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Potential benefits of learning analytics (LA) for improving students' performance, predicting students' success, and enhancing teaching and learning practice have increasingly been recognized in higher education. However, the adoption of LA in higher education institutions (HEIs) to date remains sporadic and predominantly small in scale due to several socio-technical challenges. To better understand why HEIs struggle to scale LA adoption, it is needed to untangle adoption challenges and their related factors. This paper presents the findings of a study that sought to investigate the associations of adoption factors with challenges HEIs face in the adoption of LA and how these associations are compared among HEIs at different scopes of adoption. The study was based on a series of semi-structured interviews with senior managers in HEIs. The interview data were thematically analysed to identify the main challenges in LA adoption. The connections between challenges and other factors related to LA adoption were analysed using epistemic network analysis (ENA). From senior managers' viewpoints, ethical issues of informed consent and resistance culture had the strongest links with challenges of learning analytic adoption in HEI; this was especially true for those institutions that had not adopted LA or who were in the initial phase of adoption (i.e., preparing for or partially implementing LA). By contrast, among HEIs that had fully adopted LA, the main challenges were found to be associated with centralized leadership, gaps in the analytic capabilities, external stakeholders, and evaluations of technology. Based on the results, we discuss implications for LA strategy that can be useful for institutions at various stages of LA adoption, from early stages of interest to the full adoption phase.

Smart learning environments (SLEs) have gained considerable momentum in the last 20 years. The term SLE has emerged to encompass a set of recent trends in the field of educational technology, heavily influenced by the growing impact of technologies, such as cloud services, mobile devices, and interconnected objects. However, the term SLE has been used inconsistently by the technology-enhanced learning (TEL) community since different research works employ the adjective "smart" to refer to different aspects of novel learning environments. Previous surveys on SLEs are narrowly focused on specific technologies or remain at a theoretical level that does not discuss practical implications found in empirical studies. To address this inconsistency and also to contribute to a common understanding of the SLE concept, this article presents a systematic literature review of papers published between 2000 and 2019 discussing SLEs in empirical studies. Sixty-eight papers out of an initial list of 1341 papers were analyzed to identify the following: 1) what affordances make a learning environment smart; 2) which technologies are used in SLEs; and 3) in what pedagogical contexts are SLEs used. Considering the limitations of previous surveys, and the inconsistent use of the SLE concept in the TEL community, this article presents a comprehensive characterization to describe SLEs through their affordances, the technologies used, and pedagogical approaches considered in the selected papers. As a result, specific core functions of SLEs are identified and explained. This work aims at ensuring a relevant knowledge base and reference toward the implementation of future SLEs.

Many modern web-based systems provide a "responsive" design that allows material and services to be accessed on mobile and desktop devices, with the aim of providing "ubiquitous access." Besides offering access to learning materials such as podcasts and videos across multiple locations, mobile, wearable and ubiquitous technologies have some additional affordances that may enable new forms of learning on MOOCs. We can divide these into two categories: firstly, "context-sensitive features" including delivery of content for a specific location, enabling a seamless continuity of learning across settings, and linking people in a location with others in a virtual representation of that place; secondly social learning opportunities to connect people as they move within and across locations, to enable "crowd-sourced learning." In this paper we explore these aspects of mobile and accessible learning for MOOCs, drawing on examples from MOOC courses, mobile toolkits, and crowd-sourced learning sites.

This paper surveys the state of the art on prediction in MOOCs through a systematic literature review (SLR). The main objectives are: first, to identify the characteristics of the MOOCs used for prediction, second, to describe the prediction outcomes, third, to classify the prediction features, fourth, to determine the techniques used to predict the variables, and, fifth, to identify the metrics used to evaluate the predictive models. Results show there is strong interest in predicting dropouts in MOOCs. A variety of predictive models are used, though regression and support vector machines stand out. There is also wide variety in the choice of prediction features, but clickstream data about platform use stands out. Future research should focus on developing and applying predictive models that can be used in more heterogeneous contexts (in terms of platforms, thematic areas, and course durations), on predicting new outcomes and making connections among them (e.g., predicting learners' expectancies), on enhancing the predictive power of current models by improving algorithms or adding novel higher-order features (e.g., efficiency, constancy, etc.).

One of the characteristics of massive open online courses (MOOCs) is that the overall number of social interactions tend to be higher than in traditional courses, hindering the analysis of social learning. Learners typically ask or answer questions using the forum. This makes messages a rich source of information, which can be used to infer learners' behavior and outcomes. It is not feasible for teachers to process all forum messages and automated tools and analysis are required. Although there are some tools for analyzing learners' interactions, there is a need for methodologies and integrated tools that help to interpret the learning process based on social interactions in the forum. This paper presents the 3S (Social, Sentiments, Skills) learning analytics methodology for analyzing forum interactions in MOOCs. This methodology considers a temporal analysis combining the social, sentiments, and skill dimensions that can be extracted from forum data. We also introduce LAT[turned E]S, a learning analytics tool for edX/Open edX related to the three dimensions (3S), which includes visualizations to guide the proposed methodology. We apply the 3S methodology and the tool to an MOOC on Java programming. Results showed, among others, the action-reaction effect produced when learners increase their participation after instructor's events. Moreover, a decrease of positive sentiments over time and before deadlines of open-ended assignments was also observed and that there were certain skills, which caused more troubles (e.g., arrays and loops). These results acknowledge the importance of using a learning analytics methodology to detect problems in MOOCs.

Educational computer-based competition environments need to be designed with a set of features that enhance the learning process. Although recently some frameworks for the design of educational computer-based systems (e.g., educational games) have been proposed, they do not focus on the details of the competition. Therefore, the design of educational computer-based competition environments is still an open issue. We propose the 4NESS framework for the design of such competition environments. This framework classifies the competition features into four dimensions: easiness, fairness, awareness, and adaptiveness. We designed the ISCARE educational computer-based competition environment implementing these four dimensions to evaluate and validate some included features for competition, and conducted experiments during three consecutive years. Students considered the computer-based competition environment with the proposed features, including a modification of the Swiss system, to be very easy to use, fair for pairing students, moderately fair for calculating scores, with good awareness of their state during the competition and that of their peers, and with contents of appropriate level, especially for the group working with adaptive contents. Adaptation of contents made students increase their learning gains in 0.5 sigmas during the competition. Pairings were seen as with students of similar levels. And final scores were moderately fair: while the order tends to be similar as compared to the results in the post-test, students grades with high performance tend to be lower in the competition environment.

Since Massive Open Online Courses (MOOCs) started to become part of the scene of Higher Education (HE), many institutions have joined the race of MOOC creation. However, producing MOOCs has shown to be a cumbersome and expensive activity for HE institutions. For this reason, many universities have started to explore and experiment with hybrid initiatives in which locally produced and third-party MOOCs are reused and integrated into traditional courses. Most of the hybrid initiatives described in the literature so far focus on flipped classroom experiences, although there are some other possibilities for integrating MOOCs in the curriculum. Moreover, few studies have reported on the institutional support required for implementing hybrid initiatives, and their benefits from a curriculum perspective. In order to shed some light on the opportunities that arise from the reuse of MOOCs, this paper presents H-MOOC, a framework that describes hybrid MOOC-based initiatives as a continuum of two factors: (1) institutional support to reuse an existing MOOC, and (2) curricular content alignment between the MOOC and the program, or the course hybridized. In addition, H-MOOC proposes indicators to measure the impact of these initiatives at both educational and institutional levels. Examples of actual hybrid initiatives and a set of guiding questions are presented to show how to apply the H-MOOC framework in different contexts.

Self-regulated learning (SRL) environments provide students with activities to improve their learning (e.g., by solving exercises), but they might also provide optional activities (e.g., changing an avatar image or setting goals) where students can decide whether they would like to use or do them and how. Few works have dealt with the use of optional activities in SRL environments. This paper thus analyzes the use of optional activities in two case studies with a SRL approach. We found that the level of use of optional activities was low with only 23.1 percent of students making use of some functionality, while the level of use of learning activities was higher. Optional activities which are not related to learning are used more. We also explored the behavior of students using some of the optional activities in the courses such as setting goals and voting comments, finding that students finished the goals they set in more than 50 percent of the time and that they voted their peers' comments in a positive way. We also found that gender and the type of course can influence which optional activities are used. Moreover, the relations of the use of optional activities with proficient exercises and learning gains is low when taking out third variables, but we believe that optional activities might motivate students and produce better learning in an indirect way.

A lack of student motivation is a problem in many courses in electrical engineering. Introducing competition between students can enhance their motivation, but it can also generate negative emotions. This paper presents an empirical study of students in a telecommunications engineering degree; it measured their level of motivation, and their emotions about competition in education in general, and in particular about the Information System for Competition based on pRoblem solving in Education (ISCARE). ISCARE makes adaptive matches, pairing students who share a similar knowledge level. The study results show that students had moderate levels of motivation and experienced no negative emotions while using ISCARE. Under certain circumstances, therefore, competition in education, using technology systems that provide competition, can produce motivation without generating negative emotions. Female students and students with low ISCARE scores were less motivated and experienced more negative emotions. In addition, motivation and emotions toward ISCARE were more positive than they had been toward competition in general.

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.