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The purpose of this paper is to analyse the critical role reflection plays in work-based learning (WBL).

This paper presents an contextualist examination of reflection in the WBL environment.

People consciously reflect in order to understand events in their lives and as a consequence hopefully add and enhance meaning.

Reflection is associated therefore with “looking back” and examining the past in order to learn from what happened and perhaps not repeat mistakes. However, it is also increasingly associated with reflecting on action (Schon, 1983) and encourages an exploring of thoughts and feelings; looking for insights; and maximizing on self-awareness which all tie the process closely to identity formation (Lacan, 1977).

If used effectively and purposefully reflection facilitates ongoing personal and professional learning, and creates and develops practitioners capable of demonstrating their progression towards learning outcomes and required standards. Reflection can also provide a structure in which to make sense of learning, so that concepts and theories become embedded in practice, and constant thought and innovation are simultaneously fostered.

By actively considering the thoughts and actions one becomes aware of the power of reflective thinking as a tool for continuous improvement, and one that has implications beyond the personal.

This paper represents the first study which examines the role reflection plays in WBL.

The growth of online communities and social media has led to a growing need for methods, concepts, and tools for researching online cultures. Particular attention should be paid to polarizing online discussion cultures and dynamics that increase inequality in online environments. Social media has enormous potential to create good, but in order to unlock its full potential, we also need to examine the mechanisms keeping these spaces monotonous, homogenous, and even hostile toward some groups. With this need in mind, I have developed the concept and theory of othering online discourse (OOD).

This chapter introduces and defines the concept of OOD and explains the key characteristics and different attributes of OOD in relation to other concepts that deal with disruptive and discriminatory behavior in online spaces. The attributes of OOD are demonstrated drawing on examples gathered from the Finnish Suomi24 (Finland24) forum.

Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and established companies to get the needed funds to support innovations. After one decade of research, mainly focused on relations between variables and outcomes of the CF campaign, the literature shows methodological lacks about the study of its overall behavior. These reflect into a weak theoretical understanding and inconsistent managerial guidance, leading to a 27% success ratio of campaigns. To bridge this gap, this paper embraces a “complex system” perspective of the CF campaign, able to explore the system's behavior of a campaign over time, in light of its causal loop structure.

By adopting and following the document model building (DMB) methodology, a set of 26 variables and mutual causal relations modeled the system “Crowdfunding campaign” and a data set based on them and crafted to model the “Crowdfunding campaign” with a causal loop diagram. Finally, system archetypes have been used to link the causal loop structure with qualitative trends of CF's behavior (i.e. the raised capital over time).

The research brought to 26 variables making the system a “Crowdfunding campaign.” The variables influence each other, thus showing a set of feedback loops, whose structure determines the behavior of the CF campaign. The causal loop structure is traced back to three system archetypes, presiding the behavior in three stages of the campaign.

The value of this paper is both methodological and theoretical. First, the DMB methodology has been expanded and reinforced concerning previous applications; second, we carried out a causation analysis, unlike the common correlation analysis; further, we created a theoretical model of a “Crowdfunding Campaign” unlike the common empirical models built on CF platform's data.