This report summarizes the outcomes of the second international workshop on Data Systems Education: Bridging Education Practice with Education Research (DataEd '23). The workshop was held in conjunction with the SIGMOD '23 conference in Seattle, USA on June 23, 2023. The aim of the workshop was to provide a dedicated venue for presenting and and discussing data management systems education experiences and research by bringing together the database and the computing education research communities to share findings, to crosspollinate perspectives and methods, and to shed light on opportunities for mutual progress in data systems education. The program featured two keynote talks, eight research paper presentations, and a discussion session. In this report, we present the workshop's main results, observations, and emerging research directions.@en

In recent years, database education has been receiving more attention, with research in various directions such as the development of tools for education, the analysis of students’ homework, and the exploration of misconceptions. Misconceptions are mistakes in student reasoning that lead to errors during problem-solving. Recent work has documented misconceptions and errors in SQL. In this study we test the prevalence of several of these misconceptions through a multiple-choice questionnaire, to see if they hold on a larger, more diverse, student population. We found that all misconceptions are held to some extent, with prevalence scores ranging from one to fifty-two percent of the student population. Additionally, we have uncovered previously unidentified areas of struggle, allowing us to identify new misconceptions.@en

This report summarizes the outcomes of the first international workshop on Data Systems Education: Bridging Education Practice with Education Research (DataEd '22). The workshop was held in conjunction with the SIGMOD '22 conference in Philadelphia, USA on June 17, 2022. The aim of the workshop was to provide a dedicated venue for presenting and and discussing data management systems education experiences and research by bringing together the database and the computing education research communities to share findings, to crosspollinate perspectives and methods, and to shed light on opportunities for mutual progress in data systems education. The program featured two keynote talks, ten research paper presentations, a discussion session, and an industry panel discussion. In this report, we present the workshop's main results, observations, and emerging research directions.

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Querying a relational database is typically taught in practice by using an exercise database. Such databases may be simple toy examples or elaborate and complex schemas that mimic the real world. Which of these are preferable for students is yet unknown. Research has shown that while more complex exercise databases may hinder learning, they also benefit student engagement, as more complex databases are seen as more realistic. In our mixed-methods study, we explore what aspects of an exercise database contribute to student engagement in database education. To gain insight into what students would deem engaging, we asked 56 students to design, implement, and reflect on engaging databases for database education. The results imply that students are engaged by highly diverse yet easily understood database business domains, relatively simple database structures, and conceivable yet seemingly realistic amounts of data. The results challenge some previous study results while supporting approaches found in some textbooks, and provide guidelines and inspiration for educators designing exercise databases for querying and introducing relational database concepts.

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Several educational studies have argued for the contextualization of assignments, i.e., for providing a context or a story instead of an abstract or symbolic problem statement. Such contextualization may have beneficial effects such as higher student engagement and lower dropout rates. In the domain of database education, textbooks and educators typically provide an example database for context. These are then used to introduce key concepts related to database design, and to illustrate querying. However, it remains unstudied what kinds of database contexts are engaging for novices. In this paper, we study which aspects of database domain and complexity students find engaging through student reflections on a database creation assignment. We identify six factors regarding engaging domains, and five factors for engaging complexity. The main factor for domain-related engagement was Personal interest, the main factor for complexity engagement was Matching information requirements. Our findings can help database educators and book authors to design engaging exercise databases targeted for novices.

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Interest in data systems education is increasing, especially with the rise in demand for well-trained and re-trained data scientists. The database and the computing education research communities have complementary perspectives and experiences to share with each other. The DataEd workshop is organized as a dedicated venue for these communities to come together to share findings, cross-pollinate perspectives and methods, and shed light on opportunities for mutual progress in data systems education. In the DataEd workshop, we will present and discuss data management systems education experiences and research via keynotes and paper and poster presentations.

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Prior studies in the Computer Science education literature have illustrated that novices make many mistakes in composing SQL queries. Query formulation proves to be difficult for students. Only recently, some headway was made towards understanding why SQL leads to so many mistakes, by uncovering student misconceptions. In this article, we shed new light on SQL misconceptions by analyzing the hypotheses of SQL experts on the causes of student errors. By examining the experts' perceptions, we draw on their understanding of students' misconceptions and on their experiences with studying and teaching SQL. For our analysis, we chose the Policy Delphi, a questionnaire instrument specifically designed for gathering opinions and evidence. Through a two-round process, our nineteen participants proposed and voted on underlying causes for SQL errors which resulted in a set of hypotheses per error. Our main contribution to this article is this new set of possible misconceptions. With them, we can design more complete educational approaches to address misconceptions underlying SQL errors made by students, leading to more effective SQL education.

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