One of the biggest challenges that higher learning institutions face today is to improve the quality of managerial decisions. The managerial decision making process becomes more complex as the complexity of educational entities increase. Educational institute seeks more efficient technology to better manage and support decision making procedures or assist them to set new strategies and plan for a better management of the current processes. One way to effectively address the challenges for improving the quality is to provide new knowledge related to the educational processes and entities to the managerial system. This knowledge can be extracted from historical and operational data that reside in the educational organization's databases using the techniques of data mining technology. Data mining techniques are analytical tools that can be used to extract meaningful knowledge from large data sets. This paper presents the capabilities of data mining in the context of higher educational system by i) proposing an analytical guideline for higher education institutions to enhance their current decision processes, and ii) applying data mining techniques to discover new explicit knowledge which could be useful for the decision making processes.
Automatic assessment of programming exercises is typically based on testing approach. Most automatic assessment frameworks execute tests and evaluate test results automatically, but the test data generation is not automated. No matter that automatic test data generation techniques and tools are available.
We have researched how the Java PathFinder software model checker can be adopted to the specific needs of test data generation in automatic assessment. Practical problems considered are: how to derive test data directly from students' programs (i.e., without annotation) and how to visualize and how to abstract test data automatically for students? Interesting outcomes of our research are that with minor refinements generalized symbolic execution with lazy initialization (a test data generation algorithm implemented in PathFinder) can be used to construct test data directly from students' programs without annotation, and that intermediate results of the same algorithm can be used to provide novel visualizations of the test data.
The paper describes some possible ways how to improve Olympiads in Informatics. Tasks in Olympiads are small models of programming tasks in software industry and in the limited amount of competition time contestants need to complete several software production phases - coding, testing and debugging. Currently, only coding effort is adequately graded, but grading of other activities may be improved. Ways to involve contestants in overall testing process are investigated and ways to improve solution debugging process are described. Possible scoring schemas are discussed. In International Olympiads tasks with real numbers are quite rare. Possible reasons are investigated and a way how to return such tasks back to competition arena is suggested.
Computer simulations seem to be one of the most effective ways to use computers in physics education. They encourage students to carry out the processes used in physics research: to question, predict, hypothesise, observe, interpret results etc. Their effective use requires an availability of appropriate teaching resources fitting secondary schools curricula.
This paper presents a set of computer simulations that cover the curriculum area of Mechanics and are designed to fit directly to curricula and textbooks used at Slovak grammar schools. All simulations are accompanied by brief instructions for teachers, including suggestions for learning activities and problem tasks for students. Some of them are designed as virtual laboratories.
The developed simulations were tested with a group of secondary school students and evaluated also by groups of future and practising physics teachers. The paper presents and discusses findings and conclusions from the both runs of the testing.
Our future society will be different from that we have known in the last fifty years. Futurists foresee that in the near couple decades the world's community will traverse through a period of rapid technological innovations that will change the foundations of society as we used to know it (Tapscott, 1997; Wallace, 1999; Borgmann; 1999). Changes will engulf all aspects of life (Gleick, 1999). These changes will have great impact on society, work, culture and art. People will have to innovate or evaporate (Higgins, 1995). They will have to adapt continuously to never-ending permutations and engage in a never-ending adaptation.
It makes sense, therefore, to assume that the graduates of today's schooling will need a different set of cognitive and learning skills reflecting the profound change that they will encounter. This paper traces the basic nature of future society and proposes a relevant taxonomy of future cognitive skills that will provide our students with appropriate tools to succeed in the future. We have used Bloom's taxonomy as a working ground and expanded his categories to reflect the needs of the future. This paper suggests an additional cognitive category to add to our teaching procedures named melioration, which we believe, is not addressed in today's curriculum.