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Wednesday 13 April, 18:30 - 19:30 (BST) Do happier students make better learners? How much do our emotions dictate how we learn? And can we use this information to make university courses better? These are just some of the questions we’ll be exploring as part of a special talk by some of the UK's leading academics in this area. OU Technology Enhanced Learning experts are researching a concept called ‘analytics of emotions’ which means that in the future, devices like eye trackers and facial recognition software will analyse students’ emotional states when they are learning. These devices can gauge whether students are bored or frustrated by their online materials by the amount they sigh or frown. The researchers predict in their annual Innovating Pedagogy report that that within the next 10 years, the design of university courses will be driven by how students interact socially and emotionally with their materials, peers, parents and teachers. They will elaborate on what this means for higher education in their talk. In the OpenMinds talk: Are emotions driving better university courses? the following topics will be investigated: Dr Bart Rienties, Reader in Learning Analytics at the OU, will highlight the role of emotions in learning and question why they are often ignored. Dr Ana Aznar, Postdoctoral Research Fellow, School of Psychology, University of Surrey, will explore how emotions develop in children and how they influence their learning. Garron Hillaire, OU PhD student, Institute of Educational Technology will describe how his research categorises over 200 emotions related to learning. He will reveal how traces of student data are being used for emotional measurement. With these measures he will be leveraging the OU learning laboratories to validate the approach by examining physiological responses including facial muscle movement, heart rates, and galvanic skin sensors. Most importantly in the coming year these studies will expand to a University context to explore the role of emotion in Higher Education. “The concept, “analytics of emotions” means that in the future, devices like eye trackers and facial recognition software will analyse students’ emotional states when they are learning,” said Dr Rienties. “These devices will track whether students find their content boring and frustrating, all of which can be fed back into course design. Emotions play a critical role in the learning and teaching process because they impact on learners’ motivation, self-regulation and academic achievement, so it is surprising that up to now, they have been mostly ignored in learning.”
Are emotions driving better university courses?
Are emotions driving better university courses?
Bart Rienties
dfxcthsrt
Poemes sentits
Poemes sentits
PABLOERR
cvbnm
Poemasm
Poemasm
PABLOERR
@cbkandiko visiting our ABC learning gains project today @LearningGains. Exciting :-)
Affective behaviour cognition learning gains project presentation
Affective behaviour cognition learning gains project presentation
Bart Rienties
SIRIKT Keynote: Learning Analytics: The good, the bad, or perhaps ugly? The presentation will be the introduction of learning analytics, setting it in the context of big data and the increasing role of technology in learning, emphasising the role of analytics for supporting learning. Some examples will be given, and the points will be highlighted where we have the best evidence for learning analytics being helpful. The presentation will end with some suggestions – some practical, some conceptual – for how researchers and practitioners could move forward. Dr. Bart Carlo Rienties is Reader in Learning Analytics at the Institute of Educational Technology at the Open University UK. He is programme director Learning Analytics within IET and Chair of Student Experience Project Intervention and Evaluation group, which focusses on evidence-based research on intervention of 15 modules to enhance student experience. 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, Computer-Supported Collaborative Learning, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He successfully led a range of institutional/national/European projects and received several awards for his educational innovation projects.
La rienties sirikt_27_05_2015
La rienties sirikt_27_05_2015
Bart Rienties
Across the globe many institutions and organisations have high hopes that learning analytics can play a major role in helping their organisations remain fit-for-purpose, flexible, and innovative. According to Tempelaar, Rienties, and Giesbers (2015, p. 158) “a broad goal of learning analytics is to apply the outcomes of analysing data gathered by monitoring and measuring the learning process”. Learning analytics applications in education are expected to provide institutions with opportunities to support learner progression, but more importantly in the near future provide personalised, rich learning on a large scale (Rienties, Cross, & Zdrahal, 2016; Tempelaar et al., 2015; Tobarra, Robles-Gómez, Ros, Hernández, & Caminero, 2014). Increased availability of large datasets (Arbaugh, 2014), powerful analytics engines (Tobarra et al., 2014), and skilfully designed visualisations of analytics results (González-Torres, García-Peñalvo, & Therón, 2013) mean that institutions may now be able to use the experience of the past to create supportive, insightful models of primary (and even real-time) learning processes (Arnold & Pistilli, 2012; Ferguson & Buckingham Shum, 2012; Papamitsiou & Economides, 2014). Substantial progress in learning analytics research relating to identifying at-risk students has been made in the last few years using a range of advanced computational techniques (e.g., Bayesian modelling, cluster analysis, natural language processing, machine learning, predictive modelling, social network analysis). In this EARLI SIG17 keynote, I will argue that one of the largest challenges for learning analytics and wider educational research still lies ahead of us, and that one substantial and immediate challenge is how to put the power of learning analytics into the hands of researchers, teachers and administrators. While an increasing body of literature has become available regarding how institutions have experimented with small-scale interventions (Papamitsiou & Economides, 2014), to the best of our knowledge no comprehensive conceptual model, nested within a strong evidence-base, is available that describes how researchers, teachers and administrators can use learning analytics to make successful interventions in their own practice. In this keynote, I will use the development of a foundation of an Analytics4Action Evaluation Framework (A4AEF) that is being currently tested and validated at the largest university in Europe (in terms of enrolled learners), namely the UK Open University (OU, Calvert, 2014), as an example of the complexity of different, interlinked methodological and conceptual approaches.
Keynote EARLI SIG17 The power of learning analytics: a need to move towards n...
Keynote EARLI SIG17 The power of learning analytics: a need to move towards n...
Bart Rienties
Across the globe many institutions and organisations have high hopes that learning analytics can play a major role in helping their organisations remain fit-for-purpose, flexible, and innovative. Learning analytics applications in education are expected to provide institutions with opportunities to support learner progression, but more importantly in the near future provide personalised, rich learning on a large scale. In this seminar, we will discuss lessons learned from various learning analytics applications at the OU.
The power of learning analytics for UCL: lessons learned from the Open Univer...
The power of learning analytics for UCL: lessons learned from the Open Univer...
Bart Rienties
Shipyard project management need to be improved as ship's technology are improving every day. This presentation will give you an idea of the recognized project management standards that can be used on Shipbuilding and Ship Repair Projects.
Project management standards for shipyard projects
Project management standards for shipyard projects
Fernando Remolina, PMP
Recommended
Wednesday 13 April, 18:30 - 19:30 (BST) Do happier students make better learners? How much do our emotions dictate how we learn? And can we use this information to make university courses better? These are just some of the questions we’ll be exploring as part of a special talk by some of the UK's leading academics in this area. OU Technology Enhanced Learning experts are researching a concept called ‘analytics of emotions’ which means that in the future, devices like eye trackers and facial recognition software will analyse students’ emotional states when they are learning. These devices can gauge whether students are bored or frustrated by their online materials by the amount they sigh or frown. The researchers predict in their annual Innovating Pedagogy report that that within the next 10 years, the design of university courses will be driven by how students interact socially and emotionally with their materials, peers, parents and teachers. They will elaborate on what this means for higher education in their talk. In the OpenMinds talk: Are emotions driving better university courses? the following topics will be investigated: Dr Bart Rienties, Reader in Learning Analytics at the OU, will highlight the role of emotions in learning and question why they are often ignored. Dr Ana Aznar, Postdoctoral Research Fellow, School of Psychology, University of Surrey, will explore how emotions develop in children and how they influence their learning. Garron Hillaire, OU PhD student, Institute of Educational Technology will describe how his research categorises over 200 emotions related to learning. He will reveal how traces of student data are being used for emotional measurement. With these measures he will be leveraging the OU learning laboratories to validate the approach by examining physiological responses including facial muscle movement, heart rates, and galvanic skin sensors. Most importantly in the coming year these studies will expand to a University context to explore the role of emotion in Higher Education. “The concept, “analytics of emotions” means that in the future, devices like eye trackers and facial recognition software will analyse students’ emotional states when they are learning,” said Dr Rienties. “These devices will track whether students find their content boring and frustrating, all of which can be fed back into course design. Emotions play a critical role in the learning and teaching process because they impact on learners’ motivation, self-regulation and academic achievement, so it is surprising that up to now, they have been mostly ignored in learning.”
Are emotions driving better university courses?
Are emotions driving better university courses?
Bart Rienties
dfxcthsrt
Poemes sentits
Poemes sentits
PABLOERR
cvbnm
Poemasm
Poemasm
PABLOERR
@cbkandiko visiting our ABC learning gains project today @LearningGains. Exciting :-)
Affective behaviour cognition learning gains project presentation
Affective behaviour cognition learning gains project presentation
Bart Rienties
SIRIKT Keynote: Learning Analytics: The good, the bad, or perhaps ugly? The presentation will be the introduction of learning analytics, setting it in the context of big data and the increasing role of technology in learning, emphasising the role of analytics for supporting learning. Some examples will be given, and the points will be highlighted where we have the best evidence for learning analytics being helpful. The presentation will end with some suggestions – some practical, some conceptual – for how researchers and practitioners could move forward. Dr. Bart Carlo Rienties is Reader in Learning Analytics at the Institute of Educational Technology at the Open University UK. He is programme director Learning Analytics within IET and Chair of Student Experience Project Intervention and Evaluation group, which focusses on evidence-based research on intervention of 15 modules to enhance student experience. 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, Computer-Supported Collaborative Learning, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He successfully led a range of institutional/national/European projects and received several awards for his educational innovation projects.
La rienties sirikt_27_05_2015
La rienties sirikt_27_05_2015
Bart Rienties
Across the globe many institutions and organisations have high hopes that learning analytics can play a major role in helping their organisations remain fit-for-purpose, flexible, and innovative. According to Tempelaar, Rienties, and Giesbers (2015, p. 158) “a broad goal of learning analytics is to apply the outcomes of analysing data gathered by monitoring and measuring the learning process”. Learning analytics applications in education are expected to provide institutions with opportunities to support learner progression, but more importantly in the near future provide personalised, rich learning on a large scale (Rienties, Cross, & Zdrahal, 2016; Tempelaar et al., 2015; Tobarra, Robles-Gómez, Ros, Hernández, & Caminero, 2014). Increased availability of large datasets (Arbaugh, 2014), powerful analytics engines (Tobarra et al., 2014), and skilfully designed visualisations of analytics results (González-Torres, García-Peñalvo, & Therón, 2013) mean that institutions may now be able to use the experience of the past to create supportive, insightful models of primary (and even real-time) learning processes (Arnold & Pistilli, 2012; Ferguson & Buckingham Shum, 2012; Papamitsiou & Economides, 2014). Substantial progress in learning analytics research relating to identifying at-risk students has been made in the last few years using a range of advanced computational techniques (e.g., Bayesian modelling, cluster analysis, natural language processing, machine learning, predictive modelling, social network analysis). In this EARLI SIG17 keynote, I will argue that one of the largest challenges for learning analytics and wider educational research still lies ahead of us, and that one substantial and immediate challenge is how to put the power of learning analytics into the hands of researchers, teachers and administrators. While an increasing body of literature has become available regarding how institutions have experimented with small-scale interventions (Papamitsiou & Economides, 2014), to the best of our knowledge no comprehensive conceptual model, nested within a strong evidence-base, is available that describes how researchers, teachers and administrators can use learning analytics to make successful interventions in their own practice. In this keynote, I will use the development of a foundation of an Analytics4Action Evaluation Framework (A4AEF) that is being currently tested and validated at the largest university in Europe (in terms of enrolled learners), namely the UK Open University (OU, Calvert, 2014), as an example of the complexity of different, interlinked methodological and conceptual approaches.
Keynote EARLI SIG17 The power of learning analytics: a need to move towards n...
Keynote EARLI SIG17 The power of learning analytics: a need to move towards n...
Bart Rienties
Across the globe many institutions and organisations have high hopes that learning analytics can play a major role in helping their organisations remain fit-for-purpose, flexible, and innovative. Learning analytics applications in education are expected to provide institutions with opportunities to support learner progression, but more importantly in the near future provide personalised, rich learning on a large scale. In this seminar, we will discuss lessons learned from various learning analytics applications at the OU.
The power of learning analytics for UCL: lessons learned from the Open Univer...
The power of learning analytics for UCL: lessons learned from the Open Univer...
Bart Rienties
Shipyard project management need to be improved as ship's technology are improving every day. This presentation will give you an idea of the recognized project management standards that can be used on Shipbuilding and Ship Repair Projects.
Project management standards for shipyard projects
Project management standards for shipyard projects
Fernando Remolina, PMP
Pedagogically informed designs of learning are increasingly of interest to researchers in blended and online learning, as learning design is shown to have an impact on student behaviour and outcomes. Although learning design is widely studied, often these studies are individual courses or programmes and few empirical studies have connected learning designs of a substantial number of courses with learning behaviour. In this study we linked 151 modules and 111.256 students with students' behaviour (<400 million minutes of online behaviour), satisfaction and performance at the Open University UK using multiple regression models. Our findings strongly indicate the importance of learning design in predicting and understanding Virtual Learning Environment behaviour and performance of students in blended and online environments. In line with proponents of social learning theories, our primary predictor for academic retention was the time learners spent on communication activities, controlling for various institutional and disciplinary factors. Where possible, appropriate and well designed communication tasks that align with the learning objectives of the course may be a way forward to enhance academic retention.
Global experiences with e-learning and data
Global experiences with e-learning and data
Bart Rienties
A special thanks to Avinash Boroowa, Simon Cross, Lee Farrington-Flint, Christothea Herodotou, Lynda Prescott, Kevin Mayles, Tom Olney, Lisette Toetenel, John Woodthorpe and others…A special thanks to Prof Belinda Tynan for her continuous support on analytics at the OU UK
Keynote H818 The Power of (In)formal learning: a learning analytics approach
Keynote H818 The Power of (In)formal learning: a learning analytics approach
Bart Rienties
Bart Rienties is a Reader in Learning Analytics at the Institute of Educational Technology at the Open University UK. He is programme director Learning Analytics within IET and Chair of Analytics4Action project, which focuses on evidence-based research on interventions on OU modules to enhance student experience. 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, Computer-Supported Collaborative Learning, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He successfully led a range of institutional/national/European projects and received several awards for his educational innovation projects.
Keynote address Analytics4Action Evaluation Framework: a review of evidence-...
Keynote address Analytics4Action Evaluation Framework: a review of evidence-...
Bart Rienties
Media Studies
Codes and conventions
Codes and conventions
imanzoqi
Media Studies
Pakistani Fashion Through The Decades
Pakistani Fashion Through The Decades
imanzoqi
Learning gains has increasingly become apparent within the HE literature, gained traction in government policies in the UK, and are at the heart of Teaching Excellence Framework (TFL). As such, this raises a question to what extent teaching and learning environment can actually predict students’ learning gains using principles of learning analytics. In this presentation, which is joined work with University of Surrey and Oxford Brookes, I will focus on some preliminary findings based upon developing and testing an Affective-Behaviour-Cognition learning gains model using longitudinal approach. The main aim of the research is to examine whether learning gains occur on all three levels of Affective-Behaviour-Cognition model and whether any particular student or course characteristics can predict learning gains or lack of learning and dropout. For more info, see https://abclearninggains.com/
The power of learning analytics to measure learning gains: an OU, Surrey and ...
The power of learning analytics to measure learning gains: an OU, Surrey and ...
Bart Rienties
8th UK Learning Analytics Network Meeting, The Open University, 2nd November 2016 1) The power of 151 Learning Designs on 113K+ students at the OU? 2) How can we use learning design to empower teachers? 3) How can Early Alert Systems improve Student Engagement and Academic Success? (Amara Atif, Macquarie University) 4) What evidence is there that learning design makes a difference over time and how students engage?
Learning design meets learning analytics: Dr Bart Rienties, Open University
Learning design meets learning analytics: Dr Bart Rienties, Open University
Bart Rienties
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Pedagogically informed designs of learning are increasingly of interest to researchers in blended and online learning, as learning design is shown to have an impact on student behaviour and outcomes. Although learning design is widely studied, often these studies are individual courses or programmes and few empirical studies have connected learning designs of a substantial number of courses with learning behaviour. In this study we linked 151 modules and 111.256 students with students' behaviour (<400 million minutes of online behaviour), satisfaction and performance at the Open University UK using multiple regression models. Our findings strongly indicate the importance of learning design in predicting and understanding Virtual Learning Environment behaviour and performance of students in blended and online environments. In line with proponents of social learning theories, our primary predictor for academic retention was the time learners spent on communication activities, controlling for various institutional and disciplinary factors. Where possible, appropriate and well designed communication tasks that align with the learning objectives of the course may be a way forward to enhance academic retention.
Global experiences with e-learning and data
Global experiences with e-learning and data
Bart Rienties
A special thanks to Avinash Boroowa, Simon Cross, Lee Farrington-Flint, Christothea Herodotou, Lynda Prescott, Kevin Mayles, Tom Olney, Lisette Toetenel, John Woodthorpe and others…A special thanks to Prof Belinda Tynan for her continuous support on analytics at the OU UK
Keynote H818 The Power of (In)formal learning: a learning analytics approach
Keynote H818 The Power of (In)formal learning: a learning analytics approach
Bart Rienties
Bart Rienties is a Reader in Learning Analytics at the Institute of Educational Technology at the Open University UK. He is programme director Learning Analytics within IET and Chair of Analytics4Action project, which focuses on evidence-based research on interventions on OU modules to enhance student experience. 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, Computer-Supported Collaborative Learning, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He successfully led a range of institutional/national/European projects and received several awards for his educational innovation projects.
Keynote address Analytics4Action Evaluation Framework: a review of evidence-...
Keynote address Analytics4Action Evaluation Framework: a review of evidence-...
Bart Rienties
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Codes and conventions
Codes and conventions
imanzoqi
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Pakistani Fashion Through The Decades
Pakistani Fashion Through The Decades
imanzoqi
Learning gains has increasingly become apparent within the HE literature, gained traction in government policies in the UK, and are at the heart of Teaching Excellence Framework (TFL). As such, this raises a question to what extent teaching and learning environment can actually predict students’ learning gains using principles of learning analytics. In this presentation, which is joined work with University of Surrey and Oxford Brookes, I will focus on some preliminary findings based upon developing and testing an Affective-Behaviour-Cognition learning gains model using longitudinal approach. The main aim of the research is to examine whether learning gains occur on all three levels of Affective-Behaviour-Cognition model and whether any particular student or course characteristics can predict learning gains or lack of learning and dropout. For more info, see https://abclearninggains.com/
The power of learning analytics to measure learning gains: an OU, Surrey and ...
The power of learning analytics to measure learning gains: an OU, Surrey and ...
Bart Rienties
8th UK Learning Analytics Network Meeting, The Open University, 2nd November 2016 1) The power of 151 Learning Designs on 113K+ students at the OU? 2) How can we use learning design to empower teachers? 3) How can Early Alert Systems improve Student Engagement and Academic Success? (Amara Atif, Macquarie University) 4) What evidence is there that learning design makes a difference over time and how students engage?
Learning design meets learning analytics: Dr Bart Rienties, Open University
Learning design meets learning analytics: Dr Bart Rienties, Open University
Bart Rienties
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Global experiences with e-learning and data
Keynote H818 The Power of (In)formal learning: a learning analytics approach
Keynote H818 The Power of (In)formal learning: a learning analytics approach
Keynote address Analytics4Action Evaluation Framework: a review of evidence-...
Keynote address Analytics4Action Evaluation Framework: a review of evidence-...
Codes and conventions
Codes and conventions
Pakistani Fashion Through The Decades
Pakistani Fashion Through The Decades
The power of learning analytics to measure learning gains: an OU, Surrey and ...
The power of learning analytics to measure learning gains: an OU, Surrey and ...
Learning design meets learning analytics: Dr Bart Rienties, Open University
Learning design meets learning analytics: Dr Bart Rienties, Open University
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