Computational Thinking (CT), particularly abstraction, is essential in engineering education, enabling students to break down complex systems into manageable parts. Abstraction helps learners focus on key elements of a problem, ignoring extraneous details. The PGK framework, suggested by Per-renet, Groote, and Kaasenbrood, defines abstraction across four cognitive levels: problem, algorithm, program, and execution. At a higher education institution that focuses on engineering education, we assessed students' abstraction skills using sorting algorithms, chosen for their foundational role and suitability for testing such skills. Our study focused on two areas: (1) the performance of computer science (CS) and non-CS students on algorithmic abstraction tasks, and (2) how factors like demographics, training, programming proficiency, and self-assessed abstraction mastery correlate with task performance. Results showed that all students, especially non-CS majors (including Engineering), need stronger skills at the algorithm, program (coding algorithms), and execution (code functionality) levels. Many non-CS students overestimated their abilities, highlighting a gap in mastery. Students with programming experience performed better, underscoring the importance of hands-on training. These findings suggest interventions for non-CS students are needed to gain experience in programming and to bridge the gap between perceived and actual skills. Future research should focus on discipline-specific curricula and long-term studies to ensure that all students develop the essential CT skills for the digital era.

Goal setting is the first and driving stage of the self-regulated learning cycle. Studies have shown that supporting goal setting is an effective means of improving academic performance among higher education students. However, doing so can be complex and resource intensive. In this study, a goal-setting conversational agent was designed and deployed to support higher education students in setting academic goals. Across 5-weeks, we tested the effects of goal-setting prompts (guided vs. unguided) and adaptive feedback (with vs. without) when delivered via a goal-setting conversational agent. We explored the effects of these supports (i.e., guidance and feedback) on students’ 1) goal quality and 2) goal attainment. Findings showed that guidance and feedback combined had the largest positive effect on goal quality. They also revealed that guidance alone produced initially high-quality goals which decreased in quality overtime, whereas feedback had a delayed but cumulative effect on quality across multiple goal setting iterations. However, neither guidance nor feedback had significant effects on goal attainment, and there was no significant relationship between goal quality and attainment. This study provides insights into how a goal-setting conversational agent and adaptive feedback can be used to support the academic goal setting process for higher education students.

Agent-based training systems can enhance people's social skills. The effective development of these systems needs a comprehensive architecture that outlines their components and relationships. Such an architecture can pinpoint improvement areas and future outlooks. This paper presents ARTES: a general architecture illustrating how components of agent-based social training systems work together. We studied existing systems and architectures for training and tutoring to design ARTES and identify its essential components and interaction characteristics. ARTES comprises two core components: the agent simulation of social situations, and educational elements to provide guided learning. We link ARTES's crucial components to four primary learning theories (behaviourism, cognitivism, social cognitive theory, and constructivism) to illustrate the role of agent simulation and tutoring elements in establishing desired learning outcomes. Furthermore, we map ARTES's components against eight architectures, 43 systems and three tools to indicate the components' relevance, completeness, generalisation, and deployment potential across contexts. In addition to ARTES, the paper also contributes by identifying future improvements and research directions, such as the agent's thinking, tutoring methods, knowledge transfer, and ethical implications. We believe ARTES can help bridge the gap between virtual human simulations and impactful educational learning, offering training system developers desirable features like understandability and adaptability.

Evaluation of educational innovation at the course level is dominated by frameworks that are linear, built on simple models, lack grounding in theory, and are generally not flexible enough to provide actionable recommendations for improvements. Moreover, the guidelines provided by existing literature are difficult to transfer to other contexts as most of these are aimed at specific innovations only. Therefore, there is a need for a new approach that is flexible enough to enable adaptation to different contexts, and that draws on the strengths of existing evaluation traditions. This paper forms a starting point for a larger research initiative for developing a comprehensive innovation evaluation framework. The context of the paper is a project based within the four universities of technology in The Netherlands (4TU) dedicated to strengthening collaboration in engineering education and research needed to take on global societal problems. The potential reach of our framework has implications for the wider field. This paper describes the results of an exploratory literature review to draw on the strengths of various evaluation theories to develop a new approach to evaluating educational innovation in courses. Value, Methods, and Use are the main components identified for this approach. Secondly, we developed a workshop to pilot this approach. Lastly, the workshop was presented to educational researchers, engineering educators, and educational advisors. We share lessons learned from the workshop and conclude with descriptions of future research to refine the framework to prepare its application in real innovation initiatives.

Computational Thinking (CT) is vital in today's digital era, especially in Engineering Education. While no official policy or teaching framework on CT education has been established in the Netherlands, a Western European country, there have been various initiatives for the integration of CT into the curriculum. Recognizing the crucial role of teachers in CT integration, we surveyed the perceptions and intentions of teachers in tertiary education in the Netherlands. Our survey encompassed two aspects: (1) teachers' perceptions of CT, and (2) their intentions to integrate CT into pedagogical activities. 38 teachers, mostly in Engineering Education, from across the Netherlands completed the questionnaire based on the UTAUT framework. Regarding CT perceptions, our investigation reveals that teachers possess an inadequate understanding of the relationship between CT and Computer Science, have limited training experiences in CT, and hold differing opinions on when and which constructs of CT should be integrated into different domains. Concerning teachers' intentions to integrate CT, the results exhibited a strong positive correlation between performance expectancy, attitude towards CT, and behavioral intention to implement CT in learning activities. To foster the integration of CT in tertiary education, our findings suggest the need for further development of higher education teacher training programs focused on CT and its relation to CS. Additionally, there is a call for further exploration of how to enhance teachers' performance expectancy and effort expectancy.

Describing and analysing learner behaviour using sequential data and analysis is becoming more and more popular in Learning Analytics. Nevertheless, we found a variety of definitions of learning sequences, as well as choices regarding data aggregation and the methods implemented for analysis. Furthermore, sequences are used to study different educational settings and serve as a base for various interventions. In this literature review, the authors aim to generate an overview of these aspects to describe the current state of using sequence analysis in educational support and learning analytics. The 74 included articles were selected based on the criteria that they conduct empirical research on an educational environment using sequences of learning actions as the main focus of their analysis. The results enable us to highlight different learning tasks where sequences are analysed, identify data mapping strategies for different types of sequence actions, differentiate techniques based on purpose and scope, and identify educational interventions based on the outcomes of sequence analysis.

From an early age, girls may opt out of Computer Science (CS) for not fitting the CS stereotypes of being male, asocial and technology-oriented. These stereotypes might be strengthened by children's books on programming, but little is known about this. Therefore, this paper explores the gender, social interactions and interests of characters illustrated in ten popular extracurricular Scratch and Python children's books. We found more masculine than feminine characters in all but one book. Furthermore, nearly half of the characters are illustrated alone, and 15% are interacting with computers & robots. Over two-thirds of the characters fit at least one stereotypical trait. With this paper, we aim to create awareness of stereotypes in CS books among creators, publishers and buyers. Making and using more inclusive CS materials will help close the gender gap.

Background and Context. Increasing gender diversity in the field of Computer Science (CS) benefits the economy as well as gender equality. However, several obstacles - including underdeveloped CS interests, lack of programming experience, and a misfit with the stereotypes of computer scientists - prevent women from entering the field. Although these barriers develop from an early age, research focused on children is limited. Furthermore, limited work is done within European countries.

Motivation. Many people interested in learning a programming language choose online courses to develop their skills. The concept of variables is one of the most foundational ones to learn, but can be hard to grasp for novices. Variables are researched, but to our knowledge, few empirical observations on how the concept is taught in practice exist. Objective. We investigate how the concept of variables, and the respective naming practices, are taught in introductory Massive Open Online Courses (MOOCs) teaching programming languages. Methods. We gathered qualitative data related to variables and their naming from 17 MOOCs. Collected data include connections to other programming concepts, formal definitions, used analogies, and presented names. Results. We found that variables are often taught in close connection to data types, expressions, and program execution and are often explained using the 'variable as a box' analogy. The latter finding represents a stronger focus on 'storing values', than on naming, memory, and flexibility. Furthermore, MOOCs are inconsistent when teaching naming practices. Conclusions. We recommend teachers and researchers to pay deliberate attention to the definitions and analogies used to explain the concept of variables as well as to naming practices, and in particular to variable name meaning.

Reading on digital devices has become more commonplace, while it often poses challenges to learners’ attention. In this study, we hypothesized that allowing learners to reflect on their reading phases with an empathic social robot companion might enhance learners’ attention in e-reading. To verify our assumption, we collected a novel dataset (SKEP) in an e-reading setting with social robot support. It contains 25 multimodal features from various sensors and logged data that are direct and indirect cues of attention. Based on the SKEP dataset, we comprehensively compared the difference between HRI-based (treatment) and GUI-based (control) feedback and obtained insights for intervention design. Based on the human annotation of the nearly 40 hours of video data streams from 60 subjects, we developed a machine learning model to capture attention-regulation behaviors in e-reading. We exploited a two-stage framework to recognize learners’ observable self-regulatory behaviors and conducted attention analysis. The proposed system showed a promising performance with high prediction results of e-reading with HRI, such as 72.97% accuracy in recognizing attention regulation behaviors, 74.29% accuracy in predicting knowledge gain, 75.00% for perceived interaction experience, and 75.00% for perceived social presence. We believe our work can inspire the future design of HRI-based e-reading and its analysis.

With the growing interest in programming skills in society, programming will inevitably become part of national curricula. The research presented on this poster aims to address programming for everyone and hopes to contribute to the accessibility of programming lessons for both students and teachers with various backgrounds. In order to do so, we approach the learning and teaching of a programming language from a natural language perspective, and in particular, we focus on reading code, including one of the most important programming concepts: variables.

Human attention is critical yet challenging cognitive process to measure due to its diverse definitions and non-standardized evaluation. In this work, we focus on the attention self-regulation of learners, which commonly occurs as an effort to regain focus, contrary to attention loss. We focus on easy-to-observe behavioral signs in the real-world setting to grasp learners’ attention in e-reading. We collected a novel dataset of 30 learners, which provides clues of learners’ attentional states through various metrics, such as learner behaviors, distraction self-reports, and questionnaires for knowledge gain. To achieve automatic attention regulator behavior recognition, we annotated 931,440 frames into six behavior categories every second in the short clip form, using attention self-regulation from the literature study as our labels. The preliminary Pearson correlation coefficient analysis indicates certain correlations between distraction self-reports and unimodal attention regulator behaviors. Baseline model training has been conducted to recognize the attention regulator behaviors by implementing classical neural networks to our WEDAR dataset, with the highest prediction result of 75.18% and 68.15% in subject-dependent and subject-independent settings, respectively. Furthermore, we present the baseline of using attention regulator behaviors to recognize the attentional states, showing a promising performance of 89.41% (leave-five-subject-out). Our work inspires the detection & feedback loop design for attentive e-reading, connecting multimodal interaction, learning analytics, and affective computing.

Collaboration is one of the four important 21st-century skills. With the pervasive use of sensors, interest on co-located collaboration (CC) has increased lately. Most related literature used the audio modality to detect indicators of collaboration (such as total speaking time and turn taking). CC takes place in physical spaces where group members share their social (i.e., non-verbal audio indicators like speaking time, gestures) and epistemic space (i.e., verbal audio indicators like the content of the conversation). Past literature has mostly focused on the social space to detect the quality of collaboration. In this study, we focus on both social and epistemic space with an emphasis on the epistemic space to understand different evolving collaboration patterns and collaborative convergence and quantify collaboration quality. We conduct field trials by collecting audio recordings in 14 different sessions in a university setting while the university staff and students collaborate over playing a board game to design a learning activity. This collaboration task consists of different phases with each collaborating member having been assigned a pre-fixed role. We analyze the collected group speech data to do role-based profiling and visualize it with the help of a dashboard.

Learning analytics dashboards (LADs) are designed as feedback tools for learners, but until recently, learners rarely have had a say in how LADs are designed and what information they receive through LADs. To overcome this shortcoming, we have developed a customisable LAD for Coursera MOOCs on which learners can set goals and choose indicators to monitor. Following a mixed-methods approach, we analyse 401 learners’ indicator selection behaviour in order to understand the decisions they make on the LAD and whether learner goals and self-regulated learning skills influence these decisions. We found that learners overwhelmingly chose indicators about completed activities. Goals are not associated with indicator selection behaviour, while help-seeking skills predict learners’ choice of monitoring their engagement in discussions and time management skills predict learners’ interest in procrastination indicators. The findings have implications for our understanding of learners’ use of LADs and their design.

The current study investigated the role of trust in students' attitudes towards personal data sharing in the context of e-assessment, and whether this is different for students with special educational needs and disabilities (SEND). SEND students were included as a special target group because they may feel more dependent on e-assessment technologies, and thus, more easily consent to personal data sharing. A mixed methods research design was adopted combining an online survey and a focus group interview to collect quantitative and qualitative data. The findings suggest that a considerable number of students trust e-assessment technology that does not require the physical presence of a supervisor. Students who trust are more likely to perceive e-assessment technology as having no disadvantages, and are more willing to share their personal data for e-assessment purposes. The responses of SEND and non-SEND students do not differ significantly in terms of trust. However, the results diverge regarding the relation between trust and perception of e-assessment technology as having no disadvantages. Practical implications for informed consent are discussed.

Over the past few years, massive online open courses (MOOCs) have been increasingly identified as technologies that could transform education, by providing free and high-quality content to anyone with an Internet connection. However, despite these potentials, MOOCs generally fail to keep their participants on board. One of the reasons for this phenomenon can lie in a lack of participants’ engagement. Social presence and sense of community (SoC) theories claim that a user in an online shared environment may feel more engaged if s/he perceives the others as ‘real persons’ and feels part of a community. Therefore, we developed our game elements with the purpose of developing social presence and SoC among MOOC users. The results of our experiment, from one side, show that our gamification design did positively impact users’ development of social presence and SoC, as well as their learning performance. From the other, data did not confirm that higher levels of social presence and SoC corresponded to higher engagement of MOOC users. These results have important implications for the field by enriching it with a more technologically enhanced approach towards implementing gamification, and by augmenting the social potentials of MOOCs.

This paper introduces the Visual Inspection Tool (VIT) which supports researchers in the annotation of multimodal data as well as the processing and exploitation for learning purposes. While most of the existing Multimodal Learning Analytics (MMLA) solutions are tailor-made for specific learning tasks and sensors, the VIT addresses the data annotation for different types of learning tasks that can be captured with a customisable set of sensors in a flexible way. The VIT supports MMLA researchers in 1) triangulating multimodal data with video recordings; 2) segmenting the multimodal data into time-intervals and adding annotations to the time-intervals; 3) downloading the annotated dataset and using it for multimodal data analysis. The VIT is a crucial component that was so far missing in the available tools for MMLA research. By filling this gap we also identified an integrated workflow that characterises current MMLA research. We call this workflow the Multimodal Learning Analytics Pipeline, a toolkit for orchestration, the use and application of various MMLA tools.

Collaboration is an important 21st century skill; it can take place in a remote or co-located setting. Co-located collaboration (CC) is a very complex process which involves subtle human interactions that can be described with multimodal indicators (MI) like gaze, speech and social skills. In this paper, we first give an overview of related work that has identified indicators during CC. Then, we look into the state-of-the-art studies on feedback during CC which also make use of MI. Finally, we describe a Wizard of Oz (WOz) study where we design a privacy-preserving research prototype with the aim to facilitate real-time collaboration in-the-wild during three co-located group PhD meetings (of 3–7 members). Here, human observers stationed in another room act as a substitute for sensors to track different speech-based cues (like speaking time and turn taking); this drives a real-time visualization dashboard on a public shared display. With this research prototype, we want to pave way for design-based research to track other multimodal indicators of CC by extending this prototype design using both humans and sensors.

This Research Full Paper presents the qualitative findings from a study that implemented digital badges in a university-level programming course. Motivation has been shown to play a key role in programming performance. Increasingly, gamification is being used to facilitate student learning of concepts and skills in programming. Our study examined the impact of digital badges on the intrinsic motivation levels of introductory programmers and the badge design features leading to motivational effects. We collected data over two academic sessions in 2015 using a badge system design implemented in the Moodle learning management platform. This paper focuses on the qualitative findings from three focus group sessions and personal interviews which explored student understanding of their badge experiences. Focus group results indicated that badges were positively received and motivating. Student recommendations included physical badges to highlight achievements, and competitive badges for added motivation. The results suggest that students' social interactions play a role in how badges are perceived. This study should be of interest to badge designers and educational stakeholders using or contemplating badge systems. In particular, it may be of significance to stakeholders involved in computing education as it seeks to contribute to ongoing research efforts in the introductory programming domain.

Learning analytics can bridge the gap between learning sciences and data analytics, leveraging the expertise of both fields in exploring the vast amount of data generated in online learning environments. A typical learning analytics intervention is the learning dashboard, a visualisation tool built with the purpose of empowering teachers and learners to make informed decisions about the learning process. Related work has investigated learning dashboards, yet none have explored the theoretical foundation that should inform the design and evaluation of such interventions. In this systematic literature review, we analyse the extent to which theories and models from learning sciences have been integrated into the development of learning dashboards aimed at learners. Our analysis revealed that very few dashboard evaluations take into account the educational concepts that were used as a theoretical foundation for their design. Furthermore, we report findings suggesting that comparison with peers, a common reference frame for contextualising information on learning analytics dashboards, was not perceived positively by all learners. We summarise the insights gathered through our literature review in a set of recommendations for the design and evaluation of learning analytics dashboards for learners.

Gamification in engineering education has been applied with success in the last years. Also, Massive Open Online Courses (MOOCs) are recognized as a good strategy to enhance engineering education. Nevertheless, MOOCs have two main weaknesses: first, lack of addressing personal goals; and second, low completion rates in comparison to the number of registrations to the MOOCs. To improve learning experiences in MOOCs and to strengthen self-regulated personalized learning we propose the application of gamification in MOOCs. Our assumption is that MOOC learners will better succeed in achieving their goals if they can individually personalize and plan their learning paths through gamification. This assumption is based on the implementation intention theory which claims that people who foster their goal intentions with implementation intentions are comparatively more successful in their personal goal achievements. Based on a preliminary literature review this article presents and arguments on our research idea on how to apply gamification to enhance MOOC users' goal achievement. Besides, it introduces a new perspective on MOOC completion rates based on the user intention and a new way of measuring it via the Personal Goal Achievement Ratio (PGAR) and the Overall Goal Achievement Ratio (OGAR).

Learning Pulse explores whether using a machine learning approach on multimodal data such as heart rate, step count, weather condition and learning activity can be used to predict learning performance in self-regulated learning settings. An experiment was carried out lasting eight weeks involving PhD students as participants, each of them wearing a Fitbit HR wristband and having their application on their computer recorded during their learning and working activities throughout the day. A software infrastructure for collecting multimodal learning experiences was implemented. As part of this infrastructure a Data Processing Application was developed to pre-process, analyse and generate predictions to provide feedback to the users about their learning performance. Data from different sources were stored using the xAPI standard into a cloud-based Learning Record Store. The participants of the experiment were asked to rate their learning experience through an Activity Rating Tool indicating their perceived level of productivity, stress, challenge and abilities. These self-reported performance indicators were used as markers to train a Linear Mixed Effect Model to generate learner-specific predictions of the learning performance. We discuss the advantages and the limitations of the used approach, highlighting further development points.

The collaborative learning processes of students in online learning environments can be supported by providing learning analytics-based visualisations that foster awareness and reflection about an individual's as well as the team's behaviour and their learning and collaboration processes. For this empirical study we implemented an activity widget into the online learning environment of a live five-months Master course and investigated the predictive power of the widget indicators towards the students' grades and compared the results to those from an exploratory study with data collected in previous runs of the same course where the widget had not been in use. Together with information gathered from a quantitative as well as a qualitative evaluation of the activity widget during the course, the findings of this current study show that there are indeed predictive relations between the widget indicators and the grades, especially those regarding responsiveness, and indicate that some of the observed differences in the last run could be attributed to the implemented activity widget.

The increasing accessibility of sensors allows the study and development of multimodal learning tools that create opportunities for learners to practice while receiving feedback. One of the potential learning scenarios addressed by these learning applications is the development of public speaking skills. First applications and studies showed promising empirical results in laboratory conditions. In this article we present a study where we explored the use of a multimodal learning application called the Presentation Trainer, supporting learners with a real public speaking task in the classroom. The results of this study help to understand the challenges and implications of testing such a system in a real-world learning setting, and show the actual impact compared to the use in laboratory conditions.

The acquisition of knowledge is a key aspect for learners. However, in moments of stress the cognitive capacities of learners decrease considerably, making it very difficult for learners to get access and use their already acquired knowledge. Therefore we developed The Booth, a prototypical toolkit designed to support learners to prepare for key situations that are foreseen to be stressful. It guides the learner through a series of lectures helping them to gain personal power, and become in touch with their sincere-self. This paper presents the prototype, including the description of its technical aspects and the theory behind its lectures.

This formative study introduces DojoIBL, a web-based platform to support collaborative inquiry-based learning processes. By supporting communication and collaboration with new technological affordances, DojoIBL aims at nurturing communities of inquiry. The study elaborates on the theoretical underpinning of DojoIBL, describes its added value and presents a detailed explanation about the functionalities supported. Thereafter, an evaluation about how users perceived DojoIBL has been performed. Besides, the positive acceptance of participants, the results also showed that DojoIBL seems to be a suitable tool to support essential components of communities of inquiry. The study concludes anticipating the integration of role support as future developments of DojoIBL.

This paper presents and outlines the demonstration of DojoIBL, a web-based platform that aims at nurturing communities of inquiry by supporting communication and collaboration with emerging technological affordances. The manuscript briefly elaborates on the theoretical underpinning of DojoIBL and describes the functionalities supported. It concludes anticipating the follow up implementation which will consist on the integration of role support in DojoIBL.

This short paper presents the experiences of several Dutch projects in their application of the xAPI standard and different design patterns including the deployment of Learning Record Stores. In this paper we share insights and argue for the formation of an international Special Interest Group on interoperability issues to contribute to the Open Analytics Framework as envisioned by SoLAR and enacted by the Apereo Learning Analytics Initiative. Therefore, we provide an overview of the advantages and disadvantages of implementing the current xAPI standard by presenting projects that applied xAPI in very different ways followed by the lessons learned.

We present the collected experiences since 2012 of the Dutch Special Interest Group (SIG) for Learning Analytics in the application of the xAPI standard. We have been experimenting and exchanging best practices around the application of xAPI in various contexts. The practices include different design patterns centered around Learning Record Stores. We present three projects that apply xAPI in very different ways and publish a consistent set of xAPI recipes.

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.

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.

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.

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.

The Presentation Trainer is a multimodal tool designed to support the practice of public speaking skills, by giving the user real-time feedback about different aspects of her nonverbal communication. It tracks the user's voice and body to interpret her current performance. Based on this performance the Presentation Trainer selects the type of intervention that will be presented as feedback to the user. This feedback mechanism has been designed taking in consideration the results from previous studies that show how difficult it is for learners to perceive and correctly interpret real-time feedback while practicing their speeches. In this paper we present the user experience evaluation of participants who used the Presentation Trainer to practice for an elevator pitch, showing that the feedback provided by the Presentation Trainer has a significant influence on learning.

This paper presents results from the continuous process of developing an evaluation framework of quality indicators for learning analytics (LA). Building on a previous study, a group concept mapping approach that uses multidimensional scaling and hierarchical clustering, the study presented here applies the framework to a collection of LA tools in order to evaluate the framework. Using the quantitative and qualitative results of this study, the first version of the framework was revisited so as to allow work towards an improved version of the evaluation framework of quality indicators for LA.

This paper describes the research and development of tangible interactive ambient display prototypes to support learning scenarios. Therefore a prototypical system design called the Feedback Cube is presented. The prototypes combine motion sensors, visual and auditive actuators, as well as wireless communication capabilities in a cubic layout. An initial formative study underpins the prototypes' potential to facilitate interaction and/or indicate feedback. Based on the presented results possible applications scenarios in a learning context are outlined.

Lifelong leaners are intrinsically motivated to embed learning activities into daily life activities. Nevertheless, finding a suitable combination of the two is not trivial since lifelong learners have to face conflicts of time and location. Hence, lifelong learners normally build personal learning ecologies in those moments they set aside to learn making use of their available resources. On the other hand, the advent of Near Field Communication (NFC) technology facilitates the harmonization in the interactions between the digital world and daily physical spaces. Likewise, NFC enabled phones are becoming more and more popular. The contribution of this manuscript is threefold: first, scientific literature where NFC has been used with a direct or indirect purpose to learn is reviewed, and potential uses for lifelong learners are identified; based on these findings the Ecology of Resources for Lifelong Learning is presented as suitable setup for the scaffolding of learning activities with NFC augmented physical spaces; finally, this ecology is piloted and different learning scenarios are proposed for further extension.

This paper reports about experiences and lessons learned from a recently conducted pilot study about sustainability education with mobile inquiry-based learning in a secondary school in the Netherlands. In the pilot study learners were involved in a mobile location-based game that was conducted in reserved time-slots over 5 weeks. Mobile devices of the school and of learners have been combined with a smart-energy meter network to support learning activities covering the full inquiry cycle. Analysis of data collected shows that the implementation was beneficial for learners with a low prior knowledge level and that future designs should take into account gender aspects in the design phase.

This poster paper presents a high-level description of the Metalogue project that is developing a multi-modal dialogue system that is able to implement interactive behaviors that seem natural to users and is flexible enough to exploit the full potential of multimodal interaction. We provide an outline of the initial work undertaken to define a an open architecture for the integrated Metalogue system. This system includes components that are necessary for the implementation of the processing stages for a variety of application domains: initialization, training, information gathering, orchestration, multimodality, dialogue management, speech recognition, speech synthesis and user modelling.

The article reports the findings of a Group Concept Mapping study that was conducted within the framework of the Learning Analytics Summer Institute (LASI) in the Netherlands. Learning Analytics are expected to be beneficial for students and teacher empowerment, personalization, research on learning design, and feedback for performance. The study depicted some management and economics issues and identified some possible treats. No differences were found between novices and experts on how important and feasible are changes in education triggered by Learning Analytics.

This paper reports on the development of WeBuild, a mobile learning game designed to engage learners difficult to reach with IT learning. The development is based on a mobile game engine for the Android smart phone that was devised to support the required multiplayer and location based services. We played and tested the mobile learning game in a training facility of the building industry. The results indicate that the learners accepted the game for the low entry barriers and were motivated to use the game in an educational context. This paper describes the WeBuild prototype and the underlying game engine. Eventually, it presents results from the game session that was carried to assess interface and gameplay usability, technical functionality and motivational aspects of the game design.

This position paper shows how several classical methods in adaptive learning can be addressed using IMS learning design. After a definition of four main questions to classify adaptive educational methods we describe a group of features in the levels B and C of the specification that make possible diverse types of adaptation

User-driven annotation of learning content allows the user to interact with it in a flexible and an intuitive manner and hence personalize the content. This interaction, in most cases, follows the "paper and pen" note-taking paradigm. Though not without its advantages, this paradigm does not scale when the courses are delivered online as web pages. These paper notes are not synchronous with the content, hence may seem out of context, they may be misplaced, and don’t make allowances for collaborative learning. In this paper we describe u-Annotate, a user-driven freeform digital ink annotation application for web e- Learning content which aims at facilitating the learner to annotate the online content with the aid of pen computing devices such as graphic tablets, etc. Learners can freely mark up the content, save the annotations for recall at a later date, as well as share these with other learners.

Social software is used widely in organizational knowledge management and professional learning. The PROLEARN network of excellence appreciates the trend of lowering the barriers between knowledge and learning management strategies for organizations and individuals. But, companies should not underestimate the needs for systematic support based on sound theories and technologies. We illustrate the requirements by examples and research issues for collaborative adaptive learning platforms for workplace learning in organizations

The paper introduces the background and motivation for contextualized learning experiences and a short overview of recent research work on valuable mobile applications for learning. Based on a background of situated cognition and situated learning authentic learning experiences can be supported by a variety of context parameters. The paper illustrates a general architecture for contextualized applications and identifies important issues for contextualizing learning experiences and learning content.

The ability to relate abstract knowledge to real-world experiences is indispensable in the modern society. Therefore the construction of knowledge from real-world contexts is a major issue of education. This issue is not supported by the current learning management systems. In the RAFT project we develop a system to support remote accessible field trips. One of its applications, the mobile collector, facilitates constructivistic learning processes in real-world contexts.