Humans possess a remarkable ability to recognise both simple patterns such as shapes and handwriting and very complex patterns such as faces and landscapes. To investigate one small aspect of human pattern recognition, in this study participants position lines of "best fit" to two-dimensional scatter plots of data. The study investigates…

Classroom level data driven decision-making (DDDM) involves the use of data to identify patterns of performance that reveal students' academic strengths and weaknesses relative to established learning goals, and the planning of instructional practices to support academic success for all students. Although DDDM is not a new paradigm in education,…

The success of data mining relies on the availability of high quality data. To ensure quality data mining, effective information sharing between organizations becomes a vital requirement in today's society. Since data mining often involves sensitive information of individuals, the public has expressed a deep concern about their privacy.…

The 5th International Conference on Educational Data Mining (EDM 2012) is held in picturesque Chania on the beautiful Crete island in Greece, under the auspices of the International Educational Data Mining Society (IEDMS). The EDM 2012 conference is a leading international forum for high quality research that mines large data sets of educational…

This paper describes three spreadsheet exercises demonstrating the nature and frequency of type I errors using random number generation. The exercises are designed specifically to address issues related to testing multiple relations using correlation (Demonstration I), t tests varying in sample size (Demonstration II) and multiple comparisons…

As educators, we need to stop fearing data and embrace its power. This article discusses how classroom teachers can design, implement, and analyze longitudinal assessments to diagnose issues related to student achievement and meet the demands of our evolving data-driven educational culture. Practical advice on exam production and data analysis…

In education, data-driven decision making is a buzz word that has come to mean collecting absolutely as much data as possible on everything from attendance to zero tolerance, and then having absolutely no idea what to do with it. Most educational organizations with a plethora of data usually call in a data miner, or evaluator, to make some sense…

Teachers and students increasingly enjoy unprecedented access to abundant web resources and digital libraries to enhance and enrich their classroom experiences. However, due to the distributed nature of such systems, conventional educational research methods, such as surveys and observations, provide only limited snapshots. In addition,…

The phenomenological study explored the lived experiences and perceptions of a purposive sample of 20 IT professionals (managers, engineers, administrators, and analysts) in the state of Virginia, Texas, and Washington DC. The focus of this research study was to learn the perceptions of IT professionals who are or once were in a decision-making…

A basic and classical assumption in the machine learning research area is "randomness assumption" (also known as i.i.d assumption), which states that data are assumed to be independent and identically generated by some known or unknown distribution. This assumption, which is the foundation of most existing approaches in the literature, simplifies…

This study investigated an innovative approach of program evaluation through analyses of student learning logs, demographic data, and end-of-course evaluation surveys in an online K-12 supplemental program. The results support the development of a program evaluation model for decision making on teaching and learning at the K-12 level. A case study…

The data illustrate outliers that are not mistakes and not observations that are unusually high or low. The reasons for them are all interesting historically. They illustrate that "outliers" need not be errors but may instead be particularly interesting cases. The data also illustrate that different data displays may differ in their ability to…

A common approach used for introducing algebra to young adolescents is an exploration of visual patterns and expressing these patterns as functions and algebraic expressions. Past research has indicated that many adolescents experience difficulties with this approach. This paper explores teaching actions and thinking that begins to bridge many of…

Two experiments demonstrate that 10- and 13-year-olds can learn to detect interactive patterns in data. Results also indicate the advantages of creating formal models of solution strategies and using them as a basis for instructional procedures. (Author/DEP)

This study addresses the question: "To what extent are teacher assigned subject specific grades useful for data driven decision making in schools?" Recently, schools have been urged to bring teachers and school leaders together around student-level data in an effort to increase dialogue, collaboration and professional communities to…