Software Engineering Competence Remote Evaluation Process Model

Jusas, Vacius; Nicolás, Joaquín; Misnevs, Boriss

doi:10.22364/bjmc.2017.5.3.06

Cited by 3 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The multidisciplinarity of data science offers options as a path for specialization, such as data engineering, machine learning, and algorithm development. In addition, data science serves multiple fields and there are key players and different career pathways in each field (Misnevs & Yatskiv, 2016).…”

Section: Learning Pathways (36% Of Th E Papers)mentioning

confidence: 99%

Data Science Education – A Scoping Review

2023

View full text Add to dashboard Cite

Aim/Purpose: This study aimed to evaluate the extant research on data science education (DSE) to identify the existing gaps, opportunities, and challenges, and make recommendations for current and future DSE. Background: There has been an increase in the number of data science programs especially because of the increased appreciation of data as a multidisciplinary strategic resource. This has resulted in a greater need for skills in data science to extract meaningful insights from data. However, the data science programs are not enough to meet the demand for data science skills. While there is growth in data science programs, they appear more as a rebranding of existing engineering, computer science, mathematics, and statistics programs. Methodology: A scoping review was adopted for the period 2010–2021 using six scholarly multidisciplinary databases: Google Scholar, IEEE Xplore, ACM Digital Library, ScienceDirect, Scopus, and the AIS Basket of eight journals. The study was narrowed down to 91 research articles and adopted a classification coding framework and correlation analysis for analysis. Contribution: We theoretically contribute to the growing body of knowledge about the need to scale up data science through multidisciplinary pedagogies and disciplines as the demand grows. This paves the way for future research to understand which programs can provide current and future data scientists the skills and competencies relevant to societal needs. Findings: The key results revealed the limited emphasis on DSE, especially in non-STEM (Science, Technology, Engineering, and Mathematics) disciplines. In addition, the results identified the need to find a suitable pedagogy or a set of pedagogies because of the multidisciplinary nature of DSE. Further, there is currently no existing framework to guide the design and development of DSE at various education levels, leading to sometimes inadequate programs. The study also noted the importance of various stakeholders who can contribute towards DSE and thus create opportunities in the DSE ecosystem. Most of the research studies reviewed were case studies that presented more STEM programs as compared to non-STEM. Recommendations for Practitioners: We recommend CRoss Industry Standard Process for Data Mining (CRISP-DM) as a framework to adopt collaborative pedagogies to teach data science. This research implies that it is important for academia, policymakers, and data science content developers to work closely with organizations to understand their needs. Recommendation for Researchers: We recommend future research into programs that can provide current and future data scientists the skills and competencies relevant to societal needs and how interdisciplinarity within these programs can be integrated. Impact on Society: Data science expertise is essential for tackling societal issues and generating beneficial effects. The main problem is that data is diverse and always changing, necessitating ongoing (up)skilling. Academic institutions must therefore stay current with new advances, changing data, and organizational requirements. Industry experts might share views based on their practical knowledge. The DSE ecosystem can be shaped by collaborating with numerous stakeholders and being aware of each stakeholder’s function in order to advance data science internationally. Future Research: The study found that there are a number of research opportunities that can be explored to improve the implementation of DSE, for instance, how can CRISP-DM be integrated into collaborative pedagogies to provide a fully comprehensive data science curriculum?

show abstract

Section: Learning Pathways (36% Of Th E Papers)mentioning

confidence: 99%

Data Science Education – A Scoping Review

2023

View full text Add to dashboard Cite

show abstract

“…Our gamified course was implemented in Moodle [7]-a popular platform commonly used by universities to support teaching as well as learning [8]. For enabling the required gamification elements, two Moodle plugins were deployed-H5P [9] and Level up [10].…”

Section: Introductionmentioning

confidence: 99%

Game Elements towards More Sustainable Learning in Object-Oriented Programming Course

2022

Self Cite

View full text Add to dashboard Cite

Gamification of education is considered to have the capacity to increase students’ engagement in a learning process; to drive learning and skills acquisition; and creates changes for more sustainable behavior. Sustainable behavior is especially important in studying the initial courses at a university. Object-oriented programming (OOP) is such a course in the studies for a programmer’s diploma. We applied four elements of gamification: experience points, interactive content, local team, and global team. A local team is dedicated specifically to the OOP course, but all other game elements can be applied to any course. The course was implemented in a Moodle platform, where two additional plugins for experience points and interactive content were employed. Research using the implemented gamified course in the teaching process was carried out during the fall semester in 2020 and results compared to two previous non-gamified course years. A statistically insignificant increase in the mean grade was observed. Nevertheless, the gamified course resulted in a 7% decrease in the number of students who had to retake the OOP course compared to the year 2019. The gamified course also resulted in a drastic decrease in the number of students requiring a second attempt to pass the course’s exam. The obtained results demonstrate that the gamification of OOP course resulted in more sustainable behavior of the students. Based on the results of students’ questionnaires, we highly recommend using global team game element as it showed a positive effect on students’ engagement when the number of participating students is large.

show abstract