Design for Teaching and Learning in a Networked World

Citizen inquiry is an innovative informal science learning approach, which engages members of the general public in scientific investigations sparked by their personal experience of everyday science, and to which other members can contribute. This paper aims to describe the network of interactions and contributions of Weather-it, an online Citizen Inquiry community accommodated by the nQuire-it platform, which involves people in creating and maintaining their own weather missions (investigations). The interaction patterns within Weatherit are mainly explored through social network analysis of community members and missions. The results indicate the quiet and active members within the community, their splitting into sub-communities, and their contribution and data collection methods and preferences. These results provide insight into the behaviour of people in such public engagement projects.

One of the latest trends in the educational landscape is the introduction of computer programming in the K-12 classroom to develop computational thinking in students. As computational thinking is not a skill exclusively related to computer science, it is assumed - but not yet scientifically proven - that the problem solving process may be generalized and transferred to a wide variety of problems. This paper presents a research designed to test whether the use of coding in Maths classes could have a positive impact on learning outcomes of students in their mathematical skills. Therefore, the questions we want to investigate in this paper are if the use of programming in Maths classes improves (a) modeling process and reality phenomena, (b) reasoning, (c) problem formulation and problem solving, and (d) comparison and execution of procedures and algorithms. We have therefore designed a quantitative, quasi-experimental experiment with 42 participating 6th grade (11 and 12 years old) students. Results show that there is a statistically significant increase in the understanding of mathematical processes in the experimental group, which received training in Scratch.

In this article, we propose a set of models and a prototype to capitalize and share knowledge of expert tutors using training simulators. This is a particularly important issue in contexts with strong stakes such as training of operators of nuclear power plants, where operators’ accreditation strongly depends on skills of tutors and tolerate no errors. In such a context, observation, analysis and debriefing of interactions of trainees’ operators are complex activities especially for the young tutors who do not have the expertise of confirmed tutors. Based on digital traces, our approach consists in providing a visual synthesis of trainees’ activities by using the knowledge of experts. Such a synthesis, showing the relationships between low-level traces and high-level behaviors, enables tutors to enhance their understanding and better analyse the activity in order to prepare the debriefing. Our approach has been implemented in a prototype, called D3KODE, which was evaluated according to a comparative protocol conducted with a team of tutors from EDF Group (Electricity Of France). The result demonstrated that the visual synthesis and the higher informations provided by D3KODE helped the intructors to confirm/validate more easily realizations and no-realizations of educational objectives trainees and facilitated the exchanges between tutors and trainees.

Learning analytics are being used in many educational applications in order to help students and Faculty. In our work we use

predictive

analytics, using student behaviour to predict the likely performance of end of semester final grades with a system we call PredictED. The main contribution of our approach is that our intervention automatically emailed students on a regular basis, with our prediction for the outcome of their exam performance.We targeted first year, first semester University students who often struggle with making the transition into University life where they are given much more responsibility for things like attending class, completing assignments, etc. The form of student behaviour that we used is students’ levels and types of engagement with the University’s Virtual Learning Environment (VLE), Moodle. We mined the Moodle access log files for a range of parameters based on temporal as well as content access, and use machine learning techniques to predict likely pass/fail, on a weekly basis throughout the semester using logs and outcomes from previous years as training material. We chose ten first-year modules with reasonably high failure rates, large enrolments and stability of module content across the years to implement an early warning system on. From these modules 1,558 students were registered for one of these modules. They were offered the chance to opt into receiving weekly email alerts warning them about their likely outcome. Of these 75% or 1,181 students opted into this service. Pre-intervention there were no differences between participants and non-participants on a number of measures related to previous academic record. However, postintervention the first-attempt final grade performance yielded nearly 3% improvement (58.4% to 61.2%) on average for those who opted in. This tells us that providing weekly guidance and personalised feedback to vulnerable first year students, automatically generated from monitoring of their online behaviour, has a significant positive effect on their exam performance.

Matrix factorization techniques are widely used to build collaborative filtering recommender systems. These recommenders aim at discovering latent variables or attributes that are supposed to explain and ultimately predict the interest of users. In cognitive modeling, skills and competencies are considered as key latent attributes to understand and assess student learning. For this purpose, Tatsuoka introduced the concept of Q-matrix to represent the mapping between skills and test items. In this paper we evaluate how predictive expert-created Q-matrices can be when used as a decomposition factor in a matrix factorization recommender. To this end, we developed an evaluation method using cross validation and the weighted least squares algorithm that measures the predictive accuracy of Q-matrices. Results show that expert-made Q-matrices can be reasonably accurate at predicting users success in specific circumstances that are discussed at the end of this paper.

Massive open online courses (MOOCs) are part of the lifelong learning experience of people worldwide. Many of these learners participate fully. However, the high levels of dropout on most of these courses are a cause for concern. Previous studies have suggested that there are patterns of engagement within MOOCs that vary according to the pedagogy employed. The current paper builds on this work and examines MOOCs from different providers that have been offered on the FutureLearn platform. A cluster analysis of these MOOCs shows that engagement patterns are related to pedagogy and course duration. Learners did not work through a three-week MOOC in the same ways that learners work through the first three weeks of an eight-week MOOC.

In-app reflection guidance for workplace learning means motivating and guiding users to reflect on their working and learning, based on users’ activities captured by the app. In this paper, we present a generic concept for such in-app reflection guidance for workplace learning, its implementation in three different applications, and its evaluation in three different settings (one setting per app). From this experience, we draw the following lessons learned: First, the implemented in-app reflection guidance components are perceived as useful tools for reflective learning and their usefulness increases with higher usage rates. Second, smart technological support is sufficient to trigger reflection, however with different implemented components also reflective learning takes place on different stages. A sophisticated, unobtrusive integration in the working environment is not trivial at all. Automatically created prompts need a sensible timing in order to be perceived as useful and must not disrupt the current working processes.

With the advent and growing use of crowdsourcing labor markets for a variety of applications, optimizing the quality of results produced is of prime importance. The quality of the results produced is typically a function of the performance of crowd workers. In this paper, we investigate the notion of treating crowd workers as ‘

learners

’ in a novel learning environment. This learning context is characterized by a short-lived learning phase and immediate application of learned concepts. We draw motivation from the desire of crowd workers to perform well in order to maintain a good reputation, while attaining monetary rewards successfully. Thus, we delve into training workers in specific microtasks of different types. We exploit (i)

implicit

training

, where workers are provided training when they provide erraneous responses to questions with priorly known answers, and (ii)

explicit

training

, where workers are required to go through a training phase before they attempt to work on the task itself. We evaluated our approach in 4 different types of microtasks with a total of 1200 workers, who were subjected to either one of the proposed training strategies or baseline case of

no

training

. The results show that workers who undergo training depict an improvement in performance upto 5 %, and a reduction in the task completion time upto 41 %. Additionally, crowd training led to the elimination of malicious workers and a costs-benefit gain upto nearly 15%.

Teaching and learning in higher education institutions have for some time now been seen to integrate on line activities, materials and student interaction into otherwise campus based programmes. Traditional teaching is often both classroom-based, teacher centred as well as with an emphasis on content delivery. Transformation of existing teaching practice, however, is often a daunting task for teaching professionals, and one which calls for an organizational approach. To support teaching staff in such transformation, a methodology for learning design has been developed and implemented into the organisation of a school for continuing education. Despite support from e-learning experts in the design process, most projects undertaken by teaching staff were modest in degree of innovation, and existing practices were reinforced rather than transformed. The workshops and design methodology have now become part of a so called organizational framework for learning design in order to provide a stronger incentive and better support for transformation of practice.

Mobile learning has received an increasing attention by the TEL community since 2010. While much research is available on the effectiveness of individual apps and educational approaches and despite that many higher education institutions introduced special mobile learning apps, relatively little is known about the rationale of scaling up mobile learning in higher education institutions. It reports on a case study, in which a mobile app solution has been integrated into a lecture at a major Swiss university. The study analyses the student’s use of mobile media and the use of a smart-phone app in a mobile blended learning setting. The results indicate that today’s students live in a multi device environment and are likely to use mobile apps in new contexts and settings if this is supported by an app. They also show that mobiles will not replace other delivery modes or technologies. Instead, the findings indicate that students used the mobile learning solution for extending and enriching their learning environment. Therefore, this study suggests that mobile learning needs to blend into rich learning environments, in which they co-exist with paper books, classroom experiences, laptops, and tablets. The insights define new requirements for both, mobile apps and virtual learning environments, in order to meet the future challenges of TEL in higher education.

Training children safe behavior in traffic situations is both important and challenging. One of the problems is children’s limited perceptual-motor abilities and associated difficulties with important cognitive skills required to be safe pedestrians. Existing traffic education programs focus more on theoretical knowledge, while training practical skills in the real world is dangerous, expensive and hard to organize. This paper presents a promising alternative – an intelligent virtual reality training environment that allows children to practice their pedestrian skills. It describes the interface and architecture of the system, as well as the skill model of the pedestrian safety domain. The results of the conducted pilot study show that children of the target age group rarely have problems with applying (and acquiring) “basic” pedestrian skills in the developed virtual environment. However, when applying and learning “advanced” skills, they require additional support.

One of the original goals of intelligent educational systems was to guide each student to the most appropriate educational content. In previous studies, we explored both knowledge-based and social guidance approaches and learned that each has a weak side. In the present work, we have explored the idea of combining social guidance with more traditional knowledge-based guidance systems in hopes of supporting more optimal content navigation. We propose a greedy sequencing approach aimed at maximizing each student’s level of knowledge and implemented it in the context of an open social student modeling interface. We performed a classroom study to examine the impact of this combined guidance approach. The results of our classroom study show that a greedy guidance approach positively affected students’ navigation, increased the speed of learning for strong students, and improved the overall performance of students, both within the system and through end-of-course assessments.

Currently, a lot of research in the field of intelligent tutoring systems is concerned with recognising student’s emotions and affects. The recognition is done by extracting features from information sources like speech, typing and mouse clicking behaviour or physiological sensors. According to the state-of-the-art support vector machines are the best performing classification models for those kinds of features. However, single classification models often do not deliver the best possible performance. Hence, we propose an approach for further improving the affect recognition performance, which is based on ideas from ensemble approaches and feature selection methods. The approach is proven by experiments on low-level speech features extracted from data which was collected in a study with German students solving mathematical tasks. In these experiments the proposed approach reached on average an affect recognition performance improvement of about 59% in comparison to a single SVM.

This paper reports on an iterative design process for a serious game, which aims to raise situational awareness among different stakeholders in a logistics value chain by introducing multi-user role-playing games. It does so in several phases: After introducing the field of logistics as a problem domain for an educational challenge, it firstly describes the design of an educational board game for the field of disruption handling in logistics processes. Secondly, it describes how the board game can be realized in an open-source mobile serious games platform and identifies lessons learned based on advantages and issues found. Thirdly, it derives requirements for a re-design of the mobile game and finally draws conclusions.

For MOOC learners, lecture video viewing is the central learning activity. This paper reports a large-scale analysis of in-video interactions. We categorize the video behaviors into patterns by employing a clustering methodology, based on the available types of interactions, namely, pausing, forward and backward seeking and speed changing. We focus on how learners view MOOC videos with these interaction patterns, especially on exploring the relationship between video interaction and perceived video difficulty, video revisiting behaviors and student performance. Our findings provide insights for improving the MOOC learning experiences.

Competence-based Knowledge Space Theory (CbKST) is considered a well-fitting basis for adapting Serious Games (SGs). CbKST relies on the domain model associated to a given SG to infer the so-called

competence structure

. However, building such a model can be time-consuming and a tough task for experts. We propose another approach to overcome this issue by considering the Q-Matrix that contains the mapping between the SG activities and the addressed competences. We compare the two approaches, one based on the domain model and the other on the Q-Matrix, in three SGs. We apply both approaches to two SGs, while in a third one, we apply only the Q-Matrix approach since no domain model is available. The main findings when comparing both approaches refer to the issues derived from the generated

competence structures

and the definition of competences at a suitable granularity level. This exploratory work can provide meaningful insights when applying CbKST for adapting SGs.

Autism spectrum disorder (ASD) is a neurological disorder affecting the way in which the brain processes information. It can affect all aspects of a person’s development. Autism is characterized by impairments in learning and communication, in the social interaction, imaginative ability as well as in repetitive and restricted patterns of behavior (Diagnostic and statistical manual of mental disorders: DSM-IV [12]). This research contributes to the advancement of intelligent tutoring systems by proposing a computational model in the field of specialized education in order to overcome the lack of individualized intervention, such as in the specialized education of individuals with autism. The affective intelligent tutoring system ISLA is an adaptive application evolving along with the learner’s needs. ISLA is unique and its contribution entails the model of accompaniment to help autistic children manage their emotions by analyzing the learning trace and considering the student’s current performance to respond accordingly to it during a mathematical learning situation such as addition.

Data sets coming from the educational domain often suffer from sparsity. Hence, many learning objects are not accessible by the users as they are not able to find these objects using for example a textbased search. Furthermore, the lack of information makes it difficult or even impossible to recommend such hidden learning resources. In order to address the data sparsity problem, this paper presents a new way to enhance the objects’ semantic representations. This is done by automatically assigning tags and classifications to learning objects offered by educational web portals. This way, we aim to increase the accessibility of the learning objects as well as to enable their recommendation. In contrast to popular tagging approaches that usually base the tagging of a learning object on its content or on the tags already assigned to it, the approach proposed in this paper is solely based on the objects’ usage. Therefore, tags and classifications can be exchanged between the objects and also previously un-tagged objects that do not hold any textual content can be automatically assigned with tags and classifications.

The aim to support learning communities by Web 2.0 technology leads to their investigation through the prism of learning theories. However, self-observation and self-modeling requires appropriate tools and skills. In this paper we focus on users of a forum platform and propose several tools that perform community detection, social network analysis, text mining, natural language processing, and clustering. The outcomes serve as inputs for community models that are automatically established using the

i

* information modeling approach. Stakeholders can recognize issues in their communities by visual analytics of the models. Based on this, they can refine community learning processes and community environments by retrieving new community requirements from the models. The process of model establishment was evaluated by experts in

i

* information modeling and the results show their acceptance of the proposed techniques. This solution enables also support of various well-known modeling approaches (like IMS Learning Design).

Teacher orchestration of technology-enhanced learning (TEL) processes plays a major role in students’ outcomes, especially in face-to-face classrooms. However, few studies look into the fine-grained details of how such orchestration unfolds, the challenges and cognitive overload that using technologies at a classroom level pose for teachers. This paper proposes a mixed-method approach to the study of orchestration cognitive load, combining physio-behavioural (eye-tracking) and subjective measurements (questionnaires, stimulated recall interviews). We illustrate the approach by applying it to study the orchestration of two technology-enhanced geometry lessons, by a secondary school teacher. The results of our mixed-method analyses highlight the difficulty of classroom-level (as opposed to individual- or group-level) interactions, especially in modelling students’ progress and understanding. Such insights can be useful in the design of new classroom technologies, and to focus researchers’ attention on critical orchestration episodes during their evaluation.

Coaching and reflection are established methods for learning from experiences and peer support at work. They support people with different means: While coaching is a rather formal, planned, structured and systematic process, reflection is rather informal, spontaneous and emergent. Despite these differences, coaching and reflection may complement each other. This helps to overcome barriers of the respective other method and closes a gap between formal-systematic and informal-self-organized approaches of learning at work. In this paper we ask how this complement can be supported by tools and describe an intertwined concept of reflection and coaching called “coflection”. We identify challenges associated with this concept, we present a prototype and we explain how the concept may solve problems at work by using real-world scenarios. The paper contributes to TEL by providing a concept that enables transitions between formal and informal learning.

It is a challenging task to identify eLearning courses parts that have to be revised to best suit learners’ requirements. Reading being one of the most salient learning activities, one way of doing so is to study how learners consume courses. We intend to support course authors (e.g. teachers) during courses revision by providing them with reading indicators. We use the concept of reading session to denote a learner’s active reading period, and we provide several associated reading indicators. In our server-side approach, reading sessions and indicators are calculated using web server logs. We evaluate the relevance of our proposals using logs from a major French eLearning platform. Results are promising: calculated reading sessions are theoretically more precise than other best applicable approaches, and course authors consider suggested indicators to be appropriate to courses revision. Using reading sessions and associated indicators could facilitate authors’ work of course reengineering.

The increasing accessibility of sensors has made it possible to create instructional tools able to present immediate feedback to their users. In order to study how this type of instruction can have an effect on learning, we created the

Presentation Trainer

: a prototype designed to help users to develop their nonverbal communication skills for public speaking. In this paper we present our work in progress on the

Presentation Trainer

, which includes two user studies. The studies showed that participants would gladly use the

Presentation Trainer

to prepare for oral presentations, and pointed out to some considerations required for the design of tools able to effectively support a complex learning task through immediate feedback.

We present an eye-tracking study where we augment a Massive Open Online Course (MOOC) video with the gaze information of the teacher. We tracked the gaze of a teacher while he was recording the content for a MOOC lecture. Our working hypothesis is that displaying the gaze of the teacher will act as cues in crucial moments of dyadic conversation, the teacher-student dyad, such as reference disambiguation. We collected data about students’ video interaction behaviour within a MOOC. The results show that the showing the teacher’s gaze made the content easier to follow for the students even when complex visual stimulus present in the video lecture.

Our previous works have introduced the Tsaap-notes platform dedicated to the semi automatic generation of multiple choice questionnaire providing feedbacks: it reuses interactive questions asked by teachers during lectures, as well as the notes taken by students after the presentation of the results as feedbacks integrated into the quizzes. In this paper, we introduce a new feature which aims at increasing the number of contributions of students in order to significantly improve the quality of the feedbacks used in the resulting quizzes. This feature splits the submission of an answer into several distinct phases to harvest explanations given by students, and then applies an algorithm to filter the best contributions to be integrated as feedbacks in the tests. Our approach has been validated by a first experimentation involving master students enrolled in a computer science course.

This paper presents a Learning Analytics approach for understanding the learning behavior of students while interacting with Technology Enhanced Learning tools. In this work we show that it is possible to gain insight into the learning processes of students from their interaction data. We base our study on data collected through six laboratory sessions where first-year students of Computer Engineering at the University of Genoa were using a digital electronics simulator. We exploit Process Mining methods to investigate and compare the learning processes of students. For this purpose, we measure the understandability of their process models through a complexity metric. Then we compare the various clusters of students based on their academic achievements. The results show that the measured complexity has positive correlation with the final grades of students and negative correlation with the difficulty of the laboratory sessions. Consequently, complexity of process models can be used as an indicator of variations of student learning paths.

Visualizations are increasingly being used to present student interactions and progress with online learning environments as motivations for student engagement with course content. Specifically, visualizations supporting data exploration and peer comparisons have yielded positive results in engagement. In addition, visual narratives have recently started to be used in learning environments to engage learners. This paper introduces VisEN, a visualization framework for semi-automatically constructing explorable visual narratives. VisEN was used during two successive academic years to construct individualized explorable visual narratives for undergraduate learners participating in an online Information Management course. The narratives presented engagement scores, time spent on activities and peer comparisons. This research evaluates the impact the explorable visual narratives had on student course engagement. This paper shows that the explorable visual narratives encouraged the majority of students (that were engaging poorly with course content) to engage with assigned tasks, and subsequently these students improved their engagement levels.

Sustained improvement in student achievement on national standardized tests for low socio economic status (SES) districts is critical for reducing gaps in educational inequality. We report the results of 3 years of implementation of an ICT web-based learning environment in all 11 public schools of a low SES urban district in Chile. This includes 43 fourth grade classes and 1,355 students. This is a Computer Aided Instruction program that promotes whole class collaborative learning with peer support. Effect size on the national standardized fourth grade math test is 0.33, which is three times the national improvement level over the same period and five times the improvement made by a neighboring district with a similar population. On the other hand, the same students did not make any improvements on the national standardized language test. Since each class was taught by the same teacher, only without ICT, we can therefore discount the teacher effect.

Besides game-based learning, gamification is an upcoming trend in education, studied in various empirical studies and found in many major learning management systems. Employing a newly developed qualitative instrument for assessing gamification in a system, we studied five popular LMS for their specific implementations. The instrument enabled experts to extract affordances for gamification in the five categories experiential, mechanics, rewards, goals, and social. Results show large similarities in all of the systems studied and few varieties in approaches to gamification.

Self-Directed Learning (SDL) is gaining interest, as online learning is increasingly learner-centered. FutureLearn courses provide an array of online interactions and content deliveries, which have allowed the authors to investigate a diversity of SDL elements. This preliminary research examines the SDL taking place in three FutureLearn courses, and categorises those learner actions into meaningful elements and dimensions for the learners. The SDL framework by Bouchard [1] is used to interpret the self-reported findings coming from active learners. The research uses a grounded theory approach to look for learner experiences related to four dimensions (algorithmic, conative, semiotic, and economic) of the Bouchard [1] framework, and to discover new dimensions. Various research instruments are used: online surveys, learning logs, and one-onone interviews, all collected pre-, during, or post-course. The initial adaptation of Bouchard’s framework offers insights into SDL, its meaning, and value as perceived by the learners.

In the first years of school, activity books and Montessori-like educational materials are widespread. They satisfy children’s precise psychological needs and result in funded educational practices based on game activity adopted by teachers. These materials are more effective for promoting learning if used in close interaction with an adult, they cannot be customised and the corrective feedback cannot be provided within the appropriate time frame. In this paper, we aim to overcome these limitations by exploiting a Technology Enhanced Learning (TEL) methodology to connect activity books and Montessori-like educational materials. We propose a general architecture for building hyper activity and exercise books called HAB, with three levels: multimedia, multimodality and computing; we describe a first implementation for validating this architecture, Block Magic, and outline development of the architecture under the INF@NZIA DIGI.Tales 3.6 project.

The adoption of mobile devices and context-aware technologies offers the opportunity of designing educational mobile-based games across multiple spaces that enrich the learners’ experience. But producing these games is challenging from both the authoring and technical points of view. This paper proposes a framework to facilitate the design of these games. The framework consists of two elements: (1) a narrative structure, and (2) a platform for its deployment. Both elements defined as a set of templates to be completed for facilitating both the authoring of the narrative and the design of the platform. In order to show a usage example, the framework has been used to develop a mobile-based game for a museum. The game designed has been piloted with 10 students between 6 and 12 years old. The results of the pilot show that it is technically feasible to use this framework to design a mobile-base game across three spaces: a museum, home and a classroom. The students found the activity a good and engaging learning experience.

Group work is an essential activity during both graduate and undergraduate formation. Although there is a vast theoretical literature and numerous case studies about group work, we haven’t yet seen much development concerning the assessment of individual group participants. The problem relies on the difficulty to have the perception of each student’s contribution towards the whole work. We propose and describe a novel tool to manage and assess individual group. Using the collected interactions from the tool usage we create a model for predicting ill-conditioned interactions which generate alerts. We also describe a functionality to predict the final activity grading, based on the interaction patterns and on an automatic classification of these interactions.

Recently, Massive Open Online Courses (MOOCs) have been proposed as relevant instruments for professional development. This paper reports on two editions of the HANDSON MOOC for teacher professional development. The MOOCs use the Learning Design Studio methodology as a pedagogical framework, the Integrated Learning Design Environment (ILDE) as the design infrastructure, and Moodle and Canvas as delivery platforms. The paper summarizes the design of both MOOCs, including the supporting technologies, and presents an analysis of the evolution of teachers’ perceived level of conform with approach and tooling. Data is collected in weekly and final surveys. The results show a general satisfactory level of conform in both MOOCs, which is especially high the last two weeks.

In a case study using quasi-experimental methods (within-subject repeated measures with counterbalancing), differences in students’ attitudes were assessed when they used a wiki with discussion (i.e., an enhanced wiki) and a forum with attached MS Word documents for virtual collaboration on case problems. Data from 63 online learners working with both tools was collected. Statistically significant differences were found on a technology experience measure, in favor of the wiki tool. Further, qualitative data supported this finding. This study is an extension of the authors’ previous work, adding to a holistic picture of collaborative learning using wikis and forums in online learning settings.

This paper presents the initial results of a study where we embrace and test Entwistle’s theory in order to explain the students’ interaction when using interactive learning environments (ILEs) in real conditions. In contrast to others who seek ways of adapting a system to students’ specific learning style, our aim is to find ways of designing an ILE that encourages students’ adoption of a deep approach to studying and discourages a surface approach. In this paper we focus only on the relationship between two subscales of the Approaches and Study Skills Inventory for Students (the deep subscale of interest in ideas and surface subscale of fear of failure), and metrics occurring from usage in a specific ILE. The results point to insights for instructors regarding the integration of ILEs in classrooms, as well as suggestions regarding the design of features which encourage a deep approach to studying.

The lack of open-access tool for the enhancement and promotion of soft skills is bringing the e-learning community to new educational challenges. The paper describes the implementation of ENACT, an online serious game for the standardised psychometric assessment and training of users’ negotiation skills through the interaction with virtual artificial agents. The assessment process is divided into 8 scenarios based on real life situations and investigates the user negotiation styles in relation to Rahim’s conceptualization of five different styles of handling conflict. Need analysis data and preliminary testing results of the platform are presented.

Informal learning in online knowledge communities (OKCs) comprises visitor inquiries on specific topics. Learning can occur only if the OKC adequately respond. This study aims to predict OKC response, using a social learning analytics approach based on computational linguistics and Bakhtin’s theory of dialogism. Observing the blog topic (cooking vs. politics & economics) and the visitor inquiry format (off-topic vs. on-topic), a field experiment with a 2 × 2 factorial design was conducted on a sample of N = 68 blogger communities with a total of 25,303 members. For the entire sample, the community response was influenced only by the inquiry format. In a separate examination of experimental groups, only for one examined topic (cooking) this remained true, while for the other (politics & economics) the community response only depended on the previously established dialog quality. The findings suggest identification criteria for responsive communities, which can support OKC integration in learning environments.

In very recent years, the advent of Learning Analytics (LA) has resulted in a number of publications reporting on empirical research. This literature overview identifies the mainstream of empirical LA research, and emphasizes insufficiently investigated directions that display a higher innovation potential. The mainstream consists of learning trajectory visualizations aimed to predict learner success. Single studies prove innovative by addressing in particular: informal educational settings, video and audio records as data sources, automated assessment and error/misconception analysis. A central issue of empirical LA research consists of the frequent lack of an explicit theoretical framework from educational perspective. We maintain that educational and psychological theories are urgently needed for significant progress of upcoming LA research.

In this paper we present a participatory approach to design Logic-Muse, an Intelligent Tutoring System that helps learners develop reasoning skills in multiple contexts (situations). The study was conducted jointly with the active participation of experts in the field of logic and the psychology of reasoning. An explicit catalogue of systematic errors in classical logic is built, followed by an explicit representation and encoding of the semantic knowledge behind reasoning as well as reasoning procedural structures and meta-structures. Logic-Muse innovates through its design rationale, which leads to strong structures on which learning is based. It also innovates with the projection of reasoning skills in a variety of well-defined classes of situations to ensure an absolute mastery of reasoning skills regardless of the content effect.

We report two 6-week studies, each with 10 participants, on improving time management. In each study a different interventions was administered, in parallel to otherwise regular work: In the self-tracking setting, participants used only an activity logging tool to track their time use and a reflective practice, namely daily review of time use, to improve time management. In the coaching setting, participants did the same, but additionally received weekly bilateral coaching. In both settings, participants reported learning about time management. This is encouraging, as such self-directed learning is clearly cheaper than coaching. Only participants in the coaching setting however improved their self-assessment with respect to predefined time management best practices.

This article presents a comparison of the effects of inputoutput location (co-located versus discrete) on user performance in a tangible user interface (TUI) system. We conducted a mobile eye-tracking study with two different versions of a TUI system and, despite similar performances in both conditions, our findings revealed differences in the users gaze patterns, shedding new light on the underlying cognitive processes.

A key area of application for Learning Analytics (LA) and Educational Data Mining (EDM) is lifelong learner modeling. The aim is that data gathered from different learning environments would be fed into a personal lifelong learner model that can be used to foster personalized learning experiences. As learning is increasingly happening in open and networked environments beyond the classroom and access to knowledge in these environments is mostly context-sensitive and interest-driven, learner’s contexts and interests need to constitute important features to be modeled. The context data of a learner as it is already represented by the Learning Context Data Model (LCDM) specification, describes the learner’s activities, her biological conditions, as well as the characteristics of the learning environment. Towards a lifelong learner model, a model consisting of context data can further be refined with an evolving set of interests. This paper describes an approach to extend the existing LCDM specification with interests, taking into account the importance of the interests as well as their evolution over time.

Video lectures are a valuable educational tool in higher education to support or replace face-to-face lectures in active learning strategies. In 2007 the Universitat Polit‘ecnica de Val‘encia (UPV) implemented its video lecture capture system, resulting in a high quality educational video repository, called poliMedia, with more than 10.000 mini lectures created by 1.373 lecturers. Also, in the framework of the European project transLectures, UPV has automatically generated transcriptions and translations in Spanish, Catalan and English for all videos included in the poliMedia video repository. transLectures’s objective responds to the widely-recognised need for subtitles to be provided with video lectures, as an essential service for non-native speakers and hearing impaired persons, and to allow advanced repository functionalities. Although high-quality automatic transcriptions and translations were generated in transLectures, they were not error-free. For this reason, lecturers need to manually review video subtitles to guarantee the absence of errors. The aim of this study is to evaluate the efficiency of the manual review process from automatic subtitles in comparison with the conventional generation of video subtitles from scratch. The reported results clearly indicate the convenience of providing automatic subtitles as a first step in the generation of video subtitles and the significant savings in time of up to almost 75% involved in reviewing subtitles.

The work presented in this article addresses CSCL settings in which students work with tablets in classrooms. The objective is to study how to equip teachers with tablets to monitor students’ progress and intervene when required. We propose a model that provides teachers with both quantitative and qualitative run-time feedback based on the students’ progress. An implementation of this model was tested in the context of an activity called negotiated dictation. The results suggest that the model and associated tools are easy for teachers to use and allow them to satisfactorily monitor the progress of both the class and individual students or groups.

In this paper we investigate patterns of resource usage for exam preparation based on a resource intensive blended learning course. To this end, we analyzed a blended learning, online course facilitated by Moodle. During the course, the students had to work individually and in teams. Furthermore, they were given access to a broad spectrum of learning resources such as videos, slides, wiki articles and quizzes. The logfiles obtained from Moodle were further processed and analyzed. Our analysis approach is based on association rule as well as sequential pattern mining. The results indicate that students’ activity with respect to resource usage follows common patterns during exam preparation either on the individual or the group level. These patterns also relate to the performance of students and to reflect their prior collaborative experience.

ReaderBench

is an automated software framework designed to support both students and tutors by making use of text mining techniques, advanced natural language processing, and social network analysis tools.

ReaderBench

is centered on comprehension prediction and assessment based on a cohesion-based representation of the discourse applied on different sources (e.g., textual materials, behavior tracks, metacognitive explanations, Computer Supported Collaborative Learning – CSCL – conversations). Therefore,

ReaderBench

can act as a Personal Learning Environment (PLE) which incorporates both individual and collaborative assessments. Besides the a priori evaluation of textual materials’ complexity presented to learners, our system supports the identification of reading strategies evident within the learners’ self-explanations or summaries. Moreover,

ReaderBench

integrates a dedicated cohesion-based module to assess participation and collaboration in CSCL conversations.

We present KnowBrain (KB), an open source Dropbox-like knowledge repository with social features for informal workplace learning. KB enables users (i) to share and collaboratively structure knowledge (ii) to access knowledge via sophisticated content- and metadata-based search and recommendation, and (iii) to discuss artefacts by means of multimedia-enriched Q&A. As such, KB can support, integrate and foster various collaborative learning processes related to daily work-tasks.

Communicate! is a serious game for practicing communication skills. It supports practicing interpersonal communication skills between a health care professional such as a doctor or a pharmacist, or a (business) psychologist, and a patient or client. A player selects a scenario, and holds a consultation with a virtual character. In the consultation, the player chooses between the various options offered in the scenario. The player scores on the learning goals addressed by the scenario, and gets immediate feedback through the effect of the choice between the answer options on the utterance and emotion of the virtual character. Communicate! also offers an editor for scenarios. A scenario is a graph-like structure, extended with several constructs to avoid the development of repetitive structures. We have performed several experiments with Communicate!, both with students to evaluate the use of Communicate! in various programs at Utrecht University, and with teachers to evaluate the development of scenarios for Communicate!

Recent technological advances in mobile devices enable the connection of classrooms with other virtual and physical spaces. Some approaches aim at helping teachers carry out learning situations across such spaces. However, these proposals tend to be isolated from other activities in teachers’ current common practices, and do not allow teacher-controlled flexibility of what students do during the enactment. Aiming to overcome such limitations, the Bucket-Server is a system that enables teachers to include

learning buckets

in their learning situations: containers of learning artifacts generated and/or consumed acrossspaces by students during the enactment. Teachers create

learning buckets

at design time, configuring them with constraints to regulate the degree of freedom offered to the students. These

learning buckets

can be integrated into multiple existing technologies used in different educational spaces (e.g., web, physical and 3D virtual world spaces), thus helping embed buckets in the teachers’ current common practices.

The emergence of Massive Open Online Courses (MOOCs) has caused a high disrupting effect on online education. One of the most extended MOOC platforms is Open edX. There is a demanding necessity by the instructors and students of these courses to provide timely analytics tools that can help understand the learning process at any moment. In this direction we have developed the Add-on of learNing AnaLYtics Support for open Edx (ANALYSE), which is our learning analytics contribution for Open edX. In this demonstration paper we will provide guidelines on how to use some of the ANALYSE video visualizations in order to detect problems in video resources, so that the learning process can be improved.

The paper presents the evolution of Presentation Trainer, a prototypical sensor-based toolkit that works as a public speaking instructor. It tracks the learner’s body posture, movements and voice in order to provide instructional feedback on nonverbal communication skills. Based on our design-based research the current version of the Presentation Trainer is able to provide the learner with the type of feedback that it considers to be appropriate according to the learner’s performance; it includes haptic feedback helping to reduce the learner’s cognitive load.

Automated assessment systems for the field of mathematics need to tackle a number of challenging problems. Existing systems focus on the processing of mathematic expressions and their different representations (e.g.

x

1/2

vs.

$\sqrt{x}$

). In order to correctly assess a student’s solution approach, a system has to check intermediate steps and conclusions. Typically, this assessment fails completely in the presence of a small oversight error at the beginning of an exercise. In this paper, we will show, how the idea of unit testing from the field of computer science may be used to detect and handle follow up and cascading errors in mathematic exercises. Thus, resulting in a fairer grading outcome, which is closer to manual grading. The developed technique may be used for large scale (online) courses or acceptance tests.

A fundamental objective of human-computer interaction research is to make systems that are seamlessly integrated into daily life activities. Hence, the challenge is not only to make information available to people at any time, at any place, and in any form, but specifically to say the right thing at the right time in the right way. On the other hand, the proliferation of sensor technology is facilitating the scaffolding and customization of smart learning environments. This manuscript presents an ecology of resources comprising NFC, BLE and Arduino technology, orchestrated in the context of a learning environment to provide smoothly integrated feedback via ambient displays. This ecology is proposed as a suitable solution for self-regulated learning, providing support for setting goals, setting aside time to learn, tracking study time and monitoring the progress. Hereby, the ecology is described and intriguing research questions are introduced.

Augmented reality is a technology that can be used to deploy Problem Based Learning activities that immerse students into meaningful learning activities by overlaying digital information; such as audio, video, 3D simulations, etc., to the vision of the real world. This paper explores the integration of augmented reality based activities in web courses providers and proposes a communication flow between an augmented reality application and a web based learning course provider.

A self-regulated oriented ePortfolio as a dynamic social networking tool, orchestrated along the processes of Self-Regulated Learning (SRL) with career management skills was designed. The aim of this study is to examine how time management can be positively influenced through the implementation of the ePortfolio. We conducted a quasi-experimental research with comparison groups in pre/post-tests in order to examine time management as a behavioral selfregulatory process for academic performance. The findings revealed that students tend to manage time effectively, make schedules and allocate time after the completion of the ePortfolio. Further research should measure students’ SRL and the relations among cognitive, affective, behavior and context processes.

Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for general purposes (e.g. Twitter data, Amazon reviews), there is no research addressing this issue in an educational context, despite the increased use of social media in education. In this paper we experiment with several machine learning techniques, features and preprocessing levels to identify sarcasm from students’ feedback collected via Twitter.

With the MOOC movement, education stakeholders are taking part of a pedagogical renewal. These dynamics present different advantages such as: massiveness, openness, accessibility, etc. However, it raises particular issues related to the dropout. To remedy to this issue, a promising lead resides in supporting learners’ motivation and engagement. To reach this goal, innovative pedagogic strategies and /or sophisticated Instructional design, personalization or even adaptability are needed. The purpose of this paper is to examine the point of view of literature, the dropout issue and possible solutions to motivate learners.

Our review examines the literature on Serious Games used as learning tools for people with intellectual disabilities. Although intellectual disabilities are a very broad field where each individual has very specific characteristics, it would be beneficial to have general evidence-based recommendations about how to design videogames adapted to their cognitive requirements. Thus, the first step of our investigation is to identify and review the available literature on Serious Games for intellectual disabilities classifying them according to the learning outcomes associated. Search terms identified 43 papers covering this topic and our review presents the initial results. A second aim is to understand the mechanics designed, the methods used in the investigation and the data obtained. The final goal is to identify what is working in this kind of games and how this can be generalized into a methodology to simplify the creation of more effective games for people with intellectual disabilities.

Virtual Learning Environments (VLEs) such as Moodle or Sakai are now commonplace in many educational settings, but the limited set of built-in tools (e.g. chats or forums) is often mentioned as a drawback. While successful solutions to integrate Software as a Service (SaaS) tools are reported in the literature (e.g. IMS Basic LTI and GLUE!), there are other non-SaaS tools with potential for education that cannot be integrated in VLEs. These include single-user standalone tools that are run on local computers without a web-based interface (e.g. Matlab), but also virtual machines and laboratories that are common in Computer Science-related disciplines. This paper addresses the integration of these non-SaaS tools in VLEs, proposing an architecture to help teachers to select and configure non-SaaS tools using existing integration approaches from VLEs, but that also relies on cloud infrastructures for provisioning and deploying these tools transparently to the end users.

We present a preliminary user study in an e-learning environment aimed to adapt and validate generic mechanics and player types proposed in the gamification literature. We incorporate well-known gamification mechanics into a number learning activities, implemented them as functionalities of an e-learning system, and investigate the learning effectiveness of the proposed mechanics, as well as the relations between the mechanics and their assumed player types.

Recent introduction of modern computer technology into schools and universities presented new challenges to mathematics teachers. On one hand, powerful computer tools have emerged that allow for rich animation and visualization. On the other hand, the teachers are not ready to give up using the blackboard, which is still their main workspace. This work presents a tool for teachers, that allows for more freedom than the fixed lecture slides and helps illustrating rules for transforming mathematical expressions and solving equations. Using this tool, the teacher can automatically generate solutions for mathematical problems on the fly and interactively present these to the students step by step. The solution is then blended out and the students are offered to solve similar problems on their computers interactively using the system.

This tool is a part of a larger toolkit used within several innovative Blended Learning Bridging Courses in Mathematics at Leuphana University in Lüneburg, held in a computer-equipped classroom.

Currently, there are many problems of the application development of E-Assessment such as the difficulty to use the assessment object from a platform to another one. In addition, the domain model reuse rate is very low in various application systems, and hardness to guarantee the consistency between designs and codes. Therefore, to resolve these problems, we need an approach aiming to automate the modeling and coding processes in e-assessment system. The present study describes an approach, based on service cloud computing, for integrating e-assessment functionalities of candidate LMS systems into a generalized e-assessment process.

Personalized applications like recommendation systems or open adaptive hypermedia require to facilitate reuse and interoperability of educational resources. Thus we have to solve the problem of discovering educational datasets and the problem of the fragmented landscape of competing metadata schemas. In this paper, we compare a subset of metadata schemas used by educational datasets obeying the Linked Open Data principles and we propose mappings between them.

Interest in eLearning environments is increasing, as well as in digital textbooks and gamification. The advantages of gamification in the context of education have been proven. However, gamified educational material, such as gamified digital textbooks and systems, are scarce. As an answer to the need for such material, the framework GEL (Gamification for EPUB using Linked Data) has been developed. GEL allows to incorporate gamification concepts in a digital textbook, using EPUB 3 and Linked Data. As part of GEL, we created the ontology Gamification Ontology (GO), representing the different gamification concepts, and a JavaScript library. Using GO allows to discover other gamified books, to share gamification concepts between applications and to separate the processing and representation of the gamification concepts.

We live immersed in a technological world. Learning is not an exception; most classrooms are equipped with multiple devices intended to improve the learning process for students. Especially for novice teachers, there is a need to provide usable technological tools that help them with their counterpart teaching tasks. This paper presents a set of teacher authoring tools to facilitate the tasks of identifying learning

tricky topics

, noting student difficulties, and creating quizzes for knowledge evaluation. The resulting quizzes, generated by these tools, are used at the start of learning activities, where students explain

tricky topics

by creating educational videos that use juxtaposition, and which are then shared and commented among peers.

Pervasive classroom environments with interconnected smart devices permit enacting diverse pedagogical models in education. This paper proposes an extensible architecture integrating smart display, smart phones and wearable devices to support flexible orchestration of dynamic collaborative learning activities in face-to-face educational scenarios. The paper motivates an architectural design and describes its main components based on existing systems like Signal Orchestration System (SOS) and a multi-screen cooperation middleware. An applicable scenario illustrates the usage of proposed architecture in which wearable devices are used to indicate orchestration mechanisms (group formation, change of activity), a shared display visualizes tasks with summary of the orchestration and activity progress for collective awareness and smart phones are used to interact with the shared display and complete the activities.

This paper uses a project-based learning methodology in higher education to analyse its relation to a theoretical framework of competency. Based on this analysis, we propose a set of technological tools to support the development of competency at the university level as well as a set of indicators to systematize the assessment process. Finally, indicators are related to data that can be obtained from these technological tools. This is the basis for additional work on learning analytics that is used to support the assessment of a project-based learning approach.

This paper proposes a framework which attempts to address the barriers to the development of successful educational design research through a process which identifies gaps in current practices and devises innovations to target them. Educational design research assumes an ambitious position: a dual commitment to understand and contribute to both theory and practice. This task is confounded by the complexity of the domain and the inherent multi-stakeholder nature of most initiatives. Three barriers to success are identified: the shortage of mechanisms for cross-stakeholder dialogue, the failure to account for existing practices and contexts, and the rigid processes dictated by the dynamics of research projects. We report early findings from an attempt to address these barriers, based on an extension and adaptation of the Participatory Pattern Workshop (PPW) methodology (This paper has received the support of the Learning Layers project co-funded by the European Commission; Grant Agreement Number 318209; http://learning-layers.eu/).

This paper is a continuation of earlier studies involving experiments with Communication students using a Java-Applet running in the student’s browser, developed using the Prolog programming language as embodied in a Java implementation called Prolog+CG. This makes it possible to support logic teaching through the use of interactive systems and also to do learning analytics based on the log-data from the use of the systems. The aim of the present paper is to investigate whether the use of gamification and an interactive proof system formulated in terms of controlled natural language can be helpful in logic teaching in order to obtain a better understanding of syllogistic reasoning.

The objective of this study is to verify whether Virtual Reality together with relaxation techniques incorporated into it improve the students’ attention levels. To do so we made an intervention in an “Initial Vocational Qualification Program” group of Spanish high school in the Valencia metropolitan area. We had 13 students aged between 16 and 19 that participated in the study using an Oculus Rift virtual reality headset. These students were subject to an experimental environment that simulates a beach sunset. They had to perform breathing exercises and concentrate their attention on their breathing, the rhythm of the waves and on flowers of different colors that were appearing in the environment. Experimental results have revealed that levels of attention measured with the Trail Making Test (TMT) were improved when participants had the help of the virtual environment.

Massive Open Online Courses (MOOCs) are changing the contours of the teaching and learning landscape. Assessment covers an important part of this landscape and may be a key driver for learning. This paper presents preliminary results of a qualitative study that investigated learners’ views on assessment types within a MOOC. A thematic analysis of learners’ interactions in a MOOC Facebook Group and twelve online interviews of learners in the same MOOC reveal that participants identify benefits in peer assessment but they prefer automated assessment as an already-known type. Self-assessment was not preferred by these learners. They reported that clear guidance assists them to carry out peer assessment more effectively. Some learners favored the combination of assessment types, as each of them serves a different purpose for their learning. The learners’ socio-cultural context emerged as a theme affecting both their learning and assessment activities and will be considered for future research.

This study explores approaches of implementing adaptation with the Learning Activity Management System (LAMS) as well as the technological knowledge and skills that designers develop through the creation of personalised lessons in LAMS. Postgraduate students used LAMS to design and personalise courses. To determine the ways in which adaptation was implemented, we conducted a comparative analysis among the personalised courses. To explore the technological knowledge that designers develop through course personalisation, we used specific criteria inspired by the Technological Pedagogical Content Knowledge framework (TPACK). Concluding, all participants enriched personalised courses and elaborated on various adaptation design issues.

Reflection and collaborative reflection are common means for learning at work. Based on four studies on tool supported collaborative reflection, which created insights on barriers and opportunities for such support, we describe a concept of augmenting tools with reflection and a prototype showing how the concept can be implemented in typical TEL environments.

Students are supposed to work and learn when they are in the classroom, but how are they learning? Answering this question is not so easy, but perhaps knowing the learning activities of the student and following his or her learning progress can be good supporting mechanisms. The PresenceClick environment is intended to let teachers and students nimbly capture what happens in class to provide them, in return, with information about students’ behavior during class. The system involves two platforms -a web system and a mobile application- that working together allow recording of students’ interactions and provide updated graphical visualizations about their behavior.

This paper presents the potential of a social semantic infrastructure that implements an Actor Artifact Network (AAN) with the final goal of supporting learning analytics at the workplace. Two applications were built on top of such infrastructure and make use of the emerging relations of such a AAN. A preliminary evaluation shows that an AAN can be created out of the usage of both applications, thus opening the possibility to implement learning analytics at the workplace.

A prediction system to early detect learning problems is presented. The starting point is a gamified learning system from which a massive set of usage and learning data is collected. They are analyzed using Machine Learning techniques and a prediction of each student’s performance is obtained. The information is weekly presented as a progression chart, with valuable information about students’ progression. The system has a high degree of automation, is progressive, uses learning outcomes as well as usage data, allows the evaluation and prediction of the acquired skills, and contributes to a truly formative assessment.

This paper reports results from a case study that investigated creating and sharing knowledge arising from experiences with the

Ach so!

mobile app for video annotation in healthcare education. The qualitative content analysis of the interview data indicated that Ach so! enhanced reflection when the students saw their action from videos and thus were able to evaluate their own and group performance as external observers and to create knowledge on their experiences. Ach so! promoted knowledge sharing when the students together reflected their performance and annotated successful and failed incidents. Research outcomes contributed to the design of the Ach so! and workplace practices, and suggested applying Ach so! to dynamic learning contexts and scaling the applicability of Ach so! to informal and non-formal learning contexts at workplaces.