Augmenting reality and formality of informal and non-formal settings to enhance blended learning

Visits to museums and city tours have been part of higher and secondary education curriculum activities for many years. However these activities are typically considered "less formal" when compared to those carried out in the classroom, mainly because they take place in informal or non-formal settings. Augmented Reality (AR) technologies and smartphones can transform such informal and non-formal settings into digitally augmented learning settings by superimposing "digital" layers of information over physical objects or spaces. At the same time, the formality of these settings increases when connected to formal settings through these digital layers. The right combination of AR and mobile technologies with computer-based educational tools such as Learning Management Systems (LMSs) drives this digital connection, leading to articulated blended learning activities across formal, non-formal and informal settings. This paper contributes to the TEL field with: (1) three blended learning activities illustrating the idea of augmented informal/non-formal settings; (2) results from the cross-analysis of these activities that evidence the impact of technology to enhance blended learning; and (3) a set of lessons learned about the possibilities of NFC/GPS AR technologies and LMSs for blended learning. This work provides insights for the design and implementation of similar technology-enhanced blended learning activities. © 2008-2011 IEEE

Predicting Learners' Success in a Self-paced MOOC Through Sequence Patterns of Self-regulated Learning

Proceeding of: 13th European Conference on Technology Enhanced Learning, EC-TEL 2018, Leeds, UK, September 3-5, 2018.In the past years, predictive models in Massive Open Online Courses (MOOCs) have focused on forecasting learners' success through their grades. The prediction of these grades is useful to identify problems that might lead to dropouts. However, most models in prior work predict categorical and continuous variables using low-level data. This paper contributes to extend current predictive models in the literature by considering coarse-grained variables related to Self-Regulated Learning (SRL). That is, using learners' self-reported SRL strategies and MOOC activity sequence patterns as predictors. Lineal and logistic regression modelling were used as a first approach of prediction with data collected from N = 2,035 learners who took a self-paced MOOC in Coursera. We identified two groups of learners: (1) Comprehensive, who follow the course path designed by the teacher; and (2) Targeting, who seek for the information required to pass assessments. For both type of learners, we found a group of variables as the most predictive: (1) the self-reported SRL strategies 'goal setting', 'strategic planning', 'elaboration' and 'help seeking'; (2) the activity sequences patterns 'only assessment', 'complete a video-lecture and try an assessment', 'explore the content' and 'try an assessment followed by a video-lecture'; and (3) learners' prior experience, together with the self-reported interest in course assessments, and the number of active days and time spent in the platform. These results show how to predict with more accuracy when students reach a certain status taking in to consideration not only low-level data, but complex data such as their SRL strategies.This work was supported by FONDECYT (Chile) under project initiation grant No.11150231, the MOOC-Maker Project (561533-EPP-1-2015-1-ES-EPPKA2-CBHE-JP), the LALA Project (586120-EPP-1-2017-1-ES-EPPKA2-CBHE-JP), and CONICYT/DOCTORADO NACIONAL 2016/21160081, the Spanish Ministry of Education, Culture and Sport, under an FPU fellowship (FPU016/00526) and the Spanish Ministry of Economy and Competiveness (Smartlet project, grant number TIN2017-85179-C3-1-R) funded by the Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER).Publicad

UC online engineering: organization, processes, experiences and research on MOOCS and SPOCS at the School of Engineering of the Pontificia Universidad Católica de Chile

This article presents how the development and installation of MOOC production capabilities has been carried out at the School of Engineering of the Pontificia Universidad Católica de Chile. Specifically, they range from the organizational and infrastructure changes required to the new processes developed. In addition, the different areas of research developed in the institution around the MOOCs are presented, as well as the most important pilot experiences where this type of courses is used to propose alternative pedagogical methodologies. This article aims to serve as an example to other institutions in Latin America that want to develop MOOCs design and production capacities. © 2018 IEEE.This article presents how the development and installation of MOOC production capabilities has been carried out at the School of Engineering of the Pontificia Universidad Católica de Chile. Specifically, they range from the organizational and infrastructure changes required to the new processes developed. In addition, the different areas of research developed in the institution around the MOOCs are presented, as well as the most important pilot experiences where this type of courses is used to propose alternative pedagogical methodologies. This article aims to serve as an example to other institutions in Latin America that want to develop MOOCs design and production capacities. © 2018 IEEE.Sao Paul

Tools Designed to Support Self-Regulated Learning in Online Learning Environments: A Systematic Review

International audienceSelf-regulated learning (SRL) is a crucial higher-order skill required by learners of the 21st century, who will need to become lifelong learners to adapt to the continually changing environments. Literature provides examples of tools for scaffolding SRL in online environments. In this study, we provide the state-of-the-art concerning tools that support SRL in terms of theoretical models underpinning development, supported SRL processes, tool functionalities, used data and visualizations. We reviewed 42 articles published between 2008 and 2020, including information from 25 tools designed to support SRL. Our findings indicate that (1) many of the studies do not explicitly specify the SRL theoretical model used to guide the design process of the tool; (2) goal setting, monitoring, and self-evaluation are the most prevalent SRL processes supported through functionalities such as content navigation, user input forms, collaboration features, and recommendations; (3) the relationship between tool functionalities and SRL processes are rarely described; (4) few tools assess the impact on learners' SRL process and learning performance. Finally, we highlight some lessons learned that might contribute to implementing future tools that support learners' SRL processes

Characterizing Learners’ Engagement in MOOCs: An Observational Case Study Using the NoteMyProgress Tool for Supporting Self-Regulation

International audienceRecent research shows that learners who are able to self-regulate their learning show greater levels of engagement with massive open online course (MOOC) content. To improve support for learners in their self-regulatory processes, researchers have proposed technological solutions to transform recorded MOOC data into actionable knowledge. However, studies providing empirical evidence on how these solutions impact learners' engagement with the course and their self-regulatory behavior remain scarce. In this article, we present the results of an observational case study in which NoteMyProgress (NMP), a web-based tool designed to support learners' self-regulation in MOOCs, is applied as an intervention in two MOOCs. The main aim of this article is to provide insights into how the support of learners' self-regulated learning (SRL) strategies correlates with course engagement. We performed the evaluation using a sample of 263 learners and utilized distinct data sources in order to propose indicators for learners' engagement with the course and NMP. Results show a positive correlation between learners' final grades with NMP functionalities that support goal setting, organization (note taking), and self-reflection (social comparison) SRL strategies. Furthermore, we found no significant behavioral differences in how learners with low SRL and high SRL profiles engage with the course or NMP. Finally, we discuss how these results relate to prior work and the implications for future technological solutions that seek to promote engagement in MOOCs