Grade Assignment Research Articles

The Integrated Histopathologic and Molecular Approach to Adult-type Diffuse Astrocytomas: Status of the Art, Based on the 2021 WHO Classification of Central Nervous System Tumors

The 2021 World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) improved our understanding of the brain neoplasm biology. In more details, differences between diffuse gliomas that primarily occur in adults and those that primarily occur in children have been identified by the terms “adult-type” and “pediatric-type” diffuse gliomas. More importantly, both diagnostic and grading criteria for adult-type diffuse astrocytomas have been modified, by adopting novel molecular markers: diffuse astrocytomas, <i>IDH</i>-mutant have been grouped into a single entity and graded as CNS WHO grades 2, 3, or 4, with the assignment of Grade 4 in the presence of <i>CDKN2A/B</i> homozygous deletion, regardless of the histology [1]. Additionally, at least one of the following genetic alterations has been considered as sufficient to confer to astrocytomas, <i>IDH</i> wild type, a CNS WHO grade 4: i) <i>TERT</i> promoter mutation, ii) EGFR gene amplification, iii) combined gain of whole chromosome 7 and loss of whole chromosome 10 [+7/−10]. However, histology remains the solid basis to support these new complementary molecular data, and an integrated diagnosis is highly recommended.

College English Online Teaching Model Based on Deep Learning

In today’s era, online teaching plays an important part in the college English teaching. Deep learning, famous for its ability of imitating the learning process of human brains and obtaining the internal essential features or rules of voice, videos, images, and other data, can be applied to assist and improve the college English online teaching which involves a wide use of those data. Based on the combination of the multilayer neural network model and the k-means clustering algorithm, this paper designs a kind of deep learning method that can be used to assist and improve the college English online teaching. Experiments were designed to test the reliability of this deep learning method. The results show that the optimization algorithm designed in this paper, which can adjust the learning rate, will improve the common probability gradient descent algorithm. Besides, it is proved that the deep learning’s efficiency of the CNN model is significantly higher than that of the MLP model. With the help of this deep learning method, it becomes feasible to apply the technologies related to the artificial intelligence to help teachers deeply analyze and diagnose students’ English learning behavior, replace the teachers in part to answer students’ questions in time, and automatically grade assignments in the process of the college English online teaching. Surveys and exams were then conducted to evaluate the effect of the application of the college English online teaching model based on deep learning on the students’ learning cognition and their academic performance. The results show that the college English online teaching model based on deep learning can stimulate students’ learning motivation and improve their academic performance.

Integrating evidence-based medicine skills into a medical school curriculum: a quantitative outcomes assessment

ObjectivesThis research project aims to determine the potential differential impact of two curricular approaches to teaching evidence-based medicine (EBM) on student performance on an EBM assignment administered during the first...

Knowing and doing

This study touches upon three major themes in the field of information literacy (IL): the assessment of IL, the association between IL knowledge and skills, and the dimensionality of the IL construct. Three quantitative measures were developed and tested with several samples of university students to assess knowledge and skills for core facets of IL. These measures are freely available, applicable across disciplines, and easy to administer. Results indicate they are likely to be reliable and support valid interpretations. By measuring both knowledge and practice, the tools indicated low to moderate correlations between what students know about IL, and what they actually do when evaluating and using sources in authentic, graded assignments. The study is unique in using actual coursework to compare knowing and doing regarding students’ evaluation and use of sources. It provides one of the most thorough documentations of the development and testing of IL assessment measures to date. Results also urge us to ask whether the source-focused components of IL – information seeking, source evaluation and source use – can be considered unidimensional constructs or sets of disparate and more loosely related components, and findings support their heterogeneity.

Analysis of Longitudinal Advice-Seeking Networks Following Implementation of High Stakes Testing

Abstract Teacher interactions around instructional practices have been a topic of study for a long time. Previous studies concerning such interactions have focused on questions pertaining to cross-sectional networks. In fact, very few studies have considered longitudinal networks and still fewer have employed longitudinal network models to study changes in such interactions. We analyse teachers’ advice-seeking networks, observed annually between 2010 and 2013, in schools within a district where several initiatives were implemented starting in 2011. We assess whether formal structures, teaching assignment and leadership position, and teacher characteristics, gender and experience, are associated with advice-seeking ties, and the extent to which these associations change over time. To analyse the advice-seeking networks, we implement a Bayesian longitudinal latent space network model with covariates and random sender-receiver effects. Within the Bayesian framework, we address practical aspects of a principled network analysis such as missing ties and yearly immigration and emigration of teachers. Goodness of model fit assessment is conducted using posterior predictive checks. Our results demonstrate that while some of the associations between observed covariates and teachers’ interactions varied in 2011, most were otherwise stable. In 2011, we found decreases in the associations with same grade assignment, leadership position, and teaching in the same school.

Comparison of blended versus traditional classrooms among undergraduate nursing students: A quasi-experimental study

BackgroundBlended learning is a relatively new educational approach that has been introduced into higher education in Palestine. While it has many advantages, there is no empirical evidence, nor any case studies from Palestine to support the use of blended learning over traditional classroom. ObjectivesTo compare students' learning outcomes, learning perceptions of their educational environment, and satisfaction of blended learning versus traditional classroom. DesignA quasi-experimental study. SettingA public university in Palestine. Participants102 Bachelor of Science in nursing students enrolled on the maternal health course. MethodsStudents freely chose to register for the blended teaching section (49 students) or traditional classroom (53 students), then the teaching method for each section was assigned. Student demographics, course component grades, perceptions of the educational environment, measured by the Arabic version of Dundee Ready Education Environment Measurement (DREEM) inventory, and degree of satisfaction were collected in this study. Descriptive statistics and the Independent Sample t-test were used to analyze the data. ResultsThe sample included 49 students in the blended teaching section and 53 students in the traditional section. Overall DREEM scores, Student Perceptions of Learning, and Student Perceptions of Teachers were significantly higher for students taught with the blended method compared to traditional classroom settings. The total DREEM scores were between 101 and 151 for both sections, indicating that all students, regardless of teaching method, had more positive than negative perceptions of their educational environment. Moreover, there was no significant difference in scores and total course GPA (Grade Point Average), both with and without assignment grades, or between blended and traditional learning in first, second and final exams. However, students taught with the blended format scored significantly higher in assignments than students taught the traditional classroom. ConclusionsBlended learning can be a useful educational approach in nursing education and Palestinian universities may consider using it for nursing courses.

Convolutional Neural Network Models for Automatic Preoperative Severity Assessment in Unilateral Cleft Lip.

Despite the wide range of cleft lip morphology, consistent scales to categorize preoperative severity do not exist. Machine learning has been used to increase accuracy and efficiency in detection and rating of multiple conditions, yet it has not been applied to cleft disease. The authors tested a machine learning approach to automatically detect and measure facial landmarks and assign severity grades using preoperative photographs. Preoperative images were collected from 800 unilateral cleft lip patients, manually annotated for cleft-specific landmarks, and rated using a previously validated severity scale by eight expert reviewers. Five convolutional neural network models were trained for landmark detection and severity grade assignment. Mean squared error loss and Pearson correlation coefficient for cleft width ratio, nostril width ratio, and severity grade assignment were calculated. All five models performed well in landmark detection and severity grade assignment, with the largest and most complex model, Residual Network, performing best (mean squared error, 24.41; cleft width ratio correlation, 0.943; nostril width ratio correlation, 0.879; severity correlation, 0.892). The mobile device-compatible network, MobileNet, also showed a high degree of accuracy (mean squared error, 36.66; cleft width ratio correlation, 0.901; nostril width ratio correlation, 0.705; severity correlation, 0.860). Machine learning models demonstrate the ability to accurately measure facial features and assign severity grades according to validated scales. Such models hold promise for the creation of a simple, automated approach to classifying cleft lip morphology. Further potential exists for a mobile telephone-based application to provide real-time feedback to improve clinical decision making and patient counseling.

Early Neurological Changes and Interpretation of Clinical Grades in Aneurysmal Subarachnoid Hemorrhage

ObjectivesHunt and Hess (HH) and World Federation of Neurological Surgeons (WFNS) grades are commonly used to report clinical severity of aneurysmal subarachnoid hemorrhage (aSAH). We sought to determine the impact of early neurological changes and the timing of clinical grade assignment on the prognostication accuracy. MethodsWe retrospectively reviewed a cohort of consecutive patients with aSAH who were admitted to an academic center. Patients with confirmed aneurysmal cause were included. Relevant clinical data including daily clinical grades, imaging data and functional outcome were analyzed. Favorable outcome was defined as mRS 0 to 3. Early neurological improvement (ENI) and early neurological deterioration (END) were respectively defined as any improvement or deterioration of HH grades from hospital day 1 to the earliest time from hospital day 2 to 5. ResultsOf 310 patients, 24% experienced early neurological changes from hospital day 1 to 3. For each point increase in HH grades from day 1 to day 3, the odds ratio for worse outcome was 2.57 (95% CI [1.74-3.79]) and for each point decrease in HH grades from day 1 to day 3, the odds ratio for worse outcome was 0.28 (95% CI [0.17-0.47]). Receiver Operating Characteristic curve analysis revealed that clinical grades on day 3 had higher accuracy in predicting worse outcome than clinical grades on day 1. ConclusionEarly changes in neurological status can alter trajectory of hospital course and functional outcome. The prognostic accuracy of the clinical grades from hospital day 3 is significantly greater than those on admission.

A Comparison of Teaching Methods for a Baccalaureate Nursing Health Assessment Course.

New teaching methods are designed and implemented to ensure student success and application of knowledge. One of these designs is the flipped classroom. Nursing programs are also integrating technology, including simulation, into nursing education in order to enhance student engagement. Although several research studies support flipped classroom methodology, no studies have compared traditional and flipped classroom teaching methods, as well as the use of a technology-enhanced classroom, in a baccalaureate nursing health assessment course. The purpose of this study was to compare learning outcomes and student satisfaction in an undergraduate health assessment course across three teaching methods: traditional lecture, flipped classroom, and a technology-enhanced interactive flipped classroom. All three methods incorporated virtual patient simulation. Using a quasi-experimental design, formative and summative assignment grades were compared. Student course evaluations were compared to assess satisfaction with each teaching method. Significant differences in mean grades were found in 12 of the 23 assignments. The technology-enhanced interactive flipped classroom section outperformed the traditional and flipped classroom sections on most of these assessments. Only one difference was noted in student satisfaction. The results showed that a technology-enhanced interactive flipped classroom design supported student learning. A longitudinal analysis of student performance is recommended.

Internet and Mobile Phone Addiction Self-Control Mediate Physical Exercise and Subjective Well-Being in Young Adults Using IoT

Independent Internet surfing and persistently addictive smartphone use have become a significant public health problem. This addictive behavior is more prevalent in young people, who can engage in long-term secondary inopportune outgrowths. The main aim of this study is to see whether self-control in Internet usage (SCIU) and mobile phone addiction (MPA) will mediate the relationship between physical fitness and subjective well-being (SWB) in a group of Chinese adults using IoT. 1801 university students completed the proposed standard scale grading assignments. The results of our analysis showed that SCIU directly mediated the relationship between physical exertion and SWB. MPA mediated the interaction between physical exercise and SWB in reverse. The results also showed that the multiple SCIU-MPA serial frameworks between physical exercise and SWB were statistically significant. This result indicates that SCIU and MPA’s relationships may be unique mediators in the relationship between physical exercise and SWB. Understanding the underlying interactions may have therapeutic significance for chronic, neurobiological disorders in young people with MPA. These results may also be used to improve physical intervention programs to improve the well-being of young Chinese people.

Asynchrony in Peritumoral Resting-State Blood Oxygen Level-Dependent fMRI Predicts Meningioma Grade and Invasion.

Meningioma grade is determined by histologic analysis, with detectable brain invasion resulting in a diagnosis of grade II or III tumor. However, tissue undersampling is a common problem, and invasive parts of the tumor can be missed, resulting in the incorrect assignment of a lower grade. Radiographic biomarkers may be able to improve the diagnosis of grade and identify targets for biopsy. Prior work in patients with gliomas has shown that the resting-state blood oxygen level-dependent fMRI signal within these tumors is not synchronous with normal brain. We hypothesized that blood oxygen level-dependent asynchrony, a functional marker of vascular dysregulation, could predict meningioma grade. We identified 25 patients with grade I and 11 patients with grade II or III meningiomas. Blood oxygen level-dependent time-series were extracted from the tumor and the radiographically normal control hemisphere and were included as predictors in a multiple linear regression to generate a blood oxygen level-dependent asynchrony map, in which negative values signify synchronous and positive values signify asynchronous activity relative to healthy brain. Masks of blood oxygen level-dependent asynchrony were created for each patient, and the fraction of the mask that extended beyond the contrast-enhancing tumor was computed. The spatial extent of blood oxygen level-dependent asynchrony was greater in high (grades II and III) than in low (I) grade tumors (P < 0.001) and could discriminate grade with high accuracy (area under the curve = 0.88). Blood oxygen level-dependent asynchrony radiographically discriminates meningioma grade and may provide targets for biopsy collection to aid in histologic diagnosis.

Team teaching – doświadczanie współnauczania

&lt;p&gt;W artykule przedstawiono główne założenia leżące u podstaw modelu nauczania zespołowego. Jest to jedna z czterech strategii wspólnego nauczania, obok współnauczania wspierającego, współnauczania równoległego i współnauczania uzupełniającego. Model nauczania zespołowego różni się od pozostałych, ponieważ wszyscy nauczyciele współprowadzący są w równym stopniu odpowiedzialni za planowanie, nauczanie, ocenianie i przypisywanie ocen. Współnauczyciele są postrzegani przez uczniów jako równi sobie. Autorka opisała ten model i swoje doświadczenia z nim. Istotnym aspektem omawianej strategii współnauczania są warunki, jakie powinni spełniać nauczyciele, aby ich współpraca prowadziła do osiągnięcia wyznaczonych celów, a także do własnego rozwoju zawodowego, wzajemnego uczenia się oraz kształtowania w szkole kultury współpracy.&lt;/p&gt;

Incorporation of a mock pharmacy and therapeutics committee as an entrustable professional activity supporting task

IntroductionEntrustable professional activities (EPAs) denote activities and tasks students should be able to perform by graduation irrespective of their practice setting. Formulary decision-making includes several core EPA related skills, such as utilization of drug information, written, and verbal skills. The objective of this study was to describe an EPA supporting task aimed at improving utilization of evidence-based medicine skills and its impact on student self-perceived confidence, rating of skills needed, and competence. MethodsTeams comprised of six to seven students were assigned a drug and instructed to complete the following activities: (1) background literature search, (2) drug monograph, (3) five-min presentation to simulate a live pharmacy and therapeutics (P&T) committee meeting, and (4) vote on a formulary drug in each drug class. Students completed a pre/post five-point Likert scale self-efficacy survey and a perceived importance survey. A scoring rubric assessed monograph and presentation elements (max points 30). Survey items were analyzed using Wilcoxon signed-rank test. Descriptive statistics were used for assignment grades. ResultsOne hundred ninety students completed the pre/post self-efficacy and perceived importance survey. Confidence showed statistically significant improvement (P < .001) in nine target skill areas. In ranking importance, all 12 assessed skills exhibited a statistically significant increase following the activity. ConclusionsA mock P&T activity represents an innovative way to evaluate an EPA supporting task that allows students to improve their evidence-based analysis, written, and verbal communication skills.

An Empirical Study of Students’ Perceptions on the Setup and Grading of Group Programming Assignments

Courses in computer science curricula often involve group programming assignments. Instructors are required to take several decisions on assignment setup and monitoring, team formation policies, and grading systems. Group programming projects provide unique monitoring opportunities due to the availability of both product and process data, as well as challenges in team composition, with students of varying levels of prior programming experience. To gain insights into the experiences and perceptions of students about the assignment setup and grading policies in group programming projects, we interviewed 20 computer science students from four universities. The thematic analysis highlighted factors in group composition that are considered important, as well as advantages and disadvantages of the self-selection of the teams. It also indicated three grading strategies experienced by the students, namely, being assigned the same group grade, individual grades distributed by the instructor, and grade distribution determined by the team, with perceptions about them varying greatly. Several practices for monitoring team contributions were identified. Checking the source code repositories was considered useful in recognizing slacking members, but automated metrics are not always representative of the work distribution. The analysis also uncovered student perceptions on the grading factors for programming assignments, including coding efficiency and skill.

Online Applications to Support Remote Classroom Dialogue and Assessment

This study investigates the impact of using online applications, which is integrating software or platform to support remote teaching and learning. Lots of online applications, both free and paid-for, can be used by teachers to enrich classroom interaction and to support students’ ability and understanding in the process of teaching and assessment. This study used descriptive mixed method design. To collect data, questionnaire was distributed to 140 students from senior high schools in Riau province. The findings showed that students believe in the significance of online applications to simplify creating, distributing, and grading assignments and receiving immediate feedback which is supported by some applications. On the other hand, the findings indicated that remote teaching did not create huge opportunities for effective learning and collaboration outside the classroom. Students need that the teachers should focus on pedagogy and learning, rather than technology. It is very important to provide immediate feedback during the formative assessment process to enhance students’ performance.

VMATE – Intelligent E-Learning Management System for Educational Institutions

The world is facing a huge health crisis which is demanding to reorganize the way it functions from square one. The spread of the pandemic, the shutdown of education institutions, and the shift to online learning were so fast that it barely gave any time to consider the difficulties faced by students. This is a great opportunity where educational institutions will shift to blended learning; hence it will become a new way of learning where there will be a need to find new ways to deliver the best content by using learning management systems. Therefore, the virtual learning world will create a great impact on the current education system due to the diverse effect of the epidemic. Hence different organizations are tremendously advancing their technology, and it will become more crucial over time. VMATE –Intelligent E-Learning Management System provides an interface for learners, which is of great significance and practical value for the improvement of learning and teaching quality. The use of Computers and the Internet has introduced technological conditions for teachers and students who can make good use of online information provided and communicating with others. This can be used by institutions and for different environments, where they can have computer-based instructions, blended-learning, and increased quality and quantity learning. Besides some basic management functions, the system focuses on assignment grading, assessment for various learning courses which makes it suitable to provide personalized grading and detailed feedback.

Video Grading: Giving Students Personal Feedback in an Online World

Engaging students in a distance learning environment can be difficult. One method that can help professors bridge the gap is making the use of video grading. Grading via video note is an alternative to traditional grading of careplans, discussion boards and other assignments.

An AI-Based System for Formative and Summative Assessment in Data Science Courses

Massive open online courses (MOOCs) provide hundreds of students with teaching materials, assessment tools, and collaborative instruments. The assessment activity, in particular, is demanding in terms of both time and effort; thus, the use of artificial intelligence can be useful to address and reduce the time and effort required. This paper reports on a system and related experiments finalised to improve both the performance and quality of formative and summative assessments in specific data science courses. The system is developed to automatically grade assignments composed of R commands commented with short sentences written in natural language. In our opinion, the use of the system can (i) shorten the correction times and reduce the possibility of errors and (ii) support the students while solving the exercises assigned during the course through automated feedback. To investigate these aims, an ad-hoc experiment was conducted in three courses containing the specific topic of statistical analysis of health data. Our evaluation demonstrated that automated grading has an acceptable correlation with human grading. Furthermore, the students who used the tool did not report usability issues, and those that used it for more than half of the exercises obtained (on average) higher grades in the exam. Finally, the use of the system reduced the correction time and assisted the professor in identifying correction errors.

Clear cell meningiomas are defined by a highly distinct DNA methylation profile and mutations in SMARCE1

Clear cell meningioma represents an uncommon variant of meningioma that typically affects children and young adults. Although an enrichment of loss-of-function mutations in the SMARCE1 gene has been reported for this subtype, comprehensive molecular investigations are lacking. Here we describe a molecularly distinct subset of tumors (n = 31), initially identified through genome-wide DNA methylation screening among a cohort of 3093 meningiomas, of which most were diagnosed histologically as clear cell meningioma. This cohort was further supplemented by an additional 11 histologically diagnosed clear cell meningiomas for analysis (n = 42). Targeted DNA sequencing revealed SMARCE1 mutations in 33/34 analyzed samples, accompanied by a nuclear loss of expression determined via immunohistochemistry and a decreased SMARCE1 transcript expression in the tumor cells. Analysis of time to progression or recurrence of patients within the clear cell meningioma group (n = 14) in comparison to those with meningioma WHO grade 2 (n = 220) revealed a similar outcome and support the assignment of WHO grade 2 to these tumors. Our findings indicate the existence of a highly distinct epigenetic signature of clear cell meningiomas, separate from all other variants of meningiomas, with recurrent mutations in the SMARCE1 gene. This suggests that these tumors may arise from a different precursor cell population than the broad spectrum of the other meningioma subtypes.

Prospectively Assigned AAST Grade versus Modified Hinchey Class and Acute Diverticulitis Outcomes

BackgroundThe American Association for the Surgery of Trauma (AAST) recently developed a classification system to standardize outcomes analyses for several emergency general surgery conditions. To highlight this system's full potential, we conducted a study integrating prospective AAST grade assignment within the electronic medical record. MethodsOur institution integrated AAST grade assignment into our clinical workflow in July 2018. Patients with acute diverticulitis were prospectively assigned AAST grades and modified Hinchey classes at the time of surgical consultation. Support vector machine—a machine learning algorithm attuned for small sample sizes—was used to compare the associations between the two classification systems and decision to operate and incidence of complications. Results67 patients were included (median age of 62 y, 40% male) for analysis. The decision for operative management, hospital length of stay, intensive care unit admission, and intensive care unit length of stay were associated with both increasing AAST grade and increasing modified Hinchey class (all P < 0.001). AAST grade additionally showed a correlation with complication severity (P = 0.02). Compared with modified Hinchey class, AAST grade better predicted decision to operate (88.2% versus 82.4%). ConclusionsThis study showed the feasibility of electronic medical record integration to support the full potential of AAST classification system's utility as a clinical decision-making tool. Prospectively assigned AAST grade may be an accurate and pragmatic method to find associations with outcomes, yet validation requires further study.