Learning-by-employing: the value of commitment

We analyze a dynamic principal–agent model where an infinitely-lived principal faces a sequence of finitely-lived agents who differ in their ability to produce output. The ability of an agent is initially unknown to both him and the principal. An agent’s effort affects the information on ability that is conveyed by performance. We characterize the equilibrium contracts and show that they display short–term commitment to employment when the impact of effort on output is persistent but delayed. By providing insurance against early termination, commitment encourages agents to exert effort, and thus improves on the principal’s ability to identify their talent. We argue that this helps explain the use of probationary appointments in environments in which there exists uncertainty about individual ability.

Improving learning by connecting chemistry curriculum to students' experiences

The purpose of the study was to design, implement, and assess the effects of a teaching unit about fuel sources and chemical energy on students’ learning. The unit was designed to incorporate students’ experiences in a way that was aligned with the Michigan High School Content Expectations. The study was completed with all of the students taking General Chemistry in a rural Michigan high school in the 2010-11 school year. There were 138 participants total. The participants were mostly Caucasian and the majority were in the 11th grade. Of these, 77 constituted the experimental group and were taught the unit. The additional 61 participants in the control group were given the posttest only. Data was derived from the results of pre/post tests, final assessment projects, and the researcher’s observations. A pretest that contained questions about the fuel sources was administered at the beginning of the unit. An identical posttest was administered at the completion of the unit. A final assessment project required students to choose the best fuel source for the area, and support their opinion with facts and data from their research or the learning activities and labs performed in class. The results of the study revealed that the teaching unit did produce significant learning gains in the experimental group. The results also indicated that the teaching unit added value to the current General Chemistry curriculum by expanding what students were learning. The instructional goals of the unit were aligned with the Michigan High School Content Expectations. The results also revealed that the students were able to learn to support their thinking and decisions with explanations based on the data and labs. These are essential science literacy skills. The study supported the view that connecting the required curriculum with students’ experiences and interests was effective, and that students can learn important science literacy skills, such as providing support for arguments and communicating scientific explanations, when given adequate teacher support.

Learning by the Dendritic Prediction of Somatic Spiking

Recent modeling of spike-timing-dependent plasticity indicates that plasticity involves as a third factor a local dendritic potential, besides pre- and postsynaptic firing times. We present a simple compartmental neuron model together with a non-Hebbian, biologically plausible learning rule for dendritic synapses where plasticity is modulated by these three factors. In functional terms, the rule seeks to minimize discrepancies between somatic firings and a local dendritic potential. Such prediction errors can arise in our model from stochastic fluctuations as well as from synaptic input, which directly targets the soma. Depending on the nature of this direct input, our plasticity rule subserves supervised or unsupervised learning. When a reward signal modulates the learning rate, reinforcement learning results. Hence a single plasticity rule supports diverse learning paradigms.

Is Learning by Migrating to a Megalopolis Really Important? Evidence from Thailand

We examine the effects of learning by migrating on the productivity of migrants who move to a "megalopolis" from rural areas using the Thailand Labor Force Survey. The main contribution is to the development a simple framework to test for self-selection on migration decisions and learning by migrating into the urban labor market, focusing on experimental evidence in the observational data. The role of the urban labor market is examined. In conclusion, we find significant evidence for sorting: the self-selection effects test (1) is positive among new entrants from rural areas to the urban labor market; and (2) is negative among new exits that move to rural areas from the urban labor market. Further, estimated effects of learning by migrating into a "megalopolis" have a less significant impact. These results suggest the existence of a natural selection (i.e. survival of the fittest) mechanism in the urban labor market in a developing economy.

Motor learning by field approximation.

We investigated how human subjects adapt to forces perturbing the motion of their ams. We found that this kind of learning is based on the capacity of the central nervous system (CNS) to predict and therefore to cancel externally applied perturbing forces. Our experimental results indicate: (i) that the ability of the CNS to compensate for the perturbing forces is restricted to those spatial locations where the perturbations have been experienced by the moving arm. The subjects also are able to compensate for forces experienced at neighboring workspace locations. However, adaptation decays smoothly and quickly with distance from the locations where disturbances had been sensed by the moving limb. (ii) Our experiments also how that the CNS builds an internal model of the external perturbing forces in intrinsic (muscles and / or joints) coordinates.

Learning by inductive inference /

"Invited paper for the NATO Advanced Study Institute Seminar on Computer Oriented Learning Processes, Aug. 26-Sept. 7, 1974, Bonas, France."

Learning by exporting:lessons from high-technology SMEs

We investigate the learning by exporting hypothesis by examining the effect of exporting on the subsequent innovation performance of a sample of high-technology SMEs based in the UK. We find evidence of learning by exporting, but the pattern of this effect is complex. Exporting helps high-tech SMEs innovate subsequently, but does not make them more innovation intensive. There is evidence that consistent exposure to export markets helps firms overcome the innovation hurdle, but that there is a positive scale effect of exposure to export markets which allows innovative firms to sell more of their new-to-market products on entering export markets. Service sector firms are able to reap the benefits of exposure to export markets at an earlier (entry) stage of the internationalization process than are manufacturing firms. Innovation-intensive firms exhibit a different pattern of entry to and exit from export markets from low-intensity innovators, and this is reflected in different effects of exporting. © 2012 Elsevier Ltd.

Learning by exporting:lesson from high-technology SMEs

Theory points to the existence of a learning by exporting effect, in which exposure to export markets enhances performance through exposure to the knowledge stocks of trading partners. We investigate the learning by exporting hypothesis by examining the effect of exporting on the subsequent innovation performance of UK high-tech SMEs. We find evidence of learning by exporting, but the pattern of this effect is relatively complex. Exporting helps high-tech SMEs innovate subsequently, but does not make them more innovation intensive. There is also evidence that it is consistent exposure to export markets that helps firms overcome the innovation hurdle, but that there is a positive scale effect of exposure to export markets which allows innovative firms to sell more of their new-to-market products on entering export markets. Service sector firms are able to reap the benefits of exposure to export markets at an earlier (entry) stage of the internationalization process than are manufacturing firms. Firms producing a rapidly changing portfolio of innovative products exhibit higher churn in terms of entry to and exit from export markets than low-intensity innovators, and this is reflected in the effects of entry and exit into and out of such markets.

Network learning:an empirically-derived conceptual model of learning by groups of organizations

Building on a previous conceptual article, we present an empirically derived model of network learning - learning by a group of organizations as a group. Based on a qualitative, longitudinal, multiple-method empirical investigation, five episodes of network learning were identified. Treating each episode as a discrete analytic case, through cross-case comparison, a model of network learning is developed which reflects the common, critical features of the episodes. The model comprises three conceptual themes relating to learning outcomes, and three conceptual themes of learning process. Although closely related to conceptualizations that emphasize the social and political character of organizational learning, the model of network learning is derived from, and specifically for, more extensive networks in which relations among numerous actors may be arms-length or collaborative, and may be expected to change over time.