43,807 research outputs found

    Motivation and Grade Gap Related to Gender in a Programming Course

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    In a programming course at Uppsala University, Sweden, there has been a significant difference between the average grade of female students and that of their male counterparts. This work in progress presents some results and potential solutions related to this problem, and makes them explicit

    Links between the personalities, styles and performance in computer programming

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    There are repetitive patterns in strategies of manipulating source code. For example, modifying source code before acquiring knowledge of how a code works is a depth-first style and reading and understanding before modifying source code is a breadth-first style. To the extent we know there is no study on the influence of personality on them. The objective of this study is to understand the influence of personality on programming styles. We did a correlational study with 65 programmers at the University of Stuttgart. Academic achievement, programming experience, attitude towards programming and five personality factors were measured via self-assessed survey. The programming styles were asked in the survey or mined from the software repositories. Performance in programming was composed of bug-proneness of programmers which was mined from software repositories, the grades they got in a software project course and their estimate of their own programming ability. We did statistical analysis and found that Openness to Experience has a positive association with breadth-first style and Conscientiousness has a positive association with depth-first style. We also found that in addition to having more programming experience and better academic achievement, the styles of working depth-first and saving coarse-grained revisions improve performance in programming.Comment: 27 pages, 6 figure

    Female Under-Representation in Computing Education and Industry - A Survey of Issues and Interventions

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    This survey paper examines the issue of female under-representation in computing education and industry, which has been shown from empirical studies to be a problem for over two decades. While various measures and intervention strategies have been implemented to increase the interest of girls in computing education and industry, the level of success has been discouraging. The primary contribution of this paper is to provide an analysis of the extensive research work in this area. It outlines the progressive decline in female representation in computing education. It also presents the key arguments that attempt to explain the decline and intervention strategies. We conclude that there is a need to further explore strategies that will encourage young female learners to interact more with computer educational games

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    Summer Snapshot: Exploring the Impact of Higher Achievement's Year-Round Out-of-School-Time Program on Summer Learning

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    Assesses the impact of a multiyear, intensive, academically focused OST program for motivated but underserved middle school students on test scores, summer program participation, and summer learning loss. Examines contributing factors and implications

    Responsible research and innovation in science education: insights from evaluating the impact of using digital media and arts-based methods on RRI values

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    The European Commission policy approach of Responsible Research and Innovation (RRI) is gaining momentum in European research planning and development as a strategy to align scientific and technological progress with socially desirable and acceptable ends. One of the RRI agendas is science education, aiming to foster future generations' acquisition of skills and values needed to engage in society responsibly. To this end, it is argued that RRI-based science education can benefit from more interdisciplinary methods such as those based on arts and digital technologies. However, the evidence existing on the impact of science education activities using digital media and arts-based methods on RRI values remains underexplored. This article comparatively reviews previous evidence on the evaluation of these activities, from primary to higher education, to examine whether and how RRI-related learning outcomes are evaluated and how these activities impact on students' learning. Forty academic publications were selected and its content analysed according to five RRI values: creative and critical thinking, engagement, inclusiveness, gender equality and integration of ethical issues. When evaluating the impact of digital and arts-based methods in science education activities, creative and critical thinking, engagement and partly inclusiveness are the RRI values mainly addressed. In contrast, gender equality and ethics integration are neglected. Digital-based methods seem to be more focused on students' questioning and inquiry skills, whereas those using arts often examine imagination, curiosity and autonomy. Differences in the evaluation focus between studies on digital media and those on arts partly explain differences in their impact on RRI values, but also result in non-documented outcomes and undermine their potential. Further developments in interdisciplinary approaches to science education following the RRI policy agenda should reinforce the design of the activities as well as procedural aspects of the evaluation research

    An Examination of High School Student Success In online Learning

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    Online learning education in K-12 districts across the United States has continually grown in the United States (Barbour & Kennedy, 2014). Research from online course studies of adult learners suggests several factors influence successful course completion. However, discrepancies exist as to whether the findings can be generalized to 9-12 E-learning students. Literature exploring the learner characteristics associated with successful secondary students in online studies is limited. The research on online education identifies students who are highly motivated, high-achieving, and self-starting as those that are most likely to complete online courses successfully (Barbour & Reeves, 2009). High schools across Ohio employ online learning education to support graduation pathways of all diverse learners. This study explored differences that exist between subgroups when learner characteristics in the online learning environment are compared with course completion percentage. Archival records of students who had attempted credits towards high school graduation through online learning coursework were collected from four participating school districts. The sample for this study was drawn from inner-ring suburban school districts in Northeast Ohio with an urban boundary. The subjects of this study included 214 high school students, grades 9-12, enrolled in online courses pursuing credits toward high school completion. vi Standard linear regression was calculated to predict course completion percentages based on gender, race, grade level, and grade level according to expected age as the independent variables. The results of this study provided evidence related to online learner characteristics that exist in digital learning environments. Positive results indicate students in upper-grade levels, and female students are more likely to be successful in earning credits in virtual learning environments. The analysis produced favorable outcomes for students who are at grade level to complete online courses successfully. Non-Black students are more likely to complete online courses when compared to Black students based on the findings of this research. The implications of this investigation have practical significance for school districts implementing virtual learning options across the curriculum. It is essential to continue exploring the relationship between individual learner characteristics and course completion for high school E-learners to support online education as a viable instructional pedagogy

    A Multi-Gene Genetic Programming Application for Predicting Students Failure at School

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    Several efforts to predict student failure rate (SFR) at school accurately still remains a core problem area faced by many in the educational sector. The procedure for forecasting SFR are rigid and most often times require data scaling or conversion into binary form such as is the case of the logistic model which may lead to lose of information and effect size attenuation. Also, the high number of factors, incomplete and unbalanced dataset, and black boxing issues as in Artificial Neural Networks and Fuzzy logic systems exposes the need for more efficient tools. Currently the application of Genetic Programming (GP) holds great promises and has produced tremendous positive results in different sectors. In this regard, this study developed GPSFARPS, a software application to provide a robust solution to the prediction of SFR using an evolutionary algorithm known as multi-gene genetic programming. The approach is validated by feeding a testing data set to the evolved GP models. Result obtained from GPSFARPS simulations show its unique ability to evolve a suitable failure rate expression with a fast convergence at 30 generations from a maximum specified generation of 500. The multi-gene system was also able to minimize the evolved model expression and accurately predict student failure rate using a subset of the original expressionComment: 14 pages, 9 figures, Journal paper. arXiv admin note: text overlap with arXiv:1403.0623 by other author

    Testing the Impact of Higher Achievement's Year-Round Out-of-School-Time Program on Academic Outcomes

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    Presents findings from a multiyear evaluation of an intensive long-term OST program's effect on low-income middle school students' academic performance, attitudes, and behaviors. Outlines implications for financially strapped districts
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