Measuring efficiency of teaching process and faculty in transition states using DEA analysis

U ovoj studiji koristi se DEA analiza, radi ispitivanja relativne učinkovitosti nastavnog procesa studiranja na najvećem fakultetu u Srbiji: Analiza je provedena tijekom ak. godine 2013/14. Studijom je obuhvaćeno 863 diplomirana studenta koji su završili studije na 13 studijskih programa. Ulazne varijable koje su korištene u ovoj analizi su srednja ocjena iz srednje škole i broj osvojenih bodova na kvalifikacijkom ispitu, a izlazne varijable prosječne ocjene ostvarene tijekom studija kao i duljina studiranja. Naš pristup integrira DEA - Data Envelopment Analysis i statističku analizu varijanci, a u cilju razvijanja proširenog modula za mjerenje učinkovitosti nastavnog procesa. Mjerenje učinkovitosti visokoškolskih ustanova prikazat ćemo primjenom DEA analize u mjerenju učinkovitosti svakog studenta posebno i kao mjerenje učinkovitosti studenata određenih studijskih programa, odnosno fakulteta. Učinkovitost studiranja koja se mjeri za svakog studenta pojedinačno je preko 70%, a kada se radi o mjerenju učinkovitosti i studijskih programa učinkovitost je preko 85%. Mjerenje učinkovitosti studiranja je napravljeno na primjeru fakulteta koji u svom sustavu ima 13 departmana i 17 studijskih programa osnovnih akademskih studija. Kako po zakonu Republike Srbije ne postoje integrirana sveučilišta već je svaki fakultet zasebna ustanova, svaki departman Fakulteta tehničkih nauka se možemo posmatrati kao zaseban fakultet, a sam fakultet kao sveučilište. Na taj način ovom analizom možemo prikazati mjerenje učinkovitosti sveučilišta.The aim of this study is to examine the relative efficiency of the teaching process (study) at the largest faculty in Serbia based on enveloped data (DEA analysis). The analysis was conducted in the 2013/14 academic year and includes 863 graduate students who have completed their studies in 13 academic programs. Input variables used in this analysis were the average secondary school grade and the number of scores earned on the entrance exam, while the output variables were the average grade achieved during the study and the length of study. Our approach integrates the DEA (Data Envelopment Analysis) approach and the statistical analysis of variance with the aim of developing an expanded model for measuring the efficiency of the teaching process. Measurements of efficiency of higher education institutions will be presented using the DEA analysis in measuring the efficiency of each student individually and measuring the efficiency of students of specific study programs or faculties. Efficiency of studying which is measured for each student individually is over 70%, while the efficiency of study programs is over 85%. The efficiency of studying was measured on the example of a faculty consisting of 13 departments and 17 study programs of basic academic studies. As per the law there are no integrated universities in the Republic of Serbia but each faculty is a separate institution, each department of the Faculty of Technical Sciences can be considered a separate faculty, while the faculty itself can be considered a university. Thus, this analysis can describe the measurement of efficiency of the university

A Rewriting Framework for Activities Subject to Regulations

Activities such as clinical investigations or financial processes are subject to regulations to ensure quality of results and avoid negative consequences. Regulations may be imposed by multiple governmental agencies as well as by institutional policies and protocols. Due to the complexity of both regulations and activities there is great potential for violation due to human error, misunderstanding, or even intent. Executable formal models of regulations, protocols, and activities can form the foundation for automated assistants to aid planning, monitoring, and compliance checking. We propose a model based on multiset rewriting where time is discrete and is specified by timestamps attached to facts. Actions, as well as initial, goal and critical states may be constrained by means of relative time constraints. Moreover, actions may have non-deterministic effects, that is, they may have different outcomes whenever applied. We demonstrate how specifications in our model can be straightforwardly mapped to the rewriting logic language Maude, and how one can use existing techniques to improve performance. Finally, we also determine the complexity of the plan compliance problem, that is, finding a plan that leads from an initial state to a desired goal state without reaching any undesired critical state. We consider all actions to be balanced, that is, their pre and post-conditions have the same number of facts. Under this assumption on actions, we show that the plan compliance problem is PSPACE-complete when all actions have only deterministic effects and is EXPTIME-complete when actions may have non-deterministic effects