Standards in education

Modern educational systems are based on standards. Systems in countries all over the world differ and have different tradition, so different terms are used for similar concepts. In education, standards should have a similar role as in physics, where they are empirical and measurable. Two types of standards can be defined: content or curriculum standards and performance standards, with the latter being essential. Setting educational goals or content standards is the first step in the construction of knowledge measurement procedures. In Slovenia, the traditional term 'performance objective' or 'instructional objective' can be used instead of the term 'content standards'. For each school subject on different levels in Slovenian educational system, performance standards have to be set in the future, if educational system is to be based on standards

Ongoing Analyses of Student Assessment Data Method as a Management Tool in Education

Organizacije naj bi imele postavljene jasne cilje kakovosti, upravljanje sistema in odločanje na različnih nivojih naj bi temeljilo na analizah in relevantnih podatkih. Tradicionalni vzgojno-izobraževalni sistemi in šolske prakse pogosto ne sledijo tem zahtevam. Načrtovanje v šolstvu ne more temeljiti zgolj na naštevanju učnih vsebin in metod, ampak mora biti usmerjeno učno-ciljno. Kurikul že v konceptu pomeni nekaj drugega kot učni načrt, presega zgolj načrtovanje poučevanja in učenja. Osnovne zahteve kurikularnega pristopa so racionalnost, eksaktnost in preverljivost učnih ciljev. Kurikul se obravnava na treh ravneh: načrtovani, izvedbeni in še posebej doseženi kurikul, kjer se preverja v učnem procesu dosežene merljive učne cilje. V šolskem sistemu je potrebno opredeliti standarde znanja. Opisovanje vsebinskih standardov znanja (ang. content standards) ni dovolj. Z nacionalnimi preizkusi znanja in/ali državnimi izpiti je potrebno umeriti standarde dosežkov (ang. performance standards). V šolskih sistemih z državnimi izpiti, kot je v Sloveniji matura, ali drugimi oblikami nacionalnih preverjanj znanja se dosežke poleg certificiranja lahko uporabi za povratno informacijo učiteljem, šolam in drugim strokovnjakom. Tako pridobljeni rezultati sumativnega (zbirnega) preverjanja znanja se lahko uporabijo za načrtovanje učiteljevega dela v prihodnje in za poučevanje naslednjih generacij učencevto se opredeli kot drugi nivo formativnega preverjanja znanja. Namen formativnega preverjanja je, da se ugotovi katere prilagoditve, dopolnitve in usmeritve pri poučevanju in učenju so potrebne, ko se znanje še oblikuje (formira). Metoda stalnega analiziranja izkazanega znanja kot orodje upravljanja v šolstvu lahko na dolgi rok sistematično vodi k izboljšavam pri poučevanju, večji učinkovitosti in managementu kakovosti. Disertacija v empiričnem delu opisuje razvoj, zgradbo in zmožnosti Orodja za analize izkazanega znanja ob zaključku srednje šole, slovenskega sistema povratnih informacij za šole (ang. School Performance Feedback System). Z razvojnim in raziskovalnim delom, je bila kot nadgradnja razvito Orodje za upravljanje v šolstvu, kot prispevek k razvoju managementa kakovosti v šolskih sistemih z zunanjim preverjanjem znanja. Disertacija vsebuje rezultate in izsledke več raziskav: · Prikaz zgolj enega kazalca lahko ustvarja zmotno predstavo o uspešnosti šole pri pripravi in usposabljanju dijakov za maturo. · Pri izbiri maturitetnih predmetov pride do pomembnih razlik med predmetinaravoslovne predmete izbirajo dijaki z višjim doseženim splošnim znanjem, družboslovne predmete pa dijaki z nižjim doseženim splošnim znanjem. · Šola oz. oddelki na šoli po dosežkih v znanju med predmeti niso homogeniniso enako uspešni pri vseh šolskih predmetih. Šola oz. oddelek na šoli je pri enem od predmetov lahko nadpovprečno uspešen, pri drugem pa podpovprečno. · V nekaj zaporednih letih na šoli lahko pride do pomembnih sprememb v splošnem uspehu zaradi variabilnosti v dosežkih pri posameznih predmetih. · Poleg variabilnosti dosežkov v splošnem uspehu in/ali pri posameznem predmetu med šolami je enako pomembna tudi variabilnost dosežkov splošnega uspeha in/ali variabilnost dosežkov pri posameznem predmetu med oddelki znotraj šole. · Pri izključno eksterno ocenjenih delih izpitov se fantje pri ocenjevanju doseženega znanja in spretnosti približajo dekletom in jih lahko celo presežejo. · Dodeljene učiteljeve točke za interne dele izpitov so pri nekaterih predmetih v povprečju bližajo maksimalni vrednosti in se iz leta v leto povečujejo. Ta pojav se lahko opredeli kot inflacija ocen. Metoda stalnega analiziranja izkazanega znanja učencev kot orodje upravljanja v šolstvu se lahko uporablja pri ekspertnem vodenju nacionalnih šolskih politik (državni nivo), na nivoju šolskega managementa (ravnateljev) in v svetih šol v okviru managementa kakovosti (šolski nivo), na nivoju strokovnih aktivov in predmetnih učiteljev kot vodijOrganisations should have clear quality goals, and the managing of the system and decision-making on different levels should be based on analyses and relevant data. Traditional educational systems and practices often do not follow these requirements. Planning in education cannot be based simply on lists of learning contents and methods, but must be oriented towards learning objectives. The curriculum is conceptually different from an instructional plan and it goes beyond the mere planning of teaching and learning. The fundamental requirements of the curricular approach are rationality, exactness, and the verifiability of learning objectives. The curriculum is considered on three levels: the intended, implemented, and especially attained or achieved curriculum, where the achieved measurable learning objectives are assessed. Within the school system, the standards of knowledge must be defined. Describing content standards is not sufficient. With the help of the national assessment of knowledge and/or public examinations it is necessary to set performance standards. Within school systems with public examinations, for example, the Matura exam in Slovenia or other formats of a national assessment of knowledge, such achievements can be used as feedback for teachers, schools, and other experts, in addition to being used for certification. Thus the gathered data of summative assessment can be used for planning future instructional activities – proposed for new groups of studentsthis is considered as a secondary level of formative assessment. The function of formative assessment is to establish which adjustments, additions, and directions are needed in the teaching and learning process while the knowledge is still forming. The ongoing analysis of the student assessment data method used as a management tool can in the long run systematically lead to improvements in teaching, effectiveness, as well as assessment and quality assurance. In its empirical part, this dissertation describes the development, structure, and capabilities of the Assessment of/for Learning Analytic Tool (ALA Tool), the Slovenian School Performance Feedback System. Within our researches, as a contribution to the development of quality management in school systems with external examinations, we upgraded the Tool for management in education. The dissertation contains results and outcomes of several studies: • Showing only one indicator can paint an erroneous picture of how successful a school is in preparing and instructing students for the Matura exam. • When selecting the subjects for the Matura exam, the following important variability can be observed: science optional subjects are selected by candidates with better overall achievement, while social science optional subjects are selected by candidates with significantly lower overall achievement. • Schools, or individual classes within the school, are not homogenous as far as their achievements in particular subjects are concernedthey are not equally successful at all school subjects. A school, or an individual class, can be above average in one subject, and below average in another. • Over several consecutive years there can be important changes in overall achievement in a school due to the variability in results in individual subjects. • In addition to the variability of the overall achievement and/or in individual subjects in different schools, the variability of the overall achievement and/or in individual subjects between classes within the same school is equally important. • The gap between boys and girls in externally assessed exam achievements is narrowing, and boys can even surpass girls. • Teacher-allocated points at internal parts of examinations have on average approached the maximum value in some subjects and increase every year. This phenomenon can be defined as grade inflation. The ongoing analyses of the student assessment data method as a management tool in education can be used in the expert management of school policy (the national level), among princi

Artificial intelligence and financial supervision in the euro area and the United States

Umetna inteligenca ima potencial za izboljšanje učinkovitosti in inovacij v finančnem sektorju, vendar prinaša tudi probleme. Kompleksnost in občutljivost algoritmov umetne inteligence lahko vodita v nenadne šoke in destabilizacijo finančnih sistemov. Regulatorji se soočajo s težavami pri nadzoru umetne inteligence zaradi kompleksnosti delovanja in pomanjkanja transparentnosti, kar otežuje pravočasno prepoznavanje tveganj. Umetna inteligenca pa se lahko uporabi tudi kot rešitev, čeprav ne Evropska centralna banka ne ameriške Zvezne rezerve ne uporabljajo umetne inteligence pri svojih osnovnih dejavnostih, pa obe centralni banke raziskujeta potencialno uporabo umetne inteligence pri svojem delovanju. Eden možnih primerov uporabe umetne inteligence pri finančnem nadzoru je uporaba pri obvladovanju sistemskega tveganja, kjer jo lahko uporabljamo na dveh ravneh. Na mikro ravni se umetna inteligenca lahko uporablja za mikrobonitetni nadzor in notranje upravljanje tveganj, kar omogoča bolj natančno analizo in odločanje. Nasprotno pa je uporaba umetne inteligence pri makrobonitetnem nadzoru, ki se osredotoča na stabilnost celotnega finančnega sistema, bolj zapletena zaradi pomanjkanja podatkov in kompleksnosti finančnih trgov. Za uspešno integracijo umetne inteligence v regulativne okvire so potrebni jasni pravilniki, etične smernice ter sodelovanje med regulatorji, industrijo in akademsko skupnostjo. Nadaljnje raziskave in razvoj so ključni za izboljšanje razumevanja in obvladovanja tveganj, povezanih z uporabo umetne inteligence v finančnem sektorju.Artificial intelligence has the potential to enhance efficiency and innovation in the financial sector, but it also presents challenges. The complexity and sensitivity of artificial intelligence algorithms can lead to sudden shocks and destabilization of financial systems. Regulators face difficulties in overseeing artificial intelligence due to its operational complexity and lack of transparency, which complicates timely risk identification. However, artificial intelligence can also be utilized as a solution, although neither the European Central Bank nor the Federal Reserves currently employs artificial intelligence in their core activities, both central banks are exploring the potential use of artificial intelligence in their operations. One potential application of artificial intelligence in financial oversight is its use in managing systemic risk, where it can be applied at two levels. Artificial intelligence can be used for micro-prudential supervision and internal risk management at the micro level, enabling more precise analysis and decision-making. Conversely, the use of artificial intelligence in macroprudential supervision, which focus on the stability of the entire financial system, is more complex due to data scarcity and the intricacies of financial markets. Clear policies, ethical guidelines, and collaboration among regulators, industry, and academia are essential for the successful integration of artificial intelligence into regulatory frameworks. Further research and development are crucial for improving understanding and managing the risks associated with the use of artificial intelligence in the financial sector

Effect of engineered TiO₂ and ZnO nanoparticles on erythrocytes, platelet-rich plasma and giant unilamelar phospholipid vesicles

Abstract Background Massive industrial production of engineered nanoparticles poses questions about health risks to living beings. In order to understand the underlying mechanisms, we studied the effects of TiO2 and ZnO agglomerated engineered nanoparticles (EPs) on erythrocytes, platelet-rich plasma and on suspensions of giant unilamelar phospholipid vesicles. Results Washed erythrocytes, platelet-rich plasma and suspensions of giant unilamelar phospholipid vesicles were incubated with samples of EPs. These samples were observed by different microscopic techniques. We found that TiO2 and ZnO EPs adhered to the membrane of washed human and canine erythrocytes. TiO2 and ZnO EPs induced coalescence of human erythrocytes. Addition of TiO2 and ZnO EPs to platelet-rich plasma caused activation of human platelets after 24 hours and 3 hours, respectively, while in canine erythrocytes, activation of platelets due to ZnO EPs occurred already after 1 hour. To assess the effect of EPs on a representative sample of giant unilamelar phospholipid vesicles, analysis of the recorded populations was improved by applying the principles of statistical physics. TiO2 EPs did not induce any notable effect on giant unilamelar phospholipid vesicles within 50 minutes of incubation, while ZnO EPs induced a decrease in the number of giant unilamelar phospholipid vesicles that was statistically significant (p  Conclusions These results indicate that TiO2 and ZnO EPs cause erythrocyte aggregation and could be potentially prothrombogenic, while ZnO could also cause membrane rupture.</p