Coaching knowledge, learning and mentoring in the Australian Football League

Understanding the work of Senior and Assistant Coaches in the AFL is important to better develop the next generation of performance coaches. Hence the focus of this research was to examine the knowledge, competences and learning of senior and assistant coaches in the Australian Football League. Specifically, the research sought to understand the ways in which Senior and Assistant Coaches in the AFL have come to know their “craft” with the particular aim of enhancing future coaching practice. Performance coaching is generally regarded as a cognitive activity and therefore “getting inside the heads” of AFL coaches will assist in our understanding of the complex coaching work in which they are engaged. In-depth interviews provided coaches an opportunity to reflect on their practices and how they learned their craft. Fundamental to this research was an understanding that the AFL and each club within the league be regarded as learning organizations and workplaces where learning takes place. Moreover the process of mentoring is regarded as a central learning process and a significant factor contributing to improved professional coaching practice. This applied research aims to inform coach development in Australian football, the annual review process (quality of performance) of employed coaches, and the recruitment of coaches in the AFL. Improving the quality of coaching in the AFL will, in turn, improve the performance of the players and teams, and subsequently enhance the continued development and sustainability of the game.

How can evaluative thinking and practice inform performance models for organizations and personnel

In the world today there are many ways in which we measure, count and determine whether something is worth the effort or not. In Australia and many other countries, new government legislation is requiring government-funded entities to become more transparent in their practice and to develop a more cohesive narrative about the worth, or impact, for the betterment of society. This places the executives of such entities in a position of needing evaluative thinking and practice to guide how they may build the narrative that documents and demonstrates this type of impact. In thinking about where to start, executives, project and program managers may consider this workshop as a professional development opportunity to explore both the intended and unintended consequences of performance models as tools of evaluation. This workshop will offer participants an opportunity to unpack the place of performance models as an evaluative tool through the following: · What shape does an ethical, sound and valid performance measure for an organization or personnel take? · What role does cultural specificity play in the design and development of a performance model for an organization or for personnel? · How are stakeholders able to identify risk during the design and development of such models? · When and where will dissemination strategies be required? · And so what? How can you determine that your performance model implementation has made a difference now or in the future?

The hype cycle model: A review and future directions

The hype cycle model traces the evolution of technological innovations as they pass through successive stages pronounced by the peak, disappointment, and recovery of expectations. Since its introduction by Gartner nearly two decades ago, the model has received growing interest from practitioners, and more recently from scholars. Given the model's proclaimed capacity to forecast technological development, an important consideration for organizations in formulating marketing strategies, this paper provides a critical review of the hype cycle model by seeking evidence from Gartner's own technology databases for the manifestation of hype cycles. The results of our empirical work show incongruences connected with the reports of Gartner, which motivates us to consider possible future directions, whereby the notion of hype or hyped dynamics (though not necessarily the hype cycle model itself) can be captured in existing life cycle models through the identification of peak, disappointment, and recovery patterns.