Getting Recent Graduates to the Point Where They Know What They Don't Know.

• Author: Kosicek, Michael

INTRODUCTION

While earning a university degree, students focus on success. Earning as close to a 4.0 is seen as a marker of success and as such the "best" students rarely encounter failure during their formal education. However, research has shown that failure is a better source of learning than success (McGrath 1999; Sitkin, 1992). This creates a challenge for businesses. As students enter the workplace, they are entering a world of uncertainty. The problems that they encounter will rarely have a textbook solution and they will likely encounter situations where their managers and coworkers are equally perplexed. It is not easy to learn from failure. Ucbasaran et al. (2013) state that failure represents an opportunity to learn, but in a context where it is difficult to do so. However, extensive research has shown that it is an effective tool (Byrne & Shepherd, 2015; Cope, 2011; Madsen & Desai, 2010; Minniti & Bygrave, 2001).

Expert information processing theory (Baron & Henry, 2010; Mitchell et al., 2007) suggests that traumatic experiences leading up to failure are a simple and generalizable learning context. When individuals enter a situation where failure is a distinct possibility, they will fight to avoid failure. This fight will act as a teaching device (Lipinski et al., 2013), forcing individuals into a cycle of trial and error which will lead to the creation of knowledge and expertise. Thus, we suggest that one can use the tenets of the deliberate practice model as developed in the expert-performance literature (Charness et al., 2005). Ericsson et al. (2007) suggest that the development of genuine expertise requires struggle, sacrifice, and honest, almost painful, self-assessment. Even on the job, senior managers and experienced coworkers may not know the answer to many problems that a new hire will encounter. Building early career success requires one to develop the skills and acumen to solve complex problems as new hires fight to avoid failure (Cope, 2011).

THEORY DEVELOPMENT

Expert Information Processing

Von Hayek (1937) suggest that the acquisition of human knowledge depends on explanations that render data into information. Shiffrin and Schneider (1977) and Lachman et al. (1979) build on that idea to suggest that humans process information through a framework where types of processing are differentiated (e.g., automatic versus controlled). Such processing makes the data usable when solving problems.

Expert information processing theory has its roots in Degroot (1946) who suggested a linkage between expert task performance and visual memory/visual perception using the mastery of chess as an example. However, formal theory development began in 1973 with Chase and Simon (1973) who observed that experts are different cognitively, specifically in how they process information. Their work led to the observation that skilled memory explains expert performance (Chase & Ericsson, 1982) and that differences between experts and novices exist based on the learning process endured by the experts (Glaser, 1984).

Rather than natural talent or accumulated knowledge, such as classroom learning, researchers (e.g., Barton & Pretty 2010; Ericsson, 2005) have suggested deliberate practice, engaging in real world activities rather than formal instruction, as the primary factor leading to the development of expert level cognitive systems. Deliberate practice will lead to a cognitive system consisting of both an expert level knowledge base and an expert-level problem-solving process. The process includes a repetition of the desired skills and using ongoing feedback from coaches (e.g...