Keynote FutureEDtech: Leveraging the full value of learning analytics: How to gain the most ROI both for student support and as a deployment within the VLE environment
Keynote FutureEDtech: Leveraging the full value of learning analytics: How to gain the most ROI both for student support and as a deployment within the VLE
environment
Discussant SRHE Symposium "A cross-institutional perspective on merits and ch...Bart Rienties
In the UK, the introduction of the Teaching Excellence Framework (TEF) has increased interest in
appropriate and valid measurement approaches of learning gains in Higher Education. Learning gains
are defined as growth or change in knowledge, skills, and abilities of learners over time. While the UK
government and other organisations like HEFCE expect tremendous opportunities for learning gains
to “objectively” measure the value added of higher education across institutions, empirical evidence of
the robustness, reliability, and validity of learning gains literature outside the UK is mixed. At SRHE,
we will discuss the affordances, lived experiences, and limitations of using different measurements,
conceptualisations, and methodologies of learning gains. We aim to set an evidence-based agenda of
how HEIs can effectively start to measure and implement notions of learning gains, while at the same
time discussing potential limitations and caveats.
www.abclearninggains.com @learninggains
SRHE2016: Multilevel Modelling of Learning Gains: The Impact of Module Partic...Bart Rienties
Jekaterina Rogaten1
, Bart Rienties1
, Denise Whitelock1
, Simon Cross1
, Allison Littlejohn1
, Rhona
Sharpe2
, Simon Lygo-Baker3
, Ian Scott2
, Steven Warburton3
, Ian Kinchin3
1The Open University UK, UK,
2Oxford Brooks University, UK,
3University of Surrey, UK
Research Domain: Learning, teaching and assessment (LTA)
In the UK, the introduction of the Teaching Excellence Framework (TEF) has increased interest in
appropriate and valid measurement approaches of learning gains in Higher Education. Usually
learning gains are measured using pre-post testing, but this study examines whether academic
performance can be effectively used as proxy to estimate students’ learning progress. Academic
performance of 21,192 online learners from two major faculties was retrieved from university
database. A three-level growth-curve model was estimated and results showed that 16% to 46% of
variance in students’ initial academic performance, and 51% to 77% of variance in their subsequent
learning gains was due to them studying at a particular module. In addition, the results illustrate that
students who studied in modules with initial high student achievements exhibited lower learning gains
than students learning in modules with low initial student achievements. The importance of
assessment and learning design for learning gains are outlined.
www.abclearninggains.com @learninggains
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
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.
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).
Discussant SRHE Symposium "A cross-institutional perspective on merits and ch...Bart Rienties
In the UK, the introduction of the Teaching Excellence Framework (TEF) has increased interest in
appropriate and valid measurement approaches of learning gains in Higher Education. Learning gains
are defined as growth or change in knowledge, skills, and abilities of learners over time. While the UK
government and other organisations like HEFCE expect tremendous opportunities for learning gains
to “objectively” measure the value added of higher education across institutions, empirical evidence of
the robustness, reliability, and validity of learning gains literature outside the UK is mixed. At SRHE,
we will discuss the affordances, lived experiences, and limitations of using different measurements,
conceptualisations, and methodologies of learning gains. We aim to set an evidence-based agenda of
how HEIs can effectively start to measure and implement notions of learning gains, while at the same
time discussing potential limitations and caveats.
www.abclearninggains.com @learninggains
SRHE2016: Multilevel Modelling of Learning Gains: The Impact of Module Partic...Bart Rienties
Jekaterina Rogaten1
, Bart Rienties1
, Denise Whitelock1
, Simon Cross1
, Allison Littlejohn1
, Rhona
Sharpe2
, Simon Lygo-Baker3
, Ian Scott2
, Steven Warburton3
, Ian Kinchin3
1The Open University UK, UK,
2Oxford Brooks University, UK,
3University of Surrey, UK
Research Domain: Learning, teaching and assessment (LTA)
In the UK, the introduction of the Teaching Excellence Framework (TEF) has increased interest in
appropriate and valid measurement approaches of learning gains in Higher Education. Usually
learning gains are measured using pre-post testing, but this study examines whether academic
performance can be effectively used as proxy to estimate students’ learning progress. Academic
performance of 21,192 online learners from two major faculties was retrieved from university
database. A three-level growth-curve model was estimated and results showed that 16% to 46% of
variance in students’ initial academic performance, and 51% to 77% of variance in their subsequent
learning gains was due to them studying at a particular module. In addition, the results illustrate that
students who studied in modules with initial high student achievements exhibited lower learning gains
than students learning in modules with low initial student achievements. The importance of
assessment and learning design for learning gains are outlined.
www.abclearninggains.com @learninggains
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
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.
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).
SAAIR: Implementing learning analytics at scale in an online world: lessons l...Bart Rienties
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
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
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.
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
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
Learning analytics adoption in Higher Education: Reviewing six years of exper...Bart Rienties
In this webinar, Prof Bart Rienties will reflect on the process of implementing learning analytics solutions within the UK higher education setting, its implications, and the key lessons learned in the process. The talk will specifically focus on the Open University UK (OU) experience of implementing learning analytics to support its 170k students and 5k staff. Its flagship OU Analyse has been hailed as one of the largest applications of predictive learning analytics at scale for the last five years, making OU one of the leading institutions in learning analytics domain. The talk will reflect on the strong connections between research and practice, educational theory and learning design, scholarship and professional development, and working in multi-disciplinary teams to explain why the OU is at the forefront of implementing learning analytics at scale. At the same time, not all innovations and interventions have worked. During this webinar, Prof Rienties will discuss the lessons learned from implementing learning analytics systems, how learning analytics has been adopted at OU and other UK institutions, and what the implications for higher education might be.
«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»
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
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
Bart Rienties, Parvati Raghuram, Markus Breines
With the rise of technology and distance learning, a new type of internationalisation of higher education seems to be emerging in Southern Africa higher education, which we coin as Internationalisation at a Distance. We aim to provide an initial attempt to theorise the concept of Internationalisation at a Distance through an in-depth analysis of 1295 students’ experiences while studying at the largest distance learning institution in Africa. Our regression models indicated that academic adjustment is significantly predicted by emotional adjustment, attachment towards the institution, access to technology, and internationalisation at home students. These results indicate the need for a much more complex narrative around internationalisation.
http://ideaspartnership.org/
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)
-Move towards centralised LA data infrastructure
-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)
-Maina Korir: Ethics and LA (IET)
-Anna Gillespie: Predictive Learning Analytics and role of tutors (EdD)
Prof John Domingue (Knowledge Media Institute) & Dr Thea Herodotou (IET)
-What have we learned from 5 years of large scale implementation of OU Analyse?
-Where is LA/AI going?
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
SAAIR: Implementing learning analytics at scale in an online world: lessons l...Bart Rienties
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
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
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.
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
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
Learning analytics adoption in Higher Education: Reviewing six years of exper...Bart Rienties
In this webinar, Prof Bart Rienties will reflect on the process of implementing learning analytics solutions within the UK higher education setting, its implications, and the key lessons learned in the process. The talk will specifically focus on the Open University UK (OU) experience of implementing learning analytics to support its 170k students and 5k staff. Its flagship OU Analyse has been hailed as one of the largest applications of predictive learning analytics at scale for the last five years, making OU one of the leading institutions in learning analytics domain. The talk will reflect on the strong connections between research and practice, educational theory and learning design, scholarship and professional development, and working in multi-disciplinary teams to explain why the OU is at the forefront of implementing learning analytics at scale. At the same time, not all innovations and interventions have worked. During this webinar, Prof Rienties will discuss the lessons learned from implementing learning analytics systems, how learning analytics has been adopted at OU and other UK institutions, and what the implications for higher education might be.
«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»
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
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
Bart Rienties, Parvati Raghuram, Markus Breines
With the rise of technology and distance learning, a new type of internationalisation of higher education seems to be emerging in Southern Africa higher education, which we coin as Internationalisation at a Distance. We aim to provide an initial attempt to theorise the concept of Internationalisation at a Distance through an in-depth analysis of 1295 students’ experiences while studying at the largest distance learning institution in Africa. Our regression models indicated that academic adjustment is significantly predicted by emotional adjustment, attachment towards the institution, access to technology, and internationalisation at home students. These results indicate the need for a much more complex narrative around internationalisation.
http://ideaspartnership.org/
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)
-Move towards centralised LA data infrastructure
-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)
-Maina Korir: Ethics and LA (IET)
-Anna Gillespie: Predictive Learning Analytics and role of tutors (EdD)
Prof John Domingue (Knowledge Media Institute) & Dr Thea Herodotou (IET)
-What have we learned from 5 years of large scale implementation of OU Analyse?
-Where is LA/AI going?
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Introduction to AI for Nonprofits with Tapp Network
Keynote FutureEDtech: Leveraging the full value of learning analytics: How to gain the most ROI both for student support and as a deployment within the VLE environment
1. Leveraging the full value of
learning analytics: How to gain
the most ROI both for student
support and as a deployment
within the VLE
environment
@DrBartRienties
Reader in Learning Analytics
3rd of June 2015
London
3. (Social) Learning Analytics
“LA is the measurement, collection, analysis and reporting of data about learners
and their contexts, for purposes of understanding and optimising learning and the
environments in which it occurs” (LAK 2011)
Social LA “focuses on how learners build knowledge together in their cultural
and social settings” (Ferguson & Buckingham Shum, 2012)
4.
5. 1. What evidence is there that analytics actually helps learners
to reach their potential?
2. How does the Open University UK use analytics to provide
support for students and teachers?
3. How to gain the most ROI both for student support and as a
deployment within the VLE
7. B) Linking learning design 150+ modules
with learning analytics
A) How does the OU use LA? OU Analyse
C) How do students choose
collaboration tools?
D Learning analytics with
120+ variables
8. Q2 Learning Analytics at OU: OU
Analyse
• 15+ modules, 20K+ students
• 4 different analytics approaches
• Based upon Moodle/SAS data
warehouse
• Developed in house by Knowledge
Media Institute (Prof Zdrahal)
9. Important VLE activities
XXX1: Forum (F), Subpage (S), Resource
(R), OU_content (O), No activity (N)
Possible activities each week are: F, FS, N,
O, OF, OFS, OR, ORF, ORFS, ORS, OS, R,
RF, RFS, RS, S
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
10. Start
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
Pass Fail No submit TMA-1time
VLE opens
Start
Activity space
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
11. FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
Start
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
Pass Fail No submit TMA-1time
VLE opens
Start
VLE trail: successful
student
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
12. FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
Start
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
FSF RFSOFS ORFN O SRFROF OR ORSORFS OS RS
Pass Fail No submit TMA-1time
VLE opens
Start
VLE trail: student who
did not submit
16. Four predictive models
1. Case-based reasoning (reasoning from
precedents, k-Nearest Neighbours)
A. Based on demographic data
B. Based on VLE activities
2. Classification and Regression Trees (CART)
3. Bayes networks (naïve and full)
4. Final verdict decided by voting
17. Try the demo version yourself!
URL: http://analyse.kmi.open.ac.uk
Select Dashboard in the horizontal bar on top of the screen.
Username: demo, Password: demo
This fully anonymised version does not use data of any existing OU
module. Consequently, the STUDENT’S ACTIVITY RECOMMENDER (see
the Student view) referring to the module material could not be
included.
21. Q2/Q3 Learning analytics on meso
• 157+ modules, 60K+ students
• Learning design linked to
a. Student experience
b. Learning behaviour
c. Learning performance
22.
23.
24.
25. Method – data sets
• Combination of two different data sets:
• learning design data (157 modules)
• student feedback data (51)
• VLE data (42 modules)
• Academic Performance (51)
• Data sets merged and cleaned
• 29537 students undertook these modules
26. Method – LD process
• Mapping of modules to create learning
design data by OU’s LD specialists
• Importance of consistency in mapping
process; validated in team and by Faculty
• Use of seven activity categories, derived
from five year study across eight HE
institutions
27.
28.
29.
30. Assimilative Finding and
handling
information
Communicati
on
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
41. M SD
1
Assimilative
2
Finding
info
3
Communication
4
Productive
5
Experiential
6
Interactive
7
Assessment total
9 Overall I am satisfied with the quality
of the course 81.29 14.51 .253 -.259 -.315* -.11 .018 .135 -.034 .002
10 Overall I am satisfied with my study
experience 80.52 13.20 .303* -.336* -.333* -.082 -.208 .137 .039 -.069
11 The module provided good value for
money 66.86 16.28 .312* -.345* -.420** -.163 -.035 .197 .025 -.05
12 I was satisfied with the support
provided by my tutor on this module 83.42 13.10 .230 -.231 -.263 -.049 -.051 .189 -.065 -.1
13 Overall I am satisfied with the
teaching materials on this module 78.52 15.51 .291* -.257 -.323* -.091 -.134 .16 -.021 -.063
14 Overall I was able to keep up with
the workload on this module 78.75 11.75 .182 -0.259 -.337* -.006 -.274 .012 .166 -.479**
15 The learning outcomes of this
module were clearly stated 89.09 7.01 .287* -.350* -.292* -.211 -.156 .206 .104 -.037
16 I would recommend this module to
other students 74.30 16.15 .204 -.285* -.310* -.086 -.065 .163 .052 -.036
17 The module met my expectations 74.26 14.44 .267 -.311* -.381** -.049 -.148 .152 .032 -.041
18 I enjoyed studying this module 75.40 15.49 .212 -.233 -.239 -.068 -.1 .207 -.017 .016
19 Average learning experience 77.53 13.34 .277* -.308* -.346* -.106 -.103 .177 .017 -.036
20 Average Support and workload 81.09 9.22 .277* -.327* -.399** -.038 -.211 .139 .061 -.377**
47. Dynamic interaction of sychronous and
asychronous learning
Giesbers, B., Rienties, B., Tempelaar, D.T., & Gijselaers, W. H. (2014). A dynamic analysis of the interplay between asynchronous and synchronous
communication in online learning: The impact of motivation. Journal of Computer Assisted Learning, 30(1), 30-50. Impact factor: 1.632.
48. Intrinsic Motivation ↑ initial asynchronous contributions
↑ in asynchronous and synchronous contributions
Giesbers, B., Rienties, B., Tempelaar, D.T., & Gijselaers, W. H. (2014). A dynamic analysis of the interplay between asynchronous and synchronous
communication in online learning: The impact of motivation. Journal of Computer Assisted Learning, 30(1), 30-50. Impact factor: 1.632.
49. Introduction math/stats
• Business
• 1st year students
• Blended
• 0-12 weeks after start studying
• Adaptive learning/Problem-Based
Learning
• N=990
50.
51. Diagnostic
EntryTests
Week 0 Week 1 Week 2 Week 3 Week 4 Week 6Week 5
Quiz 1 Quiz 2 Quiz 3
Final
Exam
• Math-
Exam
• Stats-
Exam
--------------------------------------------- BlackBoard LMS behaviour -----------------------------------------
Week 7
Mastery scores
MyMathlab
Mastery scores
Practice time #
Attempts
Practice time
# Attempts
Mastery scores
Practice time
# Attempts
Mastery scores
Practice time
# Attempts
Mastery scores
Practice time
# Attempts
Mastery scores
Practice time
# Attempts
Mastery scores
MyMathlab
Practice time #
Attempts
Mastery scores
MyStatlab
Mastery scores
Practice time #
Attempts
Practice time
# Attempts
Mastery scores
Practice time
# Attempts
Mastery scores
Practice time
# Attempts
Mastery scores
Practice time
# Attempts
Mastery scores
Practice time
# Attempts
Mastery scores
MyStatlab
Practice time
# Attempts
Demogra-
phic data
QMTotal
Week 8
Learning Styles,
Motivation,
Engagement
Learning
Emotions
-Learning dispositions ------------------ ------------------------------------------------------------------
Tempelaar, D., Rienties, B., Giesbers., B. (2015). In search for the most informative data for feedback generation: Learning Analytics in a data-rich context. Computers in
Human Behaviour. Impact factor: 2.067.
57. Using track data we can follow:
-who is struggling?
-where?
-when?
-why?
58.
59. Who is struggling in week 3?
What can be done about this?
• (Personalised) feedback
• (Personalised) examples
• Peer support
• Emotional/learning support
60. Implications for EURO CALL1. What evidence is there that analytics
actually helps learners to reach their
potential?
• http://evidence.laceproject.eu/
2. How does the Open University UK use
analytics to provide support for
students and teachers?
• OU Analyse
• Information Office Model
• Predictive Z-score
• Analytics4Action
61. Implications for EURO CALL3. How to gain the most ROI both for
student support and as a deployment
within the VLE
• Focus on “real” indicators for (non)
learning
• Invest in visualisations for students
(rather than teachers)
• Focus on action rather than prediction
62. Leveraging the full value of
learning analytics: How to gain
the most ROI both for student
support and as a deployment
within the VLE
environment
@DrBartRienties
Reader in Learning Analytics
3rd of June 2015
London
Editor's Notes
5131 students responded – 28%, between 18-76%
Learning Design Team has mapped 100+ modules
For each module, the learning design team together with module chairs create activity charts of what kind of activities students are expected to do in a week.
For each module, detailed information is available about the design philosophy, support materials, etc.
Explain seven categories
This came as a surprise as LD is implemented as a unique, creative process.
Cluster analysis of 40 modules (>19k students) indicate that module teams design four different types of modules: constructivist, assessment driven, balanced, or socio-constructivist. The LAK paper by Rienties and colleagues indicates that VLE engagement is higher in modules with socio-constructivist or balanced variety learning designs, and lower for constructivist designs. In terms of learning outcomes, students rate constructivist modules higher, and socio-constructivist modules lower. However, in terms of student retention (% of students passed) constructivist modules have lower retention, while socio-constructivist have higher. Thus, learning design strongly influences behaviour, experience and performance. (and we believe we are the first to have mapped this with such a large cohort).
Cluster analysis of 40 modules (>19k students) indicate that module teams design four different types of modules: constructivist, assessment driven, balanced, or socio-constructivist. The LAK paper by Rienties and colleagues indicates that VLE engagement is higher in modules with socio-constructivist or balanced variety learning designs, and lower for constructivist designs. In terms of learning outcomes, students rate constructivist modules higher, and socio-constructivist modules lower. However, in terms of student retention (% of students passed) constructivist modules have lower retention, while socio-constructivist have higher. Thus, learning design strongly influences behaviour, experience and performance. (and we believe we are the first to have mapped this with such a large cohort).
We have been customising data for various audiences such as VCE. This has been a year of change in this area, but we are timetabling key events looking forward so that this is all becoming more routine...
We have been customising data for various audiences such as VCE. This has been a year of change in this area, but we are timetabling key events looking forward so that this is all becoming more routine...