Group items tagged

Theoretical and empirical evidence in the learning sciences substantiates the view that deep engagement in learning is a function of a complex combination of learners' identities, dispositions, values, attitudes and skills. When these are fragile, learners struggle to achieve their potential in conventional assessments, and critically, are not prepared for the novelty and complexity of the challenges they will meet in the workplace, and the many other spheres of life which require personal qualities such as resilience, critical thinking and collaboration skills. To date, the learning analytics research and development communities have not addressed how these complex concepts can be modelled and analysed, and how more traditional social science data analysis can support and be enhanced by learning analytics. We report progress in the design and implementation of learning analytics based on a research validated multidimensional construct termed "learning power". We describe, for the first time, a learning analytics infrastructure for gathering data at scale, managing stakeholder permissions, the range of analytics that it supports from real time summaries to exploratory research, and a particular visual analytic which has been shown to have demonstrable impact on learners. We conclude by summarising the ongoing research and development programme and identifying the challenges of integrating traditional social science research, with learning analytics and modelling.

CORE IDEAS We decided on the name Learning Emergence because we are very much learning about emergence and complex systems phenomena ourselves, even as we develop our thinking on learning as an emergent, systemic phenomenon in different contexts. We must shift to a new paradigm for learning in schools, universities and the workplace which addresses the challenges of the 21st Century. Society needs learners who can cope with intellectual, ethical and emotional complexity of an unprecedented nature. Learning Emergence partners share an overarching focus on deep, systemic learning and leadership - the pro-active engagement of learners and leaders in their own authentic learning journey, in the context of relationship and community. We work at the intersection of (1) deep learning and sensemaking, (2) leadership, (3) complex systems, and (4) technology:

Simon Buckingham Shum Ruth Deakin Crick 2012 (In review) Theoretical and empirical evidence in the learning sciences  substantiates the view that deep engagement in learning is a  function of a  combination of learners' dispositions,  values,  attitudes and skills. When these are fragile, learners struggle to  achieve their potential in conventional assessments, and critically,  are not prepared for the novelty and complexity of the challenges  they will meet in the workplace, and the many other spheres of  life which require personal qualities such as resilience, critical  thinking and collaboration skills. To date, the learning analytics  research and development communities have not addressed how  these complex concepts can be modelled and analysed. We report  progress in the design and implementation of learning analytics  based on an empirically validated  multidimensional construct  termed  "learning power". We describe a  learning analytics  infrastructure  for gathering data at scale, managing stakeholder  permissions, the range of analytics that it supports from real time  summaries to exploratory research, and a particular visual analytic which has been shown to have demonstrable impact on learners.  We conclude by  summarising the ongoing research and  development programme.

"Rethinking Educaitonal Leadership: mapping the terrain of leadership in learning organisations in conditions of complexity, diversity and change Jul 26 2015 0 Rethinking Educational Leadership: an Open Space Symposium The purpose Symposium was to provide experienced practitioners and researchers with an opportunity to bring fresh thinking to the current challenges facing school leaders and to generate new ideas about leadership development. The Open Space Technology provided a means of capturing the collective intelligence generated by the group in response to the core question. This post reports on the outcomes of this Open Space Symposium which was held in 2013. "

"The American Statistical Association seeks to embrace science's inherent complexity and push for more data transparency by rejecting a common, oversimplified measure of statistical significance. March 15, 2016 By Colleen Flaherty Is the tyrannical reign of the P value finally ending (if it was ever tyrannical at all)? An unprecedented statement from the American Statistical Association seeks to usher in a "post-P

Information graphics or infographics are graphic visual representations of information, data or knowledge. These graphics present complex information quickly and clearly,[1] such as in signs, maps, journalism, technical writing, and education. With an information graphic, computer scientists, mathematicians, and statisticians develop and communicate concepts using a single symbol to process information.

50 MOST STUNNING EXAMPLES OF DATA VISUALIZATION AND INFOGRAPHICS Posted by Richie on Thursday, April 15, 2010 "A picture is worth a thousand words", if I had a penny for every time I heard that!! There is so much data in the world today that it has become impossible for us to analyze them with patience. Data as we perceive it, need not be boring, bland and cumbersome to remember. To make complex things seem simple, is Creativity and using pictures to represent data has been an age old method to analyze data in a fun way. From navigating the web in an entirely new dimension to understanding how the human brain works; from peeking into how Google has evolved to analyzing the inner working of the geeky mind, Infographics has completely changed the way we view content and visualize data.

Measuring Teacher Effectiveness Significant State Data Capacity is Required to Measure and Improve Teacher Effectiveness  States Increasingly Focus on Improving Teacher Effectiveness: There is significant activity at the local, state, and federal levels to  measure and improve teacher effectiveness, with an unprecedented focus on the use of student achievement as a primary indicator of  effectiveness. > 23 states require that teacher evaluations include evidence of student learning in the form of student growth and/or value-added data (NCTQ, 2011). > 17 states and DC have adopted legislation or regulations that specifically require student achievement and/or student growth to "significantly" inform or be the primary criterion in teacher evaluations(NCTQ, 2011).  States Need Significant Data Capacity to Do This Work: These policy changes have significant data implications. > The linchpin of all these efforts is that states must reliably link students and teachers in ways that capture the complex connections that  exist in schools. > If such data is to be used for high stakes decisions-such as hiring, firing, and tenure-it must be accepted as valid, reliable, and fair. > Teacher effectiveness data can be leveraged to target professional development, inform staffing assignments, tailor classroom instruction,  reflect on practice, support research, and otherwise support teachers.  Federal Policies Are Accelerating State and Local Efforts: Federal policies increasingly support states' efforts to use student  achievement data to measure teacher effectiveness. > Various competitive grant funds, including the Race to the Top grants and the Teacher Incentive Fund, require states to implement teacher  and principal evaluation systems that take student data into account.  > States applying for NCLB waivers, including the 11 that submitted requests in November 2011, must commit to implementing teacher and  principal evaluation and support systems. > P

"Abstract The authors compared the underlying student response patterns to an end-of-course rating instrument for large student samples in online, blended and face-to-face courses. For each modality, the solution produced a single factor that accounted for approximately 70% of the variance. The correlations among the factors across the class formats showed that they were identical. The authors concluded that course modality does not impact the dimensionality by which students evaluate their course experiences. The inability to verify multiple dimensions for student evaluation of instruction implies that the boundaries of a typical course are beginning to dissipate. As a result, the authors concluded that end-of-course evaluations now involve a much more complex network of interactions. Highlights ► The study models student satisfaction in the online, blended, and face-to-face course modalities. ► The course models vary technology involvement. ► Image analysis produced single dimension solutions. ► The solutions were identical across modalities. Keywords: Student rating of instruction; online learning; blended learning; factor analysis; student agency"

First, the ongoing exploration of the reliability and validity of the psychometric assessment instrument designed to measure and stimulate change in learning power, for which I was one of three originators between 2000 and 2002. To date I have been able to collect large data sets (n=>50,000) and have published reliability and validity statistics in four  peer reviewed journal articles. Second, the application of the concept and assessment of learning power in pedagogy in school, community and corporate sectors, and in particular its contribution to personalisation of learning through authentic enquiry. Third, the contribution of learning power and enquiry to what we know about complexity in education, particularly through the development of systems learning and leadership as a vehicle for organisational transformation. Finally, the application of learning power assessment strategies to the emerging field of learning analytics and agent-based modelling.

Learning Emergence deep learning | complex systems | transformative leadership | knowledge media

"'Making Systems Work - whether in healthcare, education, climate change, or making a pathway out of poverty - is the great task of our generation as a whole' and at the heart of making systems work is the problem of complexity.  Prof Tony Bryk, President of the Carnegie Foundation for the Advancement of Teaching,  spent a week with people from the Learning Emergence network, leading a Master Class for practitioners, delivering two public lectures and participating in a consultation on Learning Analytics Hubs in Networked Improvement Communities  (background).  A key idea is that in order to engage in quality improvement in any system, we need to be able to 'see the system as a whole' and not just step in and meddle with one part of it."

July 18, 2012 College Degrees, Designed by the Numbers By Marc Parry Illustration by Randy Lyhus for The Chronicle Campuses are places of intuition and serendipity: A professor senses confusion on a student's face and repeats his point; a student majors in psychology after a roommate takes a course; two freshmen meet on the quad and eventually become husband and wife. Now imagine hard data substituting for happenstance. As Katye Allisone, a freshman at Arizona State University, hunkers down in a computer lab for an 8:35 a.m. math class, the Web-based course watches her back. Answers, scores, pace, click paths-it hoovers up information, like Google. But rather than personalizing search results, data shape Ms. Allisone's class according to her understanding of the material.