International audience

Group formation is an important issue in collaborative learning, as properly formed groups can lead to better interactions between students and enhance their learning. This issue also applies to pair programming when it is used as a learning activity. When the number of students is important and/or students and teachers do not know each other very well, manual group formation, either by students or teachers, can become difficult. Many of the existing automatic methods used for automatic group formation in pair programming require a certain amount of personal information about the students, which can make the implementation of this kind of system difficult. Hence, in this paper we present an automatic pair formation method integrated to a distributed pair programming application. Our approach is based on personal data from the students collected with questionnaires within our platform, but also on trace data automatically collected from the pair programming activities completed by students. It has been experimented during an introductory programming course in higher education. The objective was to identify, among programming experience, self-efficacy, gender and past engagement in pair programming activities, the formation criteria that led to the best perceived compatibility and work distribution as well as performance. The results show that homogeneous pairs in self-efficacy are significantly better than heterogeneous pairs, both in terms of perceived compatibility and perceived work distribution.

Research on pair programming (PP) in education have shown a number of positive outcomes for learners, and especially novice programmers, such as enhanced learning, greater confidence in work quality, higher problem solving skills or enhanced interaction skills, and promotes collaborative learning. Due to these diverse advantages, pair programming in education currently follows a growing curve. Also, blended learning approaches are becoming more and more popular in education, including when learners have to learn programming. As a consequence, distributed pair programming (DPP) can be considered as a good solution to support pair programming in hybrid learning scenarios. A large number of tools from both the research community and the major integrated development environment (IDE) editors tried to study and implement DPP in their tools. However, our review of literature shows that none of them meet the requirements for delivering effective pair programming activities to novice programmers in blended learning scenarios. Based on these findings, the paper introduces a new DPP application especially designed for novice programmers. It integrates, based on some requirements identified from previous research, several features dedicated to DPP as well as other capabilities supporting extensive data collection and learning analytics. The tool has been experimented in authentic learning settings in higher education with 82 students, both in PP and DPP conditions. The experiment showed no evidence of a difference between PP and DPP on the students' perceived usability of the application, as well as on the quality of their productions.

When formative assessment involves a large number of learners, Technology-Enhanced Formative Assessments are one of the most popular solutions. However, current TEFA processes lack data-informed decision-making. By analyzing a dataset gathered from a formative assessment tool, we provide evidence about how to improve decision-making in processes that ask learners to answer the same question before and after a confrontation with peers. Our results suggest that learners' understanding increases when the proportion of correct answers before the confrontation is close to 50%, or when learners consistently rate peers' rationales. Furthermore, peer ratings are more consistent when learners' confidence degrees are consistent. These results led us to design a decision-making model whose benefits will be studied in future works.

Nowadays, the use of mobile applications is gaining popularity among people, spreading to different areas. Specifically, the use of mobile applications has boomed in the field of education, with the increasing variety of applications in the application stores (PlayStore, AppStore, etc) that address specific problems of stories becoming increasingly common in the market like: problems of reading, writing, mathematics and other topics. On the other hand, the special education is an area of attention to children with special educational needs such as attention deficit, intellectual disability, speech problems, among other problems. Specifically, children who have problems in literacy with special educational need, face a challenge during their learning process of reading and writing. Because of this, special education has begun to incorporate the use of technology through the use of mobile applications in the classroom. In this context, we believe that teaching strategies can be adapted to the development of competences, both specific and transversal, in special education students, while at the same time they can increase students motivation during their learning process. These elements are known as gamification techniques. There is a seies of gamification techniques that can be incorporated into the learning process in children with special educational needs. The present work exposes the gamification techniques incorporated in a playful way in mobile applications, as well as a methodological proposal for the integration of these techniques in special education enviroments, making a case study in conjunction with teachers and special education children. First section of the article consits of a brief introduction to the reader on the subject of the gamification techniques, in wich they are found and some examples of gamification techniques used. Section II exposes the problem that can be solved in this work, section III presents the methodology used for the preparation of this work, describing each of the stages by wich it is composed. Section IV presents the case study that was conducted in conjuntion with special education children and finally section V discusss the results and conclusions that wre obtained from the work done.

Help between peers, intended to positively influence learning, appears as a suitable activity for inquiry learning. While several studies reveal evidence that effective help-seeking and help-giving behaviors can improve learning, virtual and remote laboratories do not provide sufficient support to enable these social interactions. Based on a set of criteria defined from existing literature, we designed a management system and implemented it in Lab4CE, a remote laboratory environment for Computer Education. The first results of two experimentations reveal that learners do not tend to help each other spontaneously, while the presence of a teacher increases self-confidence on help given.

This paper addresses learning analytics for evaluation of learners performance in remote laboratories. The objectives we identified to provide self-and social awareness while learners are practicing in their virtual learning environment are threefold: (1) the definition of a performance metric that requires no assessment tests, (2) the tracking of data to infer that metric in real time, and (3) the visualization of the performance metric without impacting learners' cognitive load. To support these needs, we propose (i) a metric related to the technical rightness of instructions carried out by learners, (ii) a generic learning analytics framework featuring an enriching engine able to infer indicators, and (iii) two distinct visualization tools. These proposals have been implemented in Lab4CE, our remote laboratory for computer education, and experimented in an authentic learning context. This experimentation showed that most students have significantly used both visualization tools, and that their usage decreased while the overall learners performance increased.

Our previous work has introduced the "Tsaap-Notes" platform to increase the motivation and engagement of students in the process of collaborative note taking during lectures. In this paper, we introduce the approach "Notes as Feedback" which consists of recycling interactive questions asked during a lecture in order to semi-automatically build computer based self-assessment tests where feedback provided to students is based on the notes taken by students. A first experimentation on a group of 54 students enrolled in a computer science Master course helped to highlight the benefits of this work: increased participation in note-taking, a massive engagement of students to play the self-assessment tests, and improved student results at the final exam.

Within today's European socioeconomic context, supporting careers choices and occupational integration has become a major challenge. Education has to fit the changes of industry and job market, but this process requires a unified representation of professions and training programs. The competency concept appears to be a common vector, since it has turned to be a pervasive idea. Although industry has started specifying trades through competencies, similar attempts are not initiated for education yet. In this paper, we present a unifying model for training programs, professions and learners, built around competencies. Based on this model, several tools have been developed to help (1) educational teams to make sure that conceptions of curriculum fit the targeted learning objectives, (2) learners to make their careers choices through life easier, (3) industrial actors to identify training programs matching with their needs.

Social theories of learning demonstrated that collaborative note taking during face-to-face lecture provides important benefits: better learner engagement, collaborative learning, and knowledge building. In this paper we present Tsaap-Notes, an open micro-blogging platform dedicated to collaborative note taking that can be used as a standalone application, or fully integrated into existing virtual learning environments. Tsaap-Notes provides users with advanced features such as annotations, questions, or filtering that encourage learners to participate in the collaborative activity. Our tool has been experimented with a cohort of forty students during a short period of time, results show that learners are getting more and more familiar with Tsaap-Notes and that this application becomes useful when the time of preparing exams has come.

In this paper, we describe a web application composed of a set of tools and graphical user interfaces. This application aims at simplifying learning design and enhancing effective learning of distant lab work activities, in the field of computer education. This work is based on the educational concepts of the social constructivism theory, which focuses on the crucial role of collaboration and tutoring during online learning activities. Experiments' design and deployment are supported by an intuitive web application that graphically builds their components and features. Another web interface dedicated to education and based on the "Cockpit" model was developed. Learners and tutors are able to remotely control the whole experiment as well as each of its components, while being aware, both in real and delayed time, of the activities performed by others. Additional controls are provided to tutors in order to allow them to quickly identify difficulties and blocking situations that learners are facing. This web application is well integrated and available in a learning management system, as any traditional learning activity.

This paper introduces the modeling of a learning context supported by a service-oriented architecture to ensure tracking of profiles and activities of learners involved in Technology Enhanced Learning processes. A distributed architecture including heterogeneous learning systems and tools, together with some tracking components, is experimented within a French certification learning environment and validates our approach. This proposal is based on a standard widely supported by major editors of operating systems, thus facilitating its adoption by a large range of communities.

Even if virtualization technologies are mature enough to deliver remote experiment in a distance-learning context, they are not well-integrated into existing learning environments; as a consequence, they do not provide teachers with any mechanisms to get feedbacks on actions handled by learners. To tackle these issues, this paper presents an approach based on the Web-Based Enterprise Management (WBEM) standard. Full integration of learning and experiment contexts is ensured by an intermediate layer acting as a bridge, while tracking mechanisms stand on (1) an abstract modeling of experiments and learnerspsila information from an observation point of view, and (2) some components able to extract, store and retrieve data specified within the model. We demonstrate how this approach can be extended to satisfy additional requirements, and present an implementation based on existing open source software that validates our works.

The more learner information is shared across a wide range of heterogeneous applications and tools, the more learner profiles will be relevant, reusable and useful for many systems and environments. This proposal stands on a widely used management standard, and introduces an open and generic learner profile supported by a service-oriented architecture ensuring exchange and reuse of learner information. The profile is characterized by (1) a core model integrating the LIP standard but also some metacognitive properties, and (2) a high abstraction level offering the possibility to extend the core model. The architecture facilitates sharing and reusing of learner profiles while providing scalability. Two use cases are presented and demonstrate (1) how heterogeneous applications can transparently collaborate to strengthen shared learner profiles, and (2) how resulting profiles can easily be consulted and extracted for further exploitation.

Works presented in this paper offer teachers and learners the opportunity to express their learning objects assessments and suggestions for use directly from a learning management system, and to store these annotations within a learning object repository. Annotations are thus stored when and where they become relevant. Thanks to an open and standardized architecture, these annotations can be widely shared and exploited in various contexts such as re-authoring, curriculum designs, or learning object retrieval. Indeed, annotations can represent a basis for a (personalized) quality-based sorting mechanism helping users to find and reuse learning resources that match with their preferences. An implementation focusing on Moodle and the Ariadne knowledge pool system validates our approach.

In previous work, we suggested a model driven approach allowing for tracking and management of both learning objects' usage and content-related activities of users involved in a wide-distributed Web-based learning environment. Here we present an extension of our previous model in order to provide end-users with a personalized search tool. This application recommends learning resources according to their preferences and does not require users to fill in an electronic form; the tool also offers them the opportunity to review learning content by adding tags, comments and ratings. Moreover, work is in progress to automate execution of actions that will facilitate users to be up-to-date with new learning resources matching with their preferences and created by the whole community of actors involved in the learning environment

To allow multiple professionals to design and realise together a specific learning object (LO) by using a repository that store and index their several modifications, we need to represent the different steps followed by a LO and its metadata throughout its lifecycle. Here, we study various initiatives related to this issue and notice significant differences between them in the terms of terminology and sequences. Thus, we infer a generic representation that can be applied to any given learning situation. Finally we validate this representation by connecting it to the International E-Miage approach (computer methods for companies' management), a French "digital campus", basis of our experimentation