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
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.
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).
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.
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
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
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.
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).
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.
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
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
Open Education Challenge 2014: exploiting Linked Data in Educational Applicat...Stefan Dietze
Presentation from mentoring event of Open Education Europa Challenge (http://www.openeducationchallenge.eu/) about using Linked Data in educational applications.
B2: Open Up: Open Data in the Public SectorMarieke Guy
Parallel session [B2: Open Up: Open Data in the Public Sector] run at the Institutional Web Management Workshop 2013 (IWMW 2013) event, University of Bath on 26 - 28th June 2013.
Archaeological Training in an Open Access World: Lessons from the REWARD Proj...ariadnenetwork
Presentation by Anastasia Sakellariadi and Brian Hole (UCL Institute of Archaeology & Ubiquity Press)
EAA 2014 session: Open Access and Open Data in Archaeology
Istanbul, Turkey
13 September 2013
Presenter: Peter Burnhill, Director, EDINA national academic data centre, University of Edinburgh, Scotland UK
Presentation given at Beyond Books: What STM & Social Science publishing should learn from each other Marriott Hotel/Kensington, London, 22 April 2010
LACE: Learning Analytics Community Exchange (for LASI 2014)Doug Clow
Presentation about the LACE project (Learning Analytics Community Exchange) at LASI2014, the Learning Analytics Summer Institute held at Harvard, on 30 June 2014.
Project MILDRED: Charting Ground for Research Data Management Services at Uni...Mari Elisa Kuusniemi
Introduction: This paper describes a topical case study conducted at University of Helsinki. Current states of research data management (RDM) practices within the academic community have been under close scrutiny during summer 2016 in Project MILDRED, Development Project of Research Data Infrastructure at University of Helsinki (UH).
Mart van Duijn and Laurents Sesink gave this presentation at the 2017 LIBER conference. It deals with the challenges on the curation of born digital materials at Leiden University Libraries.
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
The Needs of stakeholders in the RDM process - the role of LEARNLEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Martin Moyle/Paul Ayris, UCL Library Services
Tutorial given at LAK13 conference, Leuven, April, 9th, 2013. The presentation is informed by WP2 of the LinkedUp-project.eu that develops an Evaluation Framework for Open Web Data (Linked Data) Applications for Education purposes.
Open Education Challenge 2014: exploiting Linked Data in Educational Applicat...Stefan Dietze
Presentation from mentoring event of Open Education Europa Challenge (http://www.openeducationchallenge.eu/) about using Linked Data in educational applications.
B2: Open Up: Open Data in the Public SectorMarieke Guy
Parallel session [B2: Open Up: Open Data in the Public Sector] run at the Institutional Web Management Workshop 2013 (IWMW 2013) event, University of Bath on 26 - 28th June 2013.
Archaeological Training in an Open Access World: Lessons from the REWARD Proj...ariadnenetwork
Presentation by Anastasia Sakellariadi and Brian Hole (UCL Institute of Archaeology & Ubiquity Press)
EAA 2014 session: Open Access and Open Data in Archaeology
Istanbul, Turkey
13 September 2013
Presenter: Peter Burnhill, Director, EDINA national academic data centre, University of Edinburgh, Scotland UK
Presentation given at Beyond Books: What STM & Social Science publishing should learn from each other Marriott Hotel/Kensington, London, 22 April 2010
LACE: Learning Analytics Community Exchange (for LASI 2014)Doug Clow
Presentation about the LACE project (Learning Analytics Community Exchange) at LASI2014, the Learning Analytics Summer Institute held at Harvard, on 30 June 2014.
Project MILDRED: Charting Ground for Research Data Management Services at Uni...Mari Elisa Kuusniemi
Introduction: This paper describes a topical case study conducted at University of Helsinki. Current states of research data management (RDM) practices within the academic community have been under close scrutiny during summer 2016 in Project MILDRED, Development Project of Research Data Infrastructure at University of Helsinki (UH).
Mart van Duijn and Laurents Sesink gave this presentation at the 2017 LIBER conference. It deals with the challenges on the curation of born digital materials at Leiden University Libraries.
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
The Needs of stakeholders in the RDM process - the role of LEARNLEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Martin Moyle/Paul Ayris, UCL Library Services
Tutorial given at LAK13 conference, Leuven, April, 9th, 2013. The presentation is informed by WP2 of the LinkedUp-project.eu that develops an Evaluation Framework for Open Web Data (Linked Data) Applications for Education purposes.
Indo-Japan Trade and Investment Highlights:
India and Japan to work IT together
Japanese firm Looking to Strengthen Aviation Defence Presence in India
Omori to Acquire Majority Stake in Multi Pack Systems
Return of Mazda in India
Currency Swap to Control Falling Rupee and Improving Financial Ties with Japan
Suzuki to make India Hub for Export of Left Wheel Drive Swift Models to other Emerging Markets
India and Japan Launch Joint Research Programs in Applied Science
The Anime Bond
Knowledge Center: Overview of Indian Labour Law
Google Analytics Konferenz 2016: Dashboards mit Google Analytics und Excel me...e-dialog GmbH
Wie Dashboards mit den Analytics Boardmitteln eingerichtet werden können und darüberhinaus in MS Excel durch Plugins automatiisert (und gepimpt) werden können.
The pH Conductivity Meters are multi parameter micro processor based highly accurate pH and conductivity meters these type of meters are best when, more than one parameter in the given solution require to be checked and recorded.For More Information Please Logon http://goo.gl/VEvLke
RDA - A preliminary study of online "Data Science" coursesValerie BRASSE
A preliminary study of online "Data Science" courses; presentation made for dicussion in the "Education and training on handling research data" Interest Group; RDA Plenary 4; Amsterdam; 22/09/2014
Presentation at the “Open Science: connecting the actors” event on the 21st of November 2022:
Share best practices, foster community, and encourage knowledge-sharing on Open Science.
At the heart of the Open Access Belgium community is the ambition to open up the way we organize and conduct scientific research.
The Open Science teams of the Belgian universities have developed and tested a wide range of training methods, training materials, networking activities
and data solutions to facilitate and foster Open Science. Achievements, tools and lessons learned by different institutions will be shared in this networking event.
Programme can be found here: https://openaccess.be/2022/10/04/open-science-connecting-the-actors/
Presentation by Stuart Macdonald of the Edinburgh University Data Library at the Graduate School of Social and Political Science Induction, 15 and 16 Septeber, 2011, University of Edinburgh
Drowning in information – the need of macroscopes for research fundingAndrea Scharnhorst
Andrea Scharnhorst (2015) Drowning in information – the need of macroscopes for research funding. Presentation at the international conference: PLANNING, PREDICTION, SCENARIOS - Using Simulations and Maps - 2015 Annual EA Conference - 11–12 May 2015 Bonn
The facets of open education. Resources, data and culture. Tuesday 17 September, 11:45 – 13:15 @ Room 13, Floor 2
Open data is data that can be freely used, reused and redistributed by anyone. Many institutes offer Open Educational Resources (OER) online. Education can benefit highly from open and linked data approaches.
Moderator: Doug Belshaw, Badges & Skills Lead, Mozilla Foundation
Panel members:
Jackie Carter, Senior Manager, MIMAS, Centre of Excellence, University of Manchester
Mathieu d’Aquin, Research Fellow, Knowledge Media Institute, Open University, UK
Davide Storti, Programme Specialist, Communication and Information Sector (CI), United Nations Educational, Scientific and Cultural Organization (UNESCO)
OKCon, Geneva, 16-18 September 2013
Could the international community collaborate to create a map of the OER world? The William and Flora Hewlett foundation selected three teams to develop a prototype in response to this challenge. These prototypes were shared at the Hewlett Foundation’s OER Grantees Meeting 2014.
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.
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.
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.
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.
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.
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.
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
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.
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.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
1. Mo#va#on
Data
on
the
Web
Some
eyecatching
opener
illustra#ng
growth
and
or
diversity
of
web
data
LAK
–
Data
Challenge
2014
#LAKdata14
Stefan
Dietze
,
Eelco
Herder
(L3S
Research
Center,
DE)
Mathieu
d’Aquin
(The
Open
University,
UK)
Davide
Taibi
(Ins=tute
for
Educa=onal
Technologies
CNR,
IT)
Hendrik
Drachsler
(Welten
Ins=tute,
Open
Universiteit
Nederland,
NL)
09/04/13Hendrik Drachsler
5. 09/04/13
LAK
Challenge
–
sponsored
by
LinkedUp
§ EC-‐funded
support
ac#on,
started
in
11/2012
§ Three
pillars:
§ LinkedUp
Challenge:
open
data
compe==on
(over
1.5
years)
[
hVp://linkedup-‐challenge.org
]
§ Linked
Educa#on
Data:
data
&
catalog
for
large-‐scale
educa=onal
Web
data
applica=ons
§ Evalua#on
Framework
for
open
data
applica=ons
http://www.linkedup-project.eu/
Partners
Stefan Dietze
9. LinkedUp
Data
Catalog
in
a
nutshell
Stefan Dietze 26 March 2014
hVp://data.linkededuca=on.org/linkedup/categories-‐explorer
§ RDF
dataset
catalog
of
Linked
Open
Data
for
learning
§ Browse,
explore
and
query
across
the
LOD
cloud
§ Federated
queries
10.
11. § Open
&
focused
track(s)
§ Final
events
at
ESWC2014
(May,
Crete)
§ Open
Track
only
§ Final
events
at
OKCon
2013
(September
2013,
Geneva)
§ Open
track
&
focused
tracks
§ Submission
details
and
calls
to
be
released
soon
§ Final
events
at
ISWC2014
(October,
Riva
del
Garda,
Italy)
May
–September
2013
October
2013
–
May
2014
May
2014
–
October
2014
?
13. 1st
Place:
PoliMedia
Exploring
poli=cal
debates
&
events
09/04/13Stefan Dietze
§ Explora#on
of
poli#cal
debates
and
news
coverage
§ Automa=cally
generated
links
between
transcripts
debates,
newspaper
ar#cles,
§ Generated
data
available
as
Linked
Data
(
hVp://data.polimedia.nl)
§ Data
sources:
1)
newspapers
in
their
original
layout
of
the
historical
newspaper
archive,
and
2)
radio
bulle=ns
of
the
Dutch
Na=onal
Press
Agency
(ANP)
§ 9000+
debates
(1945
–
1995)
§ Over
3000
media
links
Mar=jn
Kleppe,
Max
Kemman,
Henri
Beunders
(Erasmus
Universiteit
RoVerdam),
Laura
Hollink
Damir
Juric
(Vrije
Universiteit
Amsterdam),
Johan
Oomen
Jaap
Blom
(Nederlands
Ins=tuut
voor
Beeld
en
Geluid)
hVp://www.polimedia.nl/
14. 2nd
Place:
GlobeTown
Open
data
for
sustainable
development
09/04/13Stefan Dietze
§ Exploring
interac=on
between
data
about
environment,
economy
and
society
(cause
and
effect
in
complex
systems)
§ Diverse
open
government
data:
§ SWERA
renewable
energy
data:
hVp://swera.unep.net/,
§ UN
Comtrade
trade
data:
hVp://comtrade.un.org/,
§ Country
names
and
codes:
hVp://opengeocode.org,
§ OECD
sta=s=cs:
hVp://stats.oecd.org/,
§ World
Bank:
hVp://data.worldbank.org
§ Top
three
at
Apps4Climate
compe==on,
held
by
the
World
Bank
Jack
Townsend,
Andrea
Prieto-‐Vega,
Richard
Gomer,
Will
Fyson,
Dom
Hobson,
Huw
Fryer
(University
of
Southampton,
UK)
hVp://www.globe-‐town.org/
15. 3rd
Place/Peoples
Choice:
WeShare
Exploring,
annota=ng,
ra=ng
educa=onal
ICT
tools
Stefan Dietze 26 March 2014
§ Social
&
seman=c
annota#on
applica=on
for
educa#onal
ICT
tools
§ Aids
educators
to
find
tools
to
support
teaching
at
all
educa=onal
levels
§ Gathers
and
enriches
data
from
exis=ng
registries
and
datasets
§ Currently:
approx.
7000
tool
descrip#ons
§ Crowdsourcing:
educators,
tutors
etc
can
modify
and
enrich
data
Adolfo
Ruiz-‐Calleja,
Guillermo
Vega-‐Gorgojo,
Juan
I.
Asensio-‐Pérez,
Eduardo
Gómez-‐Sánchez,
Miguel
L.
Bote-‐Lorenzo,
Carlos
Alario-‐Hoyos
Universidad
de
Valladolid,
Universidad
Carlos
III
de
Madrid,
Valladolid,
Spain
hVp://seek.cloud.gsic.tel.uva.es/weshare/
16. Veni
Awards,
OKCon,
Geneva
• Live streaming of awards
• 900+ at event
• Video of awards online
18. Vidi
Compe##on
Focused Tracks
Looking for prototypes that solve a particular problem
Open Track
19. Overview
• 14 entries from 12 countries
• Currently being looked at by review panel
• Assessing using evaluation framework
• Winners will be announced at ESWC in Crete, May 2014
• Prizes for open track and focused track
• People’s Choice
Vidi
Compe##on
20. May – October
2013
• Soon to be launched!
• Awards ceremony at ISWC, Italy, October 2014
21. Learning
Analy#cs
&
Knowledge
Data
&
Challenge
Facilita=ng
Research
on
Learning
Analy=cs
and
EDM
26 March 2014
hVp://lak.linkededuca=on.org/
LAK
Dataset
(450
publica#ons
in
RDF/R)
§ ACM
Interna=onal
Conference
on
Learning
Analy=cs
and
Knowledge
(LAK)
(2011-‐13)
§ Interna=onal
Conference
on
Educa=onal
Data
Mining
(2008-‐13)
§ Journal
of
Educa=onal
Data
Mining
(2008-‐12)
LAK
Data
Challenge
§ Analyse,
explore
correlate
the
LAK
Dataset
§ At
ACM
LAK
2014
(April
2014,
Indianapolis)
22. Learning
Analy#cs
&
Knowledge
(LAK)
Dataset
§ A
corpus
of
metadata
and
full-‐text
of
all
learning
analy=cs
&
educa=onal
data
mining
publica=ons
§ Freely,
openly
available
in
variety
of
structured
formats
§ Open
access
as
well
as
previously
non-‐public
resources
Publica#on
#
of
papers
Proceedings
of
the
ACM
Interna#onal
Conference
on
Learning
Analy#cs
and
Knowledge
(LAK)
(2011-‐12)
66
The
open
access
journal
Educa#onal
Technology
&
Society
special
issue
on
“Learning
and
Knowledge
Analy#cs”:
Educa=onal
Technology
&
Society
(Special
Issue
on
Learning
&
Knowledge
Analy=cs,
edited
by
George
Siemens
&
Dragan
Gašević),
2012,
15,
(3),
pp.
1-‐163.
10
Proceedings
of
the
Interna#onal
Conference
on
Educa#onal
Data
Mining
(2008-‐12)
239
Journal
of
Educa#onal
Data
Mining
(2008-‐12)
16
Special
permission
from
ACM
26 March 2014 22Hendrik Drachsler
23. Learning
Analy#cs
&
Knowledge
(LAK)
Dataset
Extrac=on
process
26 March 2014
Further reading:
Taibi, D., Dietze, S., Fostering Analytics on Learning
Analytics Research: the LAK Dataset, in: CEUR WS
Proceedings Vol. 974, Proceedings of the LAK Data
Challenge, held at LAK2013 – The Third Conference on
Learning Analytics and Knowledge, April 2013., URL:
http://ceur-ws.org/Vol-974/lakdatachallenge2013_preface.pdfHendrik Drachsler
24. LAK
Challenge
Submissions
(accepted)in
a
nutshell
4%
7%
4%
17%
3%
3%
21%
17%
14%
10%
authors
Brazil
Canada
France
Germany
Italy
Netherlands
Serbia
Spain
United
Kingdom
26 March 2014 24Hendrik Drachsler
31. #LAKdata13
–
Central
topics
• Learners-‐model-‐data
Student-‐model-‐parameter-‐skill
• Model-‐data-‐features-‐predic=on
• network-‐community-‐discussion-‐analysis
(2011
)
26 March 2014 31
Hendrik Drachsler
EDM LAK
• Intelligent
tutoring
systems
• Accuracy
of
different
types
of
predic=ve
models
• Revealing
unexpected
paVerns
• Feature
extrac=on
• Types
of
parameter
• automa=c
support
for
edu.
Processes
• Adapta=on
and
personaliza=on
of
learning
• predic=on,
accuracy
and
precision
• More
focused
on
Teacher
Support
with
LA
to
support
students
• Promo=ng
reflec=on
for
students
and
instructors
• Informal
learning
• Leverage
human
judgment
on
informing
and
empowering
instructors
• Empowering
learners
to
reflect
over
learning
processes
• Network-‐community-‐social-‐users
Shared topics
33. #LAKdata13
–
EDM
&
LAK
26 March 2014 33
Hendrik Drachsler
| 2011 – 1st LAK
34. 26 March 2014 34
#LAKdata14
–
LAK
Data
Challenge
2014
Hendrik Drachsler
35. #LAKdata14
–
Agenda
26 March 2014LinkedUp – Dr. Hendrik Drachsler 35
Chance for some awesome gadgets:
36. Mo#va#on
Data
on
the
Web
Some
eyecatching
opener
illustra#ng
growth
and
or
diversity
of
web
data
LAK
–
Data
Challenge
2015
#LAKdata15
-‐=
FOCUS
TASKS
=-‐
Stefan
Dietze
,
Eelco
Herder
(L3S
Research
Center,
DE)
Mathieu
d’Aquin
(The
Open
University,
UK)
Davide
Taibi
(Ins=tute
for
Educa=onal
Technologies
CNR,
IT)
Hendrik
Drachsler
(Welten
Ins=tute,
Open
Universiteit
Nederland,
NL)
09/04/13Hendrik Drachsler
41. 41
This silde is available at:
http://www.slideshare.com/Drachsler
Email: hendrik.drachsler@ou.nl
Skype: celstec-hendrik.drachsler
Blogging at: http://www.drachsler.de
Twittering at: http://twitter.com/HDrachsler
Many thanks for your attention!
26 March 2014LinkedUp – Dr. Hendrik Drachsler 41