applied sciences Review Mass Collaboration and Learning: Opportunities, Challenges, and Influential Factors Majid Zamiri * and Luis M. Camarinha-Matos Faculty of Science and Technology and CTS-Uninova, Nova University of Lisbon, 2829-516 Caparica, Portugal * Correspondence: ma.zamiri@campus.fct.unl.pt Received: 7 May 2019; Accepted: 22 June 2019; Published: 28 June 2019   Abstract: Learning ecosystems can benefit from mass collaboration where large numbers of minds collectively drive intellectual efforts to learn in the form of knowledge building and sharing. Mass collaborative learning represents a significant shift away from traditional teacher-centered approach towards a self-directed model in virtual communities in which contributing members take on creative roles to maximize their learning and that of their peers. In order to design, implement, and exploit such a learning approach, influencing constituents should be identified, and appropriate conditions need to be provided. This study aims to systematically review recent literature with a view to identifying relevant affecting constituents and success factors for mass collaboration and learning—namely, the type of organizational structures, collaborative learning techniques, adopted technologies, and methods for evaluating the quality of both members’ performance, and co-created knowledge. Therefore, 100 related papers are collected, and their findings are critically evaluated. The results of evaluation are then addressed and discussed. Keywords: mass collaboration; learning; knowledge and information 1. Introduction Significant advances in information and communication technology (ICT) and more specifically Internet-based solutions that have arisen over the last few years have opened new avenues to collaborate massively in ways seemed impossible even a few decades ago. There is a great shift from hierarchical collaboration towards online decentralized models. The number of people across the globe coming to take part in collaborative initiatives has increased to unprecedented levels. History shows that mass collaboration has been helping organizations and communities to potentially reduce the barriers of starting huge projects, and successfully leverage the resources, energy, skills, talents, and knowledge. When large numbers of self-organized members actively participate in collective learning, they can help with saving money, creating a social spirit, increasing transparency, outcome ownership, and awareness, and harnessing cognitive surplus [1]. Mass collaboration is a promising approach for agile knowledge creation and sharing. This fascinating phenomenon in education and learning was successfully proven by Wikipedia. However, in today’s world of proliferation of knowledge, information, and data through the use of new digital tools, it is imperative for users to be well prepared to carefully pick those items that are reliable, true, and healthy. While the volume of online shared materials is astounding, identifying knowledge of high quality is now becoming a serious challenge. Unlike printed materials in serious newspapers, magazines, books, and academic libraries or similar information found in well-reputed radio and television broadcasts, knowledge transferred through the Internet and social media is not regulated for accuracy and quality. That is, anybody can publish anything they wish with very few limitations. People may present their opinion as a fact; and some individuals might find it as an ideal venue for personal, political, or commercial propaganda since there is no Appl. Sci. 2019, 9, 2620; doi:10.3390/app9132620 www.mdpi.com/journal/applsci