ValuED: A Blockchain-based Trading Platform to Encourage Student Engagement in Higher Education

The provision of higher education has been changing ever more quickly in the UK and worldwide, as a result of technological, economic, and geopolitical factors. The Covid-19 pandemic has accelerated such changes. The “student experience”—the interaction of students with their institution and with each other—has been changing accordingly, with less face-to-face contact. In this work, we have explored a way to improve student engagement in higher education. We describe “ValuED”, a blockchain-based trading platform using a cryptocurrency. It allows students both to buy and sell goods and services within their university community and to be rewarded for academic engagement. ValuED involves a reputation system to further incentivise participants. We describe the implementation and piloting of this platform and draw conclusions for its future use. The platform’s source code is publicly available.

Commonshare: A New Approach to Social Reputation for Online Collaborative Communities

Reputation systems are a popular feature of web-based platforms for ensuring that their users abide by platform rules and regulations and are incentivized to demonstrate honest, trustworthy conduct. Accrual of “reputation” in these platforms, most prominently those in the e-commerce domain, is motivated by self-interested goals such as acquiring an advantage over competing platform users. Therefore, in community-oriented platforms, where the goals are to foster collaboration and cooperation among community members, such reputation systems are inappropriate and indeed contrary to the intended ethos of the community and actions of its members. In this article, we argue for a new form of reputation system that encourages cooperation rather than competition, derived from conceptualizing platform communities as a networked assemblage of users and their created content. In doing so, we use techniques from social network analysis to conceive a form of reputation that represents members’ community involvement over a period of time rather than a sum of direct ratings from other members. We describe the design and implementation of our reputation system prototype called “commonshare” and preliminary results of its use within a Digital Social Innovation platform. Further, we discuss its potential to generate insight into other networked communities for their administrators and encourage cooperation between their users.

An Incentive and Reputation Mechanism Based on Blockchain for Crowd Sensing Network

Nowadays, sensors inserted in mobile applications are used for gathering data for an explicit assignment that can effectively save cost and time in crowd sensing networks (CSNs). The true value and essence of gathered statistics depend on the participation level from all the members of a CSN, i.e., service providers, data collectors, and service consumers. In comparison with the centralized conventional mechanisms that are susceptible to privacy invasion, attacks, and manipulation, this article proposes a decentralized incentive and reputation mechanism for CSN. The monetary rewards are used to motivate the data collectors and to encourage the participants to take part in the network activities. Whereas the issue of privacy leakage is dealt with using Advanced Encryption Standard (AES128) technique. Additionally, a reputation system is implemented to tackle issues like data integrity, fake reviews, and conflicts among entities. Through registering reviews, the system encourages data utilization by providing correct, consistent, and reliable data. Furthermore, simulations are performed for analyzing the gas consumed by smart contracts. Similarly, the encryption technique is ratified by comparing its execution time with other techniques that are previously used in literature. Lastly, the reputation system is inspected through analyzing the gas consumption and mining time of input string length.

‘Thank you for your compliance’: Overwatch as a Disciplinary System

Toxicity in online multiplayer games has long been an issue, and game developers implement various strategies such as reputation systems to curb such behaviour. Although Foucault’s notion of discipline seems an ideal lens through which to analyse such reputation systems, as of yet there has been little work on the subject. This article addresses the reputation system implemented in 2018 by Blizzard, who created an endorsement system in the team-based multiplayer shooter Overwatch. This successfully encouraged positive player behaviour by implementing rewards, rather than only punishments. In this article, we examine the endorsement system as an example of Foucault’s discipline, one that is particularly relevant to game design because it uses incentives as well as deterrents. We argue that the endorsement system is particularly effective as a form of discipline because it includes players as part of the process, by actively constructing subjects (gamers) to fit a pre-defined mould.

Blockchain Technology: A Brief Overview

Blockchain technology and distributed ledger has attracted massive attention and has triggered multiple projects in different industries. Blockchain is one of the most important technical invention in the recent years. It serves as an immutable ledger which allows transactions to take place in a decentralized manner. Blockchain based applications are springing up and are covering numerous fields including financial services, reputation system and Internet of Things (IoT), and so on. However, there are still many challenges of blockchain technology such as scalability and security problems waiting to be overcome. This paper presents a comprehensive overview on blockchain technology.

The role of reputation systems in digital discrimination

Reputation systems are commonplace in online markets, such as on peer-to-peer sharing platforms. These systems have been argued to be a solution to (ethnic) discrimination on such platforms. This argument is based on empirical studies showing that ethnic disadvantages are smaller for users with ratings than for users without ratings. We argue that this conclusion may be premature, because minorities have a harder time accumulating ratings. The greater benefit of ratings to minorities may be offset by their troubles acquiring any, thereby diminishing the potential for reputation systems to reduce discrimination. We tested this counterargument using a unique data set that contains information on all interactions on a peer-to-peer motorcycle rental platform. We find that the reputation system does not reduce initial inequalities between otherwise comparable renters of different ethnicity. Platforms that wish to reduce discrimination should not only make their reputation system more effective, but also help users collect ratings.