Contribution: In this article, the authors present findings and insights on the efficacy of using an educational block-based programming (BBP) environment--Blocks4DS, to teach the binary search tree (BST). Background: For a decade, BBP environments have been a hot topic in the computer science education (CSEd) community to promote interactive…

Biochemistry is a data-heavy discipline, yet teaching students to work with large datasets is absent from many undergraduate Biochemistry programs. Ensuring that future generations of students are confident in tackling problems using big data first requires that educators become comfortable teaching big data skills. The activity described herein…

Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived…

For undergraduate students to be prepared for graduate school and industry, it is imperative that they understand how to merge the theoretical insights gleaned through their undergraduate education with the raw data sets acquired through materials analysis. Thus, the ability to implement data analysis is a vital skill that students should develop.…

The quantitative evaluation of experimental data and their graphical presentation are integral to teaching and research in chemistry and the life sciences. Data are commonly fitted to physical models, which in all but the simplest cases are expressed as nonlinear mathematical functions. To facilitate data evaluation in both teaching and research…

Biostatistics courses are integral to many undergraduate biology programs. Such courses have often been taught using point-and-click software, but these programs are now seldom used by researchers or professional biologists. Instead, biology professionals typically use programming languages, such as R, which are better suited to analyzing complex…

Intelligent Tutoring Systems (ITSs) have shown success in the domain of programming, in part by providing customized hints and feedback to students. However, many popular novice programming environments still lack these intelligent features. This is due in part to their use of open-ended programming assignments, which are difficult to support with…

While student data systems are nothing new and most educators have been dealing with student data for many years, learning analytics has emerged as a new concept to capture educational big data. Learning analytics is about better understanding of the learning and teaching process and interpreting student data to improve their success and learning…

In various research areas, the availability of open datasets is considered as key for research and application purposes. These datasets are used as benchmarks to develop new algorithms and to compare them to other algorithms in given settings. Finding such available datasets for experimentation can be a challenging task in technology enhanced…

Learning objects (LOs) are digital or non-digital entities used for learning, education or training commonly stored in repositories searchable by their associated metadata. Unfortunately, based on the current standards, such metadata is often missing or incorrectly entered making search difficult or impossible. In this paper, we investigate…

The Securities and Exchange Commission (SEC) has recently announced a proposal that will require all public companies to report their financial data in Extensible Business Reporting Language (XBRL). XBRL is an extension of Extensible Markup Language (XML). Moving to a standard reporting format makes it easier for organizations to report the…

Business intelligence derived from data warehousing and data mining has become one of the most strategic management tools today, providing organizations with long-term competitive advantages. Business school curriculums and popular database textbooks cover data warehousing, but the examples and problem sets typically are small and unrealistic. The…

The ability to predict a student's performance could be useful in a great number of different ways associated with university-level learning. In this paper, a grammar guided genetic programming algorithm, G3P-MI, has been applied to predict if the student will fail or pass a certain course and identifies activities to promote learning in a…

This paper describes an empirical study that investigated the knowledge that Computer Science students have about the extent of their own previous learning. The study compared self-generated estimates of performance with actual performance on a data structures quiz taken by undergraduate students in courses requiring data structures as a…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…