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Direct linkAndré Coners; Benjamin Matthies; Carolin Vollenberg; Julian Koch – Journal of Statistics and Data Science Education, 2025
The proficient handling of data can undoubtedly be regarded as a key skill for the future. However, the need for data competencies is not limited to traditional professions in the information technology environment but is rather necessary across industries and work fields. Consequently, there is a call to integrate such Data Literacy and Data…
Descriptors: Statistics Education, Higher Education, Information Science Education, Computer Science Education
Download full textWilliamson, Joanna; Vidal Rodeiro, Carmen – Cambridge University Press & Assessment, 2022
The transition from Key Stage 4 (KS4) to post-16 education marks a shift from a broad programme of study (around 8-10 subjects) to a narrower programme (usually 1-4 subjects). Within the constraints of course availability and entry criteria, students must make important choices. Students' post-16 pathways matter because different subjects as well…
Descriptors: Class Rank, Exit Examinations, Postsecondary Education, Foreign Countries
Gill, Tim – Cambridge Assessment, 2020
The aim of this research was to determine the standard that was effectively applied to General Certificates of Secondary Education (GCSE) and A levels in June 2020 by the decision to accept the maximum of the centre-assessed grade and the calculated grade. The data for this analysis came from the results tables for GCSEs and A levels in 2019 and…
Descriptors: Academic Standards, Grades (Scholastic), Secondary Education, Exit Examinations
Rotermund, Susan; Burke, Amy – National Science Foundation, 2021
Elementary and secondary science, technology, engineering, and mathematics (STEM) education is the foundation for students' entry into postsecondary STEM majors as well as a wide variety of STEM occupations. Proficiency in STEM fields is vital to economic growth and international competitiveness and important for all citizens in an increasingly…
Descriptors: Elementary Education, Secondary Education, STEM Education, Educational Indicators
Mustapha, Aida; Samsudin, Noor Azah; Arbaiy, Nurieze; Mohammed, Rozlini; Hamid, Isredza Rahmi – Turkish Online Journal of Educational Technology - TOJET, 2016
In programming, one problem can usually be solved using different logics and constructs but still producing the same output. Sometimes students get marked down inappropriately if their solutions do not follow the answer scheme. In addition, lab exercises and programming assignments are not necessary graded by the instructors but most of the time…
Descriptors: Programming, Computer Science Education, Scoring Rubrics, Grading
Trapani, Josh; Hale, Katherine – National Science Foundation, 2019
The report provides a portrait of science and engineering (S&E) higher education in the United States, including trends over time and comparisons with other nations. S&E fields, as defined in this report, include astronomy, chemistry, physics, atmospheric sciences, earth sciences, ocean sciences, mathematics and statistics, computer…
Descriptors: Higher Education, Educational Indicators, Psychology, Biological Sciences
OECD Publishing (NJ1), 2012
When you think of someone who is an engineer, do you imagine a man or a woman wearing a hardhat? How about when you imagine a teacher standing in front of a class of schoolchildren? If you answer "a man" to the first question, and "a woman" to the second, there's probably a reason. And the reason is simply that more men than…
Descriptors: Careers, Females, Labor Market, Engineering
Sikora, Joanna; Pokropek, Artur – OECD Publishing (NJ1), 2011
This paper provides a comprehensive overview of adolescent career plans reported in PISA 2006. Its main focus is on the differences in the status and area of employment expected by girls and boys in high school. In almost all countries, girls lead boys in their interest in non-manual, high status professional occupations. This can be seen as a…
Descriptors: High School Students, Student Attitudes, Females, Foreign Countries
Hefford, Nigel A.; Keef, Stephen P. – Journal of Educational Computing Research, 2004
This analysis of gender performance differences in a first-level New Zealand university course in computer science is predicated on the model of academic ability proposed by Charles Spearman, the eminent educational psychologist and statistician. The regression model is based on the theoretical constructs of general academic ability and specific…
Descriptors: Foreign Countries, Academic Ability, Multiple Regression Analysis, Evaluation Methods
Zikopoulos, Marianthi, Ed. – 1993
This publication presents, in narrative and tabular formats, the findings of a 1991-92 survey of foreign students attending institutions of higher education in the United States, including information on nationalities, academic levels, and fields of study. The first of four chapters describes the survey effort and its relation to a sister project…
Descriptors: Business Education, College Students, Computer Science Education, Engineering Education
National Science Foundation, Washington, DC. Div. of Science Resources Studies. – 1982
Detailed statistical tables on federal funds for research and development (R&D) activities are provided in this document. Tables are organized into the following sections: research, development, and R&D plant; R&D- agency, character of work, and performer; total research- agency, performer, and field of science; basic research- agency,…
Descriptors: Colleges, Computer Science, Costs, Development
Collis, Betty; Muir, Walter – Canadian Journal of Higher Education, 1986
A national survey examined the extent of offerings of courses on the uses of computers in instruction by education faculties. Results showed extensive offerings in both undergraduate and graduate programs, but considerable diversity in content and sequence and no consistency in requirements for computer-related experience before certification.…
Descriptors: Computer Assisted Instruction, Computer Literacy, Computer Science, Curriculum Design
Jacobs, Johan – 1996
This document, which is based on data gathered during a September 1994 mail survey of 215,284 South African graduates that elicited a total response rate of 18.3%, details the remuneration of graduates (as of July 1, 1994) in the following occupational categories: physical science; geological science; mathematical; computer science; chemical…
Descriptors: Agricultural Education, Agricultural Occupations, Compensation (Remuneration), Computer Science Education
