Portfolios and pedagogy : an examination of ideology and use

Portfolio use in writing studies contexts is becoming ubiquitous and, as such, portfolios are in danger of being rendered meaningless and thus require that we more fully theorize and historicize portfolios. To this end, I examine portfolios: both the standardized portfolio used for assessment purposes and the personalized portfolio used for entering the job market. I take a critical look at portfolios as a form of technology and acknowledge some of the dangers of blindly using portfolios for gaining employment in the current economic structure of fast capitalism. As educators in the writing studies fields, it is paramount that instructors have a critical awareness of the consequences of portfolio creation on students as designers, lifelong learners, and citizens of a larger society. I argue that a better understanding of the pedagogical implications for portfolio use is imperative before implementing them in the classroom, and that a social-epistemic approach provides a valuable rethinking of portfolio use for assessment purposes. Further, I argue for the notions of meditation and transformation to be added alongside collection, selection, and reflection because they enable portfolio designers and evaluators alike to thoughtfully consider new ways of meaning-making and innovation. Also important and included with meditation and transformation is the understanding that students are ideologically positioned in the educational system. For them to begin recognizing their situatedness is a step toward becoming designers of change. The portfolio can be a site for that change, and a way for them to document their own learning and ways of making meaning over a lifetime.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.