scholarly journals Developing a Diagnostic Assessment Model

2003 ◽  
Vol 1 (2) ◽  
Author(s):  
James Wagner
Keyword(s):  
Student Achievement ◽  
Quality Assessment ◽  
Large Scale ◽  
Assessment Model ◽  
Diagnostic Assessment ◽  
Education Quality ◽  
High Stakes ◽  
Formal Testing ◽  
To Come ◽  
Grade 3

The recent implementation of annual testing at the grade 3, 6 and 9 levels by the Education Quality Assessment Office has forced the school boards in Ontario to try to come to grips with the problem of measuring student achievement. This problem is not a new one in that teachers have been concerned about evaluating student progress since the advent of schooling . In this respect, the literature suggests that most teachers are quite capable of identifying the students in their classrooms who are or are not making sufficient progress. Why then do we need formal testing and in particular, large scale high stakes assessments?

scholarly journals Why Graded Assessment for Undergraduates During the COVID-19 Lockdown? An Experience Introspection

2021 ◽  
Vol 9 (2) ◽  
pp. 55-75
Author(s):  
Abdullatif Alshamsi ◽  
Alex Zahavich ◽  
Samar El-Farra
Keyword(s):  
Online Education ◽  
Student Performance ◽  
Student Assessment ◽  
Assessment Model ◽  
Technology Infrastructure ◽  
High Stakes ◽  
Assessment Development ◽  
Student Efficacy ◽  
Institutional Accountability ◽  
To Come

This paper presents a retrospective evaluation of the Higher Colleges of Technology’s student assessments during the COVID-19 lockdown, reflecting the justified decision to deploy graded assessments during the lockdown for students to academically progress and/or graduate on time, while maintaining the quality and rigor of academic awards. The outcome-based evaluation of this paper is intended to provide lessons for any future situations of this significance and magnitude. While online education was the obvious response to the pandemic, the provision of assessments was not possible without risk. Taking a high-stakes decision that would affect the future of thousands of students, for years to come, involved complex steps of reasoning and justification. Addressing the role of graded assessment in supporting institutional accountability and transferability of students’ achievements, student efficacy and informed pedagogy alterations were the main objectives. To meet those objectives, the Higher Colleges of Technology was able to deploy an off-campus student assessment model that builds upon three pillars of adjustments (assessment development and deployment; technology infrastructure; and governance resilience) to support students’ learning, while mitigating vulnerabilities. The evaluation of student performance indicators and stakeholders’ satisfaction rates revealed a successful deployment of off-campus assessment while maintaining the traditional conventions pertaining to evaluation of assessments.

scholarly journals Identifying Levers Related to Student Performance on High-Stakes Science Exams: Examining School, Teaching, Teacher, and Professional Development Characteristics

2020 ◽  
Vol 122 (2) ◽  
pp. 1-64
Author(s):  
Christian Fischer ◽  
Brandon Foster ◽  
Ayana Mccoy ◽  
Frances Lawrenz ◽  
Chris Dede ◽  
...  
Keyword(s):  
Professional Development ◽  
Student Achievement ◽  
Student Performance ◽  
Science Teachers ◽  
Curriculum Reform ◽  
Large Scale ◽  
The United States ◽  
High Stakes ◽  
Reform Implementation ◽  
School Teaching

Background Many students enter into postsecondary education without the preparation to face the demands of postsecondary coursework in science. Increasingly, policymakers and educational researchers are responding to calls for reforming secondary education to provide more opportunity for all students to receive high-quality education and to become career and college ready. Purpose This study attempts to identify levers to increase student learning in secondary education. In particular, it examines relationships between school, teaching, teacher, and teacher professional development characteristics and student scores on high-stakes Advanced Placement (AP) examinations in the sciences. Setting This study is situated in the context of the large-scale, top-down, nationwide AP curriculum and examination reform in the sciences (biology, chemistry, physics) in the United States. This is an unprecedented opportunity to analyze changing educational landscapes in the United States with large-scale national student-, teacher-, school-, and district-level datasets across multiple science disciplines and different stages of the curriculum reform implementation connected to a standardized and high-stakes student outcome measure. Population This study analyzes nationwide data samples of the AP Biology, AP Chemistry, and AP Physics population during the first, second, and third year of the curriculum reform implementation. Across disciplines and years, the analytical samples include a total of 113,603 students and 6,046 teachers. Research Design This empirical quantitative study uses data from web-based surveys sent to all AP science teachers. Additionally, the College Board provided student- and school-level data for all students taking AP examinations. Data preparation methods included exploratory and confirmatory factor analysis. Associations with student achievement were analyzed through a multilevel ordered logistic regression analysis, separately by science discipline and year of the curriculum reform implementation. Afterwards, results were aggregated through a meta-analysis. Findings Even after controlling for student background variables, roughly 60% of the AP score variance could be explained at the teacher and school levels. In particular, teachers’ perceived administrative support, self-efficacy, teaching experience, and elements of classroom instruction were related to student performance. Notably, teachers’ professional development participation—which has been a major focus of interventions—has a small, mixed impact on student achievement. Conclusion The identified levers for improving student achievement provide a strong rationale for the continued efforts of policymakers to improve school environments and to support science teachers, with the ultimate goal of improving student learning to help all students to be prepared for college and ready for their future careers.

scholarly journals Higher Education Quality Assessment in Ethiopia: A Comparative Study

2020 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
L. Geleto Wariyo
Keyword(s):  
Higher Education ◽  
Quality Assessment ◽  
Assessment Model ◽  
Education Quality ◽  
Ministry Of Education ◽  
Design Data ◽  
Peer Reviews ◽  
Qualitative Research Design ◽  
Higher Education Quality ◽  
International Linkage

<p>The major objective of this study was analyzing the Ethiopian Higher Education quality assessment model in line with another world. The total 46 key informants were purposively selected from the data sources of this study (Ethiopian public HEIs and the Ministry of Education) and interviewed. Document analysis was another instrument.  Using descriptive qualitative research design, data were analyzed in themes qualitatively. Literatures describing the higher education quality assessment models were reviewed. The literature on the models of higher education quality assessment generally tends to converge to the general model of higher education quality assessment and tends to diverge from it while it adds many approaches to the dimensions.  It is recommended that the Ethiopian system better to be governed by an independent agency that has strong international linkage, and the system should emphasize the need of stakeholders in quality assurance and assessment. Use of diversified methodologies and existence of explicit standards for resource utilization were recommended. Rigorous interdisciplinary and cross-disciplinary peer reviews are strongly recommended in this study.</p>

scholarly journals Model for higher education quality assessment

2015 ◽  
Vol 2015 (4) ◽  
pp. 73-80
Author(s):  
Вячеслав Мирошников ◽  
Vyacheslav Miroshnikov ◽  
Виктор Круглов ◽  
Viktor Kruglov ◽  
Олег Горленко ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Educational Institution ◽  
Complete Information ◽  
Assessment Model ◽  
Education Quality ◽  
Federal State ◽  
Training Procedure ◽  
Higher Education Quality ◽  
Definition Of ◽  
The University

Quality ensuring in training students and educational institutions graduates is one of the state directions in the sphere of education. In view of this the significance consists in the development, introduction and improvement of the assessment model for the quality of training students on the baccalaureate’s , specialist’s and master’s curricula. This paper reports the model considered for the correspondence assessment of curricula to the requirements of the Federal State All-Russian Standard for Higher Vocational Education (FSARS HVE) on basis of four indices and thirtytwo criteria according to the recommendations of the Russian Accreditation Agency of the Russian federation. For each of the criteria there are shown documents and materials confirming its fulfillment. Failure to execute at least one of the criteria means lack of correspondence of the curriculum to the requirements of the FSARS HVE. A not less significant procedure of curricula quality assessment – a confirmation, by means of the presentation of documents and materials on the successful application of knowledge, abilities and skills obtained in the course of mastering a compulsory cur-riculum by students and graduates under real or simu-lated working conditions. One of the conditions for the increase of curricula effectiveness – the availability in an educational institution (EI) of the incollege system for education quality assessment which would allow planned carrying out organizational measures on a fundamental analysis and objective self-appraisal of educational activities of all departments of the EI and obtaining complete information on the curricula realization, and also correcting a training procedure with the aim of quality increase in college graduate students training. The main purpose of such incollege system consists in the definition of areas for education quality increase in all kinds of activities of the university and its departments.

Higher education quality assessment model: towards achieving educational quality standard

2015 ◽  
Vol 42 (1) ◽  
pp. 23-46 ◽  
Author(s):  
Amin Y. Noaman ◽  
Abdul Hamid M. Ragab ◽  
Ayman I. Madbouly ◽  
Ahmed M. Khedra ◽  
Ayman G. Fayoumi
Keyword(s):  
Higher Education ◽  
Quality Assessment ◽  
Quality Standard ◽  
Educational Quality ◽  
Assessment Model ◽  
Education Quality ◽  
Higher Education Quality

ROI Based Post Image Quality Assessment Technique on Multiple Localized Filtering Method On Kinect HD Sensor Mobile Robot

2018 ◽  
Vol 3 (2) ◽  
pp. 145
Author(s):  
Kholilatul Wardani ◽  
Aditya Kurniawan
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Similarity Index ◽  
Assessment Model ◽  
Sensor Data ◽  
Edge Region ◽  
Kinect Sensor ◽  
Image Region ◽  
Filtering Technique

 The ROI (Region of Interest) Image Quality Assessment is an image quality assessment model based on the SSI (Structural Similarity Index) index used in the specific image region desired to be assessed. Output assessmen value used by this image assessment model is 1 which means identical and -1 which means not identical. Assessment model of ROI Quality Assessment in this research is used to measure image quality on Kinect sensor capture result used in Mobile HD Robot after applied Multiple Localized Filtering Technique. The filter is applied to each capture sensor depth result on Kinect, with the aim to eliminate structural noise that occurs in the Kinect sensor. Assessment is done by comparing image quality before filter and after filter applied to certain region. The kinect sensor will be conditioned to capture a square black object measuring 10cm x 10cm perpendicular to a homogeneous background (white with RGB code 255,255,255). The results of kinect sensor data will be taken through EWRF 3022 by visual basic 6.0 program periodically 10 times each session with frequency 1 time per minute. The results of this trial show the same similar index (value 1: identical) in the luminance, contrast, and structural section of the edge region or edge region of the specimen. The value indicates that the Multiple Localized Filtering Technique applied to the noise generated by the Kinect sensor, based on the ROI Image Quality Assessment model has no effect on the image quality generated by the sensor.

scholarly journals Application of Three Deep Machine-Learning Algorithms in a Construction Assessment Model of Farmland Quality at the County Scale: Case Study of Xiangzhou, Hubei Province, China

Agriculture ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 72
Author(s):  
Li Wang ◽  
Yong Zhou ◽  
Qing Li ◽  
Tao Xu ◽  
Zhengxiang Wu ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Index System ◽  
Quality Index ◽  
Hubei Province ◽  
Machine Learning Algorithms ◽  
Assessment Model ◽  
Soil Conditions ◽  
The Mean ◽  
County Scale ◽  
Assessment Results

Constructing a scientific and quantitative quality-assessment model for farmland is important for understanding farmland quality, and can provide a theoretical basis and technical support for formulating rational and effective management policies and realizing the sustainable use of farmland resources. To more accurately reflect the systematic, complex, and differential characteristics of farmland quality, this study aimed to explore an intelligent farmland quality-assessment method that avoids the subjectivity of determining indicator weights while improving assessment accuracy. Taking Xiangzhou in Hubei Province, China, as the study area, 14 indicators were selected from four dimensions—terrain, soil conditions, socioeconomics, and ecological environment—to build a comprehensive assessment index system for farmland quality applicable to the region. A total of 1590 representative samples in Xiangzhou were selected, of which 1110 were used as training samples, 320 as test samples, and 160 as validation samples. Three models of entropy weight (EW), backpropagation neural network (BPNN), and random forest (RF) were selected for training, and the assessment results of farmland quality were output through simulations to compare their assessment accuracy and analyze the distribution pattern of farmland quality grades in Xiangzhou in 2018. The results showed the following: (1) The RF model for farmland quality assessment required fewer parameters, and could simulate the complex relationships between indicators more accurately and analyze each indicator’s contribution to farmland quality scientifically. (2) In terms of the average quality index of farmland, RF > BPNN > EW. The spatial patterns of the quality index from RF and BPNN were similar, and both were significantly different from EW. (3) In terms of the assessment results and precision characterization indicators, the assessment results of RF were more in line with realities of natural and socioeconomic development, with higher applicability and reliability. (4) Compared to BPNN and EW, RF had a higher data mining ability and training accuracy, and its assessment result was the best. The coefficient of determination (R2) was 0.8145, the mean absolute error (MAE) was 0.009, and the mean squared error (MSE) was 0.012. (5) The overall quality of farmland in Xiangzhou was higher, with a larger area of second- and third-grade farmland, accounting for 54.63%, and the grade basically conformed to the trend of positive distribution, showing an obvious pattern of geographical distribution, with overall high performance in the north-central part and low in the south. The distribution of farmland quality grades also varied widely among regions. This showed that RF was more suitable for the quality assessment of farmland with complex nonlinear characteristics. This study enriches and improves the index system and methodological research of farmland quality assessment at the county scale, and provides a basis for achieving a threefold production pattern of farmland quantity, quality, and ecology in Xiangzhou, while also serving as a reference for similar regions and countries.

scholarly journals Joint regression and learning from pairwise rankings for personalized image aesthetic assessment

2021 ◽  
Author(s):  
Jin Zhou ◽  
Qing Zhang ◽  
Jian-Hao Fan ◽  
Wei Sun ◽  
Wei-Shi Zheng
Keyword(s):  
Large Scale ◽  
Assessment Model ◽  
Generic Model ◽  
Small Subset ◽  
Deep Convolutional Neural Networks ◽  
Personal Taste ◽  
Hinge Loss ◽  
Novel Approach ◽  
Large Scale Dataset ◽  
Image Pairs

AbstractRecent image aesthetic assessment methods have achieved remarkable progress due to the emergence of deep convolutional neural networks (CNNs). However, these methods focus primarily on predicting generally perceived preference of an image, making them usually have limited practicability, since each user may have completely different preferences for the same image. To address this problem, this paper presents a novel approach for predicting personalized image aesthetics that fit an individual user’s personal taste. We achieve this in a coarse to fine manner, by joint regression and learning from pairwise rankings. Specifically, we first collect a small subset of personal images from a user and invite him/her to rank the preference of some randomly sampled image pairs. We then search for the K-nearest neighbors of the personal images within a large-scale dataset labeled with average human aesthetic scores, and use these images as well as the associated scores to train a generic aesthetic assessment model by CNN-based regression. Next, we fine-tune the generic model to accommodate the personal preference by training over the rankings with a pairwise hinge loss. Experiments demonstrate that our method can effectively learn personalized image aesthetic preferences, clearly outperforming state-of-the-art methods. Moreover, we show that the learned personalized image aesthetic benefits a wide variety of applications.

Developing individualized feedback for listening assessment: Combining standard setting and cognitive diagnostic assessment approaches

2021 ◽  
pp. 026553222199547
Author(s):  
Shangchao Min ◽  
Lianzhen He
Keyword(s):  
Large Scale ◽  
Standard Setting ◽  
Diagnostic Assessment ◽  
Efl Learners ◽  
Cognitive Diagnostic Assessment ◽  
Item Level ◽  
Language Assessments ◽  
Individualized Feedback ◽  
Proficiency Classifications ◽  
Acceptable Reliability

In this study, we present the development of individualized feedback for a large-scale listening assessment by combining standard setting and cognitive diagnostic assessment (CDA) approaches. We used the performance data from 3358 students’ item-level responses to a field test of a national EFL test primarily intended for tertiary-level EFL learners. The results showed that proficiency classifications and subskill mastery classifications were generally of acceptable reliability, and the two kinds of classifications were in alignment with each other at individual and group levels. The outcome of the study is a set of descriptors that describe each test taker’s ability to understand certain level of oral texts and his or her cognitive performance. The current study, by illustrating the feasibility of combining standard setting and CDA approaches to produce individualized feedback, contributes to the enhancement of score reporting and addresses the long-standing criticism that large-scale language assessments fail to provide individualized feedback to link assessment with instruction.

Sign in / Sign up

Export Citation Format

Share Document