Orchestrating learning analytics (OrLA): Supporting inter-stakeholder communication about adoption of learning analytics at the classroom level

© 2019 Australasian Journal of Educational Technology. Despite the recent surge of interest in learning analytics (LA), their adoption in everyday classroom practice is still slow. Knowledge gaps and lack of inter-stakeholder communication (particularly with educational practitioners) have been posited as critical factors for previous LA adoption failures. Yet, what issues should researchers, practitioners and other actors communicate about, when considering the adoption of an LA innovation in a particular context? We reviewed and synthesised existing literature on four focus areas related to LA, their adoption, implications for practice, and more general factors that have emerged as crucial when studying everyday classroom adoption of technologies (i.e., classroom orchestration). This synthesis resulted in two conversational frameworks and an inter-stakeholder communication tool. These can be used to guide and support conversations and decision-making about the adoption of LA innovations. We illustrate their usefulness with examples of use in ongoing LA adoption processes in Australia, Spain and Estonia

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

An Ontology-Enabled Approach for Modelling Business Processes

International audienceColoured Petri Nets (CPNs) have formal semantics and can describe any type of workflow system, behavioral and syntax wise simultaneously. They are widely studied and successfully applied in modelling of workflows and workflow systems. There is an inherent problem regarding business processes modelled with CPNs sharing and subsequently their reuse need to be considered. The Semantic Web technologies, such as ontologies, with their characteristics demonstrate that they can play an important role in this scenario. In this paper, we propose an ontological approach for representing business models in a meta-knowledge base. Firstly, the CPN ontology is defined to represent CPNs with OWL DL. Secondly, we introduce four basic types of manipulation operations on process models used to develop and modify business workflow patterns. To the best of our knowledge, representing business process definitions and business workflow patterns as knowledge based upon ontologies is a novel approach

The Proof of the Pudding: Examining Validity and Reliability of the Evaluation Framework for Learning Analytics

While learning analytics (LA) is maturing from being a trend to being part of the institutional toolbox, the need for more empirical evidences about the effects for LA on the actual stakeholders, i.e. learners and teachers, is increasing. Within this paper we report about a further evaluation iteration of the Evaluation Framework for Learning Analytics (EFLA) that provides an efficient and effective measure to get insights into the application of LA in educational institutes. For this empirical study we have thus developed and implemented several LA widgets into a MOOC platform’s dashboard and evaluated these widgets using the EFLA as well as the framework itself using principal component and reliability analysis. The results show that the EFLA is able to measure differences between widget versions. Furthermore, they indicate that the framework is highly reliable after slightly adapting its dimensions

Study Effort and Student Success: A MOOC Case Study

Learning was once defined as the function of efforts spent in relation to efforts needed [3]. Provided that effort is closely linked to time, previous research has found a positive relationship between student effort over time and student success, both in university education and Massive Open Online Courses (MOOCs). With the complex environment of tracing and identifying relevant data of student learning processes in MOOCs, this study employs learning analytics to examine this relationship for MITx 6.00x, an introductory programming and computer science MOOC hosted on the edX MOOC platform. A population sample from the MOOC (N = 32,621) was examined using logistic regression, controlling for variables that may also influence the outcome. Conversely, the outcome of this research study suggests that there is a curvilinear relationship between effort over time and student success, meaning those who exert effort for the longest amount of time in the MOOC actually have a lower probability of obtaining a certificate than others who exert effort over somewhat less time. Finally, research implications are discussed.acceptedVersio

Towards learning analytics adoption: A mixed methods study of data-related practices and policies in Latin American universities

In Latin American universities, Learning Analytics (LA) has been perceived as a promising opportunity to leverage data to meet the needs of a diverse student cohort. Although universities have been collecting educational data for years, the adoption of LA in this region is still limited due to the lack of expertise and policies for processing and using educational data. In order to get a better picture of how existing data‐related practices and policies might affect the incorporation of LA in Latin American institutions, we conducted a mixed methods study in four Latin American universities (two Chilean and two Ecuadorian). In this paper, the qualitative data were based on 37 interviews with managers and 16 focus groups with 51 teaching staff and 45 students; the quantitative data were collected through two surveys answered by 1884 students and 368 teachers, respectively. The findings reveal opportunities to incorporate LA services into existing data practices in the four case studies. However, the lack of reliable information systems and policies to regulate the use of data imposes challenges that need to be overcome for future LA adoption.In Latin American universities, Learning Analytics (LA) has been perceived as a promising opportunity to leverage data to meet the needs of a diverse student cohort. Although universities have been collecting educational data for years, the adoption of LA in this region is still limited due to the lack of expertise and policies for processing and using educational data. In order to get a better picture of how existing data‐related practices and policies might affect the incorporation of LA in Latin American institutions, we conducted a mixed methods study in four Latin American universities (two Chilean and two Ecuadorian). In this paper, the qualitative data were based on 37 interviews with managers and 16 focus groups with 51 teaching staff and 45 students; the quantitative data were collected through two surveys answered by 1884 students and 368 teachers, respectively. The findings reveal opportunities to incorporate LA services into existing data practices in the four case studies. However, the lack of reliable information systems and policies to regulate the use of data imposes challenges that need to be overcome for future LA adoption

Teacher and student facing analytics

Learning analytics systems are increasingly being designed for and implemented in classroom teaching and learning in K-12 and post-secondary contexts. For analytics to play a constructive role, it is important to consider how they are being used by teachers and students and how they can be designed to enhance and complement human decision making. In this chapter, we first discuss issues that teachers and students face in the sensemaking of learning analytics systems as well as in the subsequent phase of acting on the information provided by such systems. We then discuss the following aspects for teacher facing and then student facing analytics: (a) theoretical models underlying analytics use; (b) ways analytic systems have been designed and implemented; (c) evidence of impact the systems have had on teaching and learning. The chapter ends with an overarching discussion of challenges that concern both teacher and student facing analytics and introduces the possibilities for co-design of analytics systems to address some of these challenges