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Introducing UCL’s Open Education initiative

- August 21, 2018 in communication, Featured, guestpost, oer

Guest post by C. Yogeswaran @OpenUCL  University College London, UK — Founded to “open up university education,” UCL’s OE focus has, since February, been supplanted with new energy and focus. The open education team have been exploring ways to support Connected Curriculum, Education Strategy, and Open Scholarship goals at the institution, facilitating communication between academia and the public and inspiring new ways of undertaking education by removing (economic, geographic, and other) barriers to usage. To implement open educational practice at UCL, the project takes a three-pronged approach:
  • The launch of a proof-of-concept repository, OpenEd@UCL, dedicated to storing, sharing, and showcasing the university’s teaching materials – both academic and student generated.
  • Developing policy around open education at UCL to ensure it is embedded into community activities – this includes the repository and deposit policy and a planned OE policy, which will be determined through the Open Science Policy Platform.
  • Expanding the practice of open education across UCL through a programme of engagement. Thus far the project has run special interest group meetings, attended by those with an interest in open education, and also a workshop on open education at the recent UCL Open Science Day event. There is now a project website and Twitter feed, @OpenUCL, and we have also featured in two UCL Teaching & Learning newsletters, and internal Week@UCLstaff newsletter.

Sharing OER at UCL

As the project moves into the next phase, we are looking at increasing OER and metadata within the repository, to build a fuller and holistic picture of the teaching materials UCL has to offer, and embed more deeply open education practice at UCL. As London’s ‘Global University,’ we are keen to explore with practitioners how sharing OER can add value to teaching and learning and have wider global reach and impact. In contacting content providers we have discovered a plethora of OER across UCL which has not been catalogued or brought under one umbrella. Part of this project therefore focuses on working with those who have published OER, to make their resources searchable and discoverable. Showcasing student content and feedback is also a great way to demonstrate the outcomes of teaching/training, promote courses for prospective students, and engage students in the publishing process, and also encourages collaboration between students and staff.

Engagement activities

In the past six months we have established connections with Arena Open who provide CPD opportunities for teaching staff at UCL, and will be working with them in the new term to run workshops for staff on (a) creating open educational resources and (b) turning pre-existing teaching materials into OER. We will also be present, on a fortnightly basis, at regular research support drop-ins, to talk with UCL staff and create awareness. Highlighting incentives to publish OER is important in our communication with teaching staff. The Academic Promotions Framework already rewards open behaviours including the publication of open teaching materials, and we are in discussion with the VP for Education about introducing an Open Education commendation at the next UCL Teaching & Learning Awards ceremony. Working with the other research support services we are also looking at ways to formalise the citation and attribution of OER, as professional/reputational growth is an important part of academia.

Learning more

More information about the project is available on the OER website, or you can follow us on Twitter @OpenUCL.   — About the author Claudia is the Open Education Project Officer based at UCL Library Services.

Introducing UCL’s Open Education initiative

- August 21, 2018 in communication, Featured, guestpost, oer

Guest post by C. Yogeswaran @OpenUCL  University College London, UK — Founded to “open up university education,” UCL’s OE focus has, since February, been supplanted with new energy and focus. The open education team have been exploring ways to support Connected Curriculum, Education Strategy, and Open Scholarship goals at the institution, facilitating communication between academia and the public and inspiring new ways of undertaking education by removing (economic, geographic, and other) barriers to usage. To implement open educational practice at UCL, the project takes a three-pronged approach:
  • The launch of a proof-of-concept repository, OpenEd@UCL, dedicated to storing, sharing, and showcasing the university’s teaching materials – both academic and student generated.
  • Developing policy around open education at UCL to ensure it is embedded into community activities – this includes the repository and deposit policy and a planned OE policy, which will be determined through the Open Science Policy Platform.
  • Expanding the practice of open education across UCL through a programme of engagement. Thus far the project has run special interest group meetings, attended by those with an interest in open education, and also a workshop on open education at the recent UCL Open Science Day event. There is now a project website and Twitter feed, @OpenUCL, and we have also featured in two UCL Teaching & Learning newsletters, and internal Week@UCLstaff newsletter.

Sharing OER at UCL

As the project moves into the next phase, we are looking at increasing OER and metadata within the repository, to build a fuller and holistic picture of the teaching materials UCL has to offer, and embed more deeply open education practice at UCL. As London’s ‘Global University,’ we are keen to explore with practitioners how sharing OER can add value to teaching and learning and have wider global reach and impact. In contacting content providers we have discovered a plethora of OER across UCL which has not been catalogued or brought under one umbrella. Part of this project therefore focuses on working with those who have published OER, to make their resources searchable and discoverable. Showcasing student content and feedback is also a great way to demonstrate the outcomes of teaching/training, promote courses for prospective students, and engage students in the publishing process, and also encourages collaboration between students and staff.

Engagement activities

In the past six months we have established connections with Arena Open who provide CPD opportunities for teaching staff at UCL, and will be working with them in the new term to run workshops for staff on (a) creating open educational resources and (b) turning pre-existing teaching materials into OER. We will also be present, on a fortnightly basis, at regular research support drop-ins, to talk with UCL staff and create awareness. Highlighting incentives to publish OER is important in our communication with teaching staff. The Academic Promotions Framework already rewards open behaviours including the publication of open teaching materials, and we are in discussion with the VP for Education about introducing an Open Education commendation at the next UCL Teaching & Learning Awards ceremony. Working with the other research support services we are also looking at ways to formalise the citation and attribution of OER, as professional/reputational growth is an important part of academia.

Learning more

More information about the project is available on the OER website, or you can follow us on Twitter @OpenUCL.   — About the author Claudia is the Open Education Project Officer based at UCL Library Services.

Changing Minds by Using Open Data

- June 26, 2018 in communication, Data, Featured, guestpost, oer

Guest post by Erdinç Saçan & Robert Schuwer Fontys University of Applied Sciences, the Netherlands

The Greek philosopher Pythagoras once said:

“if you want to multiply joy, then you have to share.”

This also applies to data. Who shares data, gets a multitude of joy – value – in return.

  ICT is not just about technology – it’s about coming up with solutions to solve problems or to help people, businesses, communities and governments. Developing ICT solutions means working with people to find a solution. Students in Information & Communication Technology learn how to work with databases, analysing data and making dashboards that will help the users to make the right decisions.  Data collections are required for these learning experiences. You can create these data collections (artificially) yourself or use “real” data collections, openly available (like those from Statistics Netherlands (CBS) (https://www.cbs.nl/en-gb)) In education, data is becoming increasingly important, both in policy, management and in the education process itself. The scientific research that supports education is becoming increasingly dependent on data. Data leads to insights that help improve the quality of education (Atenas & Havemann, 2015). But in the current era where a neo-liberal approach of education seems to dominate, the “Bildung” component of education is considered more important than ever. The term Bildung is attributed to Willem van Humboldt (1767-1835). It refers to general evolution of all human qualities, not only acquiring knowledge, but also developing skills for moral judgments and critical thinking.

Study

In (Atenas & Havemann, 2015), several case studies are described where the use of open data contributes to developing the Bildung component of education. To contribute to these cases and eventually extend experiences, a practical study has been conducted. The study had the following research question: “How can using open data in data analysis learning tasks contribute to the Bildung component of the ICT Bachelor Program of Fontys School of ICT in the Netherlands?” In the study, an in-depth case study is executed, using an A / B test method. One group of students had a data set with artificial data available, while the other group worked with a set of open data from the municipality of Utrecht. A pre-test and post-test should reveal whether a difference in development of the Bildung component can be measured. Both tests were conducted by a survey. Additionally, some interviews have been conducted afterwards to collect more in-depth information and explanations for the survey results. For our A/B test, we used three data files from the municipality of Utrecht (a town in the center of the Netherlands, with ~350,000 inhabitants). These were data from all quarters in Utrecht:
  • Crime figures
  • Income
  • Level of Education
(Source: https://utrecht.dataplatform.nl/data) We assumed, all students had opinions on correlations between these three types of data, e.g. “There is a proportional relation between crime figures and level of education” or “There is an inversely proportional relation between income and level of education”. We wanted to see which opinions students had before they started working with the data and if these opinions were influenced after they had analyzed the data. A group of 40 students went to work with the data. The group was divided into 20 students who went to work with real data and 20 went to work with ‘fake’ data. Students were emailed with the three data files and the following assignment: “check CSV (Excel) file in the attachment. Please try this to do an analysis. Try to draw a minimum of 1, a maximum of 2 conclusions from it… this can be anything. As long as it leads to a certain conclusion based on the figures.” In addition, there was also a survey in which we tried to find out how students currently think about correlations between crime, income and educational level. Additionally, some students were interviewed to get some insights into the figures collected by the survey.  

Results

For the survey, 40 students have been approached. The response consisted of 25 students. All students indicated that working with real data is more fun, challenging and concrete. It motivates them. Students who worked with fake data did not like this as much. In interviews they indicated that they prefer, for example, to work with cases from companies rather than cases invented by teachers. In the interviews, the majority of students indicated that by working with real data they have come to a different understanding of crime and the reasons for it. They became aware of the social impact of data and they were triggered to think about social problems. To illustrate, here some responses students gave in interviews “Before I started working with the data, I had always thought that there was more crime in districts with a low income and less crime in districts with a high income. After I have analyzed the data, I have seen that this is not immediately the case. So my thought about this has indeed changed. It is possible, but it does not necessarily have to be that way.” (M. K.) “At first, I also thought that there would be more crime in communities with more people with a lower level of education than in communities with more people with a higher level of education. In my opinion, this image has changed in part. I do not think that a high or low level of education is necessarily linked to this, but rather to the situation in which they find themselves. So if you are highly educated, but things are really not going well (no job, poor conditions at home), then the chance of criminality is greater than if someone with a low level of education has a job.” ( A. K.) “I think it has a lot of influence. You have an image and an opinion beforehand. But the real data either shows the opposite or not. And then you think, “Oh yes, this is it.’. And working with fake data, is not my thing. It has to provide real insights.” (M.D.)

Conclusion

Our experiment provided positive indications that contributing to the Bildung component of education by using open data in data analysis exercises is possible. Next steps to develop are both extending these experiences to larger groups of students and to more topics in the curriculum.  

References

Atenas, J. & Havemann, L. (2015). Open Data as Open Educational Resources: Towards Transversal Skills and Global Citizenship. Open praxis7(4), 377-389. http://dx.doi.org/10.5944/openpraxis.7.4.233 Atenas, J., & Havemann, L. (Eds.). (2015). Open Data as Open Educational Resources: Case studies of emerging practice. London: Open Knowledge, Open Education Working Group. https://education.okfn.org/handbooks/open-data-as-open-educational-resources/ 
About the authors  Erdinç Saçan is a Senior Teacher of ICT & Business and the Coordinator of the Minor Digital Marketing @ Fontys University of Applied Sciences, School of ICT in Eindhoven, the Netherlands. He previously worked at Corendon, TradeDoubler and Prijsvrij.nl       Robert Schuwer is Professor Open Educational Resources at Fontys University of Applied Sciences, School of ICT in Eindhoven, the Netherlands and  holds the UNESCO Chair on Open Educational Resources and Their Adoption by Teachers, Learners and Institutions.

Changing Minds by Using Open Data

- June 26, 2018 in communication, Data, Featured, guestpost, oer

Guest post by Erdinç Saçan & Robert Schuwer Fontys University of Applied Sciences, the Netherlands

The Greek philosopher Pythagoras once said:

“if you want to multiply joy, then you have to share.”

This also applies to data. Who shares data, gets a multitude of joy – value – in return.

  ICT is not just about technology – it’s about coming up with solutions to solve problems or to help people, businesses, communities and governments. Developing ICT solutions means working with people to find a solution. Students in Information & Communication Technology learn how to work with databases, analysing data and making dashboards that will help the users to make the right decisions.  Data collections are required for these learning experiences. You can create these data collections (artificially) yourself or use “real” data collections, openly available (like those from Statistics Netherlands (CBS) (https://www.cbs.nl/en-gb)) In education, data is becoming increasingly important, both in policy, management and in the education process itself. The scientific research that supports education is becoming increasingly dependent on data. Data leads to insights that help improve the quality of education (Atenas & Havemann, 2015). But in the current era where a neo-liberal approach of education seems to dominate, the “Bildung” component of education is considered more important than ever. The term Bildung is attributed to Willem van Humboldt (1767-1835). It refers to general evolution of all human qualities, not only acquiring knowledge, but also developing skills for moral judgments and critical thinking.

Study

In (Atenas & Havemann, 2015), several case studies are described where the use of open data contributes to developing the Bildung component of education. To contribute to these cases and eventually extend experiences, a practical study has been conducted. The study had the following research question: “How can using open data in data analysis learning tasks contribute to the Bildung component of the ICT Bachelor Program of Fontys School of ICT in the Netherlands?” In the study, an in-depth case study is executed, using an A / B test method. One group of students had a data set with artificial data available, while the other group worked with a set of open data from the municipality of Utrecht. A pre-test and post-test should reveal whether a difference in development of the Bildung component can be measured. Both tests were conducted by a survey. Additionally, some interviews have been conducted afterwards to collect more in-depth information and explanations for the survey results. For our A/B test, we used three data files from the municipality of Utrecht (a town in the center of the Netherlands, with ~350,000 inhabitants). These were data from all quarters in Utrecht:
  • Crime figures
  • Income
  • Level of Education
(Source: https://utrecht.dataplatform.nl/data) We assumed, all students had opinions on correlations between these three types of data, e.g. “There is a proportional relation between crime figures and level of education” or “There is an inversely proportional relation between income and level of education”. We wanted to see which opinions students had before they started working with the data and if these opinions were influenced after they had analyzed the data. A group of 40 students went to work with the data. The group was divided into 20 students who went to work with real data and 20 went to work with ‘fake’ data. Students were emailed with the three data files and the following assignment: “check CSV (Excel) file in the attachment. Please try this to do an analysis. Try to draw a minimum of 1, a maximum of 2 conclusions from it… this can be anything. As long as it leads to a certain conclusion based on the figures.” In addition, there was also a survey in which we tried to find out how students currently think about correlations between crime, income and educational level. Additionally, some students were interviewed to get some insights into the figures collected by the survey.  

Results

For the survey, 40 students have been approached. The response consisted of 25 students. All students indicated that working with real data is more fun, challenging and concrete. It motivates them. Students who worked with fake data did not like this as much. In interviews they indicated that they prefer, for example, to work with cases from companies rather than cases invented by teachers. In the interviews, the majority of students indicated that by working with real data they have come to a different understanding of crime and the reasons for it. They became aware of the social impact of data and they were triggered to think about social problems. To illustrate, here some responses students gave in interviews “Before I started working with the data, I had always thought that there was more crime in districts with a low income and less crime in districts with a high income. After I have analyzed the data, I have seen that this is not immediately the case. So my thought about this has indeed changed. It is possible, but it does not necessarily have to be that way.” (M. K.) “At first, I also thought that there would be more crime in communities with more people with a lower level of education than in communities with more people with a higher level of education. In my opinion, this image has changed in part. I do not think that a high or low level of education is necessarily linked to this, but rather to the situation in which they find themselves. So if you are highly educated, but things are really not going well (no job, poor conditions at home), then the chance of criminality is greater than if someone with a low level of education has a job.” ( A. K.) “I think it has a lot of influence. You have an image and an opinion beforehand. But the real data either shows the opposite or not. And then you think, “Oh yes, this is it.’. And working with fake data, is not my thing. It has to provide real insights.” (M.D.)

Conclusion

Our experiment provided positive indications that contributing to the Bildung component of education by using open data in data analysis exercises is possible. Next steps to develop are both extending these experiences to larger groups of students and to more topics in the curriculum.  

References

Atenas, J. & Havemann, L. (2015). Open Data as Open Educational Resources: Towards Transversal Skills and Global Citizenship. Open praxis7(4), 377-389. http://dx.doi.org/10.5944/openpraxis.7.4.233 Atenas, J., & Havemann, L. (Eds.). (2015). Open Data as Open Educational Resources: Case studies of emerging practice. London: Open Knowledge, Open Education Working Group. https://education.okfn.org/handbooks/open-data-as-open-educational-resources/ 
About the authors  Erdinç Saçan is a Senior Teacher of ICT & Business and the Coordinator of the Minor Digital Marketing @ Fontys University of Applied Sciences, School of ICT in Eindhoven, the Netherlands. He previously worked at Corendon, TradeDoubler and Prijsvrij.nl       Robert Schuwer is Professor Open Educational Resources at Fontys University of Applied Sciences, School of ICT in Eindhoven, the Netherlands and  holds the UNESCO Chair on Open Educational Resources and Their Adoption by Teachers, Learners and Institutions.

Learning Analytics Policy Development

- June 25, 2018 in communication, Data, Featured, guestpost

Written by Anne-Marie Scott  — The University of Edinburgh has just launched their Principles and Purposes for Learning Analytics. In order to develop institutional policy on learning analytics, in 2016 we convened a task group reporting to our Senate Learning and Teaching Committee, and our Knowledge Strategy Committee. The task group was convened by Professor Dragan Gasevic, Chair of Learning Analytics and Informatics. The group included Professor Sian Bayne, Assistant Principal Digital Education; representatives from academic Colleges; the Edinburgh University’s Students Association; and representatives from Student Systems and Information Services. Our Director of Academic Services produced an initial draft of a Learning Analytics policy for review by our institutional task group. It was a relatively detailed policy which covered the following sorts of topics:
  • Definitions
  • Sources of data for learning analytics
  • Sources of data for learning analytics
  • Initiating learning analytics activities
  • Transparency and consent
  • Privacy and access to data
  • Retention and disposal of data
  • Validity and interpretation of data
  • Supporting positive interventions
  • Enabling students to reflect on their learning
  • Supporting staff to make the most of learning analytics
  • Oversight of Learning Analytics activities
  • Other relevant policies
Ethical values, legal obligations and the reasons for engaging with learning analytics were all embedded in the policy, but as we worked on revisions, considered inputs from external sources, and planned how to consult on a draft it became clear that this detailed policy was likely to beg more questions than it answered without being more explicit about our values and our ethical position upfront. We also had to contend with periods of time where there was limited data protection resource available to the task group, and where the legal basis for processing under GDPR that would be available to us was still being debated in the House of Lords. At the same time as we were developing local policy, colleagues at Edinburgh (Prof Dragan Gasevic and Dr Yi-Shan Tsai) were involved with the EU Sheila project, developing a learning analytics policy development framework for the EU. There were several key outputs from that project that we used in pre-print form to inform our work: In particular, the group concept mapping activity carried out by the Sheila project (surveying various European Universities) identified that defining objectives for learning analytics was very important, but also very hard (http://sheilaproject.eu/wp-content/uploads/2017/04/The-state-of-learning-analytics-in-Europe.pdf). As part of our local policy development, myself and Dragan Gasevic met and discussed what we felt were the 6 main purposes for learning analytics in an Edinburgh context, and these were written up into the policy as a means of tackling this issue head-on for Edinburgh. The literature review on learning analytics adoption that the Sheila project produced also identified various challenges to adoption, and on further consideration I drafted a separate Purposes and Principles document which extracted various of the principles embedded in the detailed policy and responded to many of the challenges and concerns identified in the literature review. Given some of the challenges we were experiencing around clarity on new data protection legislation for resolving areas the more detailed policy, this was the point at which our task group decided to separate the two pieces and start with a consultation on Purposes and Principles only. The Purposes and Principles were outlined and discussed at Senate in early 2017 and then taken to each School for discussion as part of the consultation plan that Academic Services devised for us. To support this consultation we also developed a webpage that outlined existing research and operational activities in learning analytics at Edinburgh (https://www.ed.ac.uk/information-services/learning-technology/learning-analytics). This high-level values-first route proved to be an effective way to start, as consultation with many Schools identified that the level of knowledge and understanding of learning analytics was highly variable across the institution, and that there were significant pockets of concern about ethics and about support for staff and students to make more use of data. The Sheila project also ran a student survey at Edinburgh during this time period and we were also able to finesse the Principles and Purposes to respond to student concerns and expectations. In considering how to achieve oversight and governance in the absence of the more detailed policy, and in a potentially quite complex and changing area, we also proposed the establishment of a Learning Analytics Review Group. As we pursue more data-driven operational activities this helps close out an ethical review gap in our operational activities. This governance model is now of interest to colleagues working on institutional data governance activities more generally. Once the Principles and Purposes were approved, with support from our Data Protection Officer, and more clarity on GDPR we were then able to tidy up the more detailed policy which defines the ‘mechanics’ of how activities can be initiated, what roles and responsibilities exist, what sources of data might be implicated etc. This policy was approved by our Senate Learning and Teaching Committee in May 2018. Importantly, this policy has also been able to link in to other work around data governance within the institution, and formally recognises the role that our institutional ‘Data Stewards’ have to play in the approvals process for learning analytics projects. Important inputs to the development of policy (as well as the Sheila project inputs) included:   — About the author
Anne-Marie Scott is Deputy Director of Learning, Teaching and Web Services, at the University of Edinburgh. Her background is in the design, management and support for academic IT services, particularly those used to support teaching and learning activities online. Amongst her interests are the use of new media and the open web in teaching and learning, scalable online learning platforms, and learning analytics.   Originally published in https://ammienoot.com/brain-fluff/learning-analytics-policy-development/ 

Learning Analytics Policy Development

- June 25, 2018 in communication, Data, Featured, guestpost

Written by Anne-Marie Scott  — The University of Edinburgh has just launched their Principles and Purposes for Learning Analytics. In order to develop institutional policy on learning analytics, in 2016 we convened a task group reporting to our Senate Learning and Teaching Committee, and our Knowledge Strategy Committee. The task group was convened by Professor Dragan Gasevic, Chair of Learning Analytics and Informatics. The group included Professor Sian Bayne, Assistant Principal Digital Education; representatives from academic Colleges; the Edinburgh University’s Students Association; and representatives from Student Systems and Information Services. Our Director of Academic Services produced an initial draft of a Learning Analytics policy for review by our institutional task group. It was a relatively detailed policy which covered the following sorts of topics:
  • Definitions
  • Sources of data for learning analytics
  • Sources of data for learning analytics
  • Initiating learning analytics activities
  • Transparency and consent
  • Privacy and access to data
  • Retention and disposal of data
  • Validity and interpretation of data
  • Supporting positive interventions
  • Enabling students to reflect on their learning
  • Supporting staff to make the most of learning analytics
  • Oversight of Learning Analytics activities
  • Other relevant policies
Ethical values, legal obligations and the reasons for engaging with learning analytics were all embedded in the policy, but as we worked on revisions, considered inputs from external sources, and planned how to consult on a draft it became clear that this detailed policy was likely to beg more questions than it answered without being more explicit about our values and our ethical position upfront. We also had to contend with periods of time where there was limited data protection resource available to the task group, and where the legal basis for processing under GDPR that would be available to us was still being debated in the House of Lords. At the same time as we were developing local policy, colleagues at Edinburgh (Prof Dragan Gasevic and Dr Yi-Shan Tsai) were involved with the EU Sheila project, developing a learning analytics policy development framework for the EU. There were several key outputs from that project that we used in pre-print form to inform our work: In particular, the group concept mapping activity carried out by the Sheila project (surveying various European Universities) identified that defining objectives for learning analytics was very important, but also very hard (http://sheilaproject.eu/wp-content/uploads/2017/04/The-state-of-learning-analytics-in-Europe.pdf). As part of our local policy development, myself and Dragan Gasevic met and discussed what we felt were the 6 main purposes for learning analytics in an Edinburgh context, and these were written up into the policy as a means of tackling this issue head-on for Edinburgh. The literature review on learning analytics adoption that the Sheila project produced also identified various challenges to adoption, and on further consideration I drafted a separate Purposes and Principles document which extracted various of the principles embedded in the detailed policy and responded to many of the challenges and concerns identified in the literature review. Given some of the challenges we were experiencing around clarity on new data protection legislation for resolving areas the more detailed policy, this was the point at which our task group decided to separate the two pieces and start with a consultation on Purposes and Principles only. The Purposes and Principles were outlined and discussed at Senate in early 2017 and then taken to each School for discussion as part of the consultation plan that Academic Services devised for us. To support this consultation we also developed a webpage that outlined existing research and operational activities in learning analytics at Edinburgh (https://www.ed.ac.uk/information-services/learning-technology/learning-analytics). This high-level values-first route proved to be an effective way to start, as consultation with many Schools identified that the level of knowledge and understanding of learning analytics was highly variable across the institution, and that there were significant pockets of concern about ethics and about support for staff and students to make more use of data. The Sheila project also ran a student survey at Edinburgh during this time period and we were also able to finesse the Principles and Purposes to respond to student concerns and expectations. In considering how to achieve oversight and governance in the absence of the more detailed policy, and in a potentially quite complex and changing area, we also proposed the establishment of a Learning Analytics Review Group. As we pursue more data-driven operational activities this helps close out an ethical review gap in our operational activities. This governance model is now of interest to colleagues working on institutional data governance activities more generally. Once the Principles and Purposes were approved, with support from our Data Protection Officer, and more clarity on GDPR we were then able to tidy up the more detailed policy which defines the ‘mechanics’ of how activities can be initiated, what roles and responsibilities exist, what sources of data might be implicated etc. This policy was approved by our Senate Learning and Teaching Committee in May 2018. Importantly, this policy has also been able to link in to other work around data governance within the institution, and formally recognises the role that our institutional ‘Data Stewards’ have to play in the approvals process for learning analytics projects. Important inputs to the development of policy (as well as the Sheila project inputs) included:   — About the author
Anne-Marie Scott is Deputy Director of Learning, Teaching and Web Services, at the University of Edinburgh. Her background is in the design, management and support for academic IT services, particularly those used to support teaching and learning activities online. Amongst her interests are the use of new media and the open web in teaching and learning, scalable online learning platforms, and learning analytics.   Originally published in https://ammienoot.com/brain-fluff/learning-analytics-policy-development/ 

Copyright Reform – CREATe Resources

- June 13, 2018 in communication, copyright, Featured

Guest post by Kerry Patterson CREATe Community Manager Copyright Reform is a few votes away. The European Union may require those who share news to obtain licences first (permissions against payment). The EU may require platforms to filter content uploaded by users (aimed at music files but also applying to new digital expressions, such as memes and parodies). Following the adoption of a position of the Council of the European Union on 25 May 2018, the European Parliament’s Legal Affairs Committee (JURI) will vote on the proposed Copyright Directive on 20 June. It is extremely rare for a later plenary vote to overturn the lead committee’s position. So, the destiny of the controversial directive may be settled shortly. This is an important junction in copyright policy, as the Copyright Directive could be the most far reaching European copyright intervention since the 2001 Information Society Directive. CREATe is the UK Centre for Copyright and New Business Models in the Creative Economy, based at the University of Glasgow. The Centre brings together an interdisciplinary team of academics from law, economics, management, computer science, sociology, psychology, ethnography and critical studies. CREATe believes that we can know who is right, and who is wrong. Our resource page [http://www.create.ac.uk/eu-copyright-reform] tracks the progress of the European Commission’s Reform Package through the complex EU process of law making and signposts significant independent scientific research. It also offers a timeline of the policy making process for the Copyright in the Digital Single Market directive, and access to draft documents where they have become available (sometimes as leaks).
Text Kerry Patterson -CREATe Community Manager https://www.create.ac.uk  Images Davide Bonazzi/Copyright User

Copyright Reform – CREATe Resources

- June 13, 2018 in communication, copyright, Featured

Guest post by Kerry Patterson CREATe Community Manager Copyright Reform is a few votes away. The European Union may require those who share news to obtain licences first (permissions against payment). The EU may require platforms to filter content uploaded by users (aimed at music files but also applying to new digital expressions, such as memes and parodies). Following the adoption of a position of the Council of the European Union on 25 May 2018, the European Parliament’s Legal Affairs Committee (JURI) will vote on the proposed Copyright Directive on 20 June. It is extremely rare for a later plenary vote to overturn the lead committee’s position. So, the destiny of the controversial directive may be settled shortly. This is an important junction in copyright policy, as the Copyright Directive could be the most far reaching European copyright intervention since the 2001 Information Society Directive. CREATe is the UK Centre for Copyright and New Business Models in the Creative Economy, based at the University of Glasgow. The Centre brings together an interdisciplinary team of academics from law, economics, management, computer science, sociology, psychology, ethnography and critical studies. CREATe believes that we can know who is right, and who is wrong. Our resource page [http://www.create.ac.uk/eu-copyright-reform] tracks the progress of the European Commission’s Reform Package through the complex EU process of law making and signposts significant independent scientific research. It also offers a timeline of the policy making process for the Copyright in the Digital Single Market directive, and access to draft documents where they have become available (sometimes as leaks).
Text Kerry Patterson -CREATe Community Manager https://www.create.ac.uk  Images Davide Bonazzi/Copyright User

Adopting Open Textbooks in the UK

- March 27, 2018 in communication, Featured, guestpost, oer, OpenTextbooks


By Beatriz de los Arcos In March of 2017 the Open Education Research (OER) Hub received a small grant from the William and Flora Hewlett Foundation to assess whether current US models of open textbook adoption would translate to the …

Adopting Open Textbooks in the UK

- March 27, 2018 in communication, Featured, guestpost, oer, OpenTextbooks


By Beatriz de los Arcos In March of 2017 the Open Education Research (OER) Hub received a small grant from the William and Flora Hewlett Foundation to assess whether current US models of open textbook adoption would translate to the UK HE context. In a short space of time we put together under the UK Open Textbook Project a team of interested parties, which included David Kernohan and Viv Rolfe this side of the Atlantic, and David Ernst (Open Textbook Network) and OpenStax on American soil. The cost of textbooks in the US is massive. Data from the Bureau of Labor Statistics reports that textbook prices have increased by 88% in the past ten years. The average student enrolling in the 2015-16 academic year had to budget between $1230 and $1390 for textbooks and course materials. To put this in context, a loaf of bread is $2.50 and a pint of milk, 40 cents. That’s over 3000 pints of milk and nearly 500 loaves of bread that you’d need to go without in order to purchase your textbooks (and we all know in bad weather what’s the first thing that goes from supermarket shelves). Seriously though, academic performance is also taking a hit: Student PIRGS says that two thirds of students don’t buy a required textbook because they are too expensive, with cost having a negative impact on which and how many courses they register for. Can you imagine how you would cope in your course without the textbook? Research tells us that earning a poor grade, failing or dropping out would not come as a surprise.   The Open Textbook Library defines open textbooks as “textbooks that have been funded, published, and licensed to be freely used, adapted, and distributed. These books can be downloaded for no cost, or printed at low cost”. Because they serve to offset the cost of traditional textbooks, open textbooks have a reason to exist, and the fact that $5 million have been put aside by Congress to fund an open textbook grant program demonstrates that in the US the issue is treated with grave concern. However, is cost a valid argument to adopt open textbooks in the UK? In a recent report on the financial position of students in higher education in England, commissioned by the Department for Education we learn that: “Compared with the cost of tuition fees, expenditure on direct course costs made up a smaller proportion of full-time students’ participation costs – they spent on average £512 (six per cent of total participation costs) on these items in the 2014/15 academic year. Fulltime students spent the most on computers (£253), followed by printing, photocopying and stationery (£105), then books (£101) and other equipment (£31).” (p. 279) £101 does not sound like a lot of money, does it? Students in England are delivered a brutal blow by having to pay fees of £9000 a year, not by the amount of money spent on textbooks. It is true that we don’t want to add to their woes and anything we can save them comes as a bonus. What I’d like to highlight here is that if open textbooks are to be adopted in the UK, we need to look beyond cost and sing out loud what we (teachers and students) can do with an open textbook that we can’t do with a traditional textbook. My emphasis in the above definition has to be on “licensed to be freely used, adapted and distributed”. As part of the work carried out by the UK Open Textbooks Project, the team ran a total of fourteen workshops in eight HE institutions in England, Scotland and the Republic of Ireland. The aim of these was to raise awareness of open textbooks and to invite participants to review an open textbook from the Open Textbook Library. As it happened, I facilitated workshops in Glasgow Caledonian University, where registration fees are zero pounds, and NUIGalway, where students pay a ‘contribution’ of €3000 per year. Neither of these universities would see cost as the only swinging logic to use an open textbook in the classroom, but both could reasonably buy into the idea of an open textbook as a living creature that can be adapted ad libitum. An open textbook is more than free; it is free with permissions; permission to reorder chapters, localise examples, translate into any language, add content to, delete paragraphs, link to external sources, and more. More. More. Think about it. Ask your students to think about it. UK Open Textbook Project  If you do and you’d like our support, get in touch: @UKOpenTextbooks.
About the autor Beatriz de los Arcos is a researcher in the Institute of Educational Technology at The Open University, UK and Academic Lead for the Global OER Graduate Network. She has worked on a vast range of open education research projects, including OER Research Hub where she led the project’s work on the impact of OER use on teaching and learning in K-12.  Her work has been recognized with an Open Courseware Consortium ACE Award for Research Excellence (2014) and The Open University Engaging Research Award (2015). She can be followed as @celTatis on Twitter.