Babak Naderi

Magnetic signatures in air for mobile devices

Recently, a new authentication method based on 3D signatures created in air is proposed for mobile devices [4]. The 3D signature is created in air using a properly shaped magnet (a rod or ring) taken in hand. It is based on influencing compass sensor embedded in the new generation of mobile devices. In this paper, we present implementation of this technology on a mobile device (iPhone 3GS). It can demonstrate authentication process using a gesture in the from of a 3D signature freely created in the space around the device by a magnet held in hand. Movement of the magnet in the from of a signature produces a temporal change in the magnetic field sensed by the embedded compass sensor, and can be used as a basis for authentication. As magnetic signatures are performed in 3D space, they can provide a wider choice for authentication, and they can not be easily hardcopied.

Effect of being observed on the reliability of responses in crowdsourcing micro-task platforms

In this paper, the reliability of responses collected in two crowdsourcing studies is compared. Two methods to evaluate the reliability of responses (one noticeable and one unnoticeable method for workers) have been employed. The unnoticeable method is included in both studies; the noticeable method is employed in one study only. The study containing the noticeable reliability check method resulted in a higher consistency of the responses than the other one. We assume that the difference is a result of the obvious reliability check method: Workers improve their performance due to the awareness that they are being observed.

Development and Validation of Extrinsic Motivation Scale for Crowdsourcing Micro-task Platforms

In this paper, we introduce a scale for measuring the extrinsic motivation of crowd workers. The new questionnaire is strongly based on the Work Extrinsic Intrinsic Motivation Scale (WEIMS) [17] and theoretically follows the Self-Determination Theory (SDT) of motivation. The questionnaire has been applied and validated in a crowdsourcing micro-task platform. This instrument can be used for studying the dynamics of extrinsic motivation by taking into account individual differences and provide meaningful insights which will help to design a proper incentives framework for each crowd worker that eventually leads to a better performance, an increased well-being, and higher overall quality.

MagiGuitar: a guitar that is played in air!

In this work we present MagiGuitar - a guitar music performance application played in air on iPhone 3GS using a magnet! Users can play the mobile guitar application by moving a permanent magnet around a mobile device embedding a compass sensor (magnetometer). The touch less magnetic music performance technique allows users to play the mobile guitar application using highly intuitive hand gestures in the form of strumming action similar to a real guitar but in air. The proposed technique provides higher degree of flexibility for music performance, as the interaction space is extended to 3D space around the device. This allows users to play music in mobile devices using more natural, comfortable and flexible hand gestures as done with real instruments.

Who are the Crowdworkers

Crowdworkers are the key component and the main drive of the crowdsourcing microtask platforms. Their skills, ability, and diversity shape the functionalities and define the scope of services that can be provided by platforms. Depending on the platform, crowdworkers exhibit a different degree of diversity in gender, education, the country of origin, and socioeconomical background.

Understanding the Crowd: Ethical and Practical Matters in the Academic Use of Crowdsourcing

The driving force behind digital crowdsourcing are its workers: working, hidden behind the scenes, churning out data in experiments, participating in research studies, completing little tasks to accomplish HITs online. Understanding workers and crowdwork better is therefore key to develop a more effective and fair use of crowdsourcing for research. This chapter attempts to help develop an understanding of the various aspects of the crowd by drawing parallels between workers of different platforms (AMT, Microworkers and Crowdee) through quantitative and qualitative analysis of current and newly collected data. A picture of the crowd is drawn by uncovering their motivations, workplaces, skills and infrastructure, issues and perspectives about the design of microtasks, the employers and the microtask-based platforms. Legal and ethical perspectives on crowdwork are also discussed, and online resources are reviewed that researchers can use as a primer to employ crowdworkers in an ethical and fair way. The chapter provides information, a review of internationally recognised ethical principles and practical advice to those who would like to use crowdsourcing for experiments and to carry out research studies as an informed researcher and crowd employer.

What Influences Workers’ Performance?

The inadequacy of collected data through crowdsourcing microtask jobs was addressed numerously. Different reasons were given, namely task related (ill-designed jobs like given instruction may be misunderstood), worker related (participants who do not focus enough, share their attention with a parallel activity and do not work as instructed or try to maximize their monetary benefit with minimum effort), and environment related (workers may be interrupted or use inadequate equipment) [77, 82, 83, 93]. To reduce their impact, different quality control approaches were proposed such as using gold standards, majority voting, and behavioral logging to evaluate reliability of the collected data in post-processing [17, 31]. In the context of QoE, researchers have used additional methods like content questions and consistency tests [46, 47].

How to Measure Motivation

In this chapter, the development of the Crowdwork Motivation Scale (CWMS) for measuring the general underlying motivation of crowdworkers is described.

What Determines Task Selection Strategies

In this chapter, five studies are described aiming to answer questions about factors influencing the task choice of crowdworkers. Accepting to perform a microtask indicates that corresponding motives exist and are more powerful than obstacles which lead to enough motivation for performing the task. The first study aimed to find out the relevant factors (motives and obstacles) that are influencing the workers’ task choice.

Theoretical Background on Motivation

In this chapter, a taxonomy of motivation of crowdworkers is presented which is empirically evaluated during this dissertation.