. The workshop included an introduction of both learning analytics and learning design, as well as an exploration of how these could be employed in MOOCs. Some of the group work was focused on the Agincourt MOOC run by the University of Southampton on the FutureLearn platform.
The ethics of MOOC research: why we should involve learnersRebecca Ferguson
Presentation given by Rebecca Ferguson at the FutureLearn Academic Network (FLAN) meeting at the University of Southampton, UK, on 2 December 2015. #flnetwork
(My) Key Concepts for Online Learning Design (2021)John MacMillan
Presentation slides from the 2021 Jisc ConnectMore session on online learning design. The presentation covered planning, resource design, and presence.
EMMA Summer School - C. Padron-Napoles - Choosing a MOOC approach that meets ...EUmoocs
This workshop will give a good opportunity to participants to get acquainted with the main concepts taken into account in the different existing MOOC approaches from pedagogical, technical and market perspectives. This hands-on session will allow participants to establish proper mappings between learning objectives and the choices for designing and developing their MOOC considering learning, human and budgetary resources. At the end of the workshop, participants will have a better overview of how their MOOCs would look like from the design perspective and initial plans for their implementation would be prepared.
This presentation was given during the EMMA Summer School, that took place in Ischia (Italy) on 4-11 July 2015.
More info on the website: http://project.europeanmoocs.eu/project/get-involved/summer-school/
Follow our MOOCs: http://platform.europeanmoocs.eu/MOOCs
Design and deliver your MOOC with EMMA: http://project.europeanmoocs.eu/project/get-involved/become-an-emma-mooc-provider/
Five short presentations from a panel session at the Learning Analytics and Knowledge Conference 2015, on the topic of "Learning Analytics - European Perspectives", held at Marist College, Poughkeepsie on March 18th 2015. The speakers are: Rebecca Ferguson, Alejandra Martinz Mones, Kairit Tammets, Alan Berg, Anne Boyer, and Adam Cooper.
De toekomst van Learning Analytics - wat is haalbaar en wat is wenselijk?SURF Events
Woensdag 11 november
Sessieronde 4
Titel: De toekomst van Learning Analytics - wat is haalbaar en wat is wenselijk?
Spreker(s): Doug Clow (Open University UK), Hendrik Drachsler (Open Universiteit)
Zaal: Leeuwen I
'Visions of future learning'. A presentation given by Rebecca Ferguson to the Plato Institute at the National Hellenic Research Foundation, Athens, Greece on 14 November 2014.
Bring your own idea - Visual learning analyticsJoris Klerkx
Workshop on visual learning analytics that was part of LASI 2014 - http://www.solaresearch.org/events/lasi-2/lasi2014/
Examples of learning dashboards were presented during the workshop by Sven Charleer:
http://www.slideshare.net/svencharleer/learning-dashboard-visual-learning-analytics-workshop-lasi2014-h-harvard
Scaling up learning analytics solutions: Is privacy a show-stopper?Tore Hoel
1) The document discusses the challenges of scaling up learning analytics solutions from research labs to the classroom in light of privacy and ethics concerns.
2) It notes that learning analytics could be considered unlawful if students do not have control over and consent to how their data is used.
3) The presentation raises important questions about data ownership, student consent, and limiting data collection and use to only what is necessary for educational purposes.
A learning design toolkit for creating effective learning activitiesgrainne
This document summarizes a learning design toolkit created by researchers to help teachers design effective learning activities. The toolkit addresses the gap between educational technology potential and how technologies are actually applied based on sound pedagogical principles. It involves reviewing learning theories, defining components of learning activities, and mapping them to real examples. The toolkit guides teachers through articulating information needs to produce lesson plans. It prompts them to consider pedagogical approaches, tasks, tools, and assessments when creating or modifying activities.
This document discusses the relationship between learning design and learning analytics. It argues that learning design provides context that helps frame analytics questions and identify appropriate analysis. A MOOC planner is presented that prompts designers to plan different activity types like delivered content, reflection, collaboration, and assessment. Analytics can then provide insight into how learners engaged with those different activities. The document also discusses clustering analysis of learner engagement patterns in MOOCs, like samplers, strong starters, mid-way dropouts, and keen completers. Engagement patterns can vary based on pedagogy and learning design.
Talk by Rebeca Ferguson (Open University, UK, and LACE project).
The promise of learning analytics is that they will enable us to understand and optimize learning and the environments in which it takes place. The intention is to develop models, algorithms, and processes that can be widely used. In order to do this, we need to move from small-scale research within our disciplines towards large-scale implementation across our institutions. This is a tough challenge, because educational institutions are stable systems, resistant to change. To avoid failure and maximize success, implementation of learning analytics at scale requires careful consideration of the entire ‘TEL technology complex’. This complex includes the different groups of people involved, the educational beliefs and practices of those groups, the technologies they use, and the specific environments within which they operate. Providing reliable and trustworthy analytics is just one part of implementing analytics at scale. It is also important to develop a clear strategic vision, assess institutional culture critically, identify potential barriers to adoption, develop approaches that can overcome these, and put in place appropriate forms of support, training, and community building. In her keynote, Rebecca introduced tools, resources, organisations and case studies that can be used to support the deployment of learning analytics at scale
By the end of the Carpe Diem workshop, participants should be able to create a blueprint poster with a mission statement and outcomes for their module design. They should also be able to create a storyboard showing content sequencing and assessments. Participants will build at least two prototype online activities and get feedback from students. On the second day, participants reflect on their designs and build out a prototype activity. They then get feedback from student reality checkers and review their designs to see what needs adjustment.
Co-designing learning dashboards for scalable feedbackTinne De Laet
This document discusses co-designing learning dashboards for providing scalable feedback. It describes two dashboards created at KU Leuven: LISSA for advisors and students, and REX for students. LISSA displays grade and activity data to support advisor-student dialog. Evaluations found it helps focus conversations on personal paths. REX is student-facing and shows exam results with tips. A design process involved stakeholders and started with available data to provide actionable but nuanced feedback. Context matters in dashboard design and simply copying solutions may not work.
This document discusses rethinking assessment practices in technology-enhanced learning. It addresses factors like open educational resources and shifting focus from content to activities. eAssessment is available 24/7 with instant feedback and different question types. ePortfolios and various tools in the VLE like Moodle quizzes, blogs, wikis and forums are mentioned. Principles around empowering and engaging students in assessment are outlined. There is discussion on whether we over-assess, building in variability, and moving to awards-based assessment. Different types of learning activities and assessment are also categorized.
Learning Analytics (or: The Data Tsunami Hits Higher Education)Simon Buckingham Shum
Keynote Address to The Impact of Higher Education: Addressing the Challenges of the 21st CenturyEuropean Association for Institutional Research (EAIR) 35th Annual Forum 2013, Erasmus University, Rotterdam, the Netherlands, 28-31 August 2013. http://www.eair.nl/forum/rotterdam
The document discusses visions for the future of learning analytics based on a presentation given by Rebecca Ferguson. It outlines several potential futures for learning analytics, including learners being monitored by their learning environments, learners' personal data being tracked, and learners controlling their own data. It also discusses various challenges regarding ethics, regulation, validity, and affect that will need to be addressed for learning analytics to achieve its potential while avoiding negative consequences. The overall message is that learning analytics show promise to improve education if developed and applied carefully and ethically with student well-being and consent as top priorities.
Presentation by Rebecca Ferguson at Learning and Knowledge 2015 (LAK15), Poughkeepsie, NY, USA.
Massive open online courses (MOOCs) are now being used across the world to provide millions of learners with access to education. Many learners complete these courses successfully, or to their own satisfaction, but the high numbers who do not finish remain a subject of concern for platform providers and educators. In 2013, a team from Stanford University analysed engagement patterns on three MOOCs run on the Coursera platform. They found four distinct patterns of engagement that emerged from MOOCs based on videos and assessments. However, not all platforms take this approach to learning design. Courses on the FutureLearn platform are underpinned by a social-constructivist pedagogy, which includes discussion as an important element. In this paper, we analyse engagement patterns on four FutureLearn MOOCs and find that only two clusters identified previously apply in this case. Instead, we see seven distinct patterns of engagement: Samplers, Strong Starters, Returners, Mid-way Dropouts, Nearly There, Late Completers and Keen Completers. This suggests that patterns of engagement in these massive learning environments are influenced by decisions about pedagogy. We also make some observations about approaches to clustering in this context.
Carpe Diem MOOC:Practical Lessons Learnt- Berlin, Online Educa 2014Gilly Salmon
The document summarizes a MOOC on the Carpe Diem learning design methodology. It provides details on the course aims, design process, participation rates, lessons learned, and research findings. The MOOC used the 6-stage Carpe Diem process to structure content and activities. It engaged over 1000 educators and found that groups, badges, and applying the methodology to their own teaching were beneficial, though attrition made sustained collaboration challenging.
Teaching in MOOCs: Unbundling the roles of the educatorRebecca Ferguson
Teaching in MOOCs: Unbundling the roles of the educator, a presentation given at the design4learning conference at The Open University, Milton Keynes, UK by Rebecca Ferguson (co-authored with Denise Whitelock) on 26 November 2014.
This presentation proposes that Social Learning Analytics (SLA) can be usefully thought of as a subset of learning analytics approaches. SLA focuses on how learners build knowledge together in their cultural and social settings. In the context of online social learning, it takes into account both formal and informal educational environments, including networks and communities. The paper introduces the broad rationale for SLA by reviewing some of the key drivers that make social learning so important today. Five forms of SLA are identified, including those which are inherently social, and others which have social dimensions. The paper goes on to describe early work towards implementing these analytics on SocialLearn, an online learning space in use at the UK’s Open University, and the challenges that this is raising. This work takes an iterative approach to analytics, encouraging learners to respond to and help to shape not only the analytics but also their associated recommendations
Educational Technologies: Learning Analytics and Artificial IntelligenceXavier Ochoa
The document discusses the role of educational technologies like learning analytics and artificial intelligence. It provides examples of how learning analytics can be used to analyze academic data to gain insights about difficult courses, dropout paths, and the relationship between courses. This allows universities to identify issues and redesign programs. It also discusses using learning analytics to build tools like academic advising dashboards that provide personalized recommendations to students about course loads. While artificial intelligence can provide automated feedback at scale, the quality of feedback is still limited and human judgment remains important.
This document discusses the potential for learning analytics to provide insights into student learning. It notes that while basic analytics on outcomes and trends are currently used, learning analytics could offer more nuanced insights at the individual student level by analyzing digital traces of their interactions. However, it cautions that analytics need to be developed with an understanding of what types of learning and learners are being cultivated. A framework is presented for assessing "learning dispositions" like curiosity, creativity and collaboration through student surveys or behavioral analytics. The document advocates for analytics that align with cultivating lifelong, self-directed learners and sees opportunities to provide rapid feedback to students, teachers and instructional designers.
Best Practices in Learning Management Systems (LMS) - American Honors Faculty...American Honors
- Plan the course structure in advance by creating folders and modules and including all important documents, assignments, and due dates from the start. Restrict student access to unused items.
- Use modules to separate out term-length resources and limit repetition of due dates which can automatically be added to a calendar.
- Provide overview pages and PowerPoint handouts as key resources for students. Embed files, links, images, and videos directly into modules for easy access.
- Ensure all content is properly contextualized and relates back to course themes and questions. The LMS gradebook should accurately reflect all coursework.
Five short presentations from a panel session at the Learning Analytics and Knowledge Conference 2015, on the topic of "Learning Analytics - European Perspectives", held at Marist College, Poughkeepsie on March 18th 2015. The speakers are: Rebecca Ferguson, Alejandra Martinz Mones, Kairit Tammets, Alan Berg, Anne Boyer, and Adam Cooper.
De toekomst van Learning Analytics - wat is haalbaar en wat is wenselijk?SURF Events
Woensdag 11 november
Sessieronde 4
Titel: De toekomst van Learning Analytics - wat is haalbaar en wat is wenselijk?
Spreker(s): Doug Clow (Open University UK), Hendrik Drachsler (Open Universiteit)
Zaal: Leeuwen I
'Visions of future learning'. A presentation given by Rebecca Ferguson to the Plato Institute at the National Hellenic Research Foundation, Athens, Greece on 14 November 2014.
Bring your own idea - Visual learning analyticsJoris Klerkx
Workshop on visual learning analytics that was part of LASI 2014 - http://www.solaresearch.org/events/lasi-2/lasi2014/
Examples of learning dashboards were presented during the workshop by Sven Charleer:
http://www.slideshare.net/svencharleer/learning-dashboard-visual-learning-analytics-workshop-lasi2014-h-harvard
Scaling up learning analytics solutions: Is privacy a show-stopper?Tore Hoel
1) The document discusses the challenges of scaling up learning analytics solutions from research labs to the classroom in light of privacy and ethics concerns.
2) It notes that learning analytics could be considered unlawful if students do not have control over and consent to how their data is used.
3) The presentation raises important questions about data ownership, student consent, and limiting data collection and use to only what is necessary for educational purposes.
A learning design toolkit for creating effective learning activitiesgrainne
This document summarizes a learning design toolkit created by researchers to help teachers design effective learning activities. The toolkit addresses the gap between educational technology potential and how technologies are actually applied based on sound pedagogical principles. It involves reviewing learning theories, defining components of learning activities, and mapping them to real examples. The toolkit guides teachers through articulating information needs to produce lesson plans. It prompts them to consider pedagogical approaches, tasks, tools, and assessments when creating or modifying activities.
This document discusses the relationship between learning design and learning analytics. It argues that learning design provides context that helps frame analytics questions and identify appropriate analysis. A MOOC planner is presented that prompts designers to plan different activity types like delivered content, reflection, collaboration, and assessment. Analytics can then provide insight into how learners engaged with those different activities. The document also discusses clustering analysis of learner engagement patterns in MOOCs, like samplers, strong starters, mid-way dropouts, and keen completers. Engagement patterns can vary based on pedagogy and learning design.
Talk by Rebeca Ferguson (Open University, UK, and LACE project).
The promise of learning analytics is that they will enable us to understand and optimize learning and the environments in which it takes place. The intention is to develop models, algorithms, and processes that can be widely used. In order to do this, we need to move from small-scale research within our disciplines towards large-scale implementation across our institutions. This is a tough challenge, because educational institutions are stable systems, resistant to change. To avoid failure and maximize success, implementation of learning analytics at scale requires careful consideration of the entire ‘TEL technology complex’. This complex includes the different groups of people involved, the educational beliefs and practices of those groups, the technologies they use, and the specific environments within which they operate. Providing reliable and trustworthy analytics is just one part of implementing analytics at scale. It is also important to develop a clear strategic vision, assess institutional culture critically, identify potential barriers to adoption, develop approaches that can overcome these, and put in place appropriate forms of support, training, and community building. In her keynote, Rebecca introduced tools, resources, organisations and case studies that can be used to support the deployment of learning analytics at scale
By the end of the Carpe Diem workshop, participants should be able to create a blueprint poster with a mission statement and outcomes for their module design. They should also be able to create a storyboard showing content sequencing and assessments. Participants will build at least two prototype online activities and get feedback from students. On the second day, participants reflect on their designs and build out a prototype activity. They then get feedback from student reality checkers and review their designs to see what needs adjustment.
Co-designing learning dashboards for scalable feedbackTinne De Laet
This document discusses co-designing learning dashboards for providing scalable feedback. It describes two dashboards created at KU Leuven: LISSA for advisors and students, and REX for students. LISSA displays grade and activity data to support advisor-student dialog. Evaluations found it helps focus conversations on personal paths. REX is student-facing and shows exam results with tips. A design process involved stakeholders and started with available data to provide actionable but nuanced feedback. Context matters in dashboard design and simply copying solutions may not work.
This document discusses rethinking assessment practices in technology-enhanced learning. It addresses factors like open educational resources and shifting focus from content to activities. eAssessment is available 24/7 with instant feedback and different question types. ePortfolios and various tools in the VLE like Moodle quizzes, blogs, wikis and forums are mentioned. Principles around empowering and engaging students in assessment are outlined. There is discussion on whether we over-assess, building in variability, and moving to awards-based assessment. Different types of learning activities and assessment are also categorized.
Learning Analytics (or: The Data Tsunami Hits Higher Education)Simon Buckingham Shum
Keynote Address to The Impact of Higher Education: Addressing the Challenges of the 21st CenturyEuropean Association for Institutional Research (EAIR) 35th Annual Forum 2013, Erasmus University, Rotterdam, the Netherlands, 28-31 August 2013. http://www.eair.nl/forum/rotterdam
The document discusses visions for the future of learning analytics based on a presentation given by Rebecca Ferguson. It outlines several potential futures for learning analytics, including learners being monitored by their learning environments, learners' personal data being tracked, and learners controlling their own data. It also discusses various challenges regarding ethics, regulation, validity, and affect that will need to be addressed for learning analytics to achieve its potential while avoiding negative consequences. The overall message is that learning analytics show promise to improve education if developed and applied carefully and ethically with student well-being and consent as top priorities.
Presentation by Rebecca Ferguson at Learning and Knowledge 2015 (LAK15), Poughkeepsie, NY, USA.
Massive open online courses (MOOCs) are now being used across the world to provide millions of learners with access to education. Many learners complete these courses successfully, or to their own satisfaction, but the high numbers who do not finish remain a subject of concern for platform providers and educators. In 2013, a team from Stanford University analysed engagement patterns on three MOOCs run on the Coursera platform. They found four distinct patterns of engagement that emerged from MOOCs based on videos and assessments. However, not all platforms take this approach to learning design. Courses on the FutureLearn platform are underpinned by a social-constructivist pedagogy, which includes discussion as an important element. In this paper, we analyse engagement patterns on four FutureLearn MOOCs and find that only two clusters identified previously apply in this case. Instead, we see seven distinct patterns of engagement: Samplers, Strong Starters, Returners, Mid-way Dropouts, Nearly There, Late Completers and Keen Completers. This suggests that patterns of engagement in these massive learning environments are influenced by decisions about pedagogy. We also make some observations about approaches to clustering in this context.
Carpe Diem MOOC:Practical Lessons Learnt- Berlin, Online Educa 2014Gilly Salmon
The document summarizes a MOOC on the Carpe Diem learning design methodology. It provides details on the course aims, design process, participation rates, lessons learned, and research findings. The MOOC used the 6-stage Carpe Diem process to structure content and activities. It engaged over 1000 educators and found that groups, badges, and applying the methodology to their own teaching were beneficial, though attrition made sustained collaboration challenging.
Teaching in MOOCs: Unbundling the roles of the educatorRebecca Ferguson
Teaching in MOOCs: Unbundling the roles of the educator, a presentation given at the design4learning conference at The Open University, Milton Keynes, UK by Rebecca Ferguson (co-authored with Denise Whitelock) on 26 November 2014.
This presentation proposes that Social Learning Analytics (SLA) can be usefully thought of as a subset of learning analytics approaches. SLA focuses on how learners build knowledge together in their cultural and social settings. In the context of online social learning, it takes into account both formal and informal educational environments, including networks and communities. The paper introduces the broad rationale for SLA by reviewing some of the key drivers that make social learning so important today. Five forms of SLA are identified, including those which are inherently social, and others which have social dimensions. The paper goes on to describe early work towards implementing these analytics on SocialLearn, an online learning space in use at the UK’s Open University, and the challenges that this is raising. This work takes an iterative approach to analytics, encouraging learners to respond to and help to shape not only the analytics but also their associated recommendations
Educational Technologies: Learning Analytics and Artificial IntelligenceXavier Ochoa
The document discusses the role of educational technologies like learning analytics and artificial intelligence. It provides examples of how learning analytics can be used to analyze academic data to gain insights about difficult courses, dropout paths, and the relationship between courses. This allows universities to identify issues and redesign programs. It also discusses using learning analytics to build tools like academic advising dashboards that provide personalized recommendations to students about course loads. While artificial intelligence can provide automated feedback at scale, the quality of feedback is still limited and human judgment remains important.
This document discusses the potential for learning analytics to provide insights into student learning. It notes that while basic analytics on outcomes and trends are currently used, learning analytics could offer more nuanced insights at the individual student level by analyzing digital traces of their interactions. However, it cautions that analytics need to be developed with an understanding of what types of learning and learners are being cultivated. A framework is presented for assessing "learning dispositions" like curiosity, creativity and collaboration through student surveys or behavioral analytics. The document advocates for analytics that align with cultivating lifelong, self-directed learners and sees opportunities to provide rapid feedback to students, teachers and instructional designers.
Best Practices in Learning Management Systems (LMS) - American Honors Faculty...American Honors
- Plan the course structure in advance by creating folders and modules and including all important documents, assignments, and due dates from the start. Restrict student access to unused items.
- Use modules to separate out term-length resources and limit repetition of due dates which can automatically be added to a calendar.
- Provide overview pages and PowerPoint handouts as key resources for students. Embed files, links, images, and videos directly into modules for easy access.
- Ensure all content is properly contextualized and relates back to course themes and questions. The LMS gradebook should accurately reflect all coursework.
The PPP technique is a common method for teaching English as a foreign language. It involves three stages: presentation, practice, and production. In the presentation stage, the teacher introduces new vocabulary and concepts. Comprehension checks are used to ensure student understanding. In the practice stage, students engage in controlled activities to reinforce learning. The production stage allows students to use their new knowledge communicatively through activities like role-plays and discussions. Games and other interactive methods are employed throughout to make practice enjoyable for students.
Repetition is defined as repeating something that has already been said or written, or the recurrence of an action or event. The document discusses how repetition can be used effectively in teaching by helping students remember new vocabulary, grammar rules, and dialogues, but it requires using varied methods to avoid becoming boring. Some effective ways to incorporate repetition into class include short reviews at the beginning and end of lessons, using flashcards, and having students repeat dialogues with fewer written prompts over time. While repetition can aid learning if done strategically, it depends on the teacher's implementation and ensuring students confirm their understanding rather than just repeating through rote learning.
This document provides an overview of a data analysis course covering various statistical techniques including correlation, regression, hypothesis testing, clustering, and time series analysis. The course covers descriptive statistics, data exploration, probability distributions, simple and multiple linear regression analysis, logistic regression analysis, and model building for credit risk analysis. Notes are provided on correlation calculation and its properties. Assumptions and interpretations of linear regression are also summarized. The document is intended as a high-level overview of topics covered in the course rather than an in-depth treatment.
Dr. Hendrik Drachsler is an associate professor researching learning analytics, personalization, recommender systems, and mobile learning. His research focuses on applying these topics in schools, higher education, and medical education. He discusses learning analytics frameworks and models, challenges around educational data standards and privacy, and the importance of developing learner competencies like data literacy and agency.
The document discusses blended learning, which combines different modes of delivery including classroom training, web-based training, and mobile learning. Blended learning allows for active learning and customization to individual learners. It has emerged as a natural choice for training companies and higher education due to benefits like cost savings and flexibility. Advancing technologies will continue impacting and expanding blended learning opportunities.
Business research report proposal expansion through virtual classesGagan Dharwal
The research proposal aims to study the expansion of Geelong Grammar School's educational reach through virtual classes. The proposal outlines the problem statement, research questions, literature review, research methodology, data collection and analysis methods, and expected outcomes. Specifically, the proposal will examine factors affecting course management system selection, faculty training requirements, and student/administrator needs for online courses. Data will be collected through surveys, interviews, and virtual classroom recordings then analyzed using qualitative methods to evaluate the effectiveness and student experience of virtual classes as a supplement to regular teaching. The expected outcome is that virtual classes can help Geelong Grammar School expand its educational coverage while providing students flexible learning opportunities.
Invited talk, INSIGHT Centre for Data Analytics, Univ. Galway, 2 Oct 2013, http://www.insight-centre.org
Abstract:
Data and analytics are transforming how organisations work in all sectors. While there are clearly ethical issues around big data and privacy, there may also be an argument that educational institutions have a moral obligation to use all the information they have to maximize the learner's progress. So, assuming education can't (arguably shouldn't) resist this revolution, the question is how to harness this new capability intelligently. Learning Analytics is an exploding research field and startup market: do leaders know what to ask when the vendors roll up with dazzling dashboards? In this talk I'll provide an overview of developments, and consider some of the key questions we should be asking. Like any modelling technology and accounting system, analytics are not neutral, and do not passively describe sociotechnical reality: they begin to shape it. Moreover, they start with the things that are easiest to count, which doesn't necessarily equate to the things we value in learning. Given the crisis in education at many levels, what realities do we want analytics to perpetuate, or bring into being?
Bio:
Simon Buckingham Shum is Professor of Learning Informatics at the UK Open University's Knowledge Media Institute. He researches, teaches and consults on Learning Analytics, Collective Intelligence and Argument Visualization. His background is B.Sc. Psychology, M.Sc. Ergonomics and Ph.D. Human-Computer Interaction. He co-edited Visualizing Argumentation (Springer 2003), the standard reference in the field, followed by Knowledge Cartography (2008). In the field of Learning Analytics, he served as Program Co-Chair of the 2nd International Learning Analytics LAK12 conference, chaired the LAK13 Discourse-Centric Learning Analytics workshop, and the LASI13 Dispositional Learning Analytics workshop. He is a co-founder of the Society for Learning Analytics Research, Compendium Institute, LearningEmergence.net, and was Co-Founder and General Editor of the Journal of Interactive Media in Education. He serves on the Advisory Groups for a variety of learning analytics initiatives in education and enterprise, and is a Visiting Fellow at University of Bristol Graduate School of Education. Contact him via http://simon.buckinghamshum.net
This document discusses MOOCs and learning analytics. It provides an overview of MOOCs, including their characteristics and growth. It also discusses learning analytics, defining it as measuring data about learners and contexts to optimize learning. Various learning analytics methods and applications are outlined, including at the EDSA and OU. The OU's Analyse tool for early identification of at-risk students using machine learning is also summarized.
How can universities scale up learning analytics beyond small-scale pilots to seriously use data to improve student learning? This interactive workshop was designed to help you think this through for your institution.
Universities are hard to change. Having good data and analytics is a good start, but is only one part of success. This session will provide tools and frameworks to help you analyse what else is needed, building on experiences of successful large-scale learning analytics activity at the Open University and the University of Technology, Sydney, and from the pan-European Learning Analytics Community Exchange project.
Slides for a talk at Bett, London, 20 January 2016.
The document discusses learning analytics and the Jisc learning analytics service. It provides an overview of what learning analytics is, the goals of the Jisc service which include helping institutions get started with learning analytics and providing standard tools, and the components of the Jisc service including a code of practice, community resources, data collection and products like Data Explorer and Study Goal. It also discusses working with institutions, engagement activities, the on-boarding process, and engaging with solution providers.
Jisc is developing a learning analytics service to help higher education institutions in the UK improve student retention and attainment. The service will provide institutions access to standard analytic tools and technologies, and will include a code of practice on legal and ethical issues. A pilot program is underway from 2015-2017 to test the tools and metrics before a full service launch in September 2017. The goals are to help students through personalized learning and improved employability. The service will include an analytic toolkit, online community, and data standards to enable institutions to participate.
1) The document discusses three paradigmatic positions that institutions may take regarding ethics and privacy in learning analytics: proceed with caution and respect existing policies, proceed with caution while still trying to be respectful, or adopt a data-driven approach and adapt policies accordingly.
2) Technical infrastructure is a major concern, as it can constrain or determine an institution's data policies. Systems developed by commercial platforms may not prioritize privacy and individual control.
3) The discussion activity prompts reflection on an institution's current position, any conflicts between stakeholder views, the technical systems that influence policy, and open questions about technology and privacy.
The document discusses national learning analytics in the UK and Jisc's role in providing learning analytics services. It describes Jisc's learning analytics tools and products like the Data Explorer dashboards, Study Goal app, and Learning Data Hub. It outlines Jisc's onboarding process for institutions and examples of how they are working with universities and colleges to implement learning analytics.
Learning Analytics: Realizing the Big Data Promise in the CSUJohn Whitmer, Ed.D.
The word “analytics” has become a buzzword in current educational technology conversations, applied to everything from analysis of student work to LMS usage reporting to institutional analysis of ERP data. Broadly speaking, Learner Analytics refers to the analysis of student data using statistical techniques to improve decision-making. In the context of educational technology, Learner Analytics promises to improve our understanding of effective (and ineffective) student learning and technology usage. What progress have we seen in realizing this promise? This session offers a discussion of the promise of Learner Analytics, current research findings and tools, and explores examples from CSU Chico and the CSU Office of the Chancellor.
Introduction to Learning Analytics - Framework and Implementation ConcernsTore Hoel
This document provides an introduction to learning analytics, including:
1. A definition of learning analytics as the measurement, collection, analysis and reporting of learner data to understand and optimize learning.
2. An overview of how learning analytics is used in universities, schools, and the workplace to predict student performance, track progress, and personalize instruction.
3. A framework model showing how data is transformed into analytics and insights to benefit learners, teachers, and institutions.
The document discusses open learning analytics and the case for openness. It summarizes key points from a presentation including:
- Learning analytics can help identify at-risk students and improve courses, but also raises issues regarding privacy, bias, and transparency.
- Open source approaches to learning analytics aim to address these issues through open data standards, algorithms, and governance structures.
- Early examples from the UK and France explore open learning analytics to provide transparency and safeguards around predictive modeling.
- Ensuring understanding of predictive models, managing consent appropriately, and exploring techniques like counterfactual explanations can help address transparency concerns with learning analytics.
Jisc learning analytics service core slidesPaul Bailey
The document summarizes Jisc's learning analytics service, which aims to help higher education institutions use student data and analytics to improve student outcomes. The service provides tools for predictive modeling, dashboards, and an app for students. It also offers guidance on legal and ethical issues, workshops on implementation, and connects institutions with analytics solution providers. The goal is to support 40 institutions by 2018 through the free core service and additional fee-based products and services.
This document discusses learning analytics and some of the opportunities and issues regarding its use. It describes how learning analytics involves collecting and analyzing student data to better understand students and their learning needs. It provides examples of how some universities are using analytics to identify at-risk students and target interventions. However, it also notes some privacy and ethical concerns and the need for policies around transparent and responsible use of student data. The document advocates for student consent, engagement, and developing skills across institutions to ensure analytics are implemented ethically.
This document discusses learning analytics, which involves measuring, retrieving, collecting, and analyzing student data from various learning environments. Learning analytics can help educators track student progress and behavior to improve instruction and support. However, there are also challenges around data storage, privacy, and ensuring analytics are aligned with educational goals. Opportunities exist to capture more detailed behavioral data through tools, but institutions must have the capacity to maintain analytics systems and apply insights pedagogically.
ow-a-days data volumes are growing rapidly in several domains. Many factors have contributed to this growth, including inter alia proliferation of observational devices, miniaturization of various sensors ,improved logging and tracking of systems, and improvements in the quality and capacity of both disk storage and networks .Analyzing such data provides insights that can be used to guide decision making. To be effective, analysis must be timely and cope with data scales. The scale of the data and the rates at which they arrive make manual inspection infeasible. As an educational management tool, predictive analytics can help and improve the quality of education by letting decision makers address critical issues such as enrollment management and curriculum Development. This paper presents an analytical study of this approach’s prospects for education planning. The goals of predictive analytics are to produce relevant information, actionable insight, better outcomes, and smarter decisions, and to predict future events by analyzing the volume, veracity, velocity, variety, value of large amounts of data and interactive exploration.
This document defines learning analytics as an emerging field that uses sophisticated analytic tools to improve learning and education. It draws from fields like business intelligence, web analytics, academic analytics, and educational data mining. Learning analytics seeks to analyze large amounts of online educational data in real-time to improve student outcomes, identify at-risk students, and enable timely interventions. The goal is to better understand how to optimize learning interactions and support student needs using insights from extensive data on student engagement and performance.
Learning analytics as a national initiativePaul Bailey
Jisc is developing a national learning analytics initiative in the UK that includes three core components: a learning analytics service, toolkit and consultancy, and a community network. The initiative aims to help institutions implement learning analytics through an onboarding process, code of practice, and open architecture service. The service includes predictive models, intervention tools, dashboards, and a student app to improve retention, outcomes, and support through analysis of educational data.
Guest presentation: SASUF Symposium: Digital Technologies, Big Data, and Cybersecurity, Vaal University of Technology, Vanderbijlpark, South Africa, 15 May 2018
RevistingABC: Beyond blended: new definitions, principles and resourcesSheila MacNeill
The document summarizes the findings of a Jisc project on curriculum and learning design in UK higher education. It discusses definitions of curriculum design and learning design. A survey of 155 UK institutions found that teaching and learning strategies are the main drivers of curriculum design and that universities are engaging in major curriculum reviews post-pandemic. Key recommendations include updating workload models to recognize staff engagement in design activities and sharing a vocabulary and examples of different modes of student participation in learning across institutions. The next phase will provide guidance on curriculum design processes and the pedagogies of diverse spaces, places and modes of participation.
Making and Breaking Habits: reflecting on unprecedented times for learning an...Sheila MacNeill
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like anxiety and depression.
Universities and post pandemic digital praxis: critically reframing education...Sheila MacNeill
This document discusses the need to critically reframe education and the university curriculum in a post-pandemic world. It highlights how the pandemic accelerated the digital transformation of universities and provided examples of public pedagogy through daily data sharing. The presentation advocates for using critical lenses like those of Freire and information literacy to challenge structures like growing inequalities. It also explores how the curriculum could become a more open and negotiated space in this context.
Which way now? Can we be directed by critical uncertainty? Sheila MacNeill
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
This document discusses the impact of the COVID-19 pandemic on digital learning and the need to embrace radical uncertainty going forward. It argues that the pandemic has required reimagining concepts like time, space, and learning. Moving beyond just returning to normal, it calls for a radical critique of educational structures and rethinking aspects like curriculum, assessment, time, and focus on self-regulated learning. The hope is that embracing radical uncertainty can help transform education for the future.
This document provides an introduction to open educational practice (OEP). It defines key terms related to open education such as open educational resources (OER), open access, open data, and open licenses. OEP is described as the complex, personal, and contextual use of OER by educators. The document outlines some important dates in the development of open education and discusses how open education is not limited to online resources but includes open sharing of teaching practices. Challenges and opportunities of practicing open education are mentioned. The document suggests ways to engage in open practice such as sharing images, networking, and using open technologies.
New ways of being and belonging: developing approaches to the new student/sta...Sheila MacNeill
The document discusses challenges and questions related to supporting new and continuing students in higher education during the transition to online learning due to COVID-19. It addresses how to help students transition to online learning, reposition pedagogical practices beyond just delivery mode, ensure an equitable experience for all students, consider the relationship between home/digital/campus environments, and support a sense of belonging within online and socially distanced learning communities.
This document discusses the need for universities to adapt their practices in response to the COVID-19 crisis. It explores different models for restructuring the academic calendar and delivering courses online or in a hybrid format. It also acknowledges that the transition to online learning has been difficult for many students, especially those from low-income backgrounds who lack reliable technology or internet access. The document advocates giving students more opportunities to provide input into how their university experience can best support engagement and socialization during this challenging time.
Technology as an Enabler in 2030 – Challenging AssumptionsSheila MacNeill
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow, releases endorphins, and promotes changes in the brain which help enhance one's emotional well-being and mental clarity.
Sheila MacNeill shares quotes about grappling with difficult challenges that seem impossible or incomprehensible. Douglas Adams encourages thinking about the unthinkable and doing the undoable. A quote from the TV show Battlestar Galactica reminds us that crises will repeat throughout history. MacNeill signs off her message by returning the discussion to her conversation partner, Tom.
Digitally enabled tertiary and adult education for challenging timesSheila MacNeill
This document discusses the role of digitally enabled tertiary and adult education in challenging times. It argues that education should be considered a public good and that public pedagogy can challenge mass populism by facilitating open, critical debate using digital technologies. The document proposes using the UHI's learning and teaching values as conceptual tools to guide pedagogical decisions and stimulate creativity. It presents a scenario for values-based course design that incorporates focus, public pedagogy approaches, and situated development within the UHI's values of open scholarship, co-production, praxis, and participation. Academic and organizational development enablers are also discussed, like working groups and action research.
Finding the Good Place: How does digital transformation really happen?Sheila MacNeill
This document discusses digital transformation in education. It defines digital transformation as creating value through new business opportunities, improved customer experiences, and foundational digital capabilities. The document compares elements of digital transformation strategies like people, services, and timelines to elements that make up the fictional "Good Place" like humanity, ethics, and morality. It discusses how digital wellbeing relates to people's health and finding a balance between policy and practice. The document advocates for academic development to be at the heart of digital transformation and critiques current professional recognition structures. It presents a model for a digitally distributed curriculum that is open, negotiated, porous, and critically informed.
A critical, collective, community based approach to enhancing digital develop...Sheila MacNeill
This document summarizes a presentation about taking a critical, collective, and community-based approach to enhancing digital development in higher education. It advocates challenging neo-liberalism through discursive and reflective processes grounded in critical pedagogy and open education. It discusses information literacy as situated practice that can be developed through more sophisticated pedagogical strategies. It argues for focusing on people and pedagogy rather than just technology and managerialism, and making academic development and open education central to organizational development. It proposes critically engaged staff development as key to digital transformation and recentering "the digital" with the curriculum as an open and negotiated space.
Re-imagining digital transformation through critical pedagogy Sheila MacNeill
This document summarizes a presentation on reimagining digital transformation through critical pedagogy. It discusses using critical frames of reference to challenge neo-liberalism and view transformation as more than just technology and managerialism. It argues that academic development and open education should be at the heart of organizational development. Critically engaged academic development is seen as key to digital transformation. The presentation focuses on recentering "the digital" around people and pedagogy, having an open and negotiated curriculum, and promoting civic responsibility over neoliberal consumerism.
unpacking the geopolitics of open for the strategic development of HESheila MacNeill
This document discusses conceptualizing what a digital university is for through an open and dialogic process grounded in critical pedagogy. A small group discussion was held between various participants both in-person and online to challenge neo-liberal views of higher education and refocus on people and pedagogy rather than technology and managerialism. The organizers believe academic development and open education should be at the heart of organizational development and proposed a revised conceptual matrix to frame these issues.
1) The document discusses teaching academic staff about digital capabilities and adapting to changing technology.
2) It introduces the Jisc Digital Capabilities Framework which outlines six elements of digital capabilities including ICT proficiency, information literacy, digital creation, communication, learning and development, and digital identity.
3) Recommendations are made to assess staff digital capabilities, provide short online courses on using technology for teaching, and designing flexible curriculum that incorporates digital skills.
Open Practice and Praxis in the context of the digital university Sheila MacNeill
Slides from presentation at #oer18 conference, 19th April 2018.
https://oer18.oerconf.org/sessions/open-practice-and-praxis-in-the-context-of-the-digital-university-1912/
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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6. Innovating Pedagogy 2014:Open University Innovation Report 3
http://www.open.ac.uk/iet/main/files/iet-web/file/ecms/web-content/Innovating_Pedagogy_2014.pdf
7. Learning Analytics: definition
“the measurement, collection, analysis and
reporting of data about learners and their
contexts, for purposes of understanding and
optimising learning and the environments in
which it occurs”
First International Conference on Learning Analytics and Knowledge
(LAK11), 2011
8. Analytics and Education
“Analytics is the process of developing
actionable insights through problem definition
and the application of statistical models and
analysis against existing and/or simulated future
data”
Adam Cooper, What is Analytics? http://publications.cetis.ac.uk/wp-content/
uploads/2012/11/What-is-Analytics-Vol1-No-5.pdf
9. Questions
A Brief History of Analytics, Adam Cooper,
http://publications.cetis.ac.uk/wp-content/uploads/2012/12/Analytics-Brief-History-Vol-1-No9.pdf
10. Questions?
Questions of information and fact:
• What happened? Analytics produces reports and
summarised descriptions of data (the past).
• What is happening now? Analytics provides alerts in
near-real time, (the present).
• Where are trends leading? Past data is extrapolated,
(the future).
A Brief History of Analytics, Adam Cooper,
http://publications.cetis.ac.uk/wp-content/uploads/2012/12/Analytics-Brief-History-Vol-1-No9.pdf
11. Questions
Questions of understanding and insight:
• How and why did something happen? Analytics builds
models and explanation, (the past).
• What is the best next action? Analytics provides one or
more recommendations, (the present).
• What is likely to happen? Analytics provides one or
more recommendations, (the present).
• What is likely to happen? Analytics provides
prediction, simulators the effect of alternative courses
of action, or identifies an optimal course of action,(the
future).
A Brief History of Analytics, Adam Cooper,
http://publications.cetis.ac.uk/wp-content/uploads/2012/12/Analytics-Brief-History-Vol-
1-No9.pdf
12. Ethics, responsibility, understanding
• Clarity, open definition of purpose, scope and boundaries, even if
that is broad and in some respects open-ended.
• Comfort and care, consideration for both the interests and the
feelings of the data subject and vigilance regarding exceptional
cases.
• Choice and consent, informed opportunity to opt-out or opt-in.
• Consequence and complaint, recognition that there may be
unforeseen consequences and therefore providing mechanisms
for redress.
• OU Ethical use of Student Data for Learning Analytics
Policyhttp://www.open.ac.uk/students/charter/essential-documents/
ethical-use-student-data-learning-analytics-policy
Legal, Risk and Ethical Aspects of Analytics in Higher Education
http://publications.cetis.ac.uk/wp-content/uploads/2012/11/Legal-Risk-and-Ethical-Aspects-of-
Analytics-in-Higher-Education-Vol1-No6.pdf
15. Current UK landscape
• Jisc Report November 2014
• 10 Universities, 2 Colleges & ULCC
“Most interviewees are reluctant to
claim any significant outcomes from
their learning analytics activities to
date – again perhaps demonstrating
that is still early days for the
technologies and process”
http://repository.jisc.ac.uk/5657/1/Learning_analytics_report.pdf
17. Challenges and opportunities
• Data Silos
• Sharing of data
• Senior management support
• Projects are bring people together
18. Activity and information
• LACE (learning analytics community exchange) :
http://www.laceproject.eu/
• SoLAR : Society for Learning Analytics
Researchhttp://solaresearch.org/
• Jisc: http://analytics.jiscinvolve.org/wp
• Cetis Analytics Series :
http://publications.cetis.ac.uk/c/analytics
• LAK15 Conference #lak15