This document discusses a workshop on using learning analytics to support students' transition from secondary to higher education. It introduces the STELA project, which aims to apply learning analytics beyond identifying at-risk students, to provide inclusive and actionable feedback for all students. The workshop agenda includes an introduction to learning analytics, discussion of how it could help with the school transition, and presentation of the STELA project ideas focusing on academic performance, engagement, skills, and well-being. Groups will discuss the project ideas and present their feedback.
Learning Dashboards for Feedback at ScaleTinne De Laet
Learning analytics is hot. But are learning dashboards scalable and sustainable solutions for providing actionable feedback to students? Can learning dashboard be applied for feedback at scale? Is learning analytics applicable in more traditional higher education settings? This talk will share experiences and lessons learned from three European projects (STELA, ABLE, and LALA ) that focuses on scalable applications of learning dashboards and their integration within actual educational practices. Can learning dashboards deployed at scale, create new learning traces? This talk shares experiences of a large scale deployment of learning dashboards with more than 12.000 students. Presented at laffas.eu.
Using learning analytics to improve student transition into and support throu...Tinne De Laet
Presentation supporting the ABLE and STELA workshop titled "Using learning analytics to improve student transition into and support throughout the 1st year" delivered at the EFYE 2016 conference in Gent, Belgium
Fighting level 3: From the LA framework to LA practice on the micro-levelHendrik Drachsler
This presentation explores shortcomings of learning analytics for the wide adoption in educational organisations. It is NOT about ethics and privacy rather than focuses on shortcomings of learning analytics for teachers and students in the classroom (micro-level). We investigated if and to what extend learning analytics dashboards are addressing educational concepts. Map opportunities and challenges for the use of Learning Analytics dashboards for the design of courses, and present an evaluation instrument for the effects of Learning Analytics called EFLA. EFLA can be used to measure the effects of LA tools at the teacher and student side. It is a robust but light (8 items) measurement to quickly investigate the level of adoption of learning analytics in a course (micro-level). The presentation concludes that Learning Analytics is still to much a computer science dicipline that does not fulfill the often claimed position of the middle space between educational and computer science research.
Scalable, Actionable, and Ethical Learning Dashboards: a reality checkTinne De Laet
Keynote presentation at Edmedia 2018 conference: https://www.aace.org/conf/edmedia/speakers/.
Results of Erasmus+ projects ABLE (www.ableproject.eu) and STELA (www.stela-project.eu) on learning dashboards for supporting first-year students.
Candace Thille: The Science of Learning, Big Data, Technology, and Transfor...Alexandra M. Pickett
Will technology change the way we teach and learn? Join Professor Thille for an engaging discussion on technology and the science of learning. She’ll share what we’ve learned from open online courses and what this means for higher education.
Presentation Slides from ISSOTL 2015.
Bronnimann, J., West, D., Heath, D. & Huijser, H. (2015) Leveraging learning analytics for future pedagogies and scholarship. Paper presented at Leading learning and the scholarship of change: 12th annual ISSOTL conference, Melbourne, Australia.
Learning Dashboards for Feedback at ScaleTinne De Laet
Learning analytics is hot. But are learning dashboards scalable and sustainable solutions for providing actionable feedback to students? Can learning dashboard be applied for feedback at scale? Is learning analytics applicable in more traditional higher education settings? This talk will share experiences and lessons learned from three European projects (STELA, ABLE, and LALA ) that focuses on scalable applications of learning dashboards and their integration within actual educational practices. Can learning dashboards deployed at scale, create new learning traces? This talk shares experiences of a large scale deployment of learning dashboards with more than 12.000 students. Presented at laffas.eu.
Using learning analytics to improve student transition into and support throu...Tinne De Laet
Presentation supporting the ABLE and STELA workshop titled "Using learning analytics to improve student transition into and support throughout the 1st year" delivered at the EFYE 2016 conference in Gent, Belgium
Fighting level 3: From the LA framework to LA practice on the micro-levelHendrik Drachsler
This presentation explores shortcomings of learning analytics for the wide adoption in educational organisations. It is NOT about ethics and privacy rather than focuses on shortcomings of learning analytics for teachers and students in the classroom (micro-level). We investigated if and to what extend learning analytics dashboards are addressing educational concepts. Map opportunities and challenges for the use of Learning Analytics dashboards for the design of courses, and present an evaluation instrument for the effects of Learning Analytics called EFLA. EFLA can be used to measure the effects of LA tools at the teacher and student side. It is a robust but light (8 items) measurement to quickly investigate the level of adoption of learning analytics in a course (micro-level). The presentation concludes that Learning Analytics is still to much a computer science dicipline that does not fulfill the often claimed position of the middle space between educational and computer science research.
Scalable, Actionable, and Ethical Learning Dashboards: a reality checkTinne De Laet
Keynote presentation at Edmedia 2018 conference: https://www.aace.org/conf/edmedia/speakers/.
Results of Erasmus+ projects ABLE (www.ableproject.eu) and STELA (www.stela-project.eu) on learning dashboards for supporting first-year students.
Candace Thille: The Science of Learning, Big Data, Technology, and Transfor...Alexandra M. Pickett
Will technology change the way we teach and learn? Join Professor Thille for an engaging discussion on technology and the science of learning. She’ll share what we’ve learned from open online courses and what this means for higher education.
Presentation Slides from ISSOTL 2015.
Bronnimann, J., West, D., Heath, D. & Huijser, H. (2015) Leveraging learning analytics for future pedagogies and scholarship. Paper presented at Leading learning and the scholarship of change: 12th annual ISSOTL conference, Melbourne, Australia.
Nurturing the Connections: The Role of Quantitative Ethnography in Learning A...Dragan Gasevic
This talk will explore connections between two emerging fields focused on harnessing the potential of data – learning analytics and quantitative ethnography. Learning analytics is focused on the analysis of data collected from user interactions with technology with the goal of advancing our understanding of and enhancing human learning. Despite some early success stories and widespread interest, producing meaningful and actionable results is still a top open research challenge for learning analytics. The talk will first explore how quantitative ethnography can offer promising approaches that can address this open challenge in learning analytics. The talk will next discuss how progress in learning analytics can be used to accelerate the development of the field of quantitative ethnography. The talk will finally outline promising directions for future research at the intersection of learning analytics and quantitative ethnography.
Jurgen Schulte is an award-winning academic at UTS who has been using an adaptive learning platform (WileyPLUS Orion) in combination with post processing of the data. In this talk he shares some of his experiences
Introduction to Learning Analytics for High School Teachers and ManagersVitomir Kovanovic
Presentation at the first Learning Analytics Learning Network (LALN) Event in Adelaide, Australia on Oct 22, 2019.
Abstract:
With the increased adoption of technology, institutions have unprecedented opportunities to continuously improve the quality of their services through data collection and analysis. Schools and universities now have data about learners and their contexts that can provide valuable insight into how they learn. Early attempts were directed towards mining educational data to identify students-at-risk and develop interventions. Recently, more sophisticated approaches are being deployed by researchers and practitioners. These include analysis of learner behaviour that leads to various learning outcomes, social networks and teams, employability, creativity, and critical thinking. Analysing digital traces generated through learning processes requires a broad suite of methods from data science, statistics, psychometrics, social and learning sciences.
This workshop aims to introduce teachers and educators to the fast growing and promising field of learning analytics. How digital data can be used for the analysis and improvement of student learning will be explored. First, we will provide an overview of learning analytics, its key methods and approaches, as well as problems for which it can be used. Secondly, attendees will engage in group learning activities to explore ways in which learning analytics could be used within their institutions. The focus will be on identifying learning-related challenges that are relevant to their particular context and exploring how learning analytics can be used to practically and effectively.
Towards Strengthening Links between Learning Analytics and AssessmentDragan Gasevic
. The emergence of learning analytics afforded for the analysis of digital traces of user interaction with technology. This analysis offers many opportunities to advance understanding and enhance learning and the environments in which learning occurs. Existing research has shown how learning analytics can provide contributions to different areas of education such as prediction of student success, uncovering learning strategies, understanding affective states, and unpacking the role social networks in learning. While these results have shown much promise, one critical challenge remains unclear – how learning analytics can help track learning progression and inform assessment especially from the perspective of the 21st century skills. This talk will explore opportunities and challenges for the integration of methods commonly used in learning analytics to analyze different digital traces with methods commonly used in assessment and psychometric research. The paper particularly focuses on open learning environments where analytics-based assessment is rather underexplored in contrast to assessment in specialized (intelligent tutoring) systems where the combined use of data mining and psychometric techniques has been established for some time now.
Observing various learning goals from peers allows learners to specify new objectives and sub-goals to improve their personal experience. Setting goals for learning enhances motivation and performance. However an unrelated goal might lead to poor outcome. Hence learners have divergent objectives for a same learning experience. Latent Dirichlet Allocation (LDA) is a model considering documents as a mixture of topics. This study then proposed a recommendation model based on LDA, able to determine distinct categories of goals within a single dataset. Results focused on a dataset of 10 learning subjects and over 16,000 goal-based Twitter messages. It showed (1) different goal categories and (2) the correlation between the LDA parameter for the number of topics and the type of subject. Evaluations of goal attributes also showed an increase of goal specificity, commitment and self-confidence after observing different types of goals from peers.
Can learning analytics offer meaningful assessment? Dragan Gasevic
The emergence of learning analytics afforded for the analysis of digital traces of user interaction with technology. This analysis offers many opportunities to advance understanding and enhance learning and the environments in which learning occurs. Existing research has shown how learning analytics can provide contributions to different areas of education such as prediction of student success, uncovering learning strategies, understanding affective states, and unpacking the role social networks in learning. While these results have shown much promise, one critical challenge remains unclear – how learning analytics can help track learning progression and inform assessment especially from the perspective of the 21st century skills. This talk will explore opportunities and challenges for the integration of methods commonly used in learning analytics to analyze different digital traces with methods commonly used in assessment. The talk particularly focuses on open learning environments where analytics-based assessment is rather underexplored in contrast to assessment in specialized (intelligent tutoring) systems where the combined use of data mining and assessment has been established for some time now.
Learning Analytics for online and on-campus education: experience and researchTinne De Laet
This presentation was used Tinne De Laet, KU Leuven, for a keynote presentation during the event: http://www.educationandlearning.nl/agenda/2017-10-13-cel-innovation-room-10-learning-and-academic-analytics organised by Leiden University, Erasmus University Rotterdam, and Delft University of Technology.
The presentations presents the results of two case studies from the Erasmus+ project ABLE and STELA, and provides 9 recommendations regarding learning analytics.
Nurturing the Connections: The Role of Quantitative Ethnography in Learning A...Dragan Gasevic
This talk will explore connections between two emerging fields focused on harnessing the potential of data – learning analytics and quantitative ethnography. Learning analytics is focused on the analysis of data collected from user interactions with technology with the goal of advancing our understanding of and enhancing human learning. Despite some early success stories and widespread interest, producing meaningful and actionable results is still a top open research challenge for learning analytics. The talk will first explore how quantitative ethnography can offer promising approaches that can address this open challenge in learning analytics. The talk will next discuss how progress in learning analytics can be used to accelerate the development of the field of quantitative ethnography. The talk will finally outline promising directions for future research at the intersection of learning analytics and quantitative ethnography.
Jurgen Schulte is an award-winning academic at UTS who has been using an adaptive learning platform (WileyPLUS Orion) in combination with post processing of the data. In this talk he shares some of his experiences
Introduction to Learning Analytics for High School Teachers and ManagersVitomir Kovanovic
Presentation at the first Learning Analytics Learning Network (LALN) Event in Adelaide, Australia on Oct 22, 2019.
Abstract:
With the increased adoption of technology, institutions have unprecedented opportunities to continuously improve the quality of their services through data collection and analysis. Schools and universities now have data about learners and their contexts that can provide valuable insight into how they learn. Early attempts were directed towards mining educational data to identify students-at-risk and develop interventions. Recently, more sophisticated approaches are being deployed by researchers and practitioners. These include analysis of learner behaviour that leads to various learning outcomes, social networks and teams, employability, creativity, and critical thinking. Analysing digital traces generated through learning processes requires a broad suite of methods from data science, statistics, psychometrics, social and learning sciences.
This workshop aims to introduce teachers and educators to the fast growing and promising field of learning analytics. How digital data can be used for the analysis and improvement of student learning will be explored. First, we will provide an overview of learning analytics, its key methods and approaches, as well as problems for which it can be used. Secondly, attendees will engage in group learning activities to explore ways in which learning analytics could be used within their institutions. The focus will be on identifying learning-related challenges that are relevant to their particular context and exploring how learning analytics can be used to practically and effectively.
Towards Strengthening Links between Learning Analytics and AssessmentDragan Gasevic
. The emergence of learning analytics afforded for the analysis of digital traces of user interaction with technology. This analysis offers many opportunities to advance understanding and enhance learning and the environments in which learning occurs. Existing research has shown how learning analytics can provide contributions to different areas of education such as prediction of student success, uncovering learning strategies, understanding affective states, and unpacking the role social networks in learning. While these results have shown much promise, one critical challenge remains unclear – how learning analytics can help track learning progression and inform assessment especially from the perspective of the 21st century skills. This talk will explore opportunities and challenges for the integration of methods commonly used in learning analytics to analyze different digital traces with methods commonly used in assessment and psychometric research. The paper particularly focuses on open learning environments where analytics-based assessment is rather underexplored in contrast to assessment in specialized (intelligent tutoring) systems where the combined use of data mining and psychometric techniques has been established for some time now.
Observing various learning goals from peers allows learners to specify new objectives and sub-goals to improve their personal experience. Setting goals for learning enhances motivation and performance. However an unrelated goal might lead to poor outcome. Hence learners have divergent objectives for a same learning experience. Latent Dirichlet Allocation (LDA) is a model considering documents as a mixture of topics. This study then proposed a recommendation model based on LDA, able to determine distinct categories of goals within a single dataset. Results focused on a dataset of 10 learning subjects and over 16,000 goal-based Twitter messages. It showed (1) different goal categories and (2) the correlation between the LDA parameter for the number of topics and the type of subject. Evaluations of goal attributes also showed an increase of goal specificity, commitment and self-confidence after observing different types of goals from peers.
Can learning analytics offer meaningful assessment? Dragan Gasevic
The emergence of learning analytics afforded for the analysis of digital traces of user interaction with technology. This analysis offers many opportunities to advance understanding and enhance learning and the environments in which learning occurs. Existing research has shown how learning analytics can provide contributions to different areas of education such as prediction of student success, uncovering learning strategies, understanding affective states, and unpacking the role social networks in learning. While these results have shown much promise, one critical challenge remains unclear – how learning analytics can help track learning progression and inform assessment especially from the perspective of the 21st century skills. This talk will explore opportunities and challenges for the integration of methods commonly used in learning analytics to analyze different digital traces with methods commonly used in assessment. The talk particularly focuses on open learning environments where analytics-based assessment is rather underexplored in contrast to assessment in specialized (intelligent tutoring) systems where the combined use of data mining and assessment has been established for some time now.
Learning Analytics for online and on-campus education: experience and researchTinne De Laet
This presentation was used Tinne De Laet, KU Leuven, for a keynote presentation during the event: http://www.educationandlearning.nl/agenda/2017-10-13-cel-innovation-room-10-learning-and-academic-analytics organised by Leiden University, Erasmus University Rotterdam, and Delft University of Technology.
The presentations presents the results of two case studies from the Erasmus+ project ABLE and STELA, and provides 9 recommendations regarding learning analytics.
Keynote Presentation: Implementing learning analytics and learning design at ...Bart Rienties
The University of the Roller Coaster
How can Higher Education function in a world struggling to save itself from climate change, pandemics and war? How can it drive innovation and shape the future as the pace of technological change constantly increases? How can it re-invent itself to respond imaginatively to the new challenges facing humanity?
We are living in an uncertain, unpredictable world with no “back to normal” any more. So, how can we re-imagine higher education when nothing can be taken for granted? What kind of technologies can help universities to adapt? What lessons can we learn from recent successes and failures? What 'best practice' examples point the way into the future? How can we shape the development of institutions, so that they are neither “ivory towers” nor “competence factories"? How can we encourage future-oriented universities in which both pedagogy and research are fit for the challenges ahead?
In the Academic Plenary, our experts will examine the threats and opportunities facing higher education today and ask how we can design new approaches that prepare staff and students to thrive in the University of the Roller Coaster.
VII Jornadas eMadrid "Education in exponential times"."Maturing the learning ...eMadrid network
VII Jornadas eMadrid "Education in exponential times"."Maturing the learning analytics framework for applied learning analytics". Hendrik Drachsler. OUNL, Países Bajos. 03/06/2017.
Learning analytics: An opportunity for higher education?Dragan Gasevic
Slides used in my keynote at the Annual Conference of the European Association of Distance Teaching Universities - The open, online, flexible higher education conference - #OOFHEC2015
Edutech_Europe Keynote Presentation: Implementing learning analytics and lear...Bart Rienties
This keynote will help you:
-Understand where to start with learning analytics
-Understand how to effectively support your staff to use data
-Critically review whether learning analytics is something for your organisation
https://www.terrapinn.com/exhibition/edutech-europe/speaker-bart-RIENTIES.stm
Let’s get there! Towards policy for adoption of learning analyticsDragan Gasevic
The field learning analytics is established with the promise for the education sector to embrace the use of data for decision making. There are many examples of successful use of learning analytics to enhance student experience, increase learning outcomes, and optimize learning environments. Despite much interest in learning analytics, many higher education institutions are still looking for effective ways that can enable systemic uptake. The talk will first describe some selected examples of the successful use of learning analytics in higher education. Key challenges identified to affect implementation of learning analytics will then be discussed. This will be followed with an overview of an approach to the development of institutional policy and strategy for the learning analytics implementation in higher education. The talk will be based on the findings of several international studies and will critically interrogate the role of institutional and cultural differences.
Applying and translating learning design and analytics approaches in your ins...Bart Rienties
This interactive workshop delivered by the University of Zagreb, Faculty of Organisation and Informatics (UZ) and the Open University UK (OU) will build on two large-scale implementations of learning design and learning analytics, and how you could potentially implement similar approaches in your institution. The OU has been implementing learning design for nearly 20 years as a structured design, specification, and review process for blended and online courses. The learning design is focused on "what students do" as part of their learning, rather than on "what teachers do" or on what will be taught.
Building on this work, UZ has recently developed the Balanced Design Planning (BDP) tool specifically for educators working in hybrid and blended contexts. The tool is more focused on intended learning outcomes and automated learning analytics and is currently being developed, tested, evaluated and implemented with 1000+ practitioners from dozens of institutions in 20+ countries as part of four European projects (eDesk, Teach4EDU, RAPIDE, iLED), and is publicly available for other institutions to use for free. It has been shown by studies conducted by OU and UZ that when these learning design (LD) approaches are used, they help educators to make real-time informed decisions based on learning analytics (LA) and improve the predictive modelling of student behaviour.
Attendees should bring their laptop for this workshop session.
Bart Rienties, Professor in Learning Analytics, Institute of Education Technology, The Open University
Digital Systems and Services for Open Access Education and LearningDemetrios G. Sampson
Demetrios G Sampson
Digital Systems and Services for Open Access Education and Learning - Seminar Slides
Beijing Forum 2013, Panel II: Global Engagement and Knowledge Sharing in Higher Education,Beijing Municipal Government, Beijing, China, 31 October – 3 November 2013
Summer School “New Media and Learning”, Peking University, Beijing, China, 17 July 2013
Joint IEEE TCLT Online Seminar and Beijing Normal University (BNU) International Course 2013 on “The New Development of Technology Enhanced Learning: Concept, Research and Best Practices”, 20 June 2013
Data-based feedback through learning dashboards: does it support the first-ye...Tinne De Laet
Presentation supporting the EFYE 2018 pre-conference workshop "Data-based feedback through learning dashboards: does it support the first-year experience" - https://efye2018.nl/programme/parallel-sessions/
Improving education by learning analtyicsTinne De Laet
These are the slides of the invited talk "improving education by learning analytics" for the LAW studiedag 2017 https://www.maastrichtuniversity.nl/nl/events/studiedag-2017.
Learning dashboards for actionable feedback: the (non)sense of chances of suc...Tinne De Laet
Presentation at Leuven Learning Lab’s first annual Educational Technology conference day on Learning Analytics
(https://www.kuleuven.be/english/education/learning-lab).
Learning analytics is hot. But are learning dashboards scalable and sustainable solutions for providing actionable feedback to students? Is learning analytics applicable in more traditional higher education settings? This talk will share experiences and lessons learned from two European projects (ABLE and STELA) that aimed at developing learning dashboards for more traditional higher education institutions and integrating it within actual educational practices. The talk will challenge your beliefs regarding “chances of success” and predictive models in higher education.
Learning dashboards for actionable feedback: the (non)sense of chances of suc...Tinne De Laet
Presentation at humane event on digital transformation in higher education (http://www.humane.eu/events/seminars-and-conferences/2018/aveiro-042018/).
Learning analytics is hot. But are learning dashboards scalable and sustainable solutions for providing actionable feedback to students? Is learning analytics applicable in more traditional higher education settings? This talk will share experiences and lessons learned from two European projects (ABLE and STELA) that aimed at developing learning dashboards for more traditional higher education institutions and integrating it within actual educational practices. The talk will challenge your beliefs regarding “chances of success” and predictive models in higher education.
Learning analytics tussen droom en daad: eerlijke ervaringen uit concrete imp...Tinne De Laet
Presentatie gegeven tijdens https://www.surf.nl/agenda/2018/05/seminar-aan-de-slag-met-learning-analytics/index.html.
Ervaringen met learning dashboard opgedaan binnen KU Leuven in kader van twee Erasmus+ projecten ABLE en STELA.
Learning dashboards voor feedback op leer- en studeervaardigheden en academis...Tinne De Laet
Keynote presentatie van LESEC annual event 2018 (https://set.kuleuven.be/LESEC/news-events/annual-event-2018) over learning dashboards. Concreet bevat de presentatie bevindingen en aanbevelingen van grootschalige piloten binnen KU Leuven in kader van twee Europese Erasmus+ projecten: ABLE en STELA.
Confidence in and beliefs about first year engineering student successTinne De Laet
This paper explores the confidence freshman engineering students have in being successful in the first study year and which study-related behaviour they believe to be important to this end. Additionally, this paper studies which feedback these students would like to receive and compares it with the experiences of second-year students regarding feedback. To this end, two questionnaires were administered: one with freshman engineering students to measure their expectations regarding study success and expected feedback and one with second-year engineering students to evaluate their first year feedback experience.
The results show that starting first-year engineering students are confident regarding their study success. This confidence is however higher than the observed first-year students success. Not surprisingly, first-year students have good intentions and believe that most academic activities are important for student success. When second-year students look back on their first year, their beliefs in the importance of these activities have strongly decreased, especially regarding the importance of preparing classes and following communication through email and the virtual learning environment. First-year students expect feedback regarding their academic performance and engagement. They expect that this feedback primarily focuses on the impact on their future study pathway rather than on comparison to peer students. Second-year students indicate that the amount of feedback they receive could be improved, but agree with the first-year students that comparative feedback is less important.
Conference Key Areas: Engineering Education Research, Attractiveness of Engineering Education, Gender and Diversity
Keywords: academic self-confidence, feedback, reasons for students success, student beliefs
Learning and study strategies: a learning analytics approach for feedbackTinne De Laet
Presentation of a learning dashboard developed by KU Leuven within the STELA project (http://stela-project.eu//).
Learning dashboard supported by learning analytics, showing off the use of technology for learning in higher education, for the transition of secondary to higher education in particular. The dashboard provides feedback on the learning and study strategies, as measured by the LASSI questionnaire.
Presentation of the learning dashboard developed by KU Leuven within the ABLE project (http://www.ableproject.eu/).
Learning dashboard supported by learning analytics, showing off the use of technology for learning in higher education, for the transition of secondary to higher education in particular. The dashboard is developed for the interaction between study advisor and student. More information in our journal paper http://ieeexplore.ieee.org/document/7959628/
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Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Ethnobotany and Ethnopharmacology:
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Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
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!
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
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An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
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.
Successful transition from secondary to higher education using learning analytics
1. Successful transition from
secondary to higher
education using learning
analytics
TINNE DE LAET, TOM BROOS (KU LEUVEN)
JAN-PAUL VAN STAALDUINEN (TU DELFT)
PHILIPP LEITNER, MARTIN EBNER (TU GRAZ)
1
STELA - Erasmus+ Project
562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD
2. Welcome!
Who are we?
Tinne De Laet ( KU Leuven)
Head of Tutorial Services of Engineering Science
promotor STELA
background = mechanical engineer
Tom Broos (KU Leuven)
Doctoral researcher STELA
Philipp Leitner (TU Graz)
Doctoral researcher STELA
2
STELA - Erasmus+ Project
562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD
3. Welcome
Would you please introduce yourself to the people on your table
Who are you?
How familiar are you with learning analytics?
Is your institute applying learning analytics?
3
STELA - Erasmus+ Project
562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD
4. Agenda for workshop
Welcome
What is learning analytics? (10 minutes)
STELA project:
Presentation of project goal & challenges (2 minutes)
Group discussion: how could learning analytics help? (10 minutes)
STELA project:
Presentation of project ideas (10 minutes)
Group discussion on project ideas (10 minutes)
Learning analytics technology (10 minutes)
Groups present their remarks, suggestions, … (10 minutes)
Wrap up, goodbye (3 minutes)
4
STELA - Erasmus+ Project
562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD
5. Agenda for workshop
…. so what we expect from you
participate in discussion in groups
each group gathers 3 ideas, thoughts, remarks, suggestions, ..
present them to each other at end of the workshop
5
STELA - Erasmus+ Project
562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD
6. What is learning analytics?
6
STELA - Erasmus+ Project
562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD
7. What is Learning Analytics?
no universally agreed definition
“the measurement, collection, analysis and reporting of data about
learners and their contexts, for purposes of understanding and
optimizing learning and the environments in which it occurs” [1]
[1] Learning and Academic Analytics, Siemens, G., 5 August
2011, http://www.learninganalytics.net/?p=131
[2] What is Analytics? Definition and Essential Characteristics, Vol. 1, No. 5. CETIS Analytics Series,
Cooper, A., http://publications.cetis.ac.uk/2012/521
“the process of developing actionable insights through problem
definition and the application of statistical models and analysis against
existing and/or simulated future data” [2]
7
STELA - Erasmus+ Project
562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD
8. What is Learning Analytics?
no universally agreed definition
[3] Learning Analytics and Educational Data Mining, Erik Duval’s Weblog, 30 January 2012,
https://erikduval.wordpress.com/2012/01/30/learning-analytics-and-educational-data-mining/
“learning analytics is about
collecting traces that learners
leave behind and using those
traces to improve learning”
[Erik Duval, 3]
† 12 March 2016
8
9. What is Learning Analytics?
How is learning analytics different from institutional data? [4]
High-level figures:
provide an overview for internal and external reports;
used for organisational planning purposes.
Academic analytics:
figures on retention and success, used by the institution to assess performance.
Educational data mining:
searching for patterns in the data.
Learning analytics:
use of data, which may include ‘big data’,
to provide actionable intelligence for learners and teachers.
[4] Learning analytics FAQs, Rebecca Ferguson, Slideshare, http://www.slideshare.net/R3beccaF/learning-
analytics-fa-qs
9
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10. What is Learning Analytics?
Different level of analytics
adapted from http://www.slideshare.net/gsiemens/learning-analytics-educause
level beneficiaries
course-level learners, teachers, faculties
aggregate learners, teachers, tutors, counsellors, faculties
institutional administrators, funders, marketing
regional administrators, funders, policy makers
national and
international
national and international governments, policy
makers
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11. What is Learning Analytics?
data visualization versus predictive analytics
is showing data enough?
how to show data to create sense-making and impact?
is predicting study success/drop out the only thing that matters?
can both be combined?
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12. What is Learning Analytics?
learning analytics process model
[Verbert et al. 2013] Verbert K, Duval E, Klerkx J; Govaerts S, Santos JL (2013) Learning analytics dashboard
applications. American Behavioural Scientist, 10 pages. Published online February 201, doi:
10.1177/0002764213479363
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13. What is Learning Analytics?
how to evaluate learning analytics?
is perceived usefulness enough?
is increased self-awareness enough? How will you measure this?
is increased sense-making enough? How will you measure this?
how could impact be measured?
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14. What is Learning Analytics?
six critical dimensions of learning analytics
[Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning
Analytics. Educational Technology & Society, 15 (3), 42–57. http://ifets.info/journals/15_3/4.pdf ]
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15. What is Learning Analytics?
six critical dimensions of learning analytics
[Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning
Analytics. Educational Technology & Society, 15 (3), 42–57. http://ifets.info/journals/15_3/4.pdf ]
Tutors
Policy makers
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16. What is Learning Analytics?
data subjects
here: students
(could also be teachers)
data clients
students
tutors
academic administrators
policy makers
[Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning
Analytics. Educational Technology & Society, 15 (3), 42–57. http://ifets.info/journals/15_3/4.pdf ]
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17. What is Learning Analytics?
what are the objectives?
is it about reflection or prediction?
is showing data enough?
how to show data to create self-awareness, sense-making
and impact?
[Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning
Analytics. Educational Technology & Society, 15 (3), 42–57. http://ifets.info/journals/15_3/4.pdf ]
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18. What is Learning Analytics?
which data is available?
is it open? protected?
is it ethical to use the data?
[Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning
Analytics. Educational Technology & Society, 15 (3), 42–57. http://ifets.info/journals/15_3/4.pdf ]
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19. What is Learning Analytics?
Technology, algorithms, theories are at the basis of
learning analytics
open source or as close as possible to (proprietary)
university systems?
pedagogic theories for supporting students
[Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning
Analytics. Educational Technology & Society, 15 (3), 42–57. http://ifets.info/journals/15_3/4.pdf ]
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STELA - Erasmus+ Project
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20. What is Learning Analytics?
[Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning
Analytics. Educational Technology & Society, 15 (3), 42–57. http://ifets.info/journals/15_3/4.pdf ]
• conventions: ethics, personal
privacy, and similar socially
motivated limitations
• norms: restricted by laws or specific
mandated policies or standard
ethics and privacy IS a big issue
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21. What is Learning Analytics?
[Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning
Analytics. Educational Technology & Society, 15 (3), 42–57. http://ifets.info/journals/15_3/4.pdf ]
• competences: application of
learning analytics requires new
higher-order competences to
enable fruitful exploitation in
learning and teaching
• acceptance: acceptance factors
can further influence the
application or decision making that
follows an analytics process
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22. Agenda for workshop
Welcome
What is learning analytics? (10 minutes)
STELA project:
Presentation of project goal & challenges (2 minutes)
Group discussion: how could learning analytics help? (10 minutes):
Presentation of project ideas (10 minutes)
Group discussion on project ideas (10 minutes)
Learning analytics technology (10 minutes)
Groups present their remarks, suggestions, … (10 minutes)
Wrap up, goodbye (3 minutes)
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24. STELA project
focus: transition from secondary to higher education
(summer before entering university + 1st year experience)
goal: applying learning analytics to support transition
student-centered
additional focus to tutors, student counsellors
1. beyond identifying at-risk students
inclusive approach: feedback for every student
2. beyond single course
entire program
3. provide actionable feedback
ability to remediate based on feedback
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25. STELA project
Group discussion: how could
learning analytics help?
(10 minutes)
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STELA - Erasmus+ Project
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26. Group discussion: how could learning
analytics help? (10 minutes)
What are challenges in the transition from secondary to higher
education?
Which actionable feedback could support students in the
transition?
How could learning analytics help in this matter?
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27. Agenda for workshop
Welcome
What is learning analytics? (10 minutes)
STELA project:
Presentation of project goal & challenges (2 minutes)
Group discussion: how could learning analytics help? (10 minutes):
Presentation of project ideas (10 minutes)
Group discussion on project ideas (10 minutes)
Learning analytics technology (10 minutes)
Groups present their remarks, suggestions, … (10 minutes)
Wrap up, goodbye (3 minutes)
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28. STELA project: project ideas
four areas of focus
1. academic performance
2. academic engagement
3. academic skills
4. academic well-being
How?
position students with respect to peers
show impact on future study pathway
→ show how students with similar profile did in the past
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29. STELA project: project ideas
(1/4) academic performance
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data (often) easily available
present at all universities
after the facts
strong relation performanceT-1 ~ performance
Source: ABLE project (2015-1-UK01-KA203-013767)
30. STELA project: project ideas
(2/4) academic engagement
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depends on context
• e.g. card swipes at Nottingham Trent University,
• learning platform activity at KU Leuven.
relation engagement ~ performance not always
straightforward.
data not always available
31. STELA project: project ideas
(3/4) academic skills
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Number of peers:
Motivation Score
Very high
PerformanceAnxiety
High
Average
Low
Very Low
Very weak Weak Average High Very High
Recommendations
First aid for stress workshop at Student Health Center
Talk to a student counselor.
often self-reported
tests and questionnaires available form pedagogy
and psychology
• Time management, motivation, persistence, …
opportunity to move from information to
recommendation
32. STELA project: project ideas
(4/4) academic well-being
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How do you feel about this course now?
Last week, others felt like this:
opportunity to complement with continuous, bi-
directional feedback
tests and questionnaires available form pedagogy
and psychology
33. Agenda for workshop
Welcome
What is learning analytics? (10 minutes)
STELA project:
Presentation of project goal & challenges (2 minutes)
Group discussion: how could learning analytics help? (10 minutes):
Presentation of project ideas (10 minutes)
Group discussion on project ideas (10 minutes)
Learning analytics technology (10 minutes)
Groups present their remarks, suggestions, … (10 minutes)
Wrap up, goodbye (3 minutes)
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STELA - Erasmus+ Project
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35. Learning Analytics technology
Challenges
multiple and different kind of data-sources
lots of data
need to be combined and analyzed
scalable
real-time?
visualized
...
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37. Learning Analytics technology
(1/3) Data Collection: Logstash¹
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flexbile and open source (Apache 2 Open Source License)
data collection, enrichtment and transportation pipeline
efficiently process log, event and unstructured data sources
¹) https://www.elastic.co/products/logstash
38. Learning Analytics technology
(2/3) Search and Analytics Engine: Elasticsearch²
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distributed, open source search and analytics engine
scalability, reliability, and easy management
developer-friendly query language covering structured,
unstructured, and time-series data
²) https://www.elastic.co/de/products/elasticsearch
39. Learning Analytics technology
(3/3) Visualization: Kibana³ or Grafana4
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3
) https://www.elastic.co/products/kibana
4
) http://grafana.org/
open source data visualization platform
interact with data through powerful graphics
easy extensibility and a variety of panels
40. Agenda for workshop
Welcome
What is learning analytics? (10 minutes)
STELA project:
Presentation of project goal & challenges (2 minutes)
Group discussion: how could learning analytics help? (10 minutes):
Presentation of project ideas (10 minutes)
Group discussion on project ideas (10 minutes)
Learning analytics technology (10 minutes)
Groups present their remarks, suggestions, … (10 minutes)
Wrap up, goodbye (3 minutes)
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