From procrastination to engagement? An experimental exploration of the effects of an adaptive virtual assistant on self-regulation in online learning

Compared to traditional classroom learning, success in online learning tends to depend more on the learner’s skill to self-regulate. Self-regulation is a complex meta-cognitive skill set that can be acquired. This study explores the effectiveness of a virtual learning assistant in terms of (a) developmental, (b) general compensatory, and (c) differential compensatory effects on learners’ self-regulatory skills in a sample of N = 157 online learners using an experimental intervention-control group design. Methods employed include behavioural trace data as well as self-reporting measures. Participants provided demographic information and responded to a 24-item self-regulation questionnaire and a 20-item personality trait questionnaire. Results indicate that the adaptive assistance did not lead to substantial developmental shifts as captured in learners’ perceived levels of self-regulation. However, various patterns of behavioural changes emerged in response to the intervention. This suggests that the virtual learning assistant has the potential to help online learners effectively compensate for deficits (in contrast to developmental shifts) in self-regulatory skills that might not yet have been developed

Assessment, development and experimental evaluation of self-regulatory support in online learning

Online learning requires a higher level of self-regulation than face-to-face learning. Learners are likely to differ in their cognitive, metacognitive, affective or motivational resources to meet this demand. Individual differences in self-regulation is one major factor contributing to success or failure in online learning, other factors include characteristics of the online learning environment and the complexity of the learning content itself. Lack of self-regulation is likely to affect learners’ engagement with the course content, may result in sub-optimal learning outcomes, including failure to complete the course. A virtual learning assistant has been designed and developed to support online learners. This research aims at ascertaining the effectiveness of providing adaptive assistance in terms of (a) compensatory and (b) developmental effects. Online learners involved in the empirical part of this study (N = 157) were randomised into one of two experimental conditions. For the intervention group, the online learning assistant provided personalised in-browser notifications. This feature was disabled for the learners in the control condition. Results indicate that the adaptive assistance did not result in noticeable developmental shifts in learners’ self-regulation as assessed via conventional self-report measures. However, learners allocated to the intervention group spent less time online per day in first three weeks of being exposed to the adaptive assistance, reduced their time commitment to entertainment websites during first two weeks, and increased their engagement with educational web resources during the first ten days. In addition to the time-varying effects, these compensatory (behavioural) shifts were moderated by learners’ individual differences in personality. The outcome of this study suggests that the utilisation of a virtual learning assistant that provides adaptive assistance can be effective in compensating for not yet developed self-regulatory skills, and subsequently help facilitating success in learning on short online courses

Chrome Plug-in to Support SRL in MOOCs

Proceeding of: 6th European MOOCs Stakeholders Summit, EMOOCs 2019 Naples, Italy, May 20–22, 2019.Massive Open Online Courses (MOOCs) have gained popularity over the last years, offering a learning environment with new opportunities and challenges. These courses attract a heterogeneous set of participants who, due to the impossibility of personal tutorship in MOOCs, are required to create their own learning path and manage one’s own learning to achieve their goals. In other words, they should be able to self-regulate their learning. Self-regulated learning (SRL) has been widely explored in settings such as face-to-face or blended learning environments. Nevertheless, research on SRL in MOOCs is still scarce, especially on supporting interventions. In this sense, this document presents MOOCnager, a Chrome plug-in to help learners improve their SRL skills. Specifically, this work focuses on 3 areas: goal setting, time management and selfevaluation. Each area is included in one of the 3 phases composing Zimmerman’s SRL Cyclical Model. In this way, the plug-in aims to support enrolees’ self-regulation throughout their complete learning process. Finally, MOOCnager was uploaded to the Chrome Web Store, in order to get a preliminary evaluation with real participants from 6 edX Java MOOCs designed by the Universidad Carlos III de Madrid (UC3M). Results were not conclusive as the use of the plug-in by the participants was very low. However, learners seem to prefer a seamless tool, integrated in the MOOC platform, which is able to assist them without any learner-tool interaction.The authors acknowledge the eMadrid Network, funded by the Madrid Regional Government (Comunidad de Madrid) with grant No. P2018/TCS-4307. This work also received partial support from the Spanish Ministry of Economy and Competitiveness/Ministry of Science, Innovation, and Universities, Projects RESET (TIN2014-53199-C3-1-R) and Smartlet (TIN2017- 85179-C3-1-R), and from the European Commission through Erasmus+ projects COMPETENSEA (574212-EPP-1-2016-1-NL-EPPKA2-CBHE-JP), LALA (586120-EPP-1-2017-1-ESEPPKA2- CBHE-JP), and InnovaT (598758-EPP-1-2018-1-AT-EPPKA2-CBHE-JP).Publicad

Delving into instructor‐led feedback interventions informed by learning analytics in massive open online courses

Producción CientíficaBackground:Providing feedback in massive open online courses (MOOCs) is chal-lenging due to the massiveness and heterogeneity of learners' population. Learninganalytics (LA) solutions aim at scaling up feedback interventions and supportinginstructors in this endeavour.Paper Objectives:This paper focuses on instructor-led feedback mediated by LAtools in MOOCs. Our goal is to answer how, to what extent data-driven feedback isprovided to learners, and what its impact is.Methods:We conducted a systematic literature review on the state-of-the-art LA-informed instructor-led feedback in MOOCs. From a pool of 227 publications, weselected 38 articles that address the topic of LA-informed feedback in MOOCs medi-ated by instructors. We applied etic content analysis to the collected data.Results and Conclusions:The results revealed a lack of empirical studies exploring LA todeliver feedback, and limited attention on pedagogy to inform feedback practices. Our find-ings suggest the need for systematization and evaluation of feedback. Additionally, there isa need for conceptual tools to guide instructors' in the design of LA-based feedback.Takeaways:We point out the need for systematization and evaluation of feedback. Weenvision that this research can support the design of LA-based feedback, thus contribut-ing to bridge the gap between pedagogy and data-driven practice in MOOCs.Consejo de Investigación de Estonia (PSG286)Ministerio de Ciencia e Innovación - Fondo Europeo de Desarrollo Regional y la Agencia Nacional de Investigación (grant PID2020-112584RB-C32) and (grant TIN2017-85179-C3-2-R)Junta de Castilla y León - Fondo Social Europeo y el Consejo Regional de Educación (grant E-47-2018-0108488

Open World Learning

This book provides state-of-the-art contemporary research insights into key applications and processes in open world learning. Open world learning seeks to understand access to education, structures, and the presence of dialogue and support systems. It explores how the application of open world and educational technologies can be used to create opportunities for open and high-quality education. Presenting ground-breaking research from an award winning Leverhulme doctoral training programme, the book provides several integrated and cohesive perspectives of the affordances and limitations of open world learning. The chapters feature a wide range of open world learning topics, ranging from theoretical and methodological discussions to empirical demonstrations of how open world learning can be effectively implemented, evaluated, and used to inform theory and practice. The book brings together a range of innovative uses of technology and practice in open world learning from 387,134 learners and educators learning and working in 136 unique learning contexts across the globe and considers the enablers and disablers of openness in learning, ethical and privacy implications, and how open world learning can be used to foster inclusive approaches to learning across educational sectors, disciplines and countries. The book is unique in exploring the complex, contradictory and multi-disciplinary nature of open world learning at an international level and will be of great interest to academics, researchers, professionals, and policy makers in the field of education technology, e-learning and digital education

A mixed method approach to studying self-regulated learning in MOOCs: combining trace data with interviews

To be successful in online education, learners should be able to self-regulate their learning due to the autonomy offered to them. Accurate measurement of learners’ self-regulated learning (SRL) in online education is necessary to determine which learners are in need of support and how to best offer support. Trace data is gathered automatically and unobtrusively during online education, and is therefore considered a valuable source to measure learners’ SRL. However, measuring SRL with trace data is challenging for two main reasons. First, without information on the how and why of learner behaviour it is difficult to interpret trace data correctly. Second, SRL activities outside of the online learning environment are not captured in trace data. To address these two challenges, we propose a mixed method approach with a sequential design. Such an approach is novel for the measurement of SRL. We present a pilot study in which we combined trace data with interview data to analyse learners’ SRL in online courses. In the interview, cued retrospective reporting was conducted by presenting learners with visualizations of their trace data. In the second part of the interview, learners’ activities outside of the online course environment were discussed. The results show that the mixed-method approach is indeed a promising approach to address the two described challenges. Suggestions for future research are provided, and include methodological considerations such as how to best visualize trace data for cued retrospective recall. &nbsp

Open World Learning

This book provides state-of-the-art contemporary research insights into key applications and processes in open world learning. Open world learning seeks to understand access to education, structures, and the presence of dialogue and support systems. It explores how the application of open world and educational technologies can be used to create opportunities for open and high-quality education. Presenting ground-breaking research from an award winning Leverhulme doctoral training programme, the book provides several integrated and cohesive perspectives of the affordances and limitations of open world learning. The chapters feature a wide range of open world learning topics, ranging from theoretical and methodological discussions to empirical demonstrations of how open world learning can be effectively implemented, evaluated, and used to inform theory and practice. The book brings together a range of innovative uses of technology and practice in open world learning from 387,134 learners and educators learning and working in 136 unique learning contexts across the globe and considers the enablers and disablers of openness in learning, ethical and privacy implications, and how open world learning can be used to foster inclusive approaches to learning across educational sectors, disciplines and countries. The book is unique in exploring the complex, contradictory and multi-disciplinary nature of open world learning at an international level and will be of great interest to academics, researchers, professionals, and policy makers in the field of education technology, e-learning and digital education

How to design for persistence and retention in MOOCs?

Design of educational interventions is typically carried out following a design cycle involving phases of investigation, conceptualization, prototyping, implementation, execution and evaluation. This cycle can be applied at different levels of granularity e.g. learning activity, module, course or programme. In this paper we consider an aspect of learner behavior that can be critical to the success of many MOOCs i.e. their persistence to study, and the related theme of learner retention. We reflect on the impact that consideration of these can have on design decisions at different stages in the design cycle with the aim of en-hancing MOOC design in relation to learner persistence and retention, with particular attention to the European context