Introduction to Gamification: Motivations, Effects and Analytics Minitrack

Many seem to believe that today’s pre-service teachers as born after 1980 are digital natives, or that they are “native speakers” of the digital language. Nevertheless, there is no evidence that their digital native characteristics determine whether or not they would use technology in the classroom. Although not widely evaluated, the four-factor, 21-item Digital Nativity Assessment Scale (DNAS) was one of the first instruments to assess digital nativeness (DN). This study aim is to explore the influence of pre-service teachers’ DN on their intention to use technology in the future classroom in Serbia, by evaluating the DNAS on Serbian sample and using it for measuring the DN. Six variables were incorporated to examine their mutual relationships based on technology acceptance model: digital nativeness, behavioral intention (BI), perceived usefulness (PU), perceived ease of use (PEU), subjective norm (SN), and technological complexity (TC). Data were collected from 688 pre-service teachers in Serbia. Exploratory factor analysis confirmed a four-factor model for the DNAS, and Serbian pre-service teachers demonstrated a high level of DN. To evaluate the hypothesized model structural equation modeling was utilized. The suggested model had a good fit for describing the BI of Serbian pre-service teachers, accounting for 27.1% of the variance in BI. It was found that direct dominant predictors of BI are digital native traits, perceived usefulness, and perceived ease of use. Significant influence of digital native traits on all other variables in the model was also confirmed. The implications for theory and practice are discussed.

The social implications of the Internet's and virtual goods' rapid expansion make the global impact of the virtual economy an intriguing subject. The paper examines the disparity between the real economy and the virtual economy from the viewpoint of economic financialization using a method of literature review. The paper comes to the conclusion that, from the standpoint of financialization, the speed of global virtual economy growth has significantly outpaced that of the real economy, creating a challenging environment for economic growth. The expansion of the virtual economy must be controlled, and the growth of the real economy must be accelerated.

Nowadays the safety of computer networks becomes more important than other characteristics. The services which are used by a huge number of users entice hacker. Especially, online payment services are often the main target of malicious software. In the article, the computer virus SpyEye spread via Internet resources is considered. The Petri-object model of propagation process is created with the use of Petri-object simulation software written in Java. The model reproduces the events of damaging website, infecting user’s resource, sending information about vulnerabilities and sending personal data. It was suggested that users are connected when they use the same website. The investigation of the spreading time for different kinds of users’ connections topology is presented. It was considered not only well-known star and chain topologies but also their combinations and the topology with random connections. Simulation results confirm the virus spreading time dependence on user’s connections topology.

Virtual worlds are quickly becoming a popular way for teens–especially younger teens 13-16 years of age–to spend time connecting with existing friends while searching for new contacts. According to KZero, in the third quarter of last year alone, 92 million new, unique users joined virtual worlds. However, as virtual worlds grow, teens are looking for more opportunities beyond just building their personal networks. Enter virtual goods–items users can earn or purchase to express themselves creatively or to gain status among their peers in a community. Those who have not spent time in online communities and worlds find it difficult to understand the motivation for purchasing virtual goods. But buying them or completing tasks to earn them is fun and challenging, in the exact same way shopping or playing games in the real world is fun and challenging. For example, some virtual goods provide an immediate advantage in games or contests, some help express your personal styles and interests, and some can be sent as gifts to friends. Sometimes people buy virtual goods because they’re impatient or competitive and don’t want to wait the number of days it would take to earn them for free. But fundamentally, virtual goods are entertainment–they make it fun to interact with friends and express personal styles.

<title>Abstract</title> As a core growth driver of China’s digital economy, live commerce faces intergenerational trust gaps—Gen Z (18–24 years, digital natives) prioritizes interactive experiences, while older adults (55 + years, digital immigrants) rely on streamer professionalism and after-sales support, leading to low repurchase rates. This study constructs a moderated mediation model with service quality (streamer professionalism, interactive experience, after-sales support) as the independent variable, trust as the mediator, digital generations as the moderator, and repurchase intention as the dependent variable. Using 600 valid questionnaires (300 Gen Z, 300 older adults) from Chinese platforms (Douyin, Taobao), we tested hypotheses via SPSS 26.0 (reliability/validity) and Mplus 8.4 (SEM + multi-group analysis). Results show: (1) All three service quality dimensions positively predict trust (β = 0.22–0.31, p &lt; 0.001) and repurchase intention (β = 0.12–0.32, p &lt; 0.01); (2) Trust partially mediates these relationships (indirect effects = 0.033–0.057, 95% CI no zero); (3) Digital generations moderate: older adults are more sensitive to streamer professionalism (β = 0.37 vs. Gen Z’s 0.22) and after-sales support (β = 0.32 vs. Gen Z’s 0.15), while Gen Z responds stronger to interactive experiences (β = 0.43 vs. older adults’ 0.18). The study enriches intergenerational trust theory in Chinese live commerce and provides practical strategies (e.g., AR try-on for Gen Z, streamer certification for older adults).

While younger adults have embraced internet technology, older adults have lagged behind in internet adoption. An age-based digital divide has developed globally. This is a concern because digital literacy is becoming an essential, rather than an optional, skill. This paper investigates the reasons why some able-bodied older adults with access to the internet choose not to use the internet. Previous studies of the age-based digital divide have identified income and education, and perceived need, as factors that influence internet use. This paper adds to knowledge on the age-based digital divide by studying the internet behavior of able-bodied older adults with internet access (rather than all older adults) and by investigating the association between “feeling too old to use the internet” and the internet use decision. This paper offers suggestions for bridging the age-based digital divide and discusses whether this divide will continue as younger adults, who are digital natives, become older adults.

Content in collaborative systems, such as Online Social Networks, is often co-owned by multiple users with different privacy expectations, leading to possible multiuser privacy conflicts. In order to address these conflicts, we argue that users should be supported by trustworthy agents that adhere to the following criteria: (i) concealment of privacy preferences, such that only necessary information is shared with others; (ii) equity of treatment, such that different kinds of users are supported equally; (iii) collaboration of users, such that a group of users can support each other in agreement and (iv) explainability of actions, such that users know why certain information about them was shared to reach a decision.

The following paper describes the implementation of three different controllers for a wheelchair. It was built for improving people's life that could have disabilities associated with functions regarding muscle strength, power of muscle of all limbs, tone of muscle of all limbs and endurance of all muscles of the body. Using three programmed methods that allow the user to have full control over the wheelchair. By acquiring voltage signals generated in eye's movements and using Neuro-Fuzzy Networks for differentiating each one, the wheelchair is able of being controlled by eye's movements. Figuring out about different kinds of user's needs and environments, the wheelchair includes voice control in spaces where noise levels are less than 40dB. The voice commands are detected using the Speech Recognition software which is a default program installed on Microsoft Windows operative system. The eye and voice controls were designed using LabVIEW and the intelligent control toolkit (ICTL). There were developed virtual simulators on C# code that enable the patient to have a previous training for having a better wheelchair control and performance. The system was tested on a person with cerebral palsy.

The nature of explanation dialogues is examined and an expert system that provides acceptable and appropriate answers and explanations to the questions posed by different kinds of users is designed. An empirical study and analysis of natural dialogues between experts, novices and partial experts is described. From this analysis a theory of explanation dialogues (extended schema-based theory, or EST) is developed. In EST questions are interpreted by combining information from different, semantically related question types that together best capture the essence and meaning of the question. This theory is applied to the design of an architecture and computational model for interpreting questions and generating explanations. The expert system, EXPLAIN, understands the nature of the question and is able to take account of the previous dialogue. The system can tailor its responses to an individual user's characteristics, including level of expertise and depth of knowledge in the domain. >

The long-tail phenomenon tells us that there are many items in the tail. However, not all tail items are the same. Each item acquires different kinds of users. Some items are loved by the general public, while some items are consumed by eccentric fans. In this paper, we propose a novel metric, item eccentricity, to incorporate this difference between consumers of the items. Eccentric items are defined as items that are consumed by eccentric users. We used this metric to analyze two real-world datasets of music and movies and observed the characteristics of items in terms of eccentricity. The results showed that our defined eccentricity of an item does not change much over time, and classified eccentric and noneccentric items present significantly distinct characteristics. The proposed metric effectively separates the eccentric and noneccentric items mixed in the tail, which could not be done with the previous measures, which only consider the popularity of items.

Today it is not easy to imagine what would be the future of user experience (UX) design in the world of Artificial Intelligence (AI). Referring to the sector of autonomous vehicles the paper aims to explore the changes that will be brought by artificial intelligence to the innovative sector of the self-driving car. According to these transformation car interiors and passengers experiences will become very different from the actual one. The aim of the research is, starting from different kind of passengers needs (Human Centered Design approach) individuating essential factors to design autonomous cars interiors and in particular to design innovative interfaces for a better communication with the passengers and a high level of living experience for different kind of users.

Different categories of drinking houses, it is claimed, are historically related to different kinds of users and usages. Industrialism, however, entrenched the ubiquitous pub amidst the song, sin and insobriety of the poor and the new working-class urban proletariat. The public house thus became a focus of social freedoms and sexual licence, as well as a locus of more formal elements of rational recreation. Yet the public house was subject to social controls of a ferocious kind and not simply licensing constraints, and some discussion is developed in examining the class basis of recreation and leisure controls. Attention finally turns to viewing the public house as an intermediate context in a relational sense, in an historical sense and in a time sense, and one deserving further sociological attention. Historically, different types of public drinking houses have generally developed out of distinct categories of social usage. The inn developed from the coaching tradition of providing refreshment and lodgings for travellers. Such houses tended over time to foster recreation and itinerant entertainers and to be a focus of not just wealthy travellers but plyers of wares and trades-but always perhaps within the context of a dominant use by the relatively wealthy. Such drinking houses catered for catholic drinking tastes-spirits, wines and beers. The taverns were originally concerned with selling wine, the availability of wine itself being boosted by the cultivation of vines in the medieval monasteries. Such taverns, by the late eighteenth century, were virtually indistinguishable from inns and met the needs of the casual drinker, catering for a wide range of users. The alehouse was the traditional village drinking house; it had none of the accommodation or the formal entertainment patterns of the inn. It was effectively the local community drinking and meeting place and was

Machine learning algorithms are widely employed in plenty of classification or regression problems. While in real business world, it is confronted with huge and disorder data pattern. To recognize different kinds of users on the internet accurately and fast becomes a challenge. In a Wechat online bargain activity, the staff found that some strange users are highly like robots or malicious users. Thus we tried a two-level stacking model to detect them. This design got a good result of 0.98 accuracy after the training phase and an accuracy of 0.90 in a new term of the testing set. Moreover, this model is adaptable to linear and nonlinear datasets because of its diverse stacking of first-level classifiers. Therefore, this paper indicates a potential of the stacking classification model in big data times.

From the cost analysis of the data communication service, the tariff models of the service are studied. On the basis of user classification for the service, the methods of cost share to different kinds of user and the models of the cost calculation according to the number of users and the interface are presented. The charge level of this service and the models of tariff structure are proposed. The reasonable profit ratio of the service has been discussed.

This paper introduces a new web application specification based on G-DEVS MS which supplies website metric analyses to the user, i.e. an informetric characterization with a topologic visualization and also an interactive manipulation of graphs. The tool provides different indicators of consistency of the web site with regards to customizable parameters.The scope of this study aims to improve the quality and attractiveness of public (government offices) and university web portals.There are some technical constraints, i.e. the bandwidth range and DNS (Domain Name Server) definitions; which are also taken into account. This tool has been designed for different kind of users that may range from webmasters through global editing policy deciders.G-DEVS models allow us to specify, test configuration by simulation, test integration of heterogeneous components using G-DEVS/HLA interoperability and thus make the implementation easier and safer, especially when we will save time by avoiding some implementation failures.