Practice based competency development: a study of resource geologists and the JORC code system

The mining industry is a major contributor to the Australian economy. The value of mining and exploration shares traded on the Australian Stock Exchange are contingent on the estimates of mineral deposits, which are disclosed publically in accordance with a reporting code maintained by the Australasian Joint Ore Reserves Committee (the JORC Code). Expert resource geologists, known as Competent Persons, provide classified estimates of mineral endowment that underpin these public statements. The JORC Code requirements for qualifying as Competent Persons are membership of an approved professional association and a minimum of five years’ relevant experience. This research set out to address a primarily practical issue: How do the mining industry, mining companies and individuals cooperate to develop resource geologists with sufficient competency to provide expert recommendations for public reporting of mineral resources? A corollary to this is ‘Are the current standards sufficient to identify the competency expectations placed on Competent Persons?’ It is challenging to place the subsequent research in any one discipline as the study draws on multiple theories across multiple domains to facilitate a relevant description of the practicebased competency development. To properly understand the the practice of resource geologists operating in a sub-sector within the JORC Code system, the research needed to explore and consolidate diverse theories such as theories on social structures, workplace learning theories and statistical reasoning education theories. In addition, as a mixed methods study, the research draws on a wide range of tools from qualitative iterative coding and theming techniques to the more rigorous statistical tools of t-tests, paired t-tests, ANOVA and the philosophically different Rasch Analysis method. This study reflects a broad curiosity in diverse concepts and theories that is combined with the researcher’s desire to provide a meaningful practical contribution to the mining industry. The practical outcome of this research is a revised set of criteria to meet Competent Persons status under the JORC Code that is supported by a competency development model. These models are generalised to reflect a revised competency model, based on the dual expectations of practice exposure and reasoning ability, and an associated competency development model, which synthesises contributions of workplace learning experiences. The contributions to the theory include a revised theory of workplace learning networks emerging from the practice context of transient professional workers. These networks are enduring, transient and egocentric and operate beyond organisational confines

Introduction to location-based mobile learning

[About the book] The report follows on from a 2-day workshop funded by the STELLAR Network of Excellence as part of their 2009 Alpine Rendez-Vous workshop series and is edited by Elizabeth Brown with a foreword from Mike Sharples. Contributors have provided examples of innovative and exciting research projects and practical applications for mobile learning in a location-sensitive setting, including the sharing of good practice and the key findings that have resulted from this work. There is also a debate about whether location-based and contextual learning results in shallower learning strategies and a section detailing the future challenges for location-based learning

When practice does not make perfect: Differentiating between productive and unproductive persistence

Research has suggested that persistence in the face of challenges plays an important role in learning. However, recent work on wheel-spinning—a type of unproductive persistence where students spend too much time struggling without achieving mastery of skills—has shown that not all persistence is uniformly beneficial for learning. For this reason, Study 1 used educational data-mining techniques to determine key differences between the behaviors associated with productive persistence and wheel-spinning in ASSISTments, an online math learning platform. This study’s results indicated that three features differentiated between these two modes of persistence: the number of hints requested in any problem, the number of bottom-out hints in the last eight problems, and the variation in the delay between solving problems of the same skill. These findings suggested that focusing on number of hints can provide insight into which students are struggling, and encouraging students to engage in longer delays between problem solving is likely helpful to reduce their wheel-spinning. Using the same definition of productive persistence in Study 1, Study 2 attempted to investigate the relationship between productive persistence and grit using Duckworth and Quinn’s (2009) Short Grit Scale. Correlational results showed that the two constructs were not significantly correlated with each other, providing implications for synthesizing literature on student persistence across computer-based learning environments and traditional classrooms

Augmenting the field experience: a student-led comparison of techniques and technologies

In this study we report on our experiences of creating and running a student fieldtrip exercise which allowed students to compare a range of approaches to the design of technologies for augmenting landscape scenes. The main study site is around Keswick in the English Lake District, Cumbria, UK, an attractive upland environment popular with tourists and walkers. The aim of the exercise for the students was to assess the effectiveness of various forms of geographic information in augmenting real landscape scenes, as mediated through a range of techniques and technologies. These techniques were: computer-generated acetate overlays showing annotated wireframe views from certain key points; a custom-designed application running on a PDA; a mediascape running on the mScape software on a GPS-enabled mobile phone; Google Earth on a tablet PC; and a head-mounted in-field Virtual Reality system. Each group of students had all five techniques available to them, and were tasked with comparing them in the context of creating a visitor guide to the area centred on the field centre. Here we summarise their findings and reflect upon some of the broader research questions emerging from the project

Statistical learning for alloy design from electronic structure calculations

The objective of this thesis is to explore how statistical learning methods can contribute to the interpretation and efficacy of electronic structure calculations. This study develops new applications of statistical learning and data mining methods to both semi-empirical and density functional theory (DFT) calculations. Each of these classes of electronic structure calculations serves as templates for different data driven discovery strategies for materials science applications. In our study of semi-empirical methods, we take advantage of the ability of data mining methods to quantitatively assess high dimensional parameterization schemes. The impact of this work includes the development of accelerated computational schemes for developing reduced order models. Another application is the use of these informatics based techniques to serve as a means for estimating parameters when data for such calculations are not available. Using density of states (DOS) spectra derived from DFT calculations we have demonstrated the classification power of singular value decomposition methods to accurately develop structural and stoichiometric classifications of compounds. Building on this work we have extended this analytical strategy to apply the predictive capacity of informatics methods to develop a new and far more robust modeling approach for DOS spectra, addressing an issue that has gone relatively unchallenged over two decades. By exploring a diverse array of materials systems (metals, ceramics, different crystal structures) this work has laid the foundations for expanding the linkages between statistical learning and statistical thermodynamics. The results of this work provide exciting new opportunities in computational based design of materials that have not been explored before

Data Science at USNA

Data Science is increasingly important to the Navy and Marine Corps. We survey some of the ways that civilian institutions are delivering Data Science curriculum, outline a vision for developing Data Science curriculum at the United States Naval Academy (USNA), and summarize some of the accomplishments and planned activities of the Data Science group at USNA