Learning analytics: Threats and opportunitiesMartin Hawksey
Slides used at ALT's White Rose Learning Technologist's SIG to introduce threats and opportunities for using Learning Analytics. Links related to this presentation are at http://bit.ly/LAWhiteRose
Bett 2016 - Implementing learning analytics in your schoolWietse van Bruggen
Presented at Bett 2016, members of the learning analytics community exchange (LACE) project presented insights into aspects schools should think about when using digital learning materials and tools that have LA capabilities.
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.
In May 2018, the new General Data Protection Regulation (GDPR) will enter into force in the European Union. This new regulation is considered as the most modern data protection law for Big Data societies of tomorrow. The GDPR will bring major changes to data ownership and the way data can be accessed, processed, stored, and analysed in the European Union. From May 2018 onwards, data subjects gain fundamental rights such as ‘the right to access data’ or ‘the right to be forgotten’. This will force Big Data system designers to follow a privacy-by-design approach for their infrastructures and fundamentally change the way data can be treated in the European Union.
The presentation provides an overview of the Trusted Learning Analytics Programme as it has been recently initiated at the University of Frankfurt and the DIPF research institute in Germany. Educational data is under special focus of the GDPR, as it is considered as highly sensitive like data from a nuclear plant. It shows opportunities and challenges for using educational data for learning analytics purposes under the light of the GDPR 2018.
Learning analytics: Threats and opportunitiesMartin Hawksey
Slides used at ALT's White Rose Learning Technologist's SIG to introduce threats and opportunities for using Learning Analytics. Links related to this presentation are at http://bit.ly/LAWhiteRose
Bett 2016 - Implementing learning analytics in your schoolWietse van Bruggen
Presented at Bett 2016, members of the learning analytics community exchange (LACE) project presented insights into aspects schools should think about when using digital learning materials and tools that have LA capabilities.
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.
In May 2018, the new General Data Protection Regulation (GDPR) will enter into force in the European Union. This new regulation is considered as the most modern data protection law for Big Data societies of tomorrow. The GDPR will bring major changes to data ownership and the way data can be accessed, processed, stored, and analysed in the European Union. From May 2018 onwards, data subjects gain fundamental rights such as ‘the right to access data’ or ‘the right to be forgotten’. This will force Big Data system designers to follow a privacy-by-design approach for their infrastructures and fundamentally change the way data can be treated in the European Union.
The presentation provides an overview of the Trusted Learning Analytics Programme as it has been recently initiated at the University of Frankfurt and the DIPF research institute in Germany. Educational data is under special focus of the GDPR, as it is considered as highly sensitive like data from a nuclear plant. It shows opportunities and challenges for using educational data for learning analytics purposes under the light of the GDPR 2018.
Presentation given at Serious Request 2015, #SR15, Heerlen.
Within the Open University we started a 12 hours marathon college, to collect money for the charity action of radiostation 3FM. The collected money will go to the red cross and support young people in conflict areas.
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.
The Impact of Learning Analytics on the Dutch Education SystemHendrik Drachsler
The article reports the findings of a Group Concept Mapping
study that was conducted within the framework of the Learning Analytics Summer Institute (LASI) in the Netherlands. Learning Analytics are expected to be beneficial for students and teacher empowerment, personalization, research on learning design, and feedback for performance. The study depicted some management and economics issues and identified some possible treats. No differences were found between novices and experts on how important and feasible are changes in education triggered by
Learning Analytics.
Paper available at: http://dl.acm.org/citation.cfm?id=2567617&CFID=427722877&CFTOKEN=73282080
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
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.
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.
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.
Presentation on learning analytics given by Rebecca Ferguson at the Nordic Learning Analytics Summer Institute (Nordic LASI), organised by the SLATE Centre, in Bergen Norway, 29 September 2017.
Examining the Value of Learning Analytics for Supporting Work-integrated Lear...Vitomir Kovanovic
Slides from our presentation at the Seventh National Conference
on Work-Integrated Learning (ACEN’18).
The full paper is available at https://www.researchgate.net/publication/328578409_Examining_the_value_of_learning_analytics_for_supporting_work-integrated_learning
Presentation by Rebecca Ferguson (IET, The Open University, UK) at the Learning Analytics Summer Institute event (LASI Asia) run in Seoul, South Korea, in September 2016. This presentation, on Visions of the Future of learning analytics, is based on work carried out by the European consortium working on the Learning Analytics Community Exchange (LACE) project.
Can medical education take advantage of Learning Analytics techniques? How? Where? In this presentation a study is analyzed pinpointing three areas in which Medical Education needs to invest and all three are related to Learning Analytics.
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
Using learning analytics to support formative assessment oln 20171111Yi-Shan Tsai
This talk covers ideas about using learning analytics to enhance formative assessment, with an introduction of two learning analytics tools developed in Australia - Loop and OnTask.
Presentation given at Serious Request 2015, #SR15, Heerlen.
Within the Open University we started a 12 hours marathon college, to collect money for the charity action of radiostation 3FM. The collected money will go to the red cross and support young people in conflict areas.
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.
The Impact of Learning Analytics on the Dutch Education SystemHendrik Drachsler
The article reports the findings of a Group Concept Mapping
study that was conducted within the framework of the Learning Analytics Summer Institute (LASI) in the Netherlands. Learning Analytics are expected to be beneficial for students and teacher empowerment, personalization, research on learning design, and feedback for performance. The study depicted some management and economics issues and identified some possible treats. No differences were found between novices and experts on how important and feasible are changes in education triggered by
Learning Analytics.
Paper available at: http://dl.acm.org/citation.cfm?id=2567617&CFID=427722877&CFTOKEN=73282080
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
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.
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.
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.
Presentation on learning analytics given by Rebecca Ferguson at the Nordic Learning Analytics Summer Institute (Nordic LASI), organised by the SLATE Centre, in Bergen Norway, 29 September 2017.
Examining the Value of Learning Analytics for Supporting Work-integrated Lear...Vitomir Kovanovic
Slides from our presentation at the Seventh National Conference
on Work-Integrated Learning (ACEN’18).
The full paper is available at https://www.researchgate.net/publication/328578409_Examining_the_value_of_learning_analytics_for_supporting_work-integrated_learning
Presentation by Rebecca Ferguson (IET, The Open University, UK) at the Learning Analytics Summer Institute event (LASI Asia) run in Seoul, South Korea, in September 2016. This presentation, on Visions of the Future of learning analytics, is based on work carried out by the European consortium working on the Learning Analytics Community Exchange (LACE) project.
Can medical education take advantage of Learning Analytics techniques? How? Where? In this presentation a study is analyzed pinpointing three areas in which Medical Education needs to invest and all three are related to Learning Analytics.
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
Using learning analytics to support formative assessment oln 20171111Yi-Shan Tsai
This talk covers ideas about using learning analytics to enhance formative assessment, with an introduction of two learning analytics tools developed in Australia - Loop and OnTask.
Supporting Higher Education to Integrate Learning Analytics_EUNIS20171107Yi-Shan Tsai
This talk summarised the SHEILA project and its preliminary findings. It was presented at the EUNIS (European University Information Systems) workshop on 7 November 2017.
Technical Challenges for Realizing Learning AnalyticsRalf Klamma
Technical Challenges for Realizing Learning Analytics
Learntec 2015, January 28, 2015, Karlsruhe, Germany,
Ralf Klamma
Advanced Community Informations Systems (ACIS) Group
RWTH Aachen University
New technologies for higher education, Management Workshop “ICT in higher education” in the framework of a VLIR-IUC program from the University of Cuenca, Ecuador, 17/03/10
Presents an overview of the learning analytics field touching on the status of the technology, the challenges it faces, the arrival of predictive analytics to education and the best approach towards a successful implementation.
Role of ICT in Shaping the Future of Pakistani Higher Education SystemZaffar Ahmed Shaikh
This study examined the challenges faced by the Pakistani higher education system (HES) in integrating information and communication technology (ICT); it aimed at understanding ICT needs, measuring the increase in ICT demand, determining the relationship between ICT and HES performance, and understanding how the HES copes with the challenges of implementing ICT. The results of these analyses were used as the basis to suggest solutions. The normative Delphi method was applied to evaluate a sample of 30 HES experts randomly selected from urban and rural areas of Pakistan by administering a literature-based 35-item questionnaire. The
experts revealed significant gaps in ICT demand and supply, ICT use, ICT-based higher education problems, and reasons for delays in ICT integration and provided suggestions for developing ICT-driven HES in Pakistan. This
study’s findings suggest that an effective and robust HES ICT policy could greatly improve the status of the Pakistani knowledge-based economy, thus helping establish ICT policy and planning, administration, and integration at the higher education level.
Bridging XAPI into Higher Education: Learning Analytics, Ownership, and PrivacyChristian Glahn
This presentation targets privacy aspects organisations need to understand and to consider for implementing XAPI and related learning analytics in complex and heterogeneous learning environments.
ICT Integration in Higher Education in Africa - Challenges and OpportunitiesGreig Krull
Saide presentation at the ICT in Higher Education Conference, 14 - 17 September 2012, Kempton Park, Johannesburg. Theme: "An African Perspective". Presentation on the challenges and opportunities for ICT integration in Higher Education. It includes case studies on PHEA ETI and OER Africa.
ICT Leadership in Higher Education: Selected ReadingsCEMCA
Compilation of papers delivered at the three events on ICT Leadership in Higher Education held at Hyderabad (2013), Kandy (June 2014), and Dhaka (December 2014), edited by Sanjaya Mishra
In this webinar, Prof Hendrik Drachsler will reflect on the process of applying learning analytics solutions within higher education settings, its implications, and the critical lessons learned in the Trusted Learning Research Program. The talk will focus on the experience of edutec.science research collective consisting of researchers from the Netherlands and Germany that contribute to the Trusted Learning Analytics (TLA) research program. The TLA program aims to provide actionable and supportive feedback to students and stands in the tradition of human-centered learning analytics concepts. Thus, the TLA program aims to contribute to unfolding the full potential of each learner. It, therefore, applies sensor technology to support psychomotor as well as web technology to support meta-cognitive and collaborative learning skills with high-informative feedback methods. Prof. Drachsler applies validated measurement instruments from the field of psychometric and investigates to what extent Learning Analytics interventions can reproduce the findings of these instruments. During this webinar, Prof Drachsler will discuss the lessons learned from implementing TLA systems. He will touch on TLA prerequisites like ethics, privacy, and data protection, as well as high informative feedback for psychomotor, collaborative, and meta-cognitive competencies and the ongoing research towards a repository, methods, tools and skills that facilitate the uptake of TLA in Germany and the Netherlands.
Dutch Cooking with xAPI Recipes, The Good, the Bad, and the ConsistentHendrik Drachsler
This paper presents the experiences of several Dutch projects in their application of the xAPI standard and different design patterns including the deployment of Learning Record Stores. In this paper we share insights and argue for the formation of an international Special Interest Group on interoperability issues to contribute to the Open Analytics Framework as envisioned by SoLAR and enacted by the Apereo Learning Analytics Initiative. Therefore, we provide an overview of the advantages and disadvantages of implementing the current xAPI standard by presenting projects that applied xAPI in very different ways followed by the lessons learned.
Methodologies for Addressing Privacy and Social Issues in Health Data: A Case...Trilateral Research
Huge quantities of complex and diverse data are generated everyday in healthcare institutions, including clinical documentation (diagnostics, lab data, imaging data, etc.), administrative data, activities and cost data, and R&D data from clinical trials.
Recent Research and Developments on Recommender Systems in TELHendrik Drachsler
Presentation given at the Learning Network seminar series at CELSTEC. Special guest was Wolfgang Reinhardt who provided his view on data science in relation to awareness improvement of knowledge workers.
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
Birgit Schmidt: RDA for Libraries from an International Perspectivedri_ireland
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
Research data management: a tale of two paradigms: Martin Donnelly
Presentation I was supposed to give at "Scotland’s Collections and the Digital Humanities" workshop in Edinburgh on May 2nd 2014. Illness prevented it, but my heroic DCC colleague Jonathan Rans stepped up and delivered the presentation on my behalf.
Research Data Management: A Tale of Two Paradigmstarastar
Presentation by Martin Donnelly, Digital Curation Centre, University of Edinburgh. Invited talk at a workshop for 'Scotland's National Collections and the Digital Humanities,' a knowledge-exchange project hosted at the University of Edinburgh. 2 May 2014. http://www.blogs.hss.ed.ac.uk/archives-now/
Similar to Turning Learning into Numbers - A Learning Analytics Framework (20)
Smart Speaker as Studying Assistant by Joao ParganaHendrik Drachsler
The thesis by Joao Pargana followed two main goals, first, a smart speaker application was created to support learners in informal learning processes through a question/answer application. Second, the impact of the application was tested amongst various users by analyzing how adoption and
transition to newer learning procedures can occur.
Dieser Entwurf eines Verhaltenskodex richtet sich an Hochschulen, die mittels Learning Analytics die Qualität des Lernens und Lehrens verbessern wollen. Der Kodex kann als Vorlage zur Erstellung von organisationsspezifischen Verhaltenskodizes dienen. Er sollte an Hochschulen, die Learning Analytics einführen wollen, durch Konsultationen mit allen Interessengruppen überprüft und an die Ziele sowie die bestehende Praxis innerhalb der jeweiligen Hochschulen angepasst werden. Der Kodex wurde auf Grundlage einer Analyse bestehender europäischer Kodizes und der in Deutschland geltenden Rechtsgrundlage vom Innovationsforum Trusted Learning Analytics des hessenweiten Projektes "Digital gestütztes Lehren und Lernen in Hessen" entwickelt.
Abstract (English):
This code of conduct can be used as a template for creating organization-specific codes of conduct in Germany. The Code was developed on the basis of an analysis of existing European codes of conduct and the legal basis for the usage of data in higher education in Germany.
Rödling, S. (2019). Entwicklung einer Applikation zum assoziativen Medien Ler...Hendrik Drachsler
Ziel der vorliegenden Bachelorarbeit ist es, den Einfluss von zusätzlicher am Handgelenk wahr-genommener Vibration in Verbindung mit der visuellen Darstellung eines Lerninhaltes auf denLernerfolg zu messen. Der Lernerfolg wird hierbei durch die Lerngeschwindigkeit sowie denUmfang der Wissenskonsolidierung über die Testreihe definiert. Zu diesem Zweck wurde eine Experimentalstudie zumAssoziativen Lernendurchgeführt. Für die Studie verwendeten 33Probanden eine App, die für die vorliegende Arbeit entwickelt wurde. Im Mittel aller Studiener-gebnisse wurden sowohl für die Lerngeschwindigkeit als auch für die Wissenskonsolidierungbessere Werte erzielt, wenn die Probanden die Möglichkeit hatten, den Lerninhalt sowohl visu-ell als auch haptisch zu erfahren. Die festgestellten Unterschiede des Lernerfolges erreichtenjedoch keine statistische Signifikanz. Die Abweichungen der Ergebnisse nach der Umsetzungder vorgeschlagenen Änderungen am Studiendesign sind abzuwarten. Die Bachelorarbeit ist vor allem für den Bildungsbereich interessant.
The present bachelor thesis aims to measure the influence of vibration perceived at the wrist in connection with the visual representation of learning content on the learning success. The learning success is defined by the learning speed and the extent of knowledge consolidation over the test series. For this purpose, an experimental study on Associative Learning was conducted. For the study, 33 test persons used an app, which was developed for the present work. On average of all study results better values were achieved for both learning speed and knowledge consolidation, if the test persons could experience the learning content both visually and haptically. However, the differences in learning outcomes did not reach statistical significance. The results of the deviations after the implementation of the proposed changes to the study design must be awaited. The Bachelor’s thesis is particularly interesting for the education sector.
E.Leute: Learning the impact of Learning Analytics with an authentic datasetHendrik Drachsler
Nowadays, data sets of the interactions of users and their corresponding demographic data are becoming more and more valuable for companies and academic institutions like universities
when optimizing their key performance indicators. Whether it is to develop a model to predict the optimal learning path for a student or to sell customers additional products, data sets to
train these models are in high demand. Despite the importance and need for big data sets it still has not become apparent to every decision-maker how crucial data sets like these are for the
future success of their operations.
The objective of this thesis is to demonstrate the use of a data set, gathered from the virtual learning environment of a distance learning university, by answering a selection of questions in
Learning Analytics. Therefore, a real-world data set was analyzed and the selected questions were answered by using state-of-the-art machine learning algorithms.
Romano, G. (2019) Dancing Trainer: A System For Humans To Learn Dancing Using...Hendrik Drachsler
Masters thesis by Romano, G., (2019). Dancing is the ability to feel the music and express it in rhythmic movements with the body. But learning how to dance can be challenging because it requires proper coordination and understanding of rhythm and beat. Dancing courses, online courses or learning with free content are ways to learn dancing. However, solutions with human-computer interaction are rare or
missing. The Dancing Trainer (DT) is proposed as a generic solution to fill this gap. For the beginning, only Salsa is implemented, but more dancing styles can be added. The DT uses the Kinect to interact multimodally with the user. Moreover, this work shows that dancing steps can be defined as gestures with the Kinect v2 to build a dancing corpus. An experiment with
25 participants is conducted to determine the user experience, strengths and weaknesses of the DT. The outcome shows that the users liked the system and that basic dancing steps were
learned.
Presentation given at PELARS Policy event, Brussles, 09.11.2016. A follow up op the first LACE Policy event in April 2015. Special focus is on the exploitation and sustainability activities for LACE in the SIG LACE SoLAR.
Recommendations for Open Online Education: An Algorithmic StudyHendrik Drachsler
Recommending courses to students in online platforms is studied widely. Almost all studies target closed platforms, that belong to a University or some other educational provider. This makes the course recommenders situation specific. Over the last years, a demand has developed for recommender system that suit open online platforms. Those platforms have some common characteristics, such as the lack of rich user profiles with content metadata. Instead they log user interactions within the platform that can be used for analysis and personalization. In this paper, we investigate how user interactions and activities tracked within open online learning platforms can be used to provide recommendations. We present a study in which we investigate the application of several state-of-the-art recommender algorithms, including a graph-based recommender approach. We use data from the OpenU open online learning platform that is in use by the Open University of the Netherlands. The results show that user-based and memory-based methods perform better than model-based and factorization methods. Particularly, the graph-based recommender system proves to outperform the classical approaches on prediction accuracy of recommendations in terms of recall. We conclude that, if the algorithms are chosen wisely, recommenders can contribute to a better experience of learners in open online courses.
Soude Fazeli, Enayat Rajabi, Leonardo Lezcano, Hendrik Drachsler, Peter Sloep
Privacy and Analytics – it’s a DELICATE Issue. A Checklist for Trusted Learni...Hendrik Drachsler
The widespread adoption of Learning Analytics (LA) and Educational Data Mining (EDM) has somewhat stagnated recently, and in some prominent cases even been reversed following concerns by governments, stakeholders and civil rights groups about privacy and ethics applied to the handling of personal data. In this ongoing discussion, fears and realities are often indistin-guishably mixed up, leading to an atmosphere of uncertainty among potential beneficiaries of Learning Analytics, as well as hesitations among institutional managers who aim to innovate their institution’s learning support by implementing data and analytics with a view on improving student success. In this presentation, we try to get to the heart of the matter, by analysing the most common views and the propositions made by the LA community to solve them. We conclude the paper with an eight-point checklist named DELICATE that can be applied by researchers, policy makers and institutional managers to facilitate a trusted implementation of Learning Analytics.
DELICATE checklist - to establish trusted Learning AnalyticsHendrik Drachsler
The DELICATE checklist contains eight action points that should be considered by managers and decision makers planning the implementation of Learning Analytics / Educational Data Mining solutions either for their own institution or with an external provider.
The eight points are:
1. Determination: Decide on the purpose of learning analytics for your institution. What aspects of learning or learner services are you trying to improve?
2. Explain: Define the scope of data collection and usage. Who has a need to have access to the data or the results? Who manages the datasets? On what criteria?
3. Legitimate: Explain how you operate within the legal frameworks, refer to the essential legislation. Is the data collection excessive, random, or fit for purpose?
4. Involve: Talk to stakeholders and give assurances about the data distribution and use. Give as much control as possible to data subjects (permission architecture), and provide access to their data for the individuals.
5. Consent: Seek consent through clear consent questions. Provide an opt-out option.
6. Anonymise: De-identify individuals as much as possible, aggregate data into meta-models.
7. Technical aspects: Monitor who has access to data, especially in areas with high staff turn-over. Establish data storage to high security standards.
8. External partners: Make sure externals provide highest data security standards. Ensure data is only used for intended purposes and not passed on to third parties.
We hope that the DELICATE checklist will be a helpful instrument for any educational institution to demystify the ethics and privacy discussions around Learning Analytics. As we have tried to show in this article, there are ways to design and provide privacy conform Learning Analytics that can benefit all stakeholders and keep control with the users themselves and within the established trusted relationship between them and the institution.
Updated Flyer of the LACE project with latest tangible outcomes and collaboration possibilities.
LACE connects players in the fields of Learning Analytics (LA) and Educational Data Mining (EDM) in order to support the development of a European community and share emerging best practices.
Objectives
-------------
• Promote knowledge creation and exchange
• Increase the evidence base about Learning Analytics
• Contribute to the definition of future directions
• Build consensus on pressing topics like data interoperability, data sharing, ethics and privacy, and Learning Analytics supported instructional design
Activities
• Organise events to connect organisations that are conducting LA/EDM research
• Create and curate a knowledge base to capture evidence for the effectiveness of Learning Analytics
• Produce reviews to inform the LACE community about latest developments in the field
What do analytics on learning analytics tell us? How can we make sense of this emerging field’s historical roots, current state, and future trends, based on how its members report and debate their research?
Challenge submissions should exploit the LAK Dataset for a meaningful purpose. This may include submissions which cover one or more of the following, non-exclusive list of topics:
Analysis & assessment of the emerging LAK community in terms of topics, people, citations or connections with other fields
Innovative applications to explore, navigate and visualise the dataset (and/or its correlation with other datasets)
Usage of the dataset as part of recommender systems
Analysis of the evolution of LAK discipline
Improvement or enrichment of the LAK Dataset
Standardisierte Medizinische Übergaben - Wie lernen, lehren und implementiere...Hendrik Drachsler
Presentation given at Workshop 22 Jahrestagung der Gesellschaft für Medizinische Ausbildung, 27.09.2013, GMA2013, Graz, Austria.
http://portal.ou.nl/documents/363049/fd32b9eb-df7b-4b18-bf5a-d9560425625e
http://creativecommons.org/licenses/by-nc-sa/3.0/
Sopka, S., Druener, S., Stieger, L., Hynes, H., Stoyanov, S., Orrego, C., Secanell, M., Maher, B., Henn, P., Drachsler, H. (2013). Standardized Medical handovers – How to Learn, teach and implement? Workshop at Jahrestagung der Gesellschaft für Medizinische Ausbildung (Annual Meeting of the Society for Medical Education), Graz, Austria.
The presentation provides an overview of the R&D activities of the Learning Analytics topic at the Open Universiteit in October 2013.
http://portal.ou.nl/documents/363049/789b3323-d55c-4e3e-93ba-a716ade14463
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., Specht, M. (2013).
Hoe ziet de toekomst van Learning Analytics er uit?Hendrik Drachsler
Presentation given in the Dutch Masterclass: 'Hoe ziet de toekomst van Learning Analytics er uit?'
http://portal.ou.nl/documents/363049/1adc41e5-52f5-4b08-8b98-bf19b635931a
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., (September, 2013). Hoe ziet de toekomst van Learning Analytics er uit? Open Universiteit, CELSTEC, Heerlen, The Netherlands.
Presentation given at Learning Analytics Summer School Institute (LASI) to kickoff the national GCM study on LA, Amsterdam, The Netherlands.
http://portal.ou.nl/documents/363049/3430aeb1-2450-4587-8f26-e56efd7b80c4
http://creativecommons.org/licenses/by-nc-sa/3.0/
Stoyanov, S., Drachsler, H. (2013). Group Concept Mapping on Learning Analytics. Presentation given at Learning Analytics Summer School Institute (LASI) to kickoff the national GCM study on LA, Amsterdam, The Netherlands.
TEL4Health research at University College Cork (UCC)Hendrik Drachsler
Invited talk given at Application of Science to Simulation, Education and Research on Training for Health Professionals Centre (ASSERT for Health Care)
http://portal.ou.nl/documents/363049/e42710d3-255b-46df-bcba-169f7a5e0341
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., (May, 2013). TEL4Health research at University College Cork (UCC). Invited talk given at Application of Science to Simulation, Education and Research on Training for Health Professionals Centre (ASSERT for Health Care). Cork, Ireland.
Evaluation of Linked Data tools for Learning AnalyticsHendrik Drachsler
Presentation given in the tutorial on 'Using Linked Data for Learning Analytics' at LAK13.
http://portal.ou.nl/documents/363049/ca242534-8996-4fc7-8e42-073cc194c763
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., Herder, E., d'Aquin, M., Dietze, S. (2013). Presentation given in the tutorial on 'Using Linked Data for Learning Analytics' at LAK2013, the Third Conference on Learning Analytics and Knowledge, Leuven, Belgium.
'Using Linked Data in Learning Analytics' is a tutorial targeting researchers in Learning Analytics interested in exploiting linked data resources, developers of Learning Analytics solutions that could benefit from Linked Data and data owners wanting to understand how linked data can help the analysis of their data in relation to other sources of information. The tutorial is described in more details at http://linkedu.eu/event/lak2013-linkeddata-tutorial/, where learning material related to the topic of the tutorial will also be disseminated.
http://portal.ou.nl/documents/363049/033208ab-9dba-43be-b1d8-80d6423c0654
http://creativecommons.org/licenses/by-nc-sa/3.0/
d'Aquin, M., Dietze, S., Herder, E., Drachsler, H. (Eds.) (2013). Tutorial: Using Linked Data in Learning Analytics. Tutorial given at LAK 2013, the Third Conference on Learning Analytics and Knowledge. Leuven, Belgium.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
Palestine last event orientationfvgnh .pptxRaedMohamed3
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.
Basic Civil Engineering Notes of Chapter-6, Topic- Ecosystem, Biodiversity Green house effect & Hydrological cycle
Types of Ecosystem
(1) Natural Ecosystem
(2) Artificial Ecosystem
component of ecosystem
Biotic Components
Abiotic Components
Producers
Consumers
Decomposers
Functions of Ecosystem
Types of Biodiversity
Genetic Biodiversity
Species Biodiversity
Ecological Biodiversity
Importance of Biodiversity
Hydrological Cycle
Green House Effect
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.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Basic phrases for greeting and assisting costumers
Turning Learning into Numbers - A Learning Analytics Framework
1. Turning Learning into Numbers
A Learning Analytics Framework
Graphic by Alex Guerten, 2008
Hendrik Drachsler & Wolfgang Greller
Centre for Learning Sciences and Technologies (CELSTEC)
1
2. Goals of the Presentation
LA Framework
Examples
Data
initiatives
Participation
2
3. A view on Learning Analytics
The Learning
Analytics
Framework
Greller, W., & Drachsler, H., (submitted). Turning Learning into Numbers.
Toward a Generic Framework for Learning Analytics. Journal of Educational
Technology & Society.
3
16. Educational Data
Verbert, K., Manouselis, N., Drachsler, H., and Duval,E. (submitted).Dataset-driven
Research to Support Learning and Knowledge Analytics. Journal of Educational Technology
& Society. 8
17. Educational Data
Drachsler, H., et al. (2010). Issues and Considerations regarding Sharable Data Sets for
Recommender Systems in Technology Enhanced Learning. 1st Workshop Recommnder
Verbert, in Manouselis, N., Drachsler, H., and Duval,E. (submitted).Dataset-driven
SystemsK., Technology Enhanced Learning (RecSysTEL@EC-TEL 2010) September, 28,
Research to Support Learning and Knowledge Analytics. Journal of Educational Technology
2010, Barcelona, Spain.
& Society. 8
18. Educational Data
Drachsler, H., et al. (2010). Issues and Considerations regarding Sharable Data Sets for
Recommender Systems in Technology Enhanced Learning. 1st Workshop Recommnder
Verbert, in Manouselis, N., Drachsler, H., and Duval,E. (submitted).Dataset-driven
SystemsK., Technology Enhanced Learning (RecSysTEL@EC-TEL 2010) September, 28,
Research to Support Learning and Knowledge Analytics. Journal of Educational Technology
2010, Barcelona, Spain.
& Society. 8
19. Educational Data
1.Privacy
2.Prepare datasets
3.Share datasets
4.Body of knowledge
Drachsler, H., et al. (2010). Issues and Considerations regarding Sharable Data Sets for
Recommender Systems in Technology Enhanced Learning. 1st Workshop Recommnder
Verbert, in Manouselis, N., Drachsler, H., and Duval,E. (submitted).Dataset-driven
SystemsK., Technology Enhanced Learning (RecSysTEL@EC-TEL 2010) September, 28,
Research to Support Learning and Knowledge Analytics. Journal of Educational Technology
2010, Barcelona, Spain.
& Society. 8
20. Technologies
Learning Analytics
Hanani et al., (2001). Information Filtering: Overview of Issues,
Research and Systems", User Modeling and User-Adapted
Interaction, 11, 2001 9
21. Technologies
Learning Analytics
Hanani et al., (2001). Information Filtering: Overview of Issues,
Research and Systems", User Modeling and User-Adapted
Interaction, 11, 2001 9
23. Technologies
Reflection
Peter Kraker, Claudia Wagner, Fleur Jeanquartier, Stefanie N. Lindstaedt (2011):
On the Way to a Science Intelligence: Visualizing TEL Tweets for Trend Detection
9
Sixth European Conference on Technology Enhanced Learning (EC-TEL 2011)
24. Technologies
Reflection
Peter Kraker, Claudia Wagner, Fleur Jeanquartier, Stefanie N. Lindstaedt (2011):
On the Way to a Science Intelligence: Visualizing TEL Tweets for Trend Detection
9
Sixth European Conference on Technology Enhanced Learning (EC-TEL 2011)
32. Privacy
1.Privacy as confidentiality
The right to be let alone (Warren and Brandeis, 1890)
2.Privacy as control
The right of the individual to decide what information
about herself should be communicated to others and
under which circumstances.
11
33. Privacy
1.Privacy as confidentiality
The right to be let alone (Warren and Brandeis, 1890)
2.Privacy as control
The right of the individual to decide what information
about herself should be communicated to others and
under which circumstances.
3.Privacy as practice
The right to intervene in the flows of existing data and
the re-negotiation of boundaries with respect to
collected data.
11
35. Privacy solutions
1.Privacy as confidentiality
Information services that minimizing, secure or
anonymize the collected information
12
36. Privacy solutions
1.Privacy as confidentiality
Information services that minimizing, secure or
anonymize the collected information
2.Privacy as control
Identity Management Systems (IDMS),
with access control rules
12
37. Privacy solutions
1.Privacy as confidentiality
Information services that minimizing, secure or
anonymize the collected information
2.Privacy as control
Identity Management Systems (IDMS),
with access control rules
3.Privacy as practice
Timestamp on data, data degradation technologies
12
39. Reading score of 15 year olds of countries
Competences
compared to the percentage of migrants
13
40. Reading score of 15 year olds of countries
Competences
compared to the percentage of migrants
1.E-literacy
2.Interpretation skills
3.Self-directedness
4.Ethical understanding
13
48. Policy guidelines
A brief guide on data licenses developed by SURF and the Centre for
Intellectual Property Law (CIER), 2009 available at
www.surffoundation.nl
18
55. Learning Analytics Challenges
• Reduce the drop-out rate by 10%
through applying Learning Analytics
prediction and reflection techniques.
• Customize data mining techniques to
learning and educational reality.
• Evaluation criteria for Learning
Analytics applications
• Generic infrastructure for sharing, analyzing and reusing
educational data.
• Applying existing privacy and legal protection solutions for
Learning Analytics.
21
56. Open issues
1. Evaluation of LA approaches
2. Comparable experiments
3. Publicly available datasets
4. Body of knowledge
5. New Learning Analytic applications
6. Privacy and data protection
7. Best practice and ethical guidelines
22
59. Special Interest Group - dataTEL
1.Networking
2.Privacy, legal, ethics
3.LA datasets
4.LA products
http://bit.ly/datatel
24
60. Many Thanks::Questions?
This presentation is
available at:
slideshare.com/
Drachsler
Blackmore’s custom-built LSD Drive
http://www.flickr.com/photos/rootoftwo/
Email: hendrik.drachsler@ou.nl
Email: wolfgang.greller@ou.nl
25