The aim of this study is to compare the master's (MA) theses in Türkiye (TR) and Finland (FIN) published between 2015-2019. A total of 765 theses were analysed in terms of year, discipline, methodological approach, research method, didactic foci, data collection tool, target group, and sample size. The results showed that FIN theses grounded on…

Integration of computational data science (CDS) into the university curriculum offers several advantages for students, faculty and the institution. This article discusses the benefits to students of introducing CDS into the university curriculum with a focus on developing skills in cheminformatics, data analysis, structure--activity relationships,…

The heterogeneous data acquired by educational institutes about students' careers (e.g., performance scores, course preferences, attendance record, demographics, etc.) has been a source of investigation for Educational Data Mining (EDM) researchers for over two decades. EDM researchers have primarily focused on course-specific data analyses of…

When pressing societal challenges (e.g., COVID-19, access to clean water) are sidelined in science classrooms, science education fails to leverage the knowledge and experiences of minoritized students in school, thus reproducing injustices in society. Our conceptual framework for "justice-centered STEM education" engages all students in…

Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise…

A common recommendation in critiques of datafication in education is for greater conversation between the two sides of the (critical) divide -- what might be characterised as sceptical social scientists and (supposedly) more technically-minded and enthusiastic data scientists. This article takes the form of a dialogue between two academics…

Interdisciplinarity is becoming increasingly important in education. With the rapidly evolving job market, an interdisciplinary education can prepare students for the flexibility and broad knowledge base required to adapt. At the University of Pisa, we recognized the value of an interdisciplinary educational environment during our participation in…

Effective mining of data from online submission systems offers the potential to improve educational outcomes by identifying student habits and behaviours and their relationship with levels of achievement. In particular, it may assist in identifying students at risk of performing poorly, allowing for early intervention. In this paper we investigate…

As information technology continues to evolve rapidly, programming skills become increasingly crucial. To be able to construct superb programming skills, the training must begin before college or even senior high school. However, when developing comprehensive training programmers, the learning and teaching processes must be considered. In order to…

For this report, the authors analyzed federal government data to look at gender, racial and ethnic diversity among those employed in and earning degrees in science, technology, engineering and math (STEM). Analysis of the STEM workforce is based solely on occupation, using data from the U.S. Census Bureau's 1990 and 2000 U.S. decennial censuses…

BHEF has achieved particular success in operationalizing its National Higher Education and Workforce Initiative (HEWI) through regional initiatives in data science and analytics (DSA). Leveraging its membership of corporate CEOs, university presidents and government agency leaders, BHEF seeded new undergraduate pathways in DSA at Case Western…

Intelligent tutoring systems can support students in solving multi-step tasks by providing hints regarding what to do next. However, engineering such next-step hints manually or via an expert model becomes infeasible if the space of possible states is too large. Therefore, several approaches have emerged to infer next-step hints automatically,…

Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management…

What do different research methods and approaches "do" in practice? The article seeks to discuss this point by drawing upon socio-material research approaches and empirical examples taken from the early stages of an extensive case study on an interdisciplinary project between two multidisciplinary fields of study, education and computer…

Most educational institutions adopted the hybrid teaching mode through learning management systems. The logging data/clickstream could describe learners' online behavior. Many researchers have used them to predict students' performance, which has led to a diverse set of findings, but how to use insights from captured data to enhance learning…