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Gamification has recently been presented as a successful strategy to engage users, with potential for online education. However, while the number of publications on gamification has been increasing in recent years, a classification of its empirical effects is still missing. We present a systematic literature review conducted with the purpose of closing this gap by clarifying what effects gamification generates on users’ behaviour in online learning. Based on the studies analysed, the game elements most used in the literature are identified and mapped with the effects they produced on learners. Furthermore, we cluster these empirical effects of gamification into six areas: performance, motivation, engagement, attitude towards gamification, collaboration, and social awareness. The findings of our systematic literature review point out that gamification and its application in online learning and in particular in Massive Online Open Courses (MOOCs) are still a young field, lacking in empirical experiments and evidence with a tendency of using gamification mainly as external rewards. Based on these results, important considerations for the gamification design of MOOCs are drawn.

Collaboration is an important 21st Century skill. Co-located (or face-to-face) collaboration (CC) analytics gained momentum with the advent of sensor technology. Most of these works have used the audio modality to detect the quality of CC. The CC quality can be detected from simple indicators of collaboration such as total speaking time or complex indicators like synchrony in the rise and fall of the average pitch. Most studies in the past focused on 'how group members talk' (i.e., spectral, temporal features of audio like pitch) and not 'what they talk'. The 'what' of the conversations is more overt contrary to the 'how' of the conversations. Very few studies studied 'what' group members talk about, and these studies were lab based showing a representative overview of specific words as topic clusters instead of analysing the richness of the content of the conversations by understanding the linkage between these words. To overcome this, we made a starting step in this technical paper based on field trials to prototype a tool to move towards automatic collaboration analytics. We designed a technical setup to collect, process and visualize audio data automatically. The data collection took place while a board game was played among the university staff with pre-assigned roles to create awareness of the connection between learning analytics and learning design. We not only did a word-level analysis of the conversations, but also analysed the richness of these conversations by visualizing the strength of the linkage between these words and phrases interactively. In this visualization, we used a network graph to visualize turn taking exchange between different roles along with the word-level and phrase-level analysis. We also used centrality measures to understand the network graph further based on how much words have hold over the network of words and how influential are certain words. Finally, we found that this approach had certain limitations in terms of automation in speaker diarization (i.e., who spoke when) and text data pre-processing. Therefore, we concluded that even though the technical setup was partially automated, it is a way forward to understand the richness of the conversations between different roles and makes a significant step towards automatic collaboration analytics. (DIPF/Orig.).

This study investigated to what extent multimodal data can be used to detect mistakes during Cardiopulmonary Resuscitation (CPR) training. We complemented the Laerdal QCPR ResusciAnne manikin with the Multimodal Tutor for CPR, a multi-sensor system consisting of a Microsoft Kinect for tracking body position and a Myo armband for collecting electromyogram information. We collected multimodal data from 11 medical students, each of them performing two sessions of two-minute chest compressions (CCs). We gathered in total 5254 CCs that were all labelled according to five performance indicators, corresponding to common CPR training mistakes. Three out of five indicators, CC rate, CC depth and CC release, were assessed automatically by the ReusciAnne manikin. The remaining two, related to arms and body position, were annotated manually by the research team. We trained five neural networks for classifying each of the five indicators. The results of the experiment show that multimodal data can provide accurate mistake detection as compared to the ResusciAnne manikin baseline. We also show that the Multimodal Tutor for CPR can detect additional CPR training mistakes such as the correct use of arms and body weight. Thus far, these mistakes were identified only by human instructors. Finally, to investigate user feedback in the future implementations of the Multimodal Tutor for CPR, we conducted a questionnaire to collect valuable feedback aspects of CPR training. (DIPF/Orig.).

This article proposes a framework of quality indicators for learning analytics that aims to standardise the evaluation of learning analytics tools and to provide a mean to capture evidence for the impact of learning analytics on educational practices in a standardised manner. The criteria of the framework and its quality indicators are based on the results of a Group Concept Mapping study conducted with experts from the field of learning analytics. The outcomes of this study are further extended with findings from a focused literature review.

Sensors can monitor physical attributes and record multimodal data in order to provide feedback. The application calligraphy trainer, exploits these affordances in the context of handwriting learning. It records the expert’s handwriting performance to compute an expert model. The application then uses the expert model to provide guidance and feedback to the learners. However, new learners can be overwhelmed by the feedback as handwriting learning is a tedious task. This paper presents the pilot study done with the calligraphy trainer to evaluate the mental effort induced by various types of feedback provided by the application. Ten participants, five in the control group and five in the treatment group, who were Ph.D. students in the technology-enhanced learning domain, took part in the study. The participants used the application to learn three characters from the Devanagari script. The results show higher mental effort in the treatment group when all types of feedback are provided simultaneously. The mental efforts for individual feedback were similar to the control group. In conclusion, the feedback provided by the calligraphy trainer does not impose high mental effort and, therefore, the design considerations of the calligraphy trainer can be insightful for multimodal feedback designers.

No systematic evaluation of smartphone/mobile apps for resuscitation training and real incident support is available to date. To provide medical, usability, and additional quality criteria for the development of apps, we conducted a mixed-methods sequential evaluation combining the perspective of medical experts and end-users. The study aims to assess the quality of current mobile apps for cardiopulmonary resuscitation (CPR) training and real incident support from expert as well as end-user perspective. Two independent medical experts evaluated the medical content of CPR apps from the Google Play store and the Apple App store. The evaluation was based on pre-defined minimum medical content requirements according to current Basic Life Support (BLS) guidelines. In a second phase, non-medical end-users tested usability and appeal of the apps that had at least met the minimum requirements. Usability was assessed with the System Usability Scale (SUS); appeal was measured with the self-developed ReactionDeck toolkit. Out of 61 apps, 46 were included in the experts' evaluation. A consolidated list of 13 apps resulted for the following layperson evaluation. The interrater reliability was substantial (kappa=.61). Layperson end-users (n=14) had a high interrater reliability (intraclass correlation 1 [ICC1]=.83, P<.001, 95% CI 0.75-0.882 and ICC2=.79, P<.001, 95% CI 0.695-0.869). Their evaluation resulted in a list of 5 recommendable apps. Although several apps for resuscitation training and real incident support are available, very few are designed according to current BLS guidelines and offer an acceptable level of usability and hedonic quality for laypersons. The results of this study are intended to optimize the development of CPR mobile apps. The app ranking supports the informed selection of mobile apps for training situations and CPR campaigns as well as for real incident support.

This article describes the theory-informed design of the ＂ELENA goes shopping＂ mobile game and reports on the evaluation of its effectiveness through a design research approach. The game aimed to foster young children's (aged 4-8) interest in a neighboring (geographically proximate) language and to familiarize them with its sounds, pronunciation and vocabulary. Additionally, it strived to involve adults in young children's language learning activities. To achieve these objectives, the game connects playful learning activities to an accessible, familiar real-world setting (supermarket). The game was developed and evaluated through three iterative design research cycles. First, interdisciplinary experts (n = 8) evaluated the game by means of a questionnaire and focus group discussion. In the second and third cycles, the game's feasibility and usability was evaluated via questionnaires, semi-structured interviews and a language learning outcome test. Results revealed that children (34) and adults (14) alike found the game useful for familiarization with and motivation to learn another language, and feasible to involve adults. Nevertheless, children could play the game autonomously with minimum adult assistance. A dependent t-test on a repeated vocabulary test revealed adults' and children's perception that the game helped them familiarize with another language to be consistent with test results. A limitation to this study is that the test was administered immediately after game playing. Future studies could explore effects of ＂real-world＂ contextualization on early second language learning and vocabulary recall by measuring after longer time spans and compare results versus a non-contextualized game.

The aviation industry is one of the most regulated industries in the world; safety is its overriding objective. In Europe, aviation maintenance training regulations rely on time-based technical experience and theoretical multiple-choice exams for a basic aircraft maintenance licence. The aviation industry and authorities are exploring the incorporation of competency-based training and assessment to keep pace with the rapidly evolving aviation industry. However, the shift from traditional time-based to competency-based education presents challenges for vocational education and training in aircraft maintenance, particularly as the assessment of transversal competencies is a newly introduced element. This study centres on transversal competencies in aircraft maintenance, aiming to uncover priorities and obstacles for training and assessing these competencies in aircraft maintenance education. Survey results from 141 aviation experts revealed that transversal competencies involving communication, teamwork, and work management are viewed as the most important transversal competencies, with communication rated highest χ2 (2) = 16.2, p < .001. In addition, four observable behaviours from these competencies were identified as most important, yet most challenging to assess during education. These findings highlight crucial areas and thus bring focus to developing new, competency-based, educational programmes for aviation maintenance.

Mobile devices offer unique opportunities to deliver learning content in authentic learning situations. Apart from being able to play various kinds of rich multimedia content, they offer new ways of tailoring information to the learner's situation or context. This paper presents the results of a study of mobile media delivery for language learning, comparing two context filters and four selection methods for language content. Thirty-five people (18 male, 17 female; M = 31.06 years, SD = 8.93) participated in this study, divided over seven treatments in total. The treatment groups were compared on knowledge gain, and the results indicated that the results differed significantly. The results found indicated an effect of both context filters as selection methods on the learner performance. In addition, the results indicated a cost/benefit trade-off that should be taken into account when developing contextualised media for learning.

Recognizing the failures of traditional Technology Enhanced Learning (TEL) initiatives to achieve performance improvement, we need to rethink how we design new TEL models that can respond to the learning requirements of the 21st century and mirror the characteristics of knowledge and learning which are fundamentally personal, social, distributed, ubiquitous, flexible, dynamic, and complex in nature. In this paper, we discuss the 3P learning model; a vision of learning characterized by the convergence of lifelong, informal, and personalized learning within a social context. The 3P learning model encompasses three core elements: Personalization, Participation, and Knowledge-Pull. We then present the social software supported learning framework as a framework that illustrates the 3P learning model in action, based on Web 2.0 concepts and social software technologies.