Comparing the Borich model with the Ranked Discrepancy Model for competency assessment: A novel approach

In 1980, Borich presented a new model that allowed errors in an individual’s judgment of self-proficiency to be offset by considering the perception of a group. The model relied upon the calculation of means for competency items measured with ordinal scales, an approach subject to debate in modern times. The purpose of our study was to explore the use of a novel approach we developed, the Ranked Discrepancy Model (RDM), as an alternative method to the Borich model for determining training needs. Data obtained from an online survey of extension professionals employed by a land-grant university in the United States was used to compare the training needs identified by applying the Borich model with those identified by applying the RDM. A very strong and statistically significant correlation existed between the scores derived from using both models, demonstrating a high level of consistency between models. Researchers conducting competency research should consider adopting the RDM given its suitability for delivering results that closely resemble findings from the Borich model while providing improved rigor in methods and increased detail about training needs.

Model Discrepancy sebagai Evaluasi Program Pendidikan

Programs designed to advance education continue to progress and develop dynamically. Improving the program requires an evaluation process. There are various evaluation models used in improving educational programs depending on the aspects needed for improvement or refinement. The purpose of this research is to discuss the basic concepts of the discrepancy model evaluation made by Provus. This research is a library study with data obtained through the study of relevant books and articles and then analyzed using a qualitative approach consisting of: (1) data reduction, (2) data display, and (3) drawing conclusions. Evaluation The discrepancy model is one type of appropriate approach in evaluating an educational and learning program. The procedures used in the discrepancy evaluation are (1) design, (2) installation, (3) process, (4) product, and (5) comparison or the fifth in the form of costs and benefits if needed. The result of the discrepancy model evaluation is knowing the gap between the expected conditions and the reality on the ground, so that it can be a guide for the next step in making decisions.

Multi-Spectral Fusion and Denoising of Color and Near-Infrared Images Using Multi-Scale Wavelet Analysis

We formulate multi-spectral fusion and denoising for the luminance channel as a maximum a posteriori estimation problem in the wavelet domain. To deal with the discrepancy between RGB and near infrared (NIR) data in fusion, we build a discrepancy model and introduce the wavelet scale map. The scale map adjusts the wavelet coefficients of NIR data to have the same distribution as the RGB data. We use the priors of the wavelet scale map and its gradient as the contrast preservation term and gradient denoising term, respectively. Specifically, we utilize the local contrast and visibility measurements in the contrast preservation term to transfer the selected NIR data to the fusion result. We also use the gradient of NIR wavelet coefficients as the weight for the gradient denoising term in the wavelet scale map. Based on the wavelet scale map, we perform fusion of the RGB and NIR wavelet coefficients in the base and detail layers. To remove noise, we model the prior of the fused wavelet coefficients using NIR-guided Laplacian distributions. In the chrominance channels, we remove noise guided by the fused luminance channel. Based on the luminance variation after fusion, we further enhance the color of the fused image. Our experimental results demonstrated that the proposed method successfully performed the fusion of RGB and NIR images with noise reduction, detail preservation, and color enhancement.

Evaluasi Implementasi Program Bantuan Operasional Sekolah (Bos) Di Smk Ypk Kesatuan Jakarta

<p>Penelitian ini bertujuan untuk mengetahui dan menganalisa hambatan- hambatan<br />dalam sosialisasi program BOS, implementasi program BOS dan manajemen<br />pengelolaan program BOS di SMK YPK Kesatuan Jakarta, dengan menggunakan<br />model evaluasi kesenjangan (Discrepancy Model Evaluation). Pengumpulan data<br />dilakukan dengan menggunakan observasi, wawancara terstruktur, dan<br />dokumentasi. Wawancara dilakukan dengan kepala Sekolah, bendahara BOS,<br />guru, orang tua dan peserta didik. Hasil penelitian menunjukkan ada kesenjangan dalam sosialisasi program BOS dan hambatan-hambatanya yaitu komunikasi yang kurang efektif , TIM BOS tidak memahami tugas dan fungsinya. Implementasi program BOS di SMK YPK Kesatuan Jakarta, 10 komponen sesuai juknis, 3 komponen terjadi ketimpangan antara juknis BOS dengan realisasi pembelanjaan yaitu pembelian alat multimedia pembelajaran, pembayaran honor guru, dan kegiatan praktek kerja industri. Manajemen pengelolaan dana BOS di SMK YPK Kesatuan Jakarta terjadi ketimpangan, peneliti tidak mendapatkan dokumen RKAS untuk dianalisis.</p>

Evaluation of a Strategic Management Program: Context, Input, Process, Product Model as a Prototype for Business Academies

The present study examines the evaluation models of strategic management (SM) programs in business academies and evaluates a sample program based on Stufflebeam's context, input, process, product (CIPP) program evaluation model. When evaluation studies used in Turkey were scrutinized, Stake's countenance model and Provus's discrepancy model were also discovered; however, the CIPP Model has generally been used. Further, this study explores (1) the history of SM education and (2) SM education within the perspectives of business academies, (3) a sample of SM education developed by a private education consulting service and (4) a theoretical background and a practical method to evaluate the program of business academies.

Data-Driven Corrections of Partial Lotka–Volterra Models

In many applications of interacting systems, we are only interested in the dynamic behavior of a subset of all possible active species. For example, this is true in combustion models (many transient chemical species are not of interest in a given reaction) and in epidemiological models (only certain subpopulations are consequential). Thus, it is common to use greatly reduced or partial models in which only the interactions among the species of interest are known. In this work, we explore the use of an embedded, sparse, and data-driven discrepancy operator to augment these partial interaction models. Preliminary results show that the model error caused by severe reductions—e.g., elimination of hundreds of terms—can be captured with sparse operators, built with only a small fraction of that number. The operator is embedded within the differential equations of the model, which allows the action of the operator to be interpretable. Moreover, it is constrained by available physical information and calibrated over many scenarios. These qualities of the discrepancy model—interpretability, physical consistency, and robustness to different scenarios—are intended to support reliable predictions under extrapolative conditions.

Evaluasi Program PPDB Berbasis Zonasi di SMP Negeri 2 Pabelan

The admission of new students (PPDB) is a school agenda that is held every year. The purpose of the study is to evaluate the zoning-based PPDB Program in SMP Negeri 2 Pabelan, Semarang Regency. Program evaluation is done by assessing any discrepancies/gaps between the program standards from the central government and the actual conditions of the PPDB program that occurred in SMP Negeri 2 Pabelan. This type of research is a program evaluation research using Discrepancy Model developed by Malcolm Provus. The Discrepancy Model consists of 5 stages: the design stage, the installation stage, the process stage, the product stage, and the cost-benefit analysis stage. However, this research only used 4 stages, namely the design stage, the installation stage, the process stage, and the product stage. Data collection used in this study were, interview, observation, and documentation. The results showed that the design of the category program was sufficient (conformity score 73.3%), the installation of the good category program (100% suitability score), the process of the good category program (suitability score 92.86%), and the program product category was good (the suitability score 87.5%).

Modeling multivariate associations with parental loneliness via perceived closeness and support

Objectives: Recent research findings suggest the prevalence of loneliness is increasing in middle-aged adults parenting children, challenging the notion this demographic is typically at low risk of loneliness. Method: The current study applied the cognitive discrepancy model as theoretical foundation to investigate the variance of individual and situational variables contributing to perceived closeness and support and consequently loneliness. Structural equation modeling was employed to identify multivariate contributors associated with parental loneliness in 323 parents with an average age of 37.69 ( SD = 5.96) years. Results: Results support the theoretical proposition that individual factors, rather than situational, contribute to a greater variance of a perceived gap in relationship closeness and support. It was found that emotional competence, ability to forgive, emotional stability, extraversion, and lower mood levels are significant contributors to a small cognitive gap in perceived relationship closeness and protective against parental loneliness. Relationship status contributed a weak direct effect over perceived relationship closeness and support. Situational factors, including number of children and household income, were non-significant risks for loneliness. Overall, the model accounted for 65% of perceived relationship closeness and support and 85% of loneliness. The limitation of small number of male participants is discussed with regard to the existing research gap investigating male loneliness. Conclusion: A Pathway to Loneliness Risk Model is proposed, demonstrating that through increasing an individual’s intrapersonal and interpersonal resources and challenging negative cognitive biases and maladaptive schemas regarding an individual’s perception of their relationships, may lead to a reduction in the individual’s risk for loneliness.