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Fitness apps are persuasive tools developed to motivate physical activity. Despite their popularity, there is little work on how social-cognitive characteristics such as culture, household size, physical activity level, perceived self-efficacy and social support influence users' willingness to use them and preference (personal vs. social). Knowing these relationships can help developers tailor fitness apps to different socio-cultural groups. Hence, we conducted two studies to address the research gap. In the first study (n = 194) aimed at recruiting participants for the second study, we asked participants about their app preference (personal vs. social), physical activity level and key demographic variables. In the second study (n = 49), we asked participants about their social-cognitive beliefs about exercise and their willingness to use a fitness app (presented as a screenshot). The results of the first study showed that, in the collectivist group (Nigerians), people in large households were more likely to be active and use the social version of a fitness app than those in small households. However, in the individualist group (Canadians/Americans), neither the preference for the social or personal version of a fitness app nor the physical activity level depended on the household size. Moreover, in the second study, in the individualist model, perceived self-efficacy and perceived self-regulation have a significant total effect on willingness to use a fitness app. However, in the collectivist model, perceived social support and outcome expectation have a significant total effect on the target construct. Finally, we found that females in individualist cultures had higher overall social-cognitive beliefs about exercise than males in individualist cultures and females in collectivist cultures. The implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

There is a dearth of knowledge on how persuasiveness of influence strategies affects students' behaviours when using online educational systems. Persuasiveness is a term used in describing a system's capability to motivate desired behaviour. Most existing approaches for assessing the persuasiveness of a system are based on subjective measures (questionnaires) which are static and do not allow for automatic measurement of systems persuasiveness at run-time. Being able to automatically predict a system's persuasiveness at run-time is essential for dynamic and continuous adaptation of the system to reflect each individual user's state. In this study, we investigate the links between persuasiveness of influence strategies and students' behaviour in an online educational system for a course. We implemented and tested Machine Learning (ML) classification models to determine whether persuasiveness had a significant impact on students' usage of a learning system. Our findings revealed that students learning data can be applied to predict the persuasiveness of different influence strategies. The implications are that by using machine learning classifiers powered with learning sessions data, online educational systems would be able to automatically adapt their persuasive strategies to improve students' engagement and learning. [ABSTRACT FROM AUTHOR]

This research presents a proposed approach that could be applied in modeling students' study strategies and performance in higher education. The research used key learning attributes, including intrinsic motivation, extrinsic motivation, autonomy, relatedness, competence, and self-esteem in the modeling. Five machine learning models were implemented, trained, evaluated, and tested with data from 924 university students. The comparative analysis reveals that tree-based models, particularly random forest and decision trees, outperform other models, achieving a prediction accuracy of 94.9%. The models built in this research can be used in predicting student study strategies and performance and this can be applied in implementing targeted interventions for improving learning progress. The research findings emphasize the importance of incorporating strategies that address diverse motivation dimensions in online educational systems, as it increases student engagement and promotes continuous learning. The findings also highlight the potential for modeling these attributes collectively to personalize and adapt learning process. [ABSTRACT FROM AUTHOR]

Personalized gamification explores user models to tailor gamification designs to mitigate cases wherein the one-size-fits-all approach ineffectively improves learning outcomes. The tailoring process should simultaneously consider user and contextual characteristics (e.g., activity to be done and geographic location), which leads to several combinations to tailor. Consequently, tools for automating gamification personalization are needed. However, which of those characteristics are relevant and how to do such tailoring are open questions. Furthermore, the required automating tools are lacking. We tackled these problems in two steps. First, we conducted an exploratory study, collecting participants' opinions on the game elements they consider the most useful for different learning activity types (LAT) via survey. Then, we modeled opinions through Conditional Decision Trees to address the aforementioned tailoring process. Second, as a product of the first step, we implemented a recommender system that suggests personalized gamification designs (which game elements to use), addressing the problem of automating gamification personalization. Our findings present empirical evidence that LAT, geographic locations, and other user characteristics affect users' preferences, enable defining gamification designs tailored to user and contextual features simultaneously, and provide technological aid for those interested in designing personalized gamification. The main implications are that demographics, game-related characteristics, geographic location, and LAT to be done, as well as the interaction between different kinds of information (user and contextual characteristics), should be considered in defining gamification designs and that personalizing gamification designs can be improved with aid from our recommender system. [ABSTRACT FROM AUTHOR]

Gamification refers to the attempt to transform different kinds of systems to be able to better invoke positive experiences such as the flow state. However, the ability of such intervention to invoke flow state is commonly believed to depend on several moderating factors including the user's traits. Currently, there is a dearth of research on the effect of user traits on the results of gamification. Gamer types (personality traits related to gaming styles and preferences) are considered some of the most relevant factors affecting the individual's susceptibility to gamification. Therefore, in this study we investigate how gamer types from the BrainHex taxonomy (achiever, conqueror, daredevil, mastermind, seeker, socializer and survivor) moderate the effects of personalized/non-personalized gamification on users' flow experience (challenge-skill balance, merging of action and awareness, clear goals, feedback, concentration, control, loss of self-consciousness and autotelic experience), enjoyment, perception of gamification and motivation. We conducted a mixed factorial within-subject experiment involving 121 elementary school students comparing a personalized version against a non-personalized version of a gamified education system. There were no main effects between personalization and students' flow experience, perception of gamification and motivation, and enjoyment. Our results also indicate patterns of characteristics that can lead students to the high flow experience (e.g., those who prefer to play multiplayer have a high flow experience in both personalized and non-personalized versions). Based on our results, we provided recommendations to advance the design of gamifed educational systems. [ABSTRACT FROM AUTHOR]

Persuasive Technologies (PT) are computational methods, strategies, and design techniques, grounded in social psychology to change user attitudes/behaviours. PTs have been applied in diverse areas, such as eCommerce, health, workplace, vehicles, urban and ambient environments. A kind of PT that has become popular in eLearning is known under the name "Gamification" – introducing game mechanics (such as points, levels, badges, leaderboards) into non-game environments. We implemented three persuasive strategies in an online learning environment supporting a University class to encourage more active engagement of students in their online learning activities. The paper presents a controlled study that shows a positive effect of the persuasive intervention on student engagement, measured by the increase in their online activities. The study results also show that personalizing the persuasive strategies to the receptiveness of individual students amplifies their effect on engagement. [ABSTRACT FROM AUTHOR]

Fairness The papers on fairness are diverse in their subject matter, covering both consumer-side fairness (fairness concerns relative to the receivers of recommendations) and provider-side fairness (concerns having to do with the creators or others providing items to be recommended). Deljoo et al.'s "A Flexible Framework for Evaluating User and Item Fairness in Recommender Systems" proposes a general class of fairness measures based on generalized cross-entropy, which unifies a wide variety of metrics that might be applied in consumer-side and provider-side group fairness problems. An examination of the fairness-aware recommendation and ranking literature shows an extensive variety of different ways of conceptualizing and quantifying recommender system fairness. [Extracted from the article]

Games are a great source of entertainment and are used by people of all ages; they motivate and engage people and affect their behavior. Therefore, games have been widely studied in many non-game contexts. Education is one of those areas where gamified, and game-based learning strategies have been implemented and explored. To engage and motivate students to quiz each other, and as a side effect, build a question bank, as well as to study the gaming and learning behavior of students, we used a peer-quizzing game called "Tower of Questions" (ToQ). The game uses some themes and mechanics found in tower defense (TD) games. The students received points for posing and answering the questions in the game in the form of gems. Students played the game with pseudonyms for one academic term and were told not to disclose their identities to anyone. We conducted a 3-month long study for two consecutive years in the same first-year undergraduate computer science course. In this paper, we present the findings from our studies using ToQ, specifically findings related to the students' self-monitoring and quizzing activities based on the game logs and two self-reported surveys from data collected in the second year ofthe study. [ABSTRACT FROM AUTHOR]

In recent years, the employment of behavior models to motivate behavior change has become a global trend in fitness application design. However, there is hardly any large-scale study of these applications to understand users' exercise-type preferences, their drivers and barriers, and the potential of employing them for gender-based tailoring. To bridge this gap, we conducted a mixed-method study among 669 participants to investigate users' exercise-type preferences (their drivers and barriers) and how they and gender can impact users' social-cognitive beliefs and projected performance of bodyweight exercises. Firstly, we presented to the study participants a behavior model performing push-up or squat bodyweight exercise in a fitness application and asked them to rate their perceived self-effcacy, self-regulation, outcome expectation, and projected (exercise) performance level as observers of the behavior model. Secondly, we presented the study participants with a preselected list of commonly employed exercise types in fitness applications and requested them to identify their most/least preferred, and the reasons behind their choices. Our results showed that there were differences between both genders in their exercise-type preferences, perceived self-effcacy and projected exercise performance level. Males prefer push-up, squat, crunch, plank, and chair dip the most, with effectiveness being the most important driver, followed by ease of performance and improvement of the physique, look, and appearance. On the other hand, females prefer squat, crunch, jumping jack, step up, and plank the most, with ease of performance being the most important driver, followed by improvement of the physique, look, appearance, and effectiveness. Moreover, males prefer running in place the least, while females prefer push-up the least, with perceived difficulty being the greatest barrier for both genders. Moreover, our analysis of variance supported the female's least preference for a push-up. Females have a lower perceived self-efficacy and projected performance level for push-up than males. We discussed the implications of our findings and provided guidelines for tailoring fitness applications on the market to users' preferences and gender. [ABSTRACT FROM AUTHOR]

Fitness apps equipped with various persuasive features have become popular worldwide due to the physical inactivity crisis. However, there is a limited understanding of the most important persuasive features that drive their adoption and the moderating effect of age and gender. To bridge this gap, we designed storyboards illustrating six of the commonly employed persuasive strategies in persuasive health applications: Goal-Setting/Self-Monitoring, Reward, Social Learning, Social Comparison, Competition and Cooperation. We conducted an empirical study in which we asked the participants to evaluate their receptiveness to the six persuasive features and their intention to use a fitness app that features them. The result of our Partial Least Square Path Modeling (PLSPM) shows that, overall, Goal-Setting/Self-Monitoring is the strongest predictor of the intention to use a fitness app, followed by Reward and Competition, both of which are in second place. However, Social Learning and Social Comparison turn out to be non-predictors of intention to use. Based on these findings, we recommend that a minimally viable (one-size-fits-all) fitness app, in a personal setting, should support a Goal-Setting/Self-Monitoring feature, coupled with a Reward feature, to increase its appeal to a wide audience. Moreover, in a social setting, it should support a Competition feature to increase its appeal to a wide audience. We discuss these findings and the gender and age differences in the relationships between users' receptiveness to the six persuasive features and their intention to use a fitness app that support them. [ABSTRACT FROM AUTHOR]

In e-commerce, the user interface design of a website is critical to its success. However, there is limited research on how colour and layout design elements influence the perception of e-commerce websites for mobile devices. To bridge this gap, we conducted an empirical study to investigate, how the layout of information and colour temperature of an e-commerce tourism website for mobile device influence essential Technology Acceptance Model (TAM) user experience (UX) design attributes and intention to use the website. The results of our Partial Least Square Path Modelling (PLSPM) showed that both interface design elements significantly influence perceived aesthetics, perceived enjoyment, perceived usefulness and intention to use. Specifically, layout (list = 0 and grid = 1) positively influences perceived aesthetics and perceived enjoyment, while colour temperature negatively influences perceived usefulness and intention to use. The first finding suggests that in tourism website design for mobile devices, a grid layout of products and services provides a better hedonic user experience than a list layout. Moreover, the second finding suggests that cooler-temperature (blue and green) tourism websites are viewed by users as more useful than warmer-temperature (orange and red) tourism websites. We discuss the implications of these findings in the context of website UX design for mobile devices in the tourism domain. [ABSTRACT FROM AUTHOR]

Authoring tools have been broadly used to design Intelligent Tutoring Systems (ITS). However, ITS community still lacks a current understanding of how authoring tools are used by non-programmer authors to design ITS. Hence, the objective of this work is to review how authoring tools have been supporting ITS design for non-programmer authors. In order to meet our goal, we conduct a Systematic Literature Review (SLR) to identify the primary studies on the use of ITS authoring tools, following a pre-defined review protocol. Among the 4622 papers retrieved from seven digital libraries published from 2009 to June 2016, 33 papers are finally included after applying our exclusion and inclusion criteria. We then identify the main ITS components authored, the ITS types designed, the features used to facilitate the authoring process, the technologies used to develop authoring tools and the time at which authoring occurs. We also look for evidence of the benefits of ITS authoring tools. In summary, the main findings of this work are: (1) there is empirical evidence of the benefits (i.e., mainly in terms of effectiveness, efficiency, quality of authored artifacts, and usability) of using ITS authoring tools for non-programmer authors, specially to aid authoring of learning content and to support authoring of model-tracing/cognitive and example-tracing tutors; 2) domain and pedagogical models have been much more targeted by authoring tools; (3) several ITS types have been authored, with an emphasis on model-tracing/cognitive and example-tracing tutors; (4) besides providing features for authoring all four ITS components, current authoring tools are also presenting general features (e.g., view learners’ statistics and reuse tutor design) to create broader authoring tools; (5) a great diversity of technologies, which include AI techniques, software solutions and distributed technologies, are used to develop ITS authoring tools; and (6) authoring tools have been mainly targeting ITS design before students’ instruction, but works are also addressing authoring during and/or post-instruction relying both on human and artificial intelligence. We conclude this work by showing several promising research opportunities that are quite important and interesting but underexplored in current research and practice. [ABSTRACT FROM AUTHOR]

There has been a continuous increase in the design and application of computer games for purposes other than entertainment in recent years. Serious games--games that motivate behavior and retain attention in serious contexts--can change the attitudes, behaviors, and habits of players. These games for change have been shown to motivate behavior change, persuade people, and promote learning using various persuasive strategies. However, persuasive strategies that motivate one player may demotivate another. In this article, we show the importance of tailoring games for change in the context of a game designed to improve healthy eating habits. We tailored a custom-designed game by adapting only the persuasive strategies employed; the game mechanics themselves did not vary. Tailoring the game design to players' personality type improved the effectiveness of the games in promoting positive attitudes, intention to change behavior, and self-efficacy. Furthermore, we show that the benefits of tailoring the game intervention are not explained by the improved player experience, but directly by the choice of persuasive strategy employed. Designers and researchers of games for change can use our results to improve the efficacy of their game-based interventions. [ABSTRACT FROM AUTHOR]

Social networking sites (SNSs) have applied personalized filtering to deal with overwhelmingly irrelevant social data. However, due to the focus of accuracy, the personalized filtering often leads to 'the filter bubble' problem where the users can only receive information that matches their pre-stated preferences but fail to be exposed to new topics. Moreover, these SNSs are black boxes, providing no transparency for the user about how the filtering mechanism decides what is to be shown in the activity stream. As a result, the user's usage experience and trust in the system can decline. This paper presents an interactive method to visualize the personalized filtering in SNSs. The proposed visualization helps to create awareness, explanation, and control of personalized filtering to alleviate the 'filter bubble' problem and increase the users' trust in the system. Three user evaluations are presented. The results show that users have a good understanding about the filter bubble visualization, and the visualization can increase users' awareness of the filter bubble, understandability of the filtering mechanism and to a feeling of control over the data stream they are seeing. The intuitiveness of the design is overall good, but a context sensitive help is also preferred. Moreover, the visualization can provide users with better usage experience and increase users' trust in the system. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editors discuss various reports within the issue on topics including social services, agile software development, and crowdsourcing.

Persuasive games for health are designed to alter human behavior or attitude using various Persuasive Technology (PT) strategies. Recent years have witnessed an increasing number of such games, which treat players as a monolithic group by adopting a one-size-fits-all design approach. Studies of gameplay motivation have shown that this is a bad approach because a motivational approach that works for one individual may actually demotivate behavior in others. In an attempt to resolve this weakness, we conducted a large-scale study on 1,108 gamers to examine the persuasiveness of ten PT strategies that are commonly employed in persuasive game design, and the receptiveness of seven gamer personalities (gamer types identified by BrianHex) to the ten PT strategies. We developed models showing the receptiveness of the gamer types to the PT strategies and created persuasive profiles, which are lists of strategies that can be employed to motivate behavior for each gamer type. We then explored the differences between the models and, based on the results, proposed two approaches for data-driven persuasive game design. The first is the one-size-fits-all approach that will motivate a majority of gamers, while not demotivating any player. The second is the personalized approach that will best persuade a particular type of gamer. We also compiled a list of the best and the worst strategies for each gamer type. Finally, to bridge the gap between game design and PT researchers, we map common game mechanics to the persuasive system design strategies. [ABSTRACT FROM AUTHOR]

In this article, we propose a novel super-agent-based framework for reputation management and community formation in decentralized systems. We describe this framework in the context of Web service selection where agents with more capabilities act as super-agents. These super-agents serve as reputation managers to maintain reputation information of services and share the information with other consumer agents that have fewer capabilities than the super-agents. In addition, super-agents can maintain communities and build community-based reputation for a service based on the opinions from all community members that have similar interests and judgement criteria as the super-agents or the other community members. A practical reward mechanism is also introduced to create incentives for super-agents to contribute their resources (to maintain reputation and form communities) and provide truthful reputation information. Experimental results obtained through simulation confirm that our approach achieves better effectiveness and scalability compared to the systems that do not use super-agents and that do not form communities. [ABSTRACT FROM AUTHOR]