The propositional nature of human associative learning

The past 50 years have seen an accumulation of evidence suggesting that associative learning depends oil high-level cognitive processes that give rise to propositional knowledge. Yet, many learning theorists maintain a belief in a learning mechanism in which links between mental representations are formed automatically. We characterize and highlight the differences between the propositional and link approaches, and review the relevant empirical evidence. We conclude that learning is the consequence of propositional reasoning processes that cooperate with the unconscious processes involved in memory retrieval and perception. We argue that this new conceptual framework allows many of the important recent advances in associative learning research to be retained, but recast in a model that provides a firmer foundation for both immediate application and future research

Construction of the Earnings and Benefits File (EBF) for Use With the Health and Retirement Survey

Analysts using the Health and Retirement Survey (HRS) often require information on earnings, labor market attachment, and social security benefits in order to better understand the factors affecting retirement and well-being at older ages. To this end, several derived variables were constructed and documented in the Earnings and Benefits File (EBF) described here. The EBF provides a set of summary earnings, employment, and social security wealth measures for a subset of HRS respondents in Wave 1 of the survey, for whom administrative records are available. The EBF, a restricted data file, is available from the University of Michigan's Institute for Social Research for matching only with versions of the HRS containing geographic detail no finer than the Census Division level. Interested users should contact [email protected] by email for further information on access to the data.

REVIVING THE MUSIC CLASSROOM THROUGH CRITICAL MUSIC PEDAGOGY:MUSICAL LEARNING-THE LANGUAGE OF LIBERATION

Traditionally, music educators adhere to practices of banking methodologies; teacher-centered instruction and hegemonic practices that create curriculum emphasizing rote learning that is devoid of content relative to their students lived experiences. Using Critical Music Pedagogy, this study focuses on flipping the classroom structure through a process of dialogical learning, social learning and Friere’s problem-posing methodologies, to encourage awareness of students individual musical prosody, student’s epistemological awareness of music literacy as a language acquisition that broadens music students perceptions of the study of music as a meta-cognitive and multi-faceted process that can be used as a language of historical narration and social change. In this inquiry, I explain the findings from a qualitative study that explored the interactions and strategies that fostered a socially alive musical learning experience. 1) Critical Music Pedagogy created a humanizing learning environment that encouraged authentic dialogue inclusive to multiple-voices. 2) Problem-posing practices broaden the range of musical learning, where the study of music transformed into a multi-layered and multi-faceted process. One overall consequence became apparent: the transitive movement of the musical learning space from a space of hegemony, conformity and uniformity to an active highly evolving social learning community

The actual challenges of financial literacy

In our always-evolving world, financial literacy and inclusion are crucial in the development of sustainable welfare and a more transparent and fairer society. We cannot forget that the subprime mortgage crisis of 2008 that has continued across the world to this day has financial illiteracy as one of the most aggravating factors. The main challenge for many consumers worldwide is that the requirements of adequate financial literacy skills have been steadily increasing over time. Individuals have to take a wide range of financial decisions and unfortunately, they sometimes overlook or simply do not know the risk attached with the decisions they are making until it is too late. The main challenges for financial literacy at the micro-level, meso-level, and macro-level are over deference to the financial industry, lack of financial knowledge, overconfidence about financial knowledge, lack of government initiatives, frameworks and regulations, lack of life-cycle planning and interesting and fascinating ways to teach financial literacy skills

Signal tracking beyond the time resolution of an atomic sensor by Kalman filtering

We study causal waveform estimation (tracking) of time-varying signals in a paradigmatic atomic sensor, an alkali vapor monitored by Faraday rotation probing. We use Kalman filtering, which optimally tracks known linear Gaussian stochastic processes, to estimate stochastic input signals that we generate by optical pumping. Comparing the known input to the estimates, we confirm the accuracy of the atomic statistical model and the reliability of the Kalman filter, allowing recovery of waveform details far briefer than the sensor's intrinsic time resolution. With proper filter choice, we obtain similar benefits when tracking partially-known and non-Gaussian signal processes, as are found in most practical sensing applications. The method evades the trade-off between sensitivity and time resolution in coherent sensing.Comment: 15 pages, 4 figure

Signal tracking beyond the time resolution of an atomic sensor by Kalman filtering

We study causal waveform estimation (tracking) of time-varying signals in a paradigmatic atomic sensor, an alkali vapor monitored by Faraday rotation probing. We use Kalman filtering, which optimally tracks known linear Gaussian stochastic processes, to estimate stochastic input signals that we generate by optical pumping. Comparing the known input to the estimates, we confirm the accuracy of the atomic statistical model and the reliability of the Kalman filter, allowing recovery of waveform details far briefer than the sensor's intrinsic time resolution. With proper filter choice, we obtain similar benefits when tracking partially-known and non-Gaussian signal processes, as are found in most practical sensing applications. The method evades the trade-off between sensitivity and time resolution in coherent sensing.Comment: 15 pages, 4 figure

Connecting the Learning: 4-H Extension and Graduation Standards

The 1998 Minnesota Graduation Rule defines what students should master during their school years. Going beyond paper-and-pencil tests, the rule requires students to demonstrate what they can do as well as what they know. As the rule has been developed, teachers and school districts have been scrambling to adjust their programs to address the individualized learning requirements that emphasize experiential, project-based learning

Construction of the Earnings and Benefits File (EBF) for Use With the Health and Retirement Survey

This paper documents the Earnings and Benefits File (EBF). The EBF is a restricted dataset created for researchers working with the Health and Retirement Survey (HRS) under a set of limited access conditions. The EBF and all derived variables contained therein are intended for research purposes only, by registered users of the public use file of the Health and Retirement Survey, and may be linked only with HRS files containing no geographic detail below the Census Division level. Details on the rationale for, and definitions of, constructed employment, earnings, and social security wealth variables in the EBF are provided, as well as a bibliography for those wishing additional information on the rules by which social security earnings data are used in calculating benefits. The EBF contains information derived for respondents of the 1992 Health and Retirement Survey who authorized the University of Michigan’s Institute for Social Research to obtain administrative records from the Social Security Administration. The EBF is described below, first in conceptual terms in Part I, and then in more technical detail in Part II. Appendices contain a detailed layout of variables and codebook for the data file along with additional descriptive statistics