The main purposes of the current deliverable D2.1 is to provide the foundations of an Evaluation Framework that can be applied to compare Open Web Data applications and rank them according to their achievements. D2.1 contains the information gained from Task 2.1 - Evaluation criteria and method review and Task 2.2 - Validation of the evaluation criteria and methods of WP2 (DoW. p. 8). According to those tasks, we conducted an expert survey with the Group Concept Mapping method to identify relevant indicators and criteria for the Evaluation Framework. In a second step, we conducted a focused literature review to extend the outcomes of the expert survey with latest indicators reported in the literature. We finally, present the initial concept of the Evaluation Framework and its criteria and indicators.
This deliverable provides the theoretical foundations for the Evaluation Framework that is further developed into a scoring sheet for the judges of LinkedUp challenge in deliverable D2.2.1. The Evaluation Framework will be further developed and amended according to the experiences collected in the three LinkedUp data competitions during the LinkedUp challenge
http://portal.ou.nl/documents/363049/ae41bc18-130b-45d2-94a6-e4b4e42726fe
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., Greller, W., Stoyanov, S., Fetahu, B., Daga, E., Parodi, E., Mosca, M., Adamou, A., Herder, E. (2013). D2.1 Evaluation Criteria and Methods. LinkedUp project. Heerlen, The Netherlands.
This is the PowerPoint presentation used by Terri Fredericka and Jillian Maruskin in their breakout session: Preparing 21st Century Ohio Learners for Success: The 12-13 Initiative at the OHIONET Annual Meeting 2009.
This is the PowerPoint presentation used by Terri Fredericka and Jillian Maruskin in their breakout session: Preparing 21st Century Ohio Learners for Success: The 12-13 Initiative at the OHIONET Annual Meeting 2009.
A brief overview of what is social media and how it is changing the landscape from traditional marketing methodologies.
Presented at Navyam 2012, the annual Marketing Summit of Shri Ram College of Commerce.
A brief look at the features of Mobile as a marketing platform and how it has been leveraged by organisations.
For India: What are the challenges and opportunities Mobile presents as a marketing medium.
Lại một mùa Giáng sinh nữa sắp tới và một năm đầy bận rộn, lo toan sắp trôi qua. Đây là thời điểm ý nghĩa và thích hợp nhất để dành tặng lời yêu thương đến người thân và bạn bè.
Từ tinh thần đó, chương trình "Babyrazzi - Chộp hình, rinh Noel cùng bé" được ra đời để mang lại không khí Giáng sinh ấm áp đển bạn, người thân và bạn bè của bạn.
Hãy tham gia chương trình để tạo những CÁNH THIỆP GIÁNG SINH vui nhộn kèm những lời chúc yêu thương, ấm áp gởi đến người thân và bạn bè. Ngoài ra, những CÁNH THIỆP GIÁNG SINH nào đẹp & ý nghĩa nhất sẽ nhận được những phần thưởng hấp dẫn.
Click vào đường link bên dưới để tham gia nhé:
http://noel.milex.com.vn
D2.3.1 Evaluation results of the LinkedUp Veni competitionHendrik Drachsler
This document D2.3.1 is the first report out of three deliverables (D2.3.2, D2.3.3) of Task 2.4 - Evaluation of challenge submissions. Task 2.4 is about the actual assessment of the participating projects within the LinkedUp Veni, Vidi and Vici competition on the basis of the LinkedUp Evaluation Framework (D2.2.1).
We especially report about the outcomes of the various competitions and analyse the practical experiences of the experts with the LinkedUp Evaluation Framework.
In the current document D2.3.1 we report about the Linked Data tools and ideas that have been submitted to the first data competition - Veni. In total, we received 23 submissions, 8 of them have been shortlisted and invite to a poster presentation at the Open Knowledge Conference (OKCon), 3 of them have been awarded at OKCon according to the Linkedup evaluation process, and one submission received an audience award.
This deliverable provides an overview of the Veni submissions, explains the evaluation procedure that result in a short list of the best submissions, justifies the decision for the winners, and also reports the experiences with the evaluation framework that has been created in the previous WP2 deliverables [7][8]
http://portal.ou.nl/documents/363049/b40fb118-6e65-4875-86e9-8def1266c552
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., Stoyanov, S., Pieper, F., Guy, M. (2013). D2.3.1 Evaluation results of the LinkedUp Veni competition. LinkedUp project. Heerlen, The Netherlands.
The main purpose of the current deliverable D2.2.1 is to hold the current version of the Evaluation Framework and to operationalise it for the LinkedUp challenge judges into a concrete evaluation instrument. This deliverable is not intended as a very elaborated report rather than a summary of the current version of the Evaluation Framework based on the extensive studies in deliverable D2.1 – Evaluation Methods and Metrics. D2.2.1will be reconsidered in the final report of WP2 to demonstrate the development of the Evaluation Framework during the life cycle of the LinkedUp project. For this purpose it is supportive to have the first version of the Evaluation Framework as a tangible outcome and an own entity as conducted in this deliverable.
http://portal.ou.nl/documents/363049/27b00ab7-2c2e-4fda-90a1-6db41e6493ac
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., Greller, W., Stoyanov, S. (2013). D2.2.1 Evaluation Frameowork. LinkedUp project. Heerlen, The Netherlands.
A brief overview of what is social media and how it is changing the landscape from traditional marketing methodologies.
Presented at Navyam 2012, the annual Marketing Summit of Shri Ram College of Commerce.
A brief look at the features of Mobile as a marketing platform and how it has been leveraged by organisations.
For India: What are the challenges and opportunities Mobile presents as a marketing medium.
Lại một mùa Giáng sinh nữa sắp tới và một năm đầy bận rộn, lo toan sắp trôi qua. Đây là thời điểm ý nghĩa và thích hợp nhất để dành tặng lời yêu thương đến người thân và bạn bè.
Từ tinh thần đó, chương trình "Babyrazzi - Chộp hình, rinh Noel cùng bé" được ra đời để mang lại không khí Giáng sinh ấm áp đển bạn, người thân và bạn bè của bạn.
Hãy tham gia chương trình để tạo những CÁNH THIỆP GIÁNG SINH vui nhộn kèm những lời chúc yêu thương, ấm áp gởi đến người thân và bạn bè. Ngoài ra, những CÁNH THIỆP GIÁNG SINH nào đẹp & ý nghĩa nhất sẽ nhận được những phần thưởng hấp dẫn.
Click vào đường link bên dưới để tham gia nhé:
http://noel.milex.com.vn
D2.3.1 Evaluation results of the LinkedUp Veni competitionHendrik Drachsler
This document D2.3.1 is the first report out of three deliverables (D2.3.2, D2.3.3) of Task 2.4 - Evaluation of challenge submissions. Task 2.4 is about the actual assessment of the participating projects within the LinkedUp Veni, Vidi and Vici competition on the basis of the LinkedUp Evaluation Framework (D2.2.1).
We especially report about the outcomes of the various competitions and analyse the practical experiences of the experts with the LinkedUp Evaluation Framework.
In the current document D2.3.1 we report about the Linked Data tools and ideas that have been submitted to the first data competition - Veni. In total, we received 23 submissions, 8 of them have been shortlisted and invite to a poster presentation at the Open Knowledge Conference (OKCon), 3 of them have been awarded at OKCon according to the Linkedup evaluation process, and one submission received an audience award.
This deliverable provides an overview of the Veni submissions, explains the evaluation procedure that result in a short list of the best submissions, justifies the decision for the winners, and also reports the experiences with the evaluation framework that has been created in the previous WP2 deliverables [7][8]
http://portal.ou.nl/documents/363049/b40fb118-6e65-4875-86e9-8def1266c552
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., Stoyanov, S., Pieper, F., Guy, M. (2013). D2.3.1 Evaluation results of the LinkedUp Veni competition. LinkedUp project. Heerlen, The Netherlands.
The main purpose of the current deliverable D2.2.1 is to hold the current version of the Evaluation Framework and to operationalise it for the LinkedUp challenge judges into a concrete evaluation instrument. This deliverable is not intended as a very elaborated report rather than a summary of the current version of the Evaluation Framework based on the extensive studies in deliverable D2.1 – Evaluation Methods and Metrics. D2.2.1will be reconsidered in the final report of WP2 to demonstrate the development of the Evaluation Framework during the life cycle of the LinkedUp project. For this purpose it is supportive to have the first version of the Evaluation Framework as a tangible outcome and an own entity as conducted in this deliverable.
http://portal.ou.nl/documents/363049/27b00ab7-2c2e-4fda-90a1-6db41e6493ac
http://creativecommons.org/licenses/by-nc-sa/3.0/
Drachsler, H., Greller, W., Stoyanov, S. (2013). D2.2.1 Evaluation Frameowork. LinkedUp project. Heerlen, The Netherlands.
This deliverable presents the data management plan for the
ARCADIA project. This data management plan describes what kind of data is generated or collected in the ARCADIA project and how this data is published openly. A simple decision process is defined that either classifies a result as public or non -public. The publishing platforms used are the pro
ject website, the OwnCloud platform and GitHub for open-sourced code. All these platforms can be accessed openly.
Supporting Collaboration and Harnessing of OER Within the Policy Framework of...Saide OER Africa
Supporting Collaboration and Harnessing of OER Within the Policy Framework of KNUST: Report Prepared by OER Africa on Behalf of the Kwame Nkrumah University of Science and Technology (KNUST). As part of a broader process of stimulating collaboration amongst distance education providers taking place under the auspices of the African Council on Distance Education’s Technical Committee on Collaboration, OER Africa and the Kwame Nkrumah University of Science and Technology (KNUST) signed a Memorandum of Understanding that has established a framework for a joint programme of action. Accordingly, OER Africa is providing support to KNUST in review of its current policies to assess the extent to which they facilitate collaboration and alternative, open licences for its educational materials.
Health OER Inter-Institutional Project Formative Evaluation of Health OER Des...Saide OER Africa
The review was to be based on a study of relevant documents, interviews with academic staff involved in institutional policy making and OER production, interviews with students who had experienced OERs (in cases where this was possible). The evaluation approach was not intended to be judgemental, but rather to explore experiences (on progress, achievements and blockages) thus far. Respondents were to be invited to look back in a way that provided experiences as a basis for identifying issues relevant to further project development. Broad approval of the Evaluation Brief was received together with valuable guidance in respect of the conduct of the review, particularly in relation to institution-specific circumstances.
India Energy Security Scenarios Calculator - BTech ProjectAditya Gupta
My undegraduate BTech Project report on assisting the Planning Commission of India (now, Niti Aayog) in building the first version of the IESS-2047 web calculator on energy sustainability.
Made in collaboration with Department of Energy and Climate Change UK, under the guidance of Shrestha Chowdhary (Young professional) and Mr. Anil Jain (Advisor, Enegry, IAS, 86) - Planning Commission.
The report focuses on the engineering aspects of the webtool and the early-stage development journey.The project had a successful release on 28th of February, 2014 at Leela Hotel, New Delhi.
ARIADNE: Final innovation agenda and action planariadnenetwork
D2.4 - The introduction to the Final Innovation Agenda and Action Plan briefly addresses the goals of ARIADNE, the objectives of the agenda and action plan, and the stakeholders and beneficiaries of the proposed activities. Also ARIADNE’s roles in the activities are addressed. These can be summarised as helping others to make a difference with regard to progress and innovation in archaeological research based on better access to and (re-)usability of research data. Furthermore, the focus areas in the 5-year innovation horizon and 10-year perspective are introduced.
Authors;
Guntram Geser (SRFG)
Franco Niccolucci (PIN)
Metis project deliverable D3.2: Draft of pilot workshopYishay Mor
This deliverable represents the analysis of best practices and workshop design from the first cycle of the METIS project methodology. Alongside this report a prototype is provided to allow access to the package of resources representing a workshop structure developed from the preliminary analysis of best practices in teacher training reported in Deliverable D3.1. Section 2 provides an account of the review of best practices, the process, current status and outcomes, and plans for the future. It also lists risks and challenges and implications to and from WP 2 and 4.
LinkedTV Deliverable 2.7 - Final Linked Media Layer and EvaluationLinkedTV
This deliverable presents the evaluation of content annotation and content enrichment systems that are part of the final tool set developed within the LinkedTV consortium. The evaluations were performed on both the Linked News and Linked Culture trial content, as well as on other content annotated for this purpose. The evaluation spans three languages: German (Linked News), Dutch (Linked
Culture) and English. Selected algorithms and tools were also subject to benchmarking in two international contests: MediaEval 2014 and TAC’14. Additionally, the Microposts 2015 NEEL Challenge is being organized with the support of LinkedTV.
The current deliverable is a report of the activities made within Task 7.2 “Workshops Coordination” in regards to the organization of the first ANDROMEDA workshop that was held virtually on the 28th and 29th September 2020. These activities include the creation of event’s programme (Agenda), the invitations sent to potential attendees, the digital promotional material created and the announcements made via social media for raising the visibility of the event. It should be stressed that the physical workshop would have taken place in Tres Cantos (Spain) in early September of 2020 and preparatory activities towards its realization were made. After the outbreak of COVID-19, the ANDROMEDA consortium following the guidelines of national authorities, decided to turn the event from physical into a virtual one. Nevertheless, the core part of this document is dedicated in presenting the topics elaborated by the speakers and the discussions made.
Project's Website: www.andromeda-project.eu
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 833881.
Links-up is a two-year research project that is co-financed by the Lifelong Learning programme
of the European Commission. The project started in November 2009 and is carried out by an international project team. The overall aim of Links-up is to combine and enhance the know-how of existing projects in the field of inclusion with learning 2.0 in order to promote better future e-inclusion projects and policies...
Project Management Leadership, And Skills : Planning And Control | Assignment...Emre Dirlik
University Of Salford Manchester
Msc Dijital Business
Module 2 : Project Management Leadership, And Skills : Planning And Control
Assignment 2 : People in Project
Software Project Management: Project PlanningMinhas Kamal
Software Project Management: ResearchColab- Project Planning (Document-4)
Presented in 4th year of Bachelor of Science in Software Engineering (BSSE) course at Institute of Information Technology, University of Dhaka (IIT, DU).
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 693319
Disclaimer: This document reflects only the author's view and the Research Executive Agency (REA) is not responsible for any use that may be made of the information it contains.
Similar to D2.1 Evaluation Criteria and Methods (20)
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.
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.
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.
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
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.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
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.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
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.
2. Page 2 of 60
LinkedUp Support Action – 317620
LinkedUp Consortium
This document is a part of the LinkedUp Support Action funded by the ICT Programme of the
Commission of the European Communities by the grant number 317620. The following partners are
involved in the project:
Leibniz Universität Hannover (LUH)
Forschungszentrum L3S
Appelstrasse 9a
30169 Hannover
Germany
Contact person: Stefan Dietze
E-mail address: dietze@L3S.de
The Open University
Walton Hall, MK7 6AA
Milton Keynes
United Kingdom
Contact person: Mathieu d'Aquin
E-mail address: m.daquin@open.ac.uk
Open Knowledge Foundation Limited LBG
Panton Street 37,
CB2 1HL Cambridge
United Kingdom
Contact person: Sander van der Waal
E-mail address: sander.vanderwaal@okfn.org
ELSEVIER BV
Radarweg 29,
1043NX AMSTERDAM
The Netherlands
Contact person: Michael Lauruhn
E-mail address: M.Lauruhn@elsevier.com
Open Universiteit Nederland
Valkenburgerweg 177,
6419 AT Heerlen
The Netherlands
Contact person: Hendrik Drachsler
E-mail address: Hendrik.Drachsler@ou.nl
EXACT Learning Solutions SPA
Viale Gramsci 19
50121 Firenze
Italy
Contact person: Elisabetta Parodi
E-mail address: e.parodi@exactls.com
Work package participants
The following partners have taken an active part in the work leading to this document, even if they
might not have directly contributed to the writing of this document or its parts:
•
•
•
•
LUH, Besnik Fetahu, Constantin Rex, Eelco Herder
OU, Enrico Daga, Alessandro Adamou
ELS, Elisabetta Parodi, Marco Mosca
OUNL, Slavi Stoyanov, Wolfgang Greller
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1. Introduction
The overall objective of WP2 is to develop an Evaluation Framework (EF) that can be applied to
compare Open Web Data applications and rank them according to their achievements. We will
consider all relevant criteria and methods for the evaluation of Open Web Data applications. It is
intended as a comprehensive overview of all possible and relevant evaluation approaches for Open
Web Data applications. This should support various domains and can be customised to specific
needs. It is intended as an instrument to standardise the evaluation of Open Web Data applications.
For the LinkedUp challenge specifically, the EF will be tailored to evaluate software applications
that are submitted in the educational domain. The challenge consists of three data competitions that
call for innovative tools in the educational domain (see FP7 LinkedUp deliverable D.1.1).
As the EF is one of the main outcomes of the FP7 LinkedUp project, this deliverable provides the
foundations for deliverable D2.2.1 that presents the first version of the EF for the LinkedUp data
competition. The deliverable contains the information gained from Task 2.1 - Evaluation criteria and
method review and Task 2.2 - Validation of the evaluation criteria and methods of WP2 (DoW. p. 8).
The EF will be further developed and amended according to the experiences collected in the three
LinkedUp data competitions.
1.1 Problem zone and evaluation issues
In order to scope the task and objectives at hand, we need to take a closer look at today’s challenges
in the field of open data and open data applications.
Data is everywhere! It is manifested through an abundance of computer systems fulfilling various
tasks in an organisational or individual context. It also emerges from collective behaviours of users
and automated agents that use these systems. In a rather recent trend to openness, many datasets are
being exposed to third-party use as linked open data (LOD). This, however, is not without
challenges. Especially in education, harmonisation and comparability are key to successful
application of LOD in a quality-assured way as demanded by general educational principles of equal
opportunities and standard qualifications, but also guided by elementary research principles,
including transparency and replicability.
In describing the challenges faced by LOD for education, we can distinguish three main hierarchical
areas for evaluation:
(1) raw datasets
(2) applications built upon such datasets
(3) added value the applications bring to education
Regarding point (1), issues related to the raw datasets of open linked data concern the data quality
and general usefulness, as well as the exchangeability of data. Quality criteria concern, among other
issues, the “cleanliness” of datasets, i.e. the state of meaningful authentic data items free of
erroneous and testing data. Quality criteria on the datasets also concern the legal clarity on the
possibilities to use them in an anonymised uncompromising way, free of legal risks. While
international laws protect the intellectual property rights (IPR) of database structures, the ownership
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is always the phenomenon of ‘groupthink’ (the negative effect of the group on the opinions of the
individual members). The analysis of individual and focus groups interview in most of the cases is
based on pre-determined classification schemas, which can be either non-exhaustive or impose bias.
In affinity diagram sessions, participants typically would suggest different solutions, both in terms of
groups of criteria and the content of these groups, which makes it difficult for researchers to come up
with a unified vision on how best to structure the information. The Delphi method requires several
iterative rounds before claiming consensus in the group. The consensus is more or less forced and the
subjective approach is always there.
We, therefore, chose the method of Group Concept Mapping (Trochim, 1989; Trochim & Kane &
Trochim, 2007). This research methodology, while building on the strengths of interviews, affinity
diagrams and the Delphi method, mitigates some of their weaknesses.
2. Group Concept Mapping
Group Concept Mapping (GCM) is a structured, mixed approach applying both quantitative and
qualitative measures to objectively identify an expert group’s common understanding about a
particular issue, in our case the evaluation indicators for open educational data. The method involved
the participants in a few simple activities that most of the people are familiar with: idea generation,
sorting of ideas into groups and rating the ideas on some values (e.g. priority and applicability). The
participants work individually, but it is the advanced statistical techniques of multidimensional
scaling and hierarchical cluster analysis that quantitatively aggregate individual input of the
participants to reveal shared patterns in the data.
One of the distinguishing characteristics of GCM is the visualisation, which is a substantial part of
the analysis. Visualisation allows for grasping at once the emerging data structures and their
interrelationship to support decision making. Group Concept Mapping produces three main types of
visualisations: conceptual maps, pattern matching and go-zones.
In contrast to the Delphi method, in GCM, there is only one round of structuring the data as the
participants work independently and anonymously for each other. Unlike interviews, GCM does not
rely on pre-determined classification schemas. The method does not need intercoder discussions to
come up with an agreement. When sorting the statements into groups, the participants, in fact, ‘code’
the concepts themselves. Then multivariate statistical analysis aggregates the individual coding
schemas across all participants. Consensus is not forced but emerges from the data. Group Concept
Mapping supports the researcher in dealing with diverse information, structured in various ways,
which is a problem in Affinity diagram sessions.
Group Concept Mapping in the LinkedUp project supports a bottom-up approach of building an
evaluation framework. The top-down approach typically defines a set of criteria. The problem,
however, is that definitions are brief using quite general terms, which may lead to people getting
different understanding of the criteria. In addition, the chance of providing a non-comprehensive set
of criteria is high.
The GCM approach generates first a number of indicators, which are then structured and weighted in
more general categories (evaluation criteria). Each evaluation criterion is operationalised through the
set of concrete indicators in a particular cluster. A numeric scale (e.g 1 to 5) can be attached to each
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and rating are also given in Appendix A. The participants got two weeks for completing both sorting
and rating. A reminder was sent every week. As in the brainstorming, the participant could save their
work and return later to continue. The analysis included multidimensional scaling and hierarchical
cluster analysis for the structured data and mean, standard deviation, and correlation for the rating
data.
3. Results
3.1 Point map
Fig. 2: Point map
Figure 2 shows the first outcome of the multidimensional scaling analysis – a point map. The closer
the statements to each other, the closer in meaning they are, which also means that more participants
cluster them together. Multidimensional scaling assigns each statement a bridging value, which is
between 0 and 1. The lower bridging value means that a statement has been grouped together with
statements around it; e.g. statements 6, 19, 77, 89, 100, 105 on the right side of figure 1. A higher
bridging value means that the statement has been grouped together with some statements further
apart from either side (e.g. statement 21 or 86 in the centre of the point map). Some groups of ideas
can be detected by eye inspection, but to make the process more efficient a hierarchical cluster
analysis is applied.
3.2 From the point map to most suitable cluster map
Several solutions suggested by the hierarchical cluster analysis have been trialed (see Figure 3). For
the final decision, we adapted the practical heuristic of ‘20-to-5’ to ‘15-to-4’ (Kane & Trochim,
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From Figure 4 it can be seen that there is a very stable Data (south) and Education (north) cluster in
the point map that do not share any statements. By contrast, Performance, which also includes some
Human Computer Interaction statements, is naturally positioned between the Data and Education
clusters. The Privacy (west) cluster always remained apart from the other clusters, but is also a very
stable and therefore important entity for the evaluation criteria. Surprisingly, the Support Group
Activities cluster never merged with the Educational clusters, as the external experts see these
statements semantically different to the educational aspects of the evaluation criteria. Moreover, it
developed as an additional application domain, next to the educational one, which promotes its own
indicators for Open Web Data applications.
The next step of processing the clustering results, is constructing meaningful labels for the clusters,
using the three available methods. The first one is to check what the GCM system suggests. The
system puts on the top of suggestions the label of a cluster named by a participant whose centroid is
the closest to the centroid of the cluster formed by the aggregation of the data from all the
participants. The second way is to look at the bridging values of the statements composing a cluster.
The statements with lower bridging value represent better a cluster. The third method is to read
through all statements in a cluster and define what is the story behind it, what the cluster wants to tell
us. To define the clusters (categories/criteria) we combined the three methods. We finally, chose the
following labels for the 6 cluster solution: 1. Support Group Activities, 2. Privacy, 3. Educational
Innovation, 4. Usability, 5. Performance, 6. Data (see Figure 5).
The most coherent clusters (with the lowest bridging value), meaning that they had the highest
agreement rate from experts for the statements contained within, are ‘Usability’ (0.17), followed by
‘Data’ (0.21), ‘Educational Innovation’ (0.22), and ‘Performance’ (0.39). The clusters with the
highest bridging value are ‘Support Group Activities’ (0.50), and ‘Privacy’ (0.81). Appendix B
presents all statistics regarding the sorting data. In the following paragraphs we will shortly
characterise each of the cluster and their triggering statements.
Fig. 5: Cluster labels