Teacher Evaluation: The Change We Wish to See; Improving the Formal Observation Process to Improve Student Learning

Teacher evaluation is a formal construct for improving instruction and student learning. Formal observations are a central component of that process. This change model explores the option of a videotaped observation model as an alternative to the current Illinois state-mandated in-person formal observation to increase teacher ownership, promote reflective practice and improve instructional practices. The evaluation process is a vehicle that promotes collaboration among building leaders and staff. The Illinois shift to a professional practice model provides a construct for a culture and climate that encourages reflection and promotes professional growth (Danielson, 2011; Darling-Hammond, 2013; Jay, 2003; Stuhlman, Hamre, Downer, & Pianta, n.d.). In examining practices related to evaluation and the formal observation, the idea is to build systems empowering teachers and focused on collaboration to promote reflection and professional growth (Myung & Martinez, 2013). The premise of the change model is to realize the context, culture, conditions and competencies that will reflect an effective system with a focus on student learning (Wagner & Kegan, 2006). Qualitative research methods were used to gain a deeper understanding of the teacher and administrator perceived value of the formal observation. Analyzing data from surveys and semi-structured interviews regarding the observation experience, the findings suggest that there is an opportunity to examine alternate structures for the formal observation to increase its value as a tool for professional growth. A further case study of the change model was conducted with three teachers and three administrators. Given responses to the case study coupled with the survey and interview data, I found there is merit to exploring how the videotaped alternative may contribute to an improved teacher evaluation process

The Role of the Formal Observation in Promoting Reflective Practice

Acheson and Gall (2011) wrote about the tension between teacher evaluation and clinical supervision. In their research they discuss the intent of clinical supervision to be a model for coaching and supporting professional growth as compared to more traditional models of teacher evaluation that were often associated with fear as a motivator. This program evaluation examines the nature of the formal observation in the teacher evaluation process and seeks to explore its role in developing reflective practitioners and promoting professional growth. This study involved researching the perspectives of teachers and administrators regarding their perceptions of the value of the formal observation process in improving teaching and learning. The data was collected through surveys and interviews and analyzed for patterns in responses. As a result of the research from this program evaluation, it was determined that the current formal observation process mandating an in-person observation of instruction is limited in its ability to foster the development of reflective practitioners. Several factors create a context that devalues what should be an optimal opportunity for professional growth. The passive role of teachers in the process, the high stakes nature of the observation as the central component in the larger evaluation process, the lack of a collaborative structure and the administrator-driven nature of the experience result in a process that has little impact on improving instruction in this study. The recommendations from this program evaluation include the exploration of alternative models for the current structure of the formal observation in the teacher evaluation process in Illinois

23 Illinois Administrative Code 50: Redefining the Formal Observation in Teacher Evaluation; A Policy Advocacy Document

This document explores how a change in the definition of the formal observation may improve the teacher evaluation system in the state of Illinois. Currently, the formal observation must be conducted in person as defined by administrative code. In an effort to increase the value and impact of the formal observation as a tool for reflection and professional growth, this paper advocates for a videotaped alternative as an option in addition to the current in-person model. The intent of including a videotaped option is to empower the teacher in the process and increase ownership for building skills as a reflective practitioner. The videotaped model also promotes a more collaborative context for the post observation conference that may lead to a more direct impact on improving teaching and learning. The state of New York (2017) has already implemented a videotaped observation model as an alternative in the teacher evaluation process and the premise of advocating for such a policy was recently the subject of a study at The Center for Educational Policy Research at Harvard (Harvard University Center for Educational Policy Research, 2015a). This policy advocacy document discusses the context and conditions by which to operationalize a similar vision in the state of Illinois

Deployment of churn prediction model in financial services industry

© 2016 IEEE. Nowadays, data analytics techniques are playing an increasingly crucial role in financial services due to the huge benefits they bring. To ensure a successful implementation of an analytics project, various factors and procedures need to be considered besides technical issues. This paper introduces some practical lessons from our deployment of a data analytics project in a leading wealth management company in Australia. Specifically, the process of building a customer churn prediction model is described. Besides common steps of data analysis, how to deal with other practical issues like data privacy and change management that are encountered by many financial companies are also introduced

A Multiple Source based Transfer Learning Framework for Marketing Campaigns

© 2018 IEEE. The rapid growing number of marketing campaigns demands an efficient learning model to identify prospective customers to target. Transfer learning is widely considered as a major way to improve the learning performance by using the generated knowledge from previous learning tasks. Most recent studies focused on transferring knowledge from source domains to target domains which may result in knowledge missing. To avoid this, we proposed a multiple source based transfer learning framework to do it reversely. The data in target domains is transferred into source domains by normalizing them into the same distributions and then improving the learning task in target domains by its generated knowledge in source domains. The proposed method is general and can deal with supervised and unsupervised inductive and transductive learning simultaneously with a compatibility to work with different machine learning models. The experiments on real-world campaign data demonstrate the performance of the proposed method

Combining heterogeneous features for time series prediction

© 2017 IEEE. Time series prediction is a challenging task in reality, and various methods have been proposed for it. However, only the historical series of values are exploited in most of existing methods. Therefore, the predictive models might be not effective in some cases, due to: (1) the historical series of values is not sufficient usually, and (2) features from heterogeneous sources such as the intrinsic features of data samples themselves, which could be very useful, are not take into consideration. To address these issues, we proposed a novel method in this paper which learns the predictive model based on the combination of dynamic features extracted from series of historical values and static features of data samples. To evaluate the performance of our proposed method, we compare it with linear regression and boosted trees, and the experimental results validate our method's superiority

Cost-sensitive churn prediction in fund management services

© Springer International Publishing AG, part of Springer Nature 2018. Churn prediction is vital to companies as to identify potential churners and prevent losses in advance. Although it has been addressed as a classification task and a variety of models have been employed in practice, fund management services have presented several special challenges. One is that financial data is extremely imbalanced since only a tiny proportion of customers leave every year. Another is a unique cost-sensitive learning problem, i.e., costs of wrong predictions for churners should be related to their account balances, while costs of wrong predictions for non-churners should be the same. To address these issues, this paper proposes a new churn prediction model based on ensemble learning. In our model, multiple classifiers are built using sampled datasets to tackle the imbalanced data issue while exploiting data fully. Moreover, a novel sampling strategy is proposed to deal with the unique cost-sensitive issue. This model has been deployed in one of the leading fund management institutions in Australia, and its effectiveness has been fully validated in real applications

A brief scale of pathological worry that everyone already has

Stress and Psychopatholog

Implementation of a method to visualize noise-induced hearing loss in mass stranded cetaceans

Assessment of the impact of noise over-exposure in stranded cetaceans is challenging, as the lesions that lead to hearing loss occur at the cellular level and inner ear cells are very sensitive to autolysis. Distinguishing ante-mortem pathology from post-mortem change has been a major constraint in diagnosing potential impact. Here, we outline a methodology applicable to the detection of noise-induced hearing loss in stranded cetaceans. Inner ears from two mass strandings of long-finned pilot whales in Scotland were processed for scanning electron microscopy observation. In one case, a juvenile animal, whose ears were fixed within 4¿hours of death, revealed that many sensory cells at the apex of the cochlear spiral were missing. In this case, the absence of outer hair cells would be compatible with overexposure to underwater noise, affecting the region which transduces the lowest frequencies of the pilot whales hearing spectrum. Perfusion of cochlea with fixative greatly improved preservation and enabled diagnostic imaging of the organ of Corti, even 30¿hours after death. This finding supports adopting a routine protocol to detect the pathological legacy of noise overexposure in mass stranded cetaceans as a key to understanding the complex processes and implications that lie behind such stranding events

Intracranial injection of AAV expressing NEP but not IDE reduces amyloid pathology in APP+PS1 transgenic mice

The accumulation of β-amyloid peptides in the brain has been recognized as an essential factor in Alzheimer\u27s disease pathology. Several proteases, including Neprilysin (NEP), endothelin converting enzyme (ECE), and insulin degrading enzyme (IDE), have been shown to cleave β-amyloid peptides (Aβ). We have previously reported reductions in amyloid in APP+PS1 mice with increased expression of ECE. In this study we compared the vector-induced increased expression of NEP and IDE. We used recombinant adeno-associated viral vectors expressing either native forms of NEP (NEP-n) or IDE (IDE-n), or engineered secreted forms of NEP (NEP-s) or IDE (IDE-s). In a six-week study, immunohistochemistry staining for total Aβ was significantly decreased in animals receiving the NEP-n and NEP-s but not for IDE-n or IDE-s in either the hippocampus or cortex. Congo red staining followed a similar trend revealing significant decreases in the hippocampus and the cortex for NEP-n and NEP-s treatment groups. Our results indicate that while rAAV-IDE does not have the same therapeutic potential as rAAV-NEP, rAAV-NEP-s and NEP-n are effective at reducing amyloid loads, and both of these vectors continue to have significant effects nine months post-injection. As such, they may be considered reasonable candidates for gene therapy trials in AD