The assessment of Indonesian EFL students' reading comprehension ability using Reading Evaluation and Decoding System (READS)

This study focused on reading comprehension ability of the English Department students in answering READS, MCQ questions. READS is an alternative standardized assessment system that is capable of measuring reading comprehension ability. This is a descriptive study based on Barrett's Taxonomy levels, such as literal comprehension, reorganization, and inferential comprehension. This study consisted of 122 students of the English Department academic year 2015 through 2018 at one of the private universities in Yogyakarta, Indonesia. This study analysis utilized the three Barrett's taxonomy scales to identify whether the students were at meet the standard, below standard, above standard or at academic warning. Finding of the research indicated that 27.8 % students categorized into academic warning (Band 2 and 3), 46.7% students categorized into below standard (Band 4) and 25.5% students categorized into meet standard (Band 5). Consequently, READS as an alternative assessment will guide the teachers to design specific reading material based on students' needs.

Application of Monte Carlo Simulation in College and University Academic Warning

With the prevalence of credit system, the stipulation of “academic warning” is written into the teaching management constitution by more colleges and universities. However, the establishment of this stipulation hasn’t formed unified and scientific standards at present. This paper aims at studying the credit setting of academic warning through the method of Monte Carlo simulation, and at applying multivariate normal distribution and variance reduction techniques to calculate relatively reasonable academic warning credit line, which provides a new train of thought and a universal method for colleges and universities to set specific standards.

Setting of Academic Warning Based on Multivariate Copula Functions

With the prevalence of credit system, the stipulation of “academic warning” is written into the teaching management constitution by more colleges and universities. However, the present research in this stipulation is only limited to the simulation of multivariate normal distribution. This paper aims to improve the current setting of academic warning through Monte Carlo simulation of multivariate Copula functions, and to calculate more reasonable academic warning credit line. The result demonstrates that the accuracy is significantly improved, therefore, this approach can provide a new train of thought and universal method for colleges and universities to set specific standards.

University Legislations and their Suitability to the Needs of Students with Special Needs: Analytical Study for University Legislations

This study aimed to review the suitability of the laws, regulations, and instructions in force at the University of Jordan for students with special needs. The study focused primarily on legislations, laws, regulations and resolutions adopted by the University of Jordan that are related to admission, housing, health insurance, registration, library, public services, financial support, testing, attendance, academic warning, deferral, extracurricular activities, and technical services support. Descriptive analytical approach was used. Percentages and frequencies were employed. About 214 articles of the law, regulations and resolutions linked to the university students were reviewed. The results indicated that the percentage of law articles related to the university legislation concerning the students with special needs has reached 0.93%, and this ratio is considered very low. Finally, the study recommended the need to review the imbalances in laws, rules, and regulations currently in force in Jordanian universities as to suit the needs of students with special needs.

Determining Need for Remediation Through Postrotation Evaluations

Introduction Postrotation evaluations are frequently used by residency program directors for early detection of residents with academic difficulties; however, the accuracy of these evaluations in assessing resident performance has been questioned. Methods This retrospective case-control study examines the ability of postrotation evaluation characteristics to predict the need for remediation. We compared the evaluations of 17 residents who were placed on academic warning or probation, from 2000 to 2007, with those for a group of peers matched on sex, postgraduate year (PGY), and entering class. Results The presence of an outlier evaluation, the number of words written in the comments section, and the percentage of evaluations with negative or ambiguous comments were all associated with the need for remediation (P = .01, P = .001, P = .002, P = < .001, respectively). In contrast, United States Medical Licensing Examination step 1 and step 2 scores, total number of evaluations received, and percentage of positive comments on the evaluations were not associated with the need for remediation (P = .06, P = .87, P = .55, respectively). Discussion Despite ambiguous evaluation comments, the length and percentage of ambiguous or negative comments did indicate future need for remediation. Conclusions Our study demonstrates that postrotation evaluation characteristics can be used to identify residents as risk. However, larger prospective studies, encompassing multiple institutions, are needed to validate various evaluation methods in measuring resident performance and to accurately predict the need for remediation.