Evaluating Digital Libraries: A Longitudinal and Multifaceted View

published or submitted for publicatio

Learning Sciences Beyond Cognition: Exploring Student Interactions in Collaborative Problem Solving

Composed of insightful essays from top figures in their respective fields, the book also shows how a thorough understanding of this critical discipline all but ensures better decision making when it comes to education

Understanding relations of individual-collective learning in work: A review of research

Abstract: A review was conducted of literature addressing learning in work, focusing on relations between individual and collective learning published in nine journals during the period 1999-2004. The journals represent three distinct fields of management/organization studies, adult education, and human resource development: all publish material about workplace learning regularly. A total of 209 articles were selected for content analysis, containing a range of material including reports of empirical research to theoretical discussion. Eight themes of individual-collective learning were identified through inductive content analysis of this literature: individual knowledge acquisition, sensemaking/reflective dialogue, levels of learning, network utility, individual human development, individuals in community, communities of practice, and a co-participation or co-emergence theme. The discussion notes apparent lack of dialogue across the fields despite similar concepts, the ontological and ideological differences among the themes of learning currently in circulation, and the low frequency of analysis of power relations in the articles reviewed

Mechanisms for the generation and regulation of sequential behaviour

A critical aspect of much human behaviour is the generation and regulation of sequential activities. Such behaviour is seen in both naturalistic settings such as routine action and language production and laboratory tasks such as serial recall and many reaction time experiments. There are a variety of computational mechanisms that may support the generation and regulation of sequential behaviours, ranging from those underlying Turing machines to those employed by recurrent connectionist networks. This paper surveys a range of such mechanisms, together with a range of empirical phenomena related to human sequential behaviour. It is argued that the empirical phenomena pose difficulties for most sequencing mechanisms, but that converging evidence from behavioural flexibility, error data arising from when the system is stressed or when it is damaged following brain injury, and between-trial effects in reaction time tasks, point to a hybrid symbolic activation-based mechanism for the generation and regulation of sequential behaviour. Some implications of this view for the nature of mental computation are highlighted

Use of automated coding methods to assess motivational behaviour in education

Teachers’ motivational behaviour is related to important student outcomes. Assessing teachers’ motivational behaviour has been helpful to improve teaching quality and enhance student outcomes. However, researchers in educational psychology have relied on self-report or observer ratings. These methods face limitations on accurately and reliably assessing teachers’ motivational behaviour; thus restricting the pace and scale of conducting research. One potential method to overcome these restrictions is automated coding methods. These methods are capable of analysing behaviour at a large scale with less time and at low costs. In this thesis, I conducted three studies to examine the applications of an automated coding method to assess teacher motivational behaviours. First, I systematically reviewed the applications of automated coding methods used to analyse helping professionals’ interpersonal interactions using their verbal behaviour. The findings showed that automated coding methods were used in psychotherapy to predict the codes of a well-developed behavioural coding measure, in medical settings to predict conversation patterns or topics, and in education to predict simple concepts, such as the number of open/closed questions or class activity type (e.g., group work or teacher lecturing). In certain circumstances, these models achieved near human level performance. However, few studies adhered to best-practice machine learning guidelines. Second, I developed a dictionary of teachers’ motivational phrases and used it to automatically assess teachers’ motivating and de-motivating behaviours. Results showed that the dictionary ratings of teacher need support achieved a strong correlation with observer ratings of need support (rfull dictionary = .73). Third, I developed a classification of teachers’ motivational behaviour that would enable more advanced automated coding of teacher behaviours at each utterance level. In this study, I created a classification that includes 57 teacher motivating and de-motivating behaviours that are consistent with self-determination theory. Automatically assessing teachers’ motivational behaviour with automatic coding methods can provide accurate, fast pace, and large scale analysis of teacher motivational behaviour. This could allow for immediate feedback and also development of theoretical frameworks. The findings in this thesis can lead to the improvement of student motivation and other consequent student outcomes

Assessing Thinking In and Through the Arts: Second Year Evaluation of the California Arts Demonstration Project

For two years, the Workshop participated in an evaluation project run by the California Arts Council. The goals of this project were to identify potentially "at-risk" student populations and then evaluate the effects of a Creative Movement or Theatre residency in the classroom. Areas for student improvement were based on the Workshop's Cycle of Artistic Inquiry which seeks to demonstrate the process of critical thinking through arts learning. The following reports deal with the findings of this project at three separate locations: The Paul Robeson & Diego Rivera Academy, John Muir Elementary, and Mission Education Center

The Net of Jewels: An exploration and shape-based guitar pedagogy for songwriters

This article offers an informal, summary description of the Net of Jewels (NOJ) method, a guitar pedagogy specifically targeted to songwriters writing songs on guitar. The core of the NOJ approach is a progressive sequence of activities that incorporate shape-directed exploration of the guitar fingerboard as an integral aspect, supporting insights about harmony and theory, advancement of guitar skills and technique, and innovative creative work. The article outlines NOJ\u27s core concepts and teaching principles, describes NOJ\u27s pedagogical sequence of topics and supporting exercises and other activities, and provides background on the method\u27s origin and evolution. This description reflects the author\u27s perspective as the developer of NOJ, based on two decades of experience in teaching and refining the method, including the design of two levels of NOJ-based courses, incorporated into the songwriting curriculum at Berklee College of Music

The Job of Human Capital: What Occupational Data Reveal About Skill Sets, Economic Growth and Regional Competitiveness

A region\u27s workforce has been described as its greatest asset. Guided by human capital theory and new growth theory, regions have pursued economic development policies to increase the number of college-educated workers and expand the pool of STEM -- science, technology, engineering, and math -- talent. Academic literature and policy interventions have focused on a region\u27s human capital in terms of educational attainment instead of a more fine-grained definition of human capital based on skills and competencies. This dissertation integrates economic and business theory and combines three federal databases to explore regional human capital assets. Findings suggest that policymakers may be overestimating the importance of STEM knowledge requiring a bachelor\u27s degree or higher and undervaluing the importance of soft skills such as communication and critical-thinking. Moreover, results indicate that regions may be best served by crafting distinct human capital interventions that reflect the particular needs of their mix of industry

The Job of Human Capital: What Occupational Data Reveal About Skill Sets, Economic Growth and Regional Competitiveness

A region\u27s workforce has been described as its greatest asset. Guided by human capital theory and new growth theory, regions have pursued economic development policies to increase the number of college-educated workers and expand the pool of STEM -- science, technology, engineering, and math -- talent. Academic literature and policy interventions have focused on a region\u27s human capital in terms of educational attainment instead of a more fine-grained definition of human capital based on skills and competencies. This dissertation integrates economic and business theory and combines three federal databases to explore regional human capital assets. Findings suggest that policymakers may be overestimating the importance of STEM knowledge requiring a bachelor\u27s degree or higher and undervaluing the importance of soft skills such as communication and critical-thinking. Moreover, results indicate that regions may be best served by crafting distinct human capital interventions that reflect the particular needs of their mix of industry