scholarly journals University Credits as a Measure of Teachers’ Pre-service and In-Service Training: A Longitudinal Approach Using Swedish Data

2022 ◽  
Vol 12 ◽  
Author(s):  
Stefan Johansson ◽  
Åse Hansson ◽  
Tarja Alatalo
Keyword(s):  
Training Data ◽  
Future Research ◽  
Special Focus ◽  
Grade Point ◽  
Subject Knowledge ◽  
Multilevel Growth Modeling ◽  
Time Period ◽  
Service Training ◽  
And Mathematics ◽  
The University

In this study, we accessed information about the university credits of all teachers born after 1971 in Sweden as a means of ascertaining the development of their subject knowledge. We examined the university credits they earned during pre-service and in-service training. Data comes from registers Gothenburg Educational Longitudinal Database (GOLD) and the teacher register. We linked GOLD to the teacher register in order to describe the knowledge development of teachers in compulsory school 1998–2014. Special focus was on Swedish language and mathematics. Multiple regression and multilevel growth modeling were used as our main methods. Results show an increase in pre-service credits during the time period and more credits in Swedish language than in mathematics. To analyze teachers’ in-service training, we followed the development of their university credits over time. Teachers with higher prerequisites in terms of grade point average tended to gain more credits in-service. The study included discussions on ideas and the implications for future research.

scholarly journals Developing Students' Creative Constructs in Mathematics with Problem-Based (PB) and Problem Posing (PP) Tasks

2021 ◽  
Vol 13 (2) ◽  
pp. 82-94
Author(s):  
Dennis B. Roble ◽  
Laila S. Lomibao ◽  
Charita A. Luna
Keyword(s):  
Problem Posing ◽  
Future Research ◽  
Control Group ◽  
Education Students ◽  
Mediating Role ◽  
Before And After ◽  
Mathematical Fluency ◽  
And Mathematics ◽  
The University ◽  
Experimental Group

The purpose of this experimental study was to examine the creative constructs of students enrolled in Differential Calculus at the University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines. This study was composed of 132 engineering and mathematics education students enrolled in two different semesters. The experimental group was chosen randomly, exposed to the problem-based HALP model teaching approach and problem posing while the control group was taught using Polya’s problem-solving heuristics. Multiple Solution Tasks (MST) test in Calculus was administered to determine their creative constructs which can be measured in terms of their level of mathematical fluency, flexibility and novelty of solutions before and after the experiment. Results indicated that the experimental group exhibited a remarkable improvement of their mathematical fluency and flexibility but still in the developing level when they are required to posit novel solutions to problems as influenced by the problem-based HALP and problem posing activities. Hence, it is recommended that mathematics teachers may utilize these methods to successfully develop students’ mathematical creativity and future research may also be explored on integrating technology and how it can influence developing student’s mathematical creativeness as well as the mediating role of their affective domains and IQ (intelligent quotient).  

University Entry Scores as a Predictor of Academic Performance in a Health Information Management Program

1998 ◽  
Vol 28 (2) ◽  
pp. 57-61 ◽  
Author(s):  
Tina Magennis ◽  
Jennifer Mitchell
Keyword(s):  
Academic Performance ◽  
Academic Success ◽  
Health Information ◽  
Information Management ◽  
Health Information Management ◽  
First Year ◽  
Grade Point ◽  
Significant Difference ◽  
And Mathematics ◽  
The University

The university entry scores for school leavers admitted to the first year of the Bachelor of Applied Science (Health Information Management) degree at the University of Sydney in 1996 were examined to determine whether the Tertiary Entrance Rank (TER) was a good predictor of academic performance, as measured by grade point average (GPA). The study also examined Higher School Certificate (HSC) results in English and mathematics, and preference selection for the health information management (HIM) course to determine whether any of these had predictive validity. The results showed that TER, HSC English and mathematics scores and preference for the course were all poor predictors of academic performance in the student's first year. Low TER was not associated with low GPA and low scores in English and mathematics were not associated with low GPA. There was no significant difference between the performance of those students who listed the HIM course as their first preference and those who did not. These results suggest that there may be no need to establish a minimum entry level for admission to the HIM course, or for prerequisites in English and mathematics. It may be that multiple criteria are required to predict academic success in this course.

Executive Functions and Clinical and Academic Outcomes in Speech-Language Pathology Graduate Students

2020 ◽  
Vol 5 (5) ◽  
pp. 1221-1230
Author(s):  
Jane Roitsch ◽  
Kimberly A. Murphy ◽  
Anastasia M. Raymer
Keyword(s):  
Executive Function ◽  
Academic Outcomes ◽  
Graduate Program ◽  
Performance Outcomes ◽  
Future Research ◽  
Speech Language Pathology ◽  
Grade Point ◽  
Praxis Ii ◽  
Language Pathology ◽  
Preliminary Study

Purpose The purpose of this study was to investigate executive function measures as they relate to clinical and academic performance outcomes of graduate speech-language pathology students. Method An observational design incorporating correlations and stepwise multiple regressions was used to determine the strength of the relationships between clinical outcomes that occurred at various time points throughout the graduate program (clinical coursework grades throughout the program and case study paper scores at the end of the program), academic outcomes (graduate grade point average and Praxis II exam in speech-language pathology scores), and executive function (EF) scores (EF assessment scores, self-reported EF scores). Participants were 37 students (36 women, M age = 24.1) in a master's degree program in speech-language pathology at a southeastern U.S. university during the 2017–2018 academic year. Results Findings of this preliminary study indicated that a limited number of objective EF scores and self-reported EF scores were related to clinical and academic outcomes of graduate speech-language pathology students. Conclusion As results of this preliminary study suggest that EF tests may be related to clinical and academic outcomes, future research can move to study the potential role of EF measures in the graduate admissions process in clinical graduate programs such as speech-language pathology.

Doctor of Business Administration (D.B.A.): A Viable Credential for Faculty in Programmatically Accredited Business Degree Programs?

10.28945/3529 ◽  
2016 ◽  
Vol 11 ◽  
pp. 217-226 ◽  
Author(s):  
Helen L MacLennan ◽  
Anthony A Pina ◽  
Kenneth A Moran ◽  
Patrick F Hafford
Keyword(s):  
Doctoral Program ◽  
Business Administration ◽  
Academic Programs ◽  
Future Research ◽  
Degree Programs ◽  
Business Programs ◽  
Professional Degree ◽  
Doctor Of Philosophy ◽  
Business Practitioners ◽  
The University

Is the Doctor of Business Administration (D.B.A) a viable degree option for those wishing a career in academe? The D.B.A. degree is often considered to be a professional degree, in-tended for business practitioners, while the Doctor of Philosophy (Ph.D.) degree is por-trayed as the degree for preparing college or university faculty. Conversely, many academic programs market their D.B.A. programs to future academicians. In this study, we investigat-ed whether the D.B.A. is, in fact, a viable faculty credential by gathering data from univer-sity catalogs and doctoral program websites and handbooks from 427 graduate business and management programs to analyze the terminal degrees held by 6159 faculty. The analysis indicated that 173 institutions (just over 40% of the total) employed 372 faculty whose ter-minal degree was the D.B.A. This constituted just over 6% of the total number of faculty. Additionally, the program and faculty qualification standards of the six regional accrediting agencies and the three programmatic accrediting agencies for business programs (AACSB, IACBE, and ACBSP) were analyzed. Results indicated that all these accrediting agencies treated the D.B.A. and Ph.D. in business identically and that the D.B.A. was universally considered to be a valid credential for teaching business at the university level. Suggestions for future research are also offered.

scholarly journals Bridging the gap: blending spatial skills instruction into a technology teacher preparation programme

2021 ◽  
Author(s):  
Diarmaid Lane ◽  
Sheryl Sorby
Keyword(s):  
Teacher Preparation ◽  
Gender Gap ◽  
Future Research ◽  
First Year ◽  
Spatial Skills ◽  
First Year Students ◽  
Base Level ◽  
Technology Teacher ◽  
And Mathematics ◽  
The Impact

AbstractIn recent years, there has been a surge in research in spatial thinking across the international community. We now know that spatial skills are malleable and that they are linked to success across multiple disciplines, most notably Science, Technology, Engineering and Mathematics (STEM). While spatial skills have been examined by cognitive scientists in laboratory environments for decades, current research is examining how these skills can be developed in field-based environments. In this paper, we present findings from a study within a Technology Teacher preparation programme where we examined first-year students’ spatial skills on entry to university. We explain why it was necessary to embed a spatial skills intervention into Year 1 of the programme and we describe the impact that this had on students’ spatial scores and on academic performance. The findings from our study highlight a consistent gender gap in spatial scores at the start of the first-year with female students entering the Technology Teacher preparation programme at a lower base level than male students. We describe how we integrated spatial development activities into an existing course and how an improvement in spatial scores and overall course performance was observed. The paper concludes by discussing the long-term sustainability of integrating spatial interventions within teacher preparation programmes while also highlighting the importance of future research to examine spatial skills as a fundamental component of technological capability.

scholarly journals Public Administration and Values Oriented to Sustainability: A Systematic Approach to the Literature

2021 ◽  
Vol 13 (5) ◽  
pp. 2566
Author(s):  
Isabel Marques ◽  
João Leitão ◽  
Alba Carvalho ◽  
Dina Pereira
Keyword(s):  
Public Administration ◽  
Future Research ◽  
Main Research ◽  
Sustainable Performance ◽  
Future Research Agenda ◽  
Research Collaborations ◽  
Work Area ◽  
The Social ◽  
The Usa ◽  
The University

Values guide actions and judgements, form the basis of attitudinal and behavioral processes, and have an impact on leaders’ decision-making, contributing to more sustainable performance. Through a bibliometric study and content analysis, 2038 articles were selected from Scopus, from the period 1994–2021, presenting global research tendencies on the subject of values, public administration, and sustainability. The results indicate that Sustainability is the most productive journal, the main research category is in social sciences, the most productive institution is the University of Queensland, the location with the most publications and research collaborations is the USA, and the authors with the greatest number of articles are Chung, from Chung-Ang University; García-Sánchez, from the University of Salamanca; and Pérez, from the University of Cantabria. Analysis of keywords shows that the most relevant are “sustainability”, “CSR”, “sustainable development”, “innovation”, and “leadership”. Time analysis of keywords reveals a tendency for lines of research in the social and work area. The results also provide data about the framing of studies in sustainability pillars and the types of values referred to and indicate the main areas of public administration studied. Finally, a future research agenda is proposed.

scholarly journals Is Call Karma Real? Resident After-Hours On-Call Imaging at the University of Saskatchewan: An Assessment of Call Volumes Including Inter-Resident Variability

2021 ◽  
pp. 084653712110263
Author(s):  
James Huynh ◽  
David Horne ◽  
Rhonda Bryce ◽  
David A Leswick
Keyword(s):  
Mean Shift ◽  
Mean Values ◽  
Body Regions ◽  
Time Period ◽  
Relative Value ◽  
Number Of Patients ◽  
After Hours ◽  
Disproportionate Number ◽  
The University ◽  
Changes Over Time

Purpose: Quantify resident caseload during call and determine if there are consistent differences in call volumes for individuals or resident subgroups. Methods: Accession codes for after-hours computed tomography (CT) cases dictated by residents between July 1, 2012 and January 9, 2017 were reviewed. Case volumes by patient visits and body regions scanned were determined and categorized according to time period, year, and individual resident. Mean shift Relative Value Units (RVUs) were calculated by year. Descriptive statistics, linear mixed modeling, and linear regression determined mean values, differences between residents, associations between independent variables and outcomes, and changes over time. Consistent differences between residents were assessed as a measure of good or bad luck / karma on call. Results: During this time there were 23,032 patients and 30,766 anatomic regions scanned during 1,652 call shifts among 32 residents. Over the whole period, there were on average 10.6 patients and 14.3 body regions scanned on weekday shifts and 22.3 patients and 29.4 body regions scanned during weekend shifts. Annually, the mean number of patients, body regions, and RVUs scanned per shift increased by an average of 0.2 (1%), 0.4 (2%), and 1.2 (5%) (all p < 0.05) respectively in regression models. There was variability in call experiences, but only 1 resident had a disproportionate number of higher volume calls and fewer lower volume shifts than expected. Conclusions: Annual increases in scan volumes were modest. Although residents’ experiences varied, little of this was attributable to consistent personal differences, including luck or call karma.

scholarly journals Deep bilinear features for Her2 scoring in digital pathology

2017 ◽  
Vol 3 (2) ◽  
pp. 811-814 ◽  
Author(s):  
Erik Rodner ◽  
Marcel Simon ◽  
Joachim Denzler
Keyword(s):  
Digital Pathology ◽  
Training Data ◽  
Large Set ◽  
Second Order Statistics ◽  
Over Expression ◽  
Point Of Interest ◽  
Winning Team ◽  
Image Patches ◽  
Parameterized Model ◽  
The University

AbstractWe present an automated approach for rating HER2 over-expressions in given whole-slide images of breast cancer histology slides. The slides have a very high resolution and only a small part of it is relevant for the rating.Our approach is based on Convolutional Neural Networks (CNN), which are directly modelling the whole computer vision pipeline, from feature extraction to classification, with a single parameterized model. CNN models have led to a significant breakthrough in a lot of vision applications and showed promising results for medical tasks. However, the required size of training data is still an issue. Our CNN models are pre-trained on a large set of datasets of non-medical images, which prevents over-fitting to the small annotated dataset available in our case. We assume the selection of the probe in the data with just a single mouse click defining a point of interest. This is reasonable especially for slices acquired together with another sample. We sample image patches around the point of interest and obtain bilinear features by passing them through a CNN and encoding the output of the last convolutional layer with its second-order statistics.Our approach ranked second in the Her2 contest held by the University of Warwick achieving 345 points compared to 348 points of the winning team. In addition to pure classification, our approach would also allow for localization of parts of the slice relevant for visual detection of Her2 over-expression.

scholarly journals Artificial Intelligence, 3D Documentation, and Rock Art—Approaching and Reflecting on the Automation of Identification and Classification of Rock Art Images

2021 ◽  
Author(s):  
Christian Horn ◽  
Oscar Ivarsson ◽  
Cecilia Lindhé ◽  
Rich Potter ◽  
Ashely Green ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Bronze Age ◽  
Data Augmentation ◽  
Rock Art ◽  
Training Data ◽  
Future Research ◽  
Rock Surface ◽  
Southern Scandinavia ◽  
Bounding Boxes

AbstractRock art carvings, which are best described as petroglyphs, were produced by removing parts of the rock surface to create a negative relief. This tradition was particularly strong during the Nordic Bronze Age (1700–550 BC) in southern Scandinavia with over 20,000 boats and thousands of humans, animals, wagons, etc. This vivid and highly engaging material provides quantitative data of high potential to understand Bronze Age social structures and ideologies. The ability to provide the technically best possible documentation and to automate identification and classification of images would help to take full advantage of the research potential of petroglyphs in southern Scandinavia and elsewhere. We, therefore, attempted to train a model that locates and classifies image objects using faster region-based convolutional neural network (Faster-RCNN) based on data produced by a novel method to improve visualizing the content of 3D documentations. A newly created layer of 3D rock art documentation provides the best data currently available and has reduced inscribed bias compared to older methods. Several models were trained based on input images annotated with bounding boxes produced with different parameters to find the best solution. The data included 4305 individual images in 408 scans of rock art sites. To enhance the models and enrich the training data, we used data augmentation and transfer learning. The successful models perform exceptionally well on boats and circles, as well as with human figures and wheels. This work was an interdisciplinary undertaking which led to important reflections about archaeology, digital humanities, and artificial intelligence. The reflections and the success represented by the trained models open novel avenues for future research on rock art.

Using Deep Learning to Understand Travel Demands in Different Urban Districts

2021 ◽  
pp. 036119812199458
Author(s):  
Shunhua Bai ◽  
Junfeng Jiao
Keyword(s):  
Built Environment ◽  
Travel Behavior ◽  
Prediction Accuracy ◽  
Travel Demand ◽  
Short Term Memory ◽  
Future Research ◽  
Demand Forecast ◽  
Time And Space ◽  
The University ◽  
The Impact

Travel demand forecast plays an important role in transportation planning. Classic models often predict people’s travel behavior based on the physical built environment in a linear fashion. Many scholars have tried to understand built environments’ predictive power on people’s travel behavior using big-data methods. However, few empirical studies have discussed how the impact might vary across time and space. To fill this research gap, this study used 2019 anonymous smartphone GPS data and built a long short-term memory (LSTM) recurrent neural network (RNN) to predict the daily travel demand to six destinations in Austin, Texas: downtown, the university, the airport, an inner-ring point-of-interest (POI) cluster, a suburban POI cluster, and an urban-fringe POI cluster. By comparing the prediction results, we found that: the model underestimated the traffic surge for the university in the fall semester and overestimated the demand for downtown on non-working days; the prediction accuracy for POI clusters was negatively related to their adjacency to downtown; and different POI clusters had cases of under- or overestimation on different occasions. This study reveals that the impact of destination attributes on people’s travel demand can vary across time and space because of their heterogeneous nature. Future research on travel behavior and built environment modeling should incorporate the temporal inconsistency to achieve better prediction accuracy.

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