Workshop objectives:
Explore how institutions like Open University UK have implemented learning analytics at scale. Workshop activities:
Presentation from the facilitator and interactive with questions via pollev, chat, and Zoom. Facilitator biography:
Dr. Bart Rienties is Professor of Learning Analytics and programme lead of the learning analytics and learning design research programme at the Institute of Educational Technology at the Open University UK. He leads a group of academics who provide university-wide learning analytics and learning design solutions and conduct evidence-based research of how students and professionals learn. As educational psychologist, he conducts multi-disciplinary research on work-based and collaborative learning environments and focuses on the role of social interaction in learning, which is published in leading academic journals and books. His primary research interests are focussed on Learning Analytics, Professional Development, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He has successfully led a range of institutional/national/European projects, and has received a range of awards for his educational innovation projects. He has published over 250 academic outputs, and is the 4th most cited author and contributor in Learning Analytics in the period 2011-2018 (Adeniji, 2019), the 5th most published author on internationalisation in the period 1900-2018 (Jing et al. 2020) and the 3rd most cited author on higher education internationalisation in Asia in the period 2013-2018 (Can & Hou, 2021), the 7th most published author on social network analysis in social sciences in the period 1999-2018 (Su et al. 2020), and the 14th most published author on educational technology in the period 2015-2018 (West & Bodily, 2020). More info at https://iet.open.ac.uk/people/bart.rienties
The document discusses lessons learned from implementing learning analytics and learning design at scale over 10 years at the Open University UK. Some key points:
1. Change is slow but can be enhanced with clear senior support, bottom-up support from teachers, and evidence-based research to change perspectives.
2. Both predictive learning analytics since 2013 and learning design since 2005 have provided insights but their impact is often forgotten or underestimated.
3. Factors like faculty engagement, teachers as champions, evidence generation, and digital literacy were critical to successfully implementing predictive learning analytics at scale.
4. Research has found learning design provides important context for learning analytics and can improve courses by closing the loop between design and enhanced learning
Learning analytics adoption in Higher Education: Reviewing six years of exper...Bart Rienties
The document summarizes a webinar by Dr. Bart Rienties on his work implementing learning analytics at scale at the Open University over the past 6 years. Some key points:
1. The Open University is a world leader in collecting and analyzing large-scale student data to provide actionable insights for students and teachers.
2. Analytics4Action supports the university-wide approach to learning analytics and provided insights into interventions for students and modules.
3. Iterative use of learning analytics establishes the need for student and module interventions, with faster feedback loops leading to better outcomes.
4. Legal, ethical and privacy challenges around learning analytics interventions must be addressed, including student consent and transparency.
Keynote Data Matters JISC What is the impact? Six years of learning analytics...Bart Rienties
The Open University (OU) was an early adopter of learning analytics, and after six years has had the opportunity to reflect on the impact of large scale adoption across the institution.
Has there been an impact on student retention/progress/completion?
How are the positives (or negatives) reflected in student satisfaction surveys?
What worked, what didn't, and with this benefit of hindsight what is, or should be, next?
What have we learned from 6 years of implementing learning analytics amongst ...Bart Rienties
By Professor Bart Rienties, Head of Academic Professional Development, Institute of Educational Technology, The Open University, UK
Abstract
The Open University UK (OU) has been implementing learning analytics since 2014, starting with one or two modules to its current practice of large-scale implementation across all its 400+ modules and 170.000+ students and 4000+ teaching staff. While a range of reviews (e.g., Adenij, 2019) and scholarly repositories (e.g., Web of Science) indicate that the OU is the largest contributor to academic output in learning analytics in the world, behind the flashy publications and practitioner outputs there are a range of complex issues in terms of ethics and privacy, data infrastructures, buy-in from staff, student engagement, and how to make sense of big data in a complex organisation like the OU.
Based upon large-scale big data research we found some interesting tensions in both design and educational theory, such as:
– 69% of engagement by students on a week by week basis is determined by how teachers are designing courses (i.e., learning design and instructional design indeed directly influence behaviour and cognition), but many teachers seem reluctant to change their learning design based upon data of what works and what does not work (e.g., making sense of data, agency);
– How teachers engage with predictive learning analytics (PLA) significantly improves student outcomes, but only a minority of teachers actually use PLA;
– Some disadvantaged groups engage more actively in OU courses, but nonetheless perform lower than non-disadvantaged students.
During this CELDA keynote I would like to share some of my own reflections of how the OU has implemented learning analytics, and how these insights are helping towards a stronger evidence-base for data-informed change. Furthermore, by sharing some of the lessons learned from implementing learning analytics on a large scale I hope to provide some dos and don’ts in terms of how you might consider to use data in your own practice and context.
Using Learning analytics to support learners and teachers at the Open UniversityBart Rienties
In this seminar Prof Bart Rienties will reflect on how the Open University UK has become a leading institution in implementing learning analytics at scale amongst its 170K students and 5K staff. Furthermore, he will discuss how learning analytics is being adopted at other UK institutions, and what the implications for higher education might be in these Covid19 times.
https://www.kent.ac.uk/cshe/news-events.html
Using student data to transform teaching and learningBart Rienties
This document summarizes a webinar given by Dr. Bart Rienties on using student data and learning analytics to transform teaching and learning. Some key points:
- Learning analytics aims to measure, collect, analyze and report data about learners to understand and optimize learning. Social learning analytics focuses on how learners build knowledge together.
- The Open University has been a world leader in collecting and analyzing large-scale student data to provide actionable insights for students, teachers, and institutional benefit. Studies have shown the importance of linking learning analytics outcomes to student satisfaction, retention, and learning design.
- Practitioners want learning analytics solutions that are integrated across an entire learning journey from initial inquiry through modules to
AI in Education Amsterdam Data Science (ADS) What have we learned after a dec...Bart Rienties
The Open University UK (OU) has been implementing learning analytics and learning design on a large scale since 2012. With its 170+ students and 4000+ teaching staff, the OU has been at the forefront of testing, implementing, and evaluating the impact of learning analytics and learning design on students outcome and retention. A range of reviews and scholarly repositories (e.g., Web of Science) indicate that the OU is the largest contributor to academic output in learning analytics and learning design in the world. However, despite the large uptake of learning analytics at the OU there are a range of complex issues in terms of buy-in from staff, data infrastructures, ethics and privacy, student engagement, and perhaps most importantly how to make sense of big and small data in a complex organisation like the OU. During his talk Bart will be presenting on the implementation and learnings.
The document discusses lessons learned from implementing learning analytics and learning design at scale over 10 years at the Open University UK. Some key points:
1. Change is slow but can be enhanced with clear senior support, bottom-up support from teachers, and evidence-based research to change perspectives.
2. Both predictive learning analytics since 2013 and learning design since 2005 have provided insights but their impact is often forgotten or underestimated.
3. Factors like faculty engagement, teachers as champions, evidence generation, and digital literacy were critical to successfully implementing predictive learning analytics at scale.
4. Research has found learning design provides important context for learning analytics and can improve courses by closing the loop between design and enhanced learning
Learning analytics adoption in Higher Education: Reviewing six years of exper...Bart Rienties
The document summarizes a webinar by Dr. Bart Rienties on his work implementing learning analytics at scale at the Open University over the past 6 years. Some key points:
1. The Open University is a world leader in collecting and analyzing large-scale student data to provide actionable insights for students and teachers.
2. Analytics4Action supports the university-wide approach to learning analytics and provided insights into interventions for students and modules.
3. Iterative use of learning analytics establishes the need for student and module interventions, with faster feedback loops leading to better outcomes.
4. Legal, ethical and privacy challenges around learning analytics interventions must be addressed, including student consent and transparency.
Keynote Data Matters JISC What is the impact? Six years of learning analytics...Bart Rienties
The Open University (OU) was an early adopter of learning analytics, and after six years has had the opportunity to reflect on the impact of large scale adoption across the institution.
Has there been an impact on student retention/progress/completion?
How are the positives (or negatives) reflected in student satisfaction surveys?
What worked, what didn't, and with this benefit of hindsight what is, or should be, next?
What have we learned from 6 years of implementing learning analytics amongst ...Bart Rienties
By Professor Bart Rienties, Head of Academic Professional Development, Institute of Educational Technology, The Open University, UK
Abstract
The Open University UK (OU) has been implementing learning analytics since 2014, starting with one or two modules to its current practice of large-scale implementation across all its 400+ modules and 170.000+ students and 4000+ teaching staff. While a range of reviews (e.g., Adenij, 2019) and scholarly repositories (e.g., Web of Science) indicate that the OU is the largest contributor to academic output in learning analytics in the world, behind the flashy publications and practitioner outputs there are a range of complex issues in terms of ethics and privacy, data infrastructures, buy-in from staff, student engagement, and how to make sense of big data in a complex organisation like the OU.
Based upon large-scale big data research we found some interesting tensions in both design and educational theory, such as:
– 69% of engagement by students on a week by week basis is determined by how teachers are designing courses (i.e., learning design and instructional design indeed directly influence behaviour and cognition), but many teachers seem reluctant to change their learning design based upon data of what works and what does not work (e.g., making sense of data, agency);
– How teachers engage with predictive learning analytics (PLA) significantly improves student outcomes, but only a minority of teachers actually use PLA;
– Some disadvantaged groups engage more actively in OU courses, but nonetheless perform lower than non-disadvantaged students.
During this CELDA keynote I would like to share some of my own reflections of how the OU has implemented learning analytics, and how these insights are helping towards a stronger evidence-base for data-informed change. Furthermore, by sharing some of the lessons learned from implementing learning analytics on a large scale I hope to provide some dos and don’ts in terms of how you might consider to use data in your own practice and context.
Using Learning analytics to support learners and teachers at the Open UniversityBart Rienties
In this seminar Prof Bart Rienties will reflect on how the Open University UK has become a leading institution in implementing learning analytics at scale amongst its 170K students and 5K staff. Furthermore, he will discuss how learning analytics is being adopted at other UK institutions, and what the implications for higher education might be in these Covid19 times.
https://www.kent.ac.uk/cshe/news-events.html
Using student data to transform teaching and learningBart Rienties
This document summarizes a webinar given by Dr. Bart Rienties on using student data and learning analytics to transform teaching and learning. Some key points:
- Learning analytics aims to measure, collect, analyze and report data about learners to understand and optimize learning. Social learning analytics focuses on how learners build knowledge together.
- The Open University has been a world leader in collecting and analyzing large-scale student data to provide actionable insights for students, teachers, and institutional benefit. Studies have shown the importance of linking learning analytics outcomes to student satisfaction, retention, and learning design.
- Practitioners want learning analytics solutions that are integrated across an entire learning journey from initial inquiry through modules to
AI in Education Amsterdam Data Science (ADS) What have we learned after a dec...Bart Rienties
The Open University UK (OU) has been implementing learning analytics and learning design on a large scale since 2012. With its 170+ students and 4000+ teaching staff, the OU has been at the forefront of testing, implementing, and evaluating the impact of learning analytics and learning design on students outcome and retention. A range of reviews and scholarly repositories (e.g., Web of Science) indicate that the OU is the largest contributor to academic output in learning analytics and learning design in the world. However, despite the large uptake of learning analytics at the OU there are a range of complex issues in terms of buy-in from staff, data infrastructures, ethics and privacy, student engagement, and perhaps most importantly how to make sense of big and small data in a complex organisation like the OU. During his talk Bart will be presenting on the implementation and learnings.
«Learning Analytics at the Open University and the UK»Bart Rienties
In this seminar, Prof Bart Rienties will reflect on how the Open University UK has become a leading institution in implementing learning analytics at scale amongst its 170K students and 5K staff. Furthermore, he will discuss how learning analytics is being adopted at other UK institutions, and what the implications for higher education might be.
eMadrid seminar on «Review and challenges in Learning Analytics»
20_05_08 «Learning Analytics en la Open University y en el Reino Unido».eMadrid network
This document summarizes a presentation by Dr. Bart Rienties on learning analytics at the Open University in the UK. It discusses how the Open University is a world leader in collecting and analyzing large-scale student data to provide actionable insights for students and academics. Key studies identified link learning analytics outcomes to student satisfaction, retention, and module learning design. The university's Analytics4Action initiative supports institution-wide learning analytics approaches. Legal and ethical challenges around student consent, transparency, and intervention processes are also addressed.
This document discusses blending MOOCs into traditional post-secondary classrooms. It outlines advantages like free access to learning and increased collaboration, as well as disadvantages like lack of instruction and completion rates. Previous studies that blended MOOCs and face-to-face learning are summarized, such as requiring participation in online MOOC components for a campus course. The document proposes a blended approach combining MOOC basic content with specific face-to-face content and concludes by discussing benefits of blended MOOCs and providing an agenda for a workshop on developing blended MOOC strategies.
Keynote Presentation: Implementing learning analytics and learning design at ...Bart Rienties
The University of the Roller Coaster
How can Higher Education function in a world struggling to save itself from climate change, pandemics and war? How can it drive innovation and shape the future as the pace of technological change constantly increases? How can it re-invent itself to respond imaginatively to the new challenges facing humanity?
We are living in an uncertain, unpredictable world with no “back to normal” any more. So, how can we re-imagine higher education when nothing can be taken for granted? What kind of technologies can help universities to adapt? What lessons can we learn from recent successes and failures? What 'best practice' examples point the way into the future? How can we shape the development of institutions, so that they are neither “ivory towers” nor “competence factories"? How can we encourage future-oriented universities in which both pedagogy and research are fit for the challenges ahead?
In the Academic Plenary, our experts will examine the threats and opportunities facing higher education today and ask how we can design new approaches that prepare staff and students to thrive in the University of the Roller Coaster.
Open instructional design and assessments - OE4BW 2020nwahls
Organization of a learning experience
Learning outcomes, learner levels, and accessibility
Active learning in self-directed and distance contexts
Turning resources and assessments into a course or textbook
E-õppe ja avatud hariduse lahendused Tallinna ÜlikoolisHans Põldoja
The document discusses open educational tools and resources at Tallinn University. It begins by defining open education and how the concept has evolved over time. It then outlines some of the open learning environments used at Tallinn University, including blogs and WordPress sites for course content, YouTube videos, and GitHub for collaborative coding projects. The document also addresses challenges in designing open online courses, such as building community and providing feedback. Overall, it presents Tallinn University's approach to open education and how open learning environments can increase accessibility and collaboration.
Designing and Evaluating Student-facing Learning Dashboards: Lessons Learnt (...Sven Charleer
Sven Charleer defended his PhD thesis on designing and evaluating student-facing learning dashboards. Over the course of his research, he developed 7 dashboards across 3 learning settings involving over 100 students and 20 instructors. His work resulted in 19 publications and has been cited over 120 times. Going forward, Charleer aims to conduct longer term evaluations and deployments of dashboards at additional universities.
Openness Initiatives in Distance EducationGülay Ekren
The document discusses openness initiatives in distance education. It provides an introduction to key concepts of openness like open educational resources (OERs), MOOCs, and open source software. It then outlines the aims and methods of the study, which involved a content analysis of 46 articles from the International Review of Research in Open and Distance Learning (IRRODL) journal. The results of the study found that research areas focused on issues like instructional design, management and organization, and educational technology. Studies also centered on themes such as OERs, MOOCs, connectivism, and open education. Most studies used qualitative or mixed methods approaches.
Edutech_Europe Keynote Presentation: Implementing learning analytics and lear...Bart Rienties
This keynote will help you:
-Understand where to start with learning analytics
-Understand how to effectively support your staff to use data
-Critically review whether learning analytics is something for your organisation
https://www.terrapinn.com/exhibition/edutech-europe/speaker-bart-RIENTIES.stm
How can you use learning analytics in your own research and practice: an intr...Bart Rienties
While many “brick-and-mortar” universities had to rapidly shift online provision during the pandemic, a range of online and distance learning universities have been teaching in blended and online formats for years. Obviously with every single click potentially interesting data might become available about how and perhaps why learners are engaging with learning materials and activities. A blossoming field of learning analytics has emerged since 2011 trying to make sense of these increased data flows. The Open University UK (OU) has been trailblazing innovative learning across the globe for 50 years. Since 2014 the OU has gradually moved from small-scale experimentation to large-scale adoption of learning analytics throughout all 400+ modules and qualifications available within the OU for its 170.000+ online learners.
This keynote will explore how you as researcher, practitioner, and/or policy maker could start to use learning analytics to better understand your educational practice. Using examples from small-scale experiments and large-scale adoptions of predictive learning analytics I will explore together with EDEN RW participants which approaches and methods in learning analytics might be useful to consider. No prior knowledge or experience of learning analytics is expected, and join me on a journey of how you could potentially use data from your learners and teachers to further improve and finetune your blended and online provision.
Dr. Bart Rienties is Professor of Learning Analytics and programme lead of the learning analytics and learning design research programme at the Institute of Educational Technology at the Open University UK. He leads a group of academics who provide university-wide learning analytics and learning design solutions and conduct evidence-based research of how students and professionals learn. His primary research interests are focussed on Learning Analytics, Professional Development, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He has successfully led a range of institutional/national/European projects, and has received a range of awards for his educational innovation projects. He has published over 285 academic outputs, and is the 2nd most published author on Networks in Education in period 1969-2020 (Saqr et al. 2022), the 3rd most cited author on higher education internationalisation in Asia in the period 2013-2018 (Can & Hou, 2021), the 4th most cited author and contributor in Learning Analytics in the period 2011-2018 (Adeniji, 2019), the 5th most published author on internationalisation in the period 1900-2018 (Jing et al. 2020) and the 7th most published author on social network analysis in social sciences in the period 1999-2018 (Su et al. 2020), and the 14th most published author on educational technology in the period 2015-2018 (West & Bodily, 2020).
The document discusses challenges in higher education and emerging technologies. It notes that while the use of technologies is increasing, they are seldom used to facilitate transformative teaching and learning. Examples of innovative practices mentioned include MOOCs, learning analytics, badges for accrediting learning, and the use of mobile phones for citizen journalism projects. The document also addresses concerns that institutions have been slow to adopt technologies and that there is a mismatch between student expectations and what institutions offer.
The document discusses challenges in higher education and emerging technologies. It notes that while the use of technologies is increasing, they are seldom used to facilitate transformative teaching and learning. Examples of innovative practices mentioned include MOOCs, learning analytics, badges for accrediting learning, and seamless learning across formal and informal settings. However, the potential of technologies remains mostly unfulfilled due to issues like a lack of engagement from institutions and policy makers.
An overview of current QEI team-led projects at the OUJisc
This document provides an overview of current projects led by the Quality Enhancement and Innovation (QEI) team at the Open University's Institute of Educational Technology. It discusses projects in four key areas: analytics, assessment design, designing for changing learners, and accessibility. Some of the projects described include developing models to analyze learner pathways, using text analytics on student comments, creating early alert indicators for student risk, evaluating online exam experiences, and developing a virtual assistant to support students with disabilities. The QEI team is working to advance educational technology, evaluation, and innovation in teaching and learning at the Open University.
Emerging technologies and Changing Teaching and Learning PracticesDaniela Gachago
This document discusses emerging technologies and changing teaching and learning practices in higher education. It notes challenges in higher education including teaching outdated skills and lack of teacher involvement in innovation. Emerging technologies promise benefits but are seldom used transformatively. The document outlines a South African project studying innovative pedagogical practices using emerging technologies and lessons learned. Case studies showed technologies can enable authentic learning when used to engage students in meaningful, collaborative tasks. Themes included the importance of passionate educators over institutional support and focusing on meaningful learning in authentic contexts.
The document describes the Inspiring Science Education tools, which were developed to support teachers in authoring and delivering technology-enhanced science lessons that follow an inquiry cycle and assess students' problem solving competences. The tools include an authoring tool to design lessons incorporating assessment tasks aligned with the PISA problem solving framework, and a delivery tool to implement the lessons and collect student assessment data. The overall goal is to help teachers improve their lesson plans and enhance students' problem solving skills.
International students in Europe keynoteBart Rienties
Abschlusskonferenz des Verbundprojekts „Internationale MINT-Studierende in Deutschland (InterMINT)“ am 21.06.2024 in Bonn
[23.11.2023]
10:15-11:00 International Students in Europe
Keynote: Prof. Bart Rienties (Open University UK)
Questions and discussion
Im Fokus der Abschlusstagung des vom BMBF geförderten Verbundprojekts „Internationale MINT-Studierende in Deutschland“ der FernUniversität in Hagen und des Bayerischen Staatsinstituts für Hochschulforschung und Hochschulplanung (IHF) steht der Studienerfolg internationaler MINT-Studierender.
Applying and translating learning design and analytics approaches in your ins...Bart Rienties
This interactive workshop delivered by the University of Zagreb, Faculty of Organisation and Informatics (UZ) and the Open University UK (OU) will build on two large-scale implementations of learning design and learning analytics, and how you could potentially implement similar approaches in your institution. The OU has been implementing learning design for nearly 20 years as a structured design, specification, and review process for blended and online courses. The learning design is focused on "what students do" as part of their learning, rather than on "what teachers do" or on what will be taught.
Building on this work, UZ has recently developed the Balanced Design Planning (BDP) tool specifically for educators working in hybrid and blended contexts. The tool is more focused on intended learning outcomes and automated learning analytics and is currently being developed, tested, evaluated and implemented with 1000+ practitioners from dozens of institutions in 20+ countries as part of four European projects (eDesk, Teach4EDU, RAPIDE, iLED), and is publicly available for other institutions to use for free. It has been shown by studies conducted by OU and UZ that when these learning design (LD) approaches are used, they help educators to make real-time informed decisions based on learning analytics (LA) and improve the predictive modelling of student behaviour.
Attendees should bring their laptop for this workshop session.
Bart Rienties, Professor in Learning Analytics, Institute of Education Technology, The Open University
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«Learning Analytics at the Open University and the UK»Bart Rienties
In this seminar, Prof Bart Rienties will reflect on how the Open University UK has become a leading institution in implementing learning analytics at scale amongst its 170K students and 5K staff. Furthermore, he will discuss how learning analytics is being adopted at other UK institutions, and what the implications for higher education might be.
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This document summarizes a presentation by Dr. Bart Rienties on learning analytics at the Open University in the UK. It discusses how the Open University is a world leader in collecting and analyzing large-scale student data to provide actionable insights for students and academics. Key studies identified link learning analytics outcomes to student satisfaction, retention, and module learning design. The university's Analytics4Action initiative supports institution-wide learning analytics approaches. Legal and ethical challenges around student consent, transparency, and intervention processes are also addressed.
This document discusses blending MOOCs into traditional post-secondary classrooms. It outlines advantages like free access to learning and increased collaboration, as well as disadvantages like lack of instruction and completion rates. Previous studies that blended MOOCs and face-to-face learning are summarized, such as requiring participation in online MOOC components for a campus course. The document proposes a blended approach combining MOOC basic content with specific face-to-face content and concludes by discussing benefits of blended MOOCs and providing an agenda for a workshop on developing blended MOOC strategies.
Keynote Presentation: Implementing learning analytics and learning design at ...Bart Rienties
The University of the Roller Coaster
How can Higher Education function in a world struggling to save itself from climate change, pandemics and war? How can it drive innovation and shape the future as the pace of technological change constantly increases? How can it re-invent itself to respond imaginatively to the new challenges facing humanity?
We are living in an uncertain, unpredictable world with no “back to normal” any more. So, how can we re-imagine higher education when nothing can be taken for granted? What kind of technologies can help universities to adapt? What lessons can we learn from recent successes and failures? What 'best practice' examples point the way into the future? How can we shape the development of institutions, so that they are neither “ivory towers” nor “competence factories"? How can we encourage future-oriented universities in which both pedagogy and research are fit for the challenges ahead?
In the Academic Plenary, our experts will examine the threats and opportunities facing higher education today and ask how we can design new approaches that prepare staff and students to thrive in the University of the Roller Coaster.
Open instructional design and assessments - OE4BW 2020nwahls
Organization of a learning experience
Learning outcomes, learner levels, and accessibility
Active learning in self-directed and distance contexts
Turning resources and assessments into a course or textbook
E-õppe ja avatud hariduse lahendused Tallinna ÜlikoolisHans Põldoja
The document discusses open educational tools and resources at Tallinn University. It begins by defining open education and how the concept has evolved over time. It then outlines some of the open learning environments used at Tallinn University, including blogs and WordPress sites for course content, YouTube videos, and GitHub for collaborative coding projects. The document also addresses challenges in designing open online courses, such as building community and providing feedback. Overall, it presents Tallinn University's approach to open education and how open learning environments can increase accessibility and collaboration.
Designing and Evaluating Student-facing Learning Dashboards: Lessons Learnt (...Sven Charleer
Sven Charleer defended his PhD thesis on designing and evaluating student-facing learning dashboards. Over the course of his research, he developed 7 dashboards across 3 learning settings involving over 100 students and 20 instructors. His work resulted in 19 publications and has been cited over 120 times. Going forward, Charleer aims to conduct longer term evaluations and deployments of dashboards at additional universities.
Openness Initiatives in Distance EducationGülay Ekren
The document discusses openness initiatives in distance education. It provides an introduction to key concepts of openness like open educational resources (OERs), MOOCs, and open source software. It then outlines the aims and methods of the study, which involved a content analysis of 46 articles from the International Review of Research in Open and Distance Learning (IRRODL) journal. The results of the study found that research areas focused on issues like instructional design, management and organization, and educational technology. Studies also centered on themes such as OERs, MOOCs, connectivism, and open education. Most studies used qualitative or mixed methods approaches.
Edutech_Europe Keynote Presentation: Implementing learning analytics and lear...Bart Rienties
This keynote will help you:
-Understand where to start with learning analytics
-Understand how to effectively support your staff to use data
-Critically review whether learning analytics is something for your organisation
https://www.terrapinn.com/exhibition/edutech-europe/speaker-bart-RIENTIES.stm
How can you use learning analytics in your own research and practice: an intr...Bart Rienties
While many “brick-and-mortar” universities had to rapidly shift online provision during the pandemic, a range of online and distance learning universities have been teaching in blended and online formats for years. Obviously with every single click potentially interesting data might become available about how and perhaps why learners are engaging with learning materials and activities. A blossoming field of learning analytics has emerged since 2011 trying to make sense of these increased data flows. The Open University UK (OU) has been trailblazing innovative learning across the globe for 50 years. Since 2014 the OU has gradually moved from small-scale experimentation to large-scale adoption of learning analytics throughout all 400+ modules and qualifications available within the OU for its 170.000+ online learners.
This keynote will explore how you as researcher, practitioner, and/or policy maker could start to use learning analytics to better understand your educational practice. Using examples from small-scale experiments and large-scale adoptions of predictive learning analytics I will explore together with EDEN RW participants which approaches and methods in learning analytics might be useful to consider. No prior knowledge or experience of learning analytics is expected, and join me on a journey of how you could potentially use data from your learners and teachers to further improve and finetune your blended and online provision.
Dr. Bart Rienties is Professor of Learning Analytics and programme lead of the learning analytics and learning design research programme at the Institute of Educational Technology at the Open University UK. He leads a group of academics who provide university-wide learning analytics and learning design solutions and conduct evidence-based research of how students and professionals learn. His primary research interests are focussed on Learning Analytics, Professional Development, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He has successfully led a range of institutional/national/European projects, and has received a range of awards for his educational innovation projects. He has published over 285 academic outputs, and is the 2nd most published author on Networks in Education in period 1969-2020 (Saqr et al. 2022), the 3rd most cited author on higher education internationalisation in Asia in the period 2013-2018 (Can & Hou, 2021), the 4th most cited author and contributor in Learning Analytics in the period 2011-2018 (Adeniji, 2019), the 5th most published author on internationalisation in the period 1900-2018 (Jing et al. 2020) and the 7th most published author on social network analysis in social sciences in the period 1999-2018 (Su et al. 2020), and the 14th most published author on educational technology in the period 2015-2018 (West & Bodily, 2020).
The document discusses challenges in higher education and emerging technologies. It notes that while the use of technologies is increasing, they are seldom used to facilitate transformative teaching and learning. Examples of innovative practices mentioned include MOOCs, learning analytics, badges for accrediting learning, and the use of mobile phones for citizen journalism projects. The document also addresses concerns that institutions have been slow to adopt technologies and that there is a mismatch between student expectations and what institutions offer.
The document discusses challenges in higher education and emerging technologies. It notes that while the use of technologies is increasing, they are seldom used to facilitate transformative teaching and learning. Examples of innovative practices mentioned include MOOCs, learning analytics, badges for accrediting learning, and seamless learning across formal and informal settings. However, the potential of technologies remains mostly unfulfilled due to issues like a lack of engagement from institutions and policy makers.
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This document provides an overview of current projects led by the Quality Enhancement and Innovation (QEI) team at the Open University's Institute of Educational Technology. It discusses projects in four key areas: analytics, assessment design, designing for changing learners, and accessibility. Some of the projects described include developing models to analyze learner pathways, using text analytics on student comments, creating early alert indicators for student risk, evaluating online exam experiences, and developing a virtual assistant to support students with disabilities. The QEI team is working to advance educational technology, evaluation, and innovation in teaching and learning at the Open University.
Emerging technologies and Changing Teaching and Learning PracticesDaniela Gachago
This document discusses emerging technologies and changing teaching and learning practices in higher education. It notes challenges in higher education including teaching outdated skills and lack of teacher involvement in innovation. Emerging technologies promise benefits but are seldom used transformatively. The document outlines a South African project studying innovative pedagogical practices using emerging technologies and lessons learned. Case studies showed technologies can enable authentic learning when used to engage students in meaningful, collaborative tasks. Themes included the importance of passionate educators over institutional support and focusing on meaningful learning in authentic contexts.
The document describes the Inspiring Science Education tools, which were developed to support teachers in authoring and delivering technology-enhanced science lessons that follow an inquiry cycle and assess students' problem solving competences. The tools include an authoring tool to design lessons incorporating assessment tasks aligned with the PISA problem solving framework, and a delivery tool to implement the lessons and collect student assessment data. The overall goal is to help teachers improve their lesson plans and enhance students' problem solving skills.
Similar to SAAIR: Implementing learning analytics at scale in an online world: lessons learned from the Open University UK (20)
International students in Europe keynoteBart Rienties
Abschlusskonferenz des Verbundprojekts „Internationale MINT-Studierende in Deutschland (InterMINT)“ am 21.06.2024 in Bonn
[23.11.2023]
10:15-11:00 International Students in Europe
Keynote: Prof. Bart Rienties (Open University UK)
Questions and discussion
Im Fokus der Abschlusstagung des vom BMBF geförderten Verbundprojekts „Internationale MINT-Studierende in Deutschland“ der FernUniversität in Hagen und des Bayerischen Staatsinstituts für Hochschulforschung und Hochschulplanung (IHF) steht der Studienerfolg internationaler MINT-Studierender.
Applying and translating learning design and analytics approaches in your ins...Bart Rienties
This interactive workshop delivered by the University of Zagreb, Faculty of Organisation and Informatics (UZ) and the Open University UK (OU) will build on two large-scale implementations of learning design and learning analytics, and how you could potentially implement similar approaches in your institution. The OU has been implementing learning design for nearly 20 years as a structured design, specification, and review process for blended and online courses. The learning design is focused on "what students do" as part of their learning, rather than on "what teachers do" or on what will be taught.
Building on this work, UZ has recently developed the Balanced Design Planning (BDP) tool specifically for educators working in hybrid and blended contexts. The tool is more focused on intended learning outcomes and automated learning analytics and is currently being developed, tested, evaluated and implemented with 1000+ practitioners from dozens of institutions in 20+ countries as part of four European projects (eDesk, Teach4EDU, RAPIDE, iLED), and is publicly available for other institutions to use for free. It has been shown by studies conducted by OU and UZ that when these learning design (LD) approaches are used, they help educators to make real-time informed decisions based on learning analytics (LA) and improve the predictive modelling of student behaviour.
Attendees should bring their laptop for this workshop session.
Bart Rienties, Professor in Learning Analytics, Institute of Education Technology, The Open University
OU/Leverhulme Open World Learning: Knowledge Exchange and Book Launch Event p...Bart Rienties
This online event will be a showcase of leading research in the field of open learning, conducted by Doctoral Scholars of The Open University and Leverhulme Trust’s Open World Learning programme, whose work is being recognised with the launch of a new open-access Open World Learning Book.
The event will feature an opening panel discussion on the achievements of our Doctoral Scholars, a collection of themed break-out sessions where scholars will share their research studies and their social impacts, and close with a roundtable where our scholars will consider the future of open learning.
Learning in the 21st century is undergoing both subtle and radical transformation due to the impact of digital, innovative, network technologies. Open learning provides unprecedented access to educational information, providing support to learners worldwide. However, it is not the technologies themselves that represent the biggest change, but the opportunities for access to formal and informal learning.
The Open World Learning programme has been funded by the Leverhulme Trust and The Open University to provide 18 Scholars the opportunity to identify changes in open learning which may exclude, rather than include those who would most benefit. Despite technological advancements, the main challenges to open learning are access-related. Our Open World Learning Scholars have been researching the barriers to access for those whose experiences open learning can benefit most and addressing issues where possible.
Hosted by Professor Bart Rienties, Programme Lead of the Open World Learning programme at the OU's Institute of Educational Technology, this two-hour event will provide a knowledge exchange platform to learn from our Open World Learning Doctoral Scholars and celebrate their exceptional achievements with the Open World Learning Book Launch.
We hope you join us and register to attend our free event. Follow us on the IETatOU Twitter and visit the IET website where a series of digital and social content will be shared highlighting the work of our Open World Learning scholars.
Visit us here: https://iet.open.ac.uk | https://twitter.com/ietatou
Education 4.0 and Computer Science: A European perspectiveBart Rienties
This systematic literature review aimed at identifying the pedagogical approaches, aligned with Education 4.0, used to support teaching computer science courses with undergraduate and graduate students in Europe. A three-step coding process was conducted to identify and analyse 20 papers. Quantitative and qualitative analysis of the selected papers revealed a three-cluster solution with common characteristics that could be used to describe those pedagogical approaches. The review also showed that the term Education 4.0 is still relatively new and has not been conceptualised in terms of computer science courses, although the characteristics of Education 4.0 are visible throughout the pedagogical approaches.
Bart Rienties, Rebecca Ferguson, Christothea Herodotou, Francisco Iniesto, Julia Sargent, Igor Balaban, Henry Muccini, Sirje Virkus
How learning gains and Quality Assurance are (mis)Aligned: An Interactive Wor...Bart Rienties
In the last five years there is an increased interest across the globe to define, conceptualise, and measure learning gains. The concept of learning gains, briefly summarised as the improvement in knowledge, skills, work-readiness and personal development made by students during their time spent in higher education, has been hailed by some as an opportunity to measure “excellence” in teaching. However, whether learning gains could be useful for quality assurance can be debated. This interactive workshop aims to provide an open platform to
discuss the opportunities and limitations of learning gains for quality assurance.
Lecture series: Using trace data or subjective data, that is the question dur...Bart Rienties
In this lecture series Bart Rienties (Professor of Learning Analytics, head of Academic Professional Development) will discuss how from the safety of your home you could use existing trace data to explore interactions between people (e.g., Twitter data, engagement data in a virtual learning environment, public data sets), and what the affordances and limitations of these trace data might be. Furthermore, he will discuss how other ways of collecting subjective data (e.g., surveys, interviews) might strengthen our understandings of complex interactions between people.
There are no prior requirements to join, and everyone is welcome. For those with a technical background you may enjoy this recent paper in PLOS ONE https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0233977. For those with a non-technical background, you may enjoy this paper https://journals.sfu.ca/flr/index.php/journal/article/view/348
How to analyse questionnaire data: an advanced sessionBart Rienties
This document outlines an advanced workshop on analyzing questionnaire data. The objectives are to familiarize participants with psychometric and linguistic techniques for analyzing questionnaire data, including computing constructs, factor analysis, reliability, validity, and advanced statistical techniques. It discusses what a questionnaire is, the questionnaire design process, strengths and limitations of questionnaires, and provides case studies on using questionnaires to measure constructs like academic motivation and student adjustment. The document provides information on collecting questionnaire data, checking reliability and validity, and using statistical analyses to test hypotheses and predict outcomes.
Questionnaire design for beginners (Bart Rienties)Bart Rienties
This document provides an introduction to questionnaire design. It discusses the objectives of using questionnaires which are to understand why they are used, the process of constructing them, and key features of good question design. It also covers strengths and limitations of questionnaires, the survey process, maximizing response rates, and types of questions. The document aims to provide guidance on best practices for designing and implementing effective questionnaires.
Presentation LMU Munich: The power of learning analytics to unpack learning a...Bart Rienties
The power of learning analytics to unpack learning and teaching: a critical perspective
Ludwig-Maximilians-Universität München
Fakultät für Psychologie und Pädagogik
Educational Technology - opportunities and pitfalls How to make the most use...Bart Rienties
The keynote presentation covered opportunities and limitations of educational technology based on learning analytics research. It included three research exemplars: 1) a study that found students' self-reported internet searching skills did not match their actual online behavior, 2) a randomized study showing how internationalized course content can encourage participation in diverse groups, and 3) a project linking multiple datasets across 150+ modules to predict student outcomes. The talk concluded by emphasizing the need to consider ethics and standardization as more educational data becomes available and harvested for learning analytics.
Unpacking academic and social adjustment of internationalisation at a distanc...Bart Rienties
Bart Rienties, Open University, United Kingdom; Jenna Mittelmeier, University of Manchester, United Kingdom; Jo Jordan,
Open University, United Kingdom; Jekaterina Rogaten, Open University, United Kingdom; Ashley Gunter, UNIVERSITY OF
SOUTH AFRICA, South Africa; Parvati Raghuram, Open University, United Kingdom
Internationalisation at a Distance and at Home: Academic and Social Adjustmen...Bart Rienties
This document summarizes a study examining academic and social adjustment of students in different internationalization contexts at the University of South Africa (UNISA). The study compared students in internationalization at home (IaH), internationalization abroad (IA), and internationalization at distance (IaD). It found no significant differences in academic or social adjustment between the three groups. IaD students had significantly higher access to technology and lower personal-emotional adjustment and attachment than IaH students. Access to technology positively predicted academic and emotional adjustment. Being from South Africa and having better access to technology positively impacted adjustment.
Overview of Effective Learning Analytics Using data and analytics to support ...Bart Rienties
Begona Nunez-Herran and Kevin Mayles (Data and Student Analytics), Rebecca Ward (Data Strategy and Governance)
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-Data governance and lessons learned
Prof Bart Rienties & PhD students (Institute of Educational Technology)
-What is the latest “blue sky” learning analytics research from the OU?
-Rogers Kalissa: Social Learning Analytics to support teaching (University of Oslo)
-Saman Rizvi: Cultural impact of MOOC learning (IET)
-Shi Min Chua: Why does no one reply to my posts (IET/WELS)
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Prof John Domingue (Knowledge Media Institute) & Dr Thea Herodotou (IET)
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Lessons learned from 200K students and 2 GB of learning gains data.Bart Rienties
OfS national conference on learning gains, Birmingham, 12 March 2019
Student Participation: how can learning gain data help students from all backgrounds access, succeed and proceed in higher education @learninggains @officeforstudents
https://abclearninggains.com/
DISTANCE EDUCATION AND AFRICAN STUDENTS” College of Agriculture and Environme...Bart Rienties
The document discusses a project exploring the role of distance education in Africa using the University of South Africa (UNISA) as a case study. The project has teams in the UK and South Africa and uses methods like questionnaires, interviews, and learning analytics data from UNISA courses. The goals are to examine equitable access to distance education for African students, assess and improve quality of education, and advance theoretical understandings of distance education through a postcolonial framework. The project takes a multidisciplinary approach and involves collaboration between various universities.
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more consistent, and more personalised service to their students and stakeholders In particular, the
development of learning analytics may empower distance learning institutions to provide near realtime
actionable feedback to teachers and students about what the “best” next step in their learning
journeys might be. For example, several institutions have started to explore the use of learning
analytics dashboards that can display learner and learning behaviour to teachers and instructional
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limitations of learning analytics
https://www.bera.ac.uk/event/ed-tech-nov
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This seminar will look at the different models being adopted globally, and use a framework to consider what might be the best approach for the OU.
DATE AND TIME: Thu 25 October 2018, 14:00 – 15:00
LOCATION: The Hub Theatre, Walton Hall, Milton Keynes
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SAAIR: Implementing learning analytics at scale in an online world: lessons learned from the Open University UK
1. @DrBartRienties
Professor of Learning Analytics
All papers referred to in this presentation can be
accessed via
https://iet.open.ac.uk/people/bart.rienties
Implementing learning analytics at
scale in an online world: lessons
learned from the Open University
UK
2.
3.
4. Now freely Available
• This open access book provides state-of-the-art contemporary research
insights into key applications and processes in open world learning.
• It explores how the application of open world and educational
technologies can be used to create opportunities for open and high-
quality education.
• Presenting ground-breaking research from an award winning
Leverhulme doctoral training programme, the book provides several
integrated and cohesive perspectives of the affordances and limitations
of open world learning.
• The book brings together a range of innovative uses of technology and
practice in open world learning from 387,134 learners and educators
learning and working in 136 unique learning contexts across the
globe
• Free to attend online event on Wednesday 9 February 2022 1400-1600,
Open World Learning, Institute of Educational Technology, The Open
University.
• https://www.routledge.com/Open-World-Learning-Research-Innovation-
and-the-Challenges-of-High-Quality/Rienties-Hampel-Scanlon-
Whitelock/p/book/9781032010915
5. What we have learned in 10 years of implementing learning
analytics and learning design at the OU
Change is slow, but can be enhanced with:
1. Clear senior management support
2. Bottom-up support from teachers and researchers who are
willing to take a risk
3. Evidence-based research can gradually change perspectives
and narratives
4. You quickly forget about the small/medium/large successes
and fail to realise that you are making a real impact
5. Large-scale innovation takes substantial time and effort
6. It is all about people…
Rienties., B. (2022). Implementing learning analytics at scale in an online world: lessons learned from the Open University UK. Liebowitz, J. (Ed). Online learning analytics. Taylor & Francis.
6. Dyckhoff, A. L., Zielke, D., Bültmann, M., Chatti, M. A., & Schroeder, U. (2012). Design and Implementation of a Learning Analytics Toolkit for Teachers. Journal of Educational Technology & Society, 15(3), 58-76.
7. Dyckhoff, A. L., Zielke, D., Bültmann, M., Chatti, M. A., & Schroeder, U. (2012). Design and Implementation of a Learning Analytics Toolkit for Teachers. Journal of Educational Technology & Society, 15(3), 58-76.
8.
9.
10. Leading global distance learning, delivering high-quality education to anyone, anywhere, anytime
The Open University
Largest
University
in Europe
No formal
entry
requirements
enter with one
A-level or less
33%
38%
of part-time
undergraduates
taught by OU in UK
173,927 formal
students
55%
of students are
'disadvantaged'
FTSE 100 have
sponsored staff on OU
courses in 2017/8
60%
66%
of new
undergraduates
are 25+ 1,300
Open University students
has a disability (23,630)
1 in 8
Students are
already in work
3 in 4
employers use
OU learning
solutions to
develop
workforce
11.
12. Predictive learning analytics (since 2013) Learning Design (since 2005)
Rienties., B. (2022). Implementing learning analytics at scale in an online world: lessons learned from the Open University UK. Liebowitz, J. (Ed). Online learning analytics. Taylor & Francis.
Rienties, B., Herodotou, C. (2022). Making sense of learning data at scale. Sharpe, R., Bennett, S., Varga-Atkins, T. (Eds). Handbook for Digital Higher Education. Edward Elgar Publishing
13. Predictive analytics to identify whether students are
going to make the next assignment
Kuzilek, J., Hlosta, M., Herrmannova, D., Zdrahal, Z., & Wolff, A. (2015). OU Analyse: analysing at-risk students at The Open University LACE Learning Analytics Review (Vol. LAK15-1). Milton Keynes: Open University.
Kuzilek, J., Hlosta, M., & Zdrahal, Z. (2017). Open University Learning Analytics dataset. Scientific Data, 4, 170171. doi: 10.1038/sdata.2017.171
Wolff, A., Zdrahal, Z., Herrmannova, D., Kuzilek, J., & Hlosta, M. (2014). Developing predictive models for early detection of at-risk students on distance learning modules, Workshop: Machine Learning and Learning Analytics
Paper presented at the Learning Analytics and Knowledge (2014), Indianapolis.
14. Start
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student
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N O S
RF
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OF OR ORS
ORFS OS RS
Pass Fail No submit TMA-1
time
VLE opens
Start
VLE trail: student
who did not submit
18. Herodotou, C., Rienties, B., Hlosta, M., Boroowa, A., Mangafa, C., Zdrahal, Z., (2020). Scalable implementation of predictive learning analytics at a distance learning university:
Insights from a longitudinal case study. Internet and Higher Education, 45, 100725.
19. Herodotou, C., Rienties, B., Hlosta, M., Boroowa, A., Mangafa, C., Zdrahal, Z., (2020). Scalable implementation of predictive learning analytics at a distance learning university:
Insights from a longitudinal case study. Internet and Higher Education, 45, 100725.
Amongst the factors shown to be critical to the scalable PLA implementation were: Faculty's engagement with OUA,
teachers as “champions”, evidence generation and dissemination, digital literacy, and conceptions about teaching
online.
21. Rets, I., Herodotou, C., Bayer, V., Hlosta, M., Rienties, B. (2021). Exploring critical factors of the perceived usefulness of a learning analytics dashboard for
distance university students. International Journal of Educational Technology in Higher Education. 18 (46).
Mixed method with 22 undergraduate business students
The majority of participants found the Study recommender useful for two
reasons:
a) to remind them of the learning material they had missed, and
b) as a means of directly accessing content (e.g., as opposed to going through the
VLE).
Perceived usefulness was influenced by
• Trustworthiness of learning analytics dashboard
• Peer comparison
• Academic self-confidence
• Change in study patterns
• “Good” vs “not-so-good” students
22.
23. Predictive learning analytics (since 2013) Learning Design (since 2005)
Rienties., B. (2021). Implementing learning analytics at scale in an online world: lessons learned from the Open University UK. Liebowitz, J. (Ed). Online learning analytics. Taylor & Francis.
Rienties, B., Herodotou, C. (2021). Making sense of learning data at scale. Sharpe, R., Bennett, S., Varga-Atkins, T. (Eds). Handbook for Digital Higher Education. Edward Elgar Publishing
24. Magic of learning design (does not come easy)
“Research on the relationship between learning design and learning
analytics has also been a focus in European research in recent years. For
example, in their research at the Open University UK, Toetenel and
Rienties combine learning design and learning analytics where learning
design provides context to empirical data about OU courses enabling the
learning analytics to give insight into learning design decisions. This
research is important as it attempts to close the virtuous cycle
between learning design to improve courses and enhancing the
quality of learning, something that has been lacking in the research
literature. For example, they study the impact of learning design on
pedagogical decision-making and on future course design, and the
relationship between learning design and student behaviour and outcomes
(Toetenel and Rienties 2016; Rienties and Toetenel 2016; Rienties et al.
2015).”
Wasson, B., & Kirschner, P. A. (2020). Learning Design: European Approaches. TechTrends, 1-13.
25. Assimilative Finding and
handling
information
Communication Productive Experiential Interactive/
Adaptive
Assessment
Type of activity Attending to
information
Searching for
and processing
information
Discussing
module related
content with at
least one other
person (student
or tutor)
Actively
constructing an
artefact
Applying
learning in a
real-world
setting
Applying
learning in a
simulated
setting
All forms of
assessment,
whether
continuous, end
of module, or
formative
(assessment for
learning)
Examples of
activity
Read, Watch,
Listen, Think
about, Access,
Observe,
Review, Study
List, Analyse,
Collate, Plot,
Find, Discover,
Access, Use,
Gather, Order,
Classify, Select,
Assess,
Manipulate
Communicate,
Debate, Discuss,
Argue, Share,
Report,
Collaborate,
Present,
Describe,
Question
Create, Build,
Make, Design,
Construct,
Contribute,
Complete,
Produce, Write,
Draw, Refine,
Compose,
Synthesise,
Remix
Practice, Apply,
Mimic,
Experience,
Explore,
Investigate,
Perform,
Engage
Explore,
Experiment,
Trial, Improve,
Model, Simulate
Write, Present,
Report,
Demonstrate,
Critique
Conole, G. (2012). Designing for Learning in an Open World. Dordrecht: Springer.
Rienties, B., Toetenel, L., (2016). The impact of learning design on student behaviour, satisfaction and performance: a cross-institutional comparison across 151
modules. Computers in Human Behavior, 60 (2016), 333-341
Open University Learning Design Initiative (OULDI)
26. Toetenel, L., Rienties, B. (2016). Analysing 157 Learning Designs using Learning Analytic approaches as a means to evaluate the impact of pedagogical
decision-making. British Journal of Educational Technology, 47(5), 981–992.
27.
28. Constructivist
Learning Design
Assessment
Learning Design
Productive
Learning Design
Socio-construct.
Learning Design
VLE Engagement
Student
Satisfaction
Student
retention
150+ modules
Week 1 Week 2 Week30
+
Rienties, B., Toetenel, L., (2016). The impact of learning design on student behaviour, satisfaction and performance: a cross-institutional comparison across 151
modules. Computers in Human Behavior, 60 (2016), 333-341
Communication
29. Assessment activities
Constructivist
Learning Design
Assessment
Learning Design
Productive
Learning Design
Socio-construct.
Learning Design
VLE Engagement
Student
Satisfaction
Student
retention
Week 1 Week 2 Week32
+
Communication & Assessment
Nguyen, Q., Rienties, B., Toetenel, L., Ferguson, R., Whitelock, D. (2017). Examining the designs of computer-based assessment and its impact on student
engagement, satisfaction, and pass rates. Computers in Human Behavior. DOI: 10.1016/j.chb.2017.03.028.
30.
31. Nguyen, Q., Rienties, B., Toetenel, L., Ferguson, R., Whitelock, D. (2017). Examining the designs of computer-based assessment and its impact on student
engagement, satisfaction, and pass rates. Computers in Human Behavior. DOI: 10.1016/j.chb.2017.03.028.
69% of what students are
doing in a week is
determined by us, teachers!
34. Rizvi, Saman; Rienties, Bart; Rogaten, Jekaterina and Kizilcec, René F. (2022). Beyond one-size-fits-all in MOOCs: Variation in learning design and persistence
of learners in different cultural and socioeconomic contexts. Computers in Human Behavior, 126, article no. 106973.
Rizvi, Saman; Rienties, Bart; Rogaten, Jekaterina and Kizilcec, René F. (2020). Investigating Variation in Learning Processes in a FutureLearn MOOC. Journal
of Computing in Higher Education pp. 162–181.
Rizvi, Saman (2022) Inclusiveness in Online Learning Designs: Geo-Cultural and Socioeconomic Perspectives. PhD Thesis, Open University UK
35. Further reflections
1. Who owns the data?
2. What about the ethics?
3. What about professional development?
4. Are we optimising the record player?
36. What we have learned in 10 years of implementing learning
analytics and learning design at the OU
Change is slow, but can be enhanced with:
1. Clear senior management support
2. Bottom-up support from teachers and researchers who are
willing to take a risk
3. Evidence-based research can gradually change perspectives
and narratives
4. You quickly forget about the small/medium/large successes
and fail to realise that you are making a real impact
5. Large-scale innovation takes substantial time and effort
6. It is all about people…
Rienties., B. (2022). Implementing learning analytics at scale in an online world: lessons learned from the Open University UK. Liebowitz, J. (Ed). Online learning analytics. Taylor & Francis.
37. @DrBartRienties
Professor of Learning Analytics
All papers referred to in this presentation can be
accessed via
https://iet.open.ac.uk/people/bart.rienties
Implementing learning analytics at
scale in an online world: lessons
learned from the Open University
UK