Systematic Literature Reviews (SLRs) are fundamental to scientific progress, yet the process is hindered by a fragmented tool ecosystem that imposes a high cognitive load. This friction suppresses the iterative, exploratory nature of scholarly work. To investigate these challenges, we conducted an exploratory design study with 20 experienced researchers. This study identified key friction points: 1) the high cognitive load of managing iterative query refinement across multiple databases, 2) the overwhelming scale and pace of publication of modern literature, and 3) the tension between automation and scholarly agency.

This research evaluates voice-based self-explanations as a pedagogical tool in preparation for lectures, assesses user preferences between voice and text, and derives design insights. We report two studies: Study 1, a quasi-experimental field study, with 247 participants divided into voice-based (N = 83), text-based (N = 81), and choice (N = 83) conditions. Study 2 uses semi-structured interviews (N = 16) to explore perceptions of the interaction paradigms in-depth. Results from the first study revealed a general preference for text, though voice users produced longer responses and more topic-related keywords. Over time, the preference for voice increased among students, from 10% to 46%, when given a choice. Study 2 suggested that factors like social presence contribute to hesitance toward voice-based explanations, with a cognitive load, self-confidence, and performance anxiety also influencing medium preferences. Our findings highlight design recommendations and demonstrate the potential of voice-based self-explanations in educational settings, indicating that mixed interfaces might better meet diverse needs.

Scientific texts convey new and complex information relevant not only to researchers but also to lay audiences. We present a randomized controlled trial that investigated whether showing a concept map, gradually building up as a user reads a scientific text, supports the cognitive processes of knowledge construction. The intervention group (n = 44) exhibited significantly more knowledge construction [t(89) = 1.94, p = .029, d = 0.41] than the control group (n = 47). The intervention supported basic knowledge construction, i.e., simple processing of information, but not medium and complex levels. This study makes two contributions: (1) showing interactive concept maps and building them up gradually alongside reading helps make scientific texts cognitively more accessible to a lay audience, e.g., to inform public debate, and (2) knowledge construction theory can be used as a theoretical foundation for measuring specific aspects of learning processes—complementing other metrics for comparative design examinations, e.g., usability, user experience, or performance-based measures.

The uptake of open science resources needs knowledge construction on the side of the readers/receivers of scientific content. The design of technologies surrounding open science resources can facilitate such knowledge construction, but this has not been investigated yet. To do so, we first conducted a scoping review of literature, from which we draw design heuristics for knowledge construction in digital environments. Subsequently, we grouped the underlying technological functionalities into three design categories: i) structuring and supporting collaboration, ii) supporting the learning process, and iii) structuring, visualising and navigating (learning) content. Finally, we mapped the design categories and associated design heuristics to core components of popular open science platforms. This mapping constitutes a design space (design implications), which informs researchers and designers in the HCI community about suitable functionalities for supporting knowledge construction in existing or new digital open science platforms.

Abstract A substantial body of human-computer interaction literature investigates tools that are intended to support reflection, e.g. under the header of quantified self or in computer-mediated learning. These works describe the issues that are reflected on by users in terms of examples, such as reflecting on financial expenditures, lifestyle, professional growth, etc. A coherent concept is missing. In this paper, the reflection object is developed based on activity theory, reflection theory and related design-oriented research. The reflection object is both what is reflected on and what is changed through reflection. It constitutes the link between reflection and other activities in which the reflecting person participates. By combining these two aspects—what is reflected on and what is changed—into a coherent conceptual unit, the concept of the reflection object provides a frame to focus on how to support learning, change and transformation, which is a major challenge when designing technologies for reflection.

This paper describes the analysis of temporal behavior of 11--15 year old students in a heavily instructionally designed adaptive e-learning environment. The e-learning system is designed to support student's acquisition of health literacy. The system adapts text difficulty depending on students' reading competence, grouping students into four competence levels. Content for the four levels of reading competence was created by clinical psychologists, pedagogues and medicine students. The e-learning system consists of an initial reading competence assessment, texts about health issues, and learning tasks related to these texts. The research question we investigate in this work is whether temporal behavior is a differentiator between students despite the system's adaptation to students' reading competence, and despite students having comparatively little freedom of action within the system. Further, we also investigated the correlation of temporal behaviour with performance. Unsupervised clustering clearly separates students into slow and fast students with respect to the time they take to complete tasks. Furthermore, topic completion time is linearly correlated with performance in the tasks. This means that we interpret working slowly in this case as diligence, which leads to more correct answers, even though the level of text difficulty matches student's reading competence. This result also points to the design opportunity to integrate advice on overarching learning strategies, such as working diligently instead of rushing through, into the student's overall learning activity. This can be done either by teachers, or via additional adaptive learning guidance within the system.

This paper discusses the potential of ICT to support reflective learning for professionals. We aggregated data collected in 20 field studies with 12 different applications, involving a total of 321 participants. The applications addressed individual reflection as well as collaborative reflection. Such a systematic analysis with different applications used across industry sectors and companies is unique in the current literature on computer-supported reflective learning in the workplace. Primarily, we assessed the reaction to reflection applications and their effectiveness regarding learning, behaviour change, and organisational impact. In addition, we investigated differences with respect to work experience. Results show that users had a positive reaction to the apps and perceived their use to be beneficial for their work by using them. In collaborative reflection an inexperienced employee can benefit from the experiences and perspectives of more experienced (co-)workers. In contrast, individual reflection was more profitable for more experienced workers. Notwithstanding the overall positive results, the actual implementation of reflection applications requires careful adaptation to the specific organisational and situational context, as well as introductory and accompanying measures to assure efficient and beneficial usage of the tools.

We present a visual interface for communicating the internal state of a coffee machine via a tree metaphor. Nature-inspired representations have a positive impact on human well-being. We also hypothesize that representing the coffee machine as a tree stimulates emotional connection to it, which leads to better maintenance performance.The first study assessed the understandability of the tree representation, comparing it with icon-based and chart-based representations. An online survey with 25 participants indicated no significant mean error difference between representations.A two-week field study assessed the maintenance performance of 12 participants, comparing the tree representation with the icon-based representation. Based on 240 interactions with the coffee machine, we concluded that participants understood the machine states significantly better in the tree representation. Their comments and behavior indicated that the tree representation encouraged an emotional engagement with the machine. Moreover, the participants performed significantly more optional maintenance tasks with the tree representation.

This paper aims to identify self-regulation strategies from students' interactions with the learning management system (LMS). We used learning analytics techniques to identify metacognitive and cognitive strategies in the data. We define three research questions that guide our studies analyzing i) self-assessments of motivation and self regulation strategies using standard methods to draw a baseline, ii) interactions with the LMS to find traces of self regulation in observable indicators, and iii) self regulation behaviours over the course duration. The results show that the observable indicators can better explain self-regulatory behaviour and its influence in performance than preliminary subjective assessments.

Traditionally, professional learning for senior professionals is organized around face-2-face trainings. Virtual trainings seem to offer an opportunity to reduce costs related to travel and travel time. In this paper we present a comparative case study that investigates the differences between traditional face-2-face trainings in physical reality, and virtual trainings via WebEx. Our goal is to identify how the way of communication impacts interaction between trainees, between trainees and trainers, and how it impacts interruptions. We present qualitative results from observations and interviews of three cases in different setups (traditional classroom, web-based with all participants co-located, web-based with all participants at different locations) and with overall 25 training participants and three trainers. The study is set within one of the Big Four global auditing companies, with advanced senior auditors as learning cohort.

The benefits of self-tracking have been thoroughly investigated in private areas of life, like health or sustainable living, but less attention has been given to the impact and benefits of self-tracking in work-related settings. Through two field studies, we introduced and evaluated a mood self-tracking application in two call centers to investigate the role of mood self-tracking at work, as well as its impact on individuals and teams. Our studies indicate that mood self-tracking is accepted and can improve performance if the application is well integrated into the work processes and matches the management style. The results show that (i) capturing moods and explicitly relating them to work tasks facilitated reflection, (ii) mood self-tracking increased emotional awareness and this improved cohesion within teams, and (iii) proactive reactions by managers to trends and changes in team members’ mood were key for acceptance of reflection and correlated with measured improvements in work performance. These findings help to better understand the role and potential of self-tracking at the workplace, and further provide insights that guide future researchers and practitioners to design and introduce these tools in a work setting.

Operating Brain-Computer Interfaces (BCIs) that are based on the detection of changes in oscillatory non-invasive electroencephalogram (EEG) typically involves learning. Commonly the learning process is distributed between the user (reliable EEG pattern generation) and the machine (robust EEG pattern detection). Standard training approaches, however, typically do not allow users to gain meaningful levels of control. A better understanding of brain functioning or the use of sophisticated machine learning are ways to enhance control. Rethinking training paradigms is another option. In this paper, we enhance our game-based training approach by adding competitive elements. Winning is a powerful motivator that increases user engagement of the typically boring BCI training experience. We report on a user with cerebral palsy who successfully gained BCI control and played the classical Tic-Tac-Toe game against his caregiver.

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.

Fall detection is a classical use case for mobile phone sensing. Nonetheless, no open dataset exists that could be used to train, test and compare fall detection algorithms. We present a dataset for mobile phone sensing-based fall detection. The dataset contains both accelerometer and gyrosc

Mutual brain-machine co-adaptation is the most common approach used to gain control over spontaneous electroencephalogram (EEG) based brain-computer interfaces (BCIs). Co-adaptation means the concurrent or alternating use of machine learning and the brain's reinforcement learning mechanisms. Results from the literature, however, suggest that current implementations of this approach does not lead to desired results ("BCI inefficiency"). In this paper, we propose an alternative strategy that implements some recommendations from educational psychology and instructional design. We present a jigsaw puzzle game for Android devices developed to train the BCI skill in individuals with cerebral palsy (CP). Preliminary results of a supporting study in four CP users suggest high user acceptance. Three out of the four users achieved better than chance accuracy in arranging pieces to form the puzzle.

Synchronisation algorithms are central components of collaborative editing software. The energy efficiency for such algorithms becomes of interest to a wide community of mobile application developers. In this paper we explore the differential synchronisation (diffsync) algorithm with re

My Places Diary is a research prototype, available on Google Play, that tracks places and movements of users throughout the day. It includes two innovative features: Firstly users’ home and workplaces are detected automatically, based on heuristics derived from earlier work on automatic semantic pla

In this paper we propose a model of Computer Supported Reflective Learning (CSRL) that links the reflection process to supportive ICT. The CSRL model has the potential to support analysis and design of CSRL solutions. It fills a gap that currently exists between theoretical work on reflection and research investigating technologies for reflection support. The model is based on theory, specifically concerning the reflection process, and on empirical work on reflective learning in work life carried out in five different test bed organizations.

Abstract—Imagine you are member of an online social system and want to upload a picture into the community pool. In current social software systems, you can probably tag your photo, share it or send it to a photo printing service and multiple other stuff. The system creates around you a space full of pictures, other interesting content (descriptions, comments) and full of users as well. The one thing current systems do not do, is understand what your pictures are about. We present here a collection of functionalities that make a step in that direction when put together to be consumed by a tag recommendation system for pictures. We use the data richness inherent in social online environments for recommending tags by analysing different aspects of the same data (text, visual contentand user context). We also give an assessment of the quality of thus recommended tags.

Social web platforms have become very popular in the so-called Web 2.0, and there is no end in sight. However, very few systematic models for the constitution of such sociotechnical infrastructures exist in the scientific literature. We therefore present a generic framework for building social web platforms based on the creation of value for individuals, communities and social networks. We applied this framework in the Neurovation project, aiming to establish a platform for creative knowledge workers. This paper describes work in progress and the lessons we have learned so far.

This paper describes the application of an ultra wideband (UWB) communication and positioning system for constructing a 3D map of the environment. Basis for the mapping functionality are the device's ability to measure the impulse response and the system's ability to determine the position of the device. A systematic analysis of the problem structure is provided and key issues are identified. The proposed solution is partly implemented, and as far as possible verified in a simple experimental setup. Experiments show on the one hand the feasibility of such a system, i.e. that walls and various objects can be detected. On the other hand, the experiments also clarify which issues have to be examined in more detail

Recently, wireless technologies have known an increasing success, thus becoming an interesting field for study. One of the topics of research are multiple antenna arrays. Signal recovery in that case is not obvious. Different methods with different performances have been suggested. From a statistical analysis of errors at the output of zero-forcing, we have constructed a method, which we present in this article, that combines zero-forcing and maximum likelihood. We will demonstrate that it provides both a low complexity and nearly optimal results regarding binary error rate (BER). Furthermore, we will show its relevancy compared to the VBLAST algorithm.