Biomedical science students’ intended graduate destinations

Undergraduate students enrolled in generalist degrees, such as biomedical science, have diverse potential graduate pathways that they may choose to pursue. The aims of this study were to evaluate the intended graduate destinations of students, the reasons they chose to study science and the perceived value of the skills they are acquiring for their intended profession. The participants were second year biomedical science students at the University of Queensland. Their responses to open-ended questions regarding their intentions, choices and perceptions were subjected to thematic analysis. Three-quarters of students mentioned one intended profession, with the remainder mentioning two or more. Overall, they identified 53 different intended graduate destinations in the fields of medicine (69%), research (34%), the science industry (14%) and allied health (8%). As reasons for studying science, students commonly reported their interest in science, the influence of role models and enjoyment or academic success in prior study. Many students, particularly those intent on pursuing medicine, said they planned to use science as a pathway to a postgraduate degree. Importantly, all students perceived that the skills they were acquiring in their degree were highly applicable to their future intended professions

DEVELOPING PROFESSIONAL IDENTITY IN BIOMEDICAL SCIENCE STUDENTS

For students in science, professional identity develops as they pursue a ‘major’ within their degrees (Nadelson et al 2017). However, unlike many disciplines, students majoring in biomedical sciences often do not intend remaining within these disciplines, instead are pursuing a career in medicine or health (Panaretos et al 2019). A biomedical science degree may provide a good knowledge basis for these careers, but can it support the development of these students’ professional identities? Students in biomedical science (n=191) identified the career they intended to pursue and described their perceptions of how their degree could contribute to their future professionalism. Most students intended to pursue medicine (70%) or health (6%). Only 12% intended a career in biomedical science, while some (7%) were unsure of their future. Students frequently identified communication, critical thinking and information literacy skills as valuable, and that qualities such as the ability to work with others, ethics and independence contributed to their developing professionalism. However, some students (6%) were unsure if or how their degree could contribute to their desired career. These findings highlight that most students see value in their biomedical science degrees, but that alignment of skills and qualities to future professions could be improved

Biomedical science students’ intended graduate destinations

Undergraduate students enrolled in generalist degrees, such as biomedical science, have diverse potential graduate pathways that they may choose to pursue. The aims of this study were to evaluate the intended graduate destinations of students, the reasons they chose to study science and the perceived value of the skills they are acquiring for their intended profession. The participants were second year biomedical science students at the University of Queensland. Their responses to open-ended questions regarding their intentions, choices and perceptions were subjected to thematic analysis. Three-quarters of students mentioned one intended profession, with the remainder mentioning two or more. Overall, they identified 53 different intended graduate destinations in the fields of medicine (69%), research (34%), the science industry (14%) and allied health (8%). As reasons for studying science, students commonly reported their interest in science, the influence of role models and enjoyment or academic success in prior study. Many students, particularly those intent on pursuing medicine, said they planned to use science as a pathway to a postgraduate degree. Importantly, all students perceived that the skills they were acquiring in their degree were highly applicable to their future intended professions

ICDAR 2003 Robust Reading Competitions: Entries, Results and Future Directions

International audienceThis paper describes the robust reading competitions for ICDAR 2003. With the rapid growth in research over the last few years on recognizing text in natural scenes, there is an urgent need to establish some common benchmark datasets, and gain a clear understanding of the current state of the art. We use the term robust reading to refer to text images that are beyond the capabilities of current commercial OCR packages. We chose to break down the robust reading problem into three sub-problems, and run competitions for each stage, and also a competition for the best overall system. The sub-problems we chose were text locating, character recognition and word recognition. By breaking down the problem in this way, we hoped to gain a better understanding of the state of the art in each of the sub-problems. Furthermore, our methodology involved storing detailed results of applying each algorithm to each image in the data sets, allowing researchers to study in depth the strengths and weaknesses of each algorithm. The text locating contest was the only one to have any entries. We give a brief description of each entry, and present the results of this contest, showing cases where the leading entries succeed and fail. We also describe an algorithm for combining the outputs of the individual text locaters, and show how the combination scheme improves on any of the individual systems

ICDAR 2003 robust reading competitions: entries, results and future directions

This paper describes the robust reading competitions for ICDAR 2003. With the rapid growth in research over the last few years on recognizing text in natural scenes, there is an urgent need to establish some common benchmark datasets, and gain a clear understanding of the current state of the art. We use the term robust reading to refer to text images that are beyond the capabilities of current commer-cial OCR packages. We chose to break down the robust reading problem into three sub-problems, and run competitions for each stage, and also a competition for the best overall system. The sub-problems we chose were text locating, character recognition and word recognition. By breaking down the problem in this way, we hoped to gain a better under-standing of the state of the art in each of the sub-problems. Furthermore, our methodology involved storing detailed results of applying each algorithm to each image in the data sets, allowing researchers to study in depth the strengths and weaknesses of each algorithm. The text locating contest was the only one to have any entries. We give a brief description of each entry, and present the results of this contest, showing cases where the leading entries succeed and fail. We also de-scribe an algorithm for combining the outputs of the individual text locaters, and show how the combination scheme improves on any of the individual systems