Neural correlates of error prediction in a complex motor task

The goal of the study was to quantify error prediction processes via neural correlates in the Electroencephalogram (EEG). Access to such a neural signal will allow to gain insights into functional and temporal aspects of error perception in the course of learning. We focused on the error negativity (Ne) or error-related negativity (ERN) as a candidate index for the prediction processes. We have used a virtual goal-oriented throwing task where participants used a lever to throw a virtual ball displayed on a computer monitor with the goal of hitting a virtual target as often as possible. After one day of practice with 400 trials, participants performed another 400 trials on a second day with EEG measurement. After error trials (i.e., when the ball missed the target), we found a sharp negative deflection in the EEG peaking 250 ms after ball release (mean amplitude: t = -2.5, df = 20, p = 0.02) and another broader negative deflection following the first, reaching from about 300 ms after release until unambiguous visual knowledge of results (KR; hitting or passing by the target; mean amplitude: t = -7.5, df = 20, p < 0.001). According to shape and timing of the two deflections, we assume that the first deflection represents a predictive Ne/ERN (prediction based on efferent commands and proprioceptive feedback) while the second deflection might have arisen from action monitoring

The Worth of Anonymous Feedback

Prima facie it is accepted that anonymity is an important feature of eLearning systems. It is easy to implement. But this simplicity belies its more serious implications, especially regarding the worth which can be attached to results derived from the interpretation and analysis of anonymously collected data. A sample of eLearning implementation cases is reviewed from the point of view of anonymously collected data for evaluation of educational quality. A reiteration of an earlier analysis of levels of anonymity leads to the introduction of the Anonymity-Purpose-Worth matrix. It is contended that if the matrix is used to characterise the data collection and analysis in eLearning evaluation settings, the worth of feedback can be better appraised and acted upon. Practitioners, researchers, and students in the eLearning field will benefit as the anonymity conditions will be clearly documented in a standardised and comparable manner

Guest Editorial

This special issue of CIT Journal of Computing and Information Technology on Emerging Web Technologies and Applications presents seven papers covering the broad spectrum of a diverse area

Bedeutungsverlust staatlicher Zivilgerichte: Einem empirischen Nachweis auf der Spur

Dem deutlichen Zuwachs des weltweiten Handelsvolumens in den vergangenen Jahrzehnten müsste auch eine Zunahme von Handelsstreitigkeiten in der Justiz gegenüberstehen. Tatsächlich aber nehmen die Fallzahlen in Handelssachen vor staatlichen Gerichten stetig ab. Zur Erklärung dieses Umstands wird in der rechtswissenschaftlichen Literatur eine Flucht in die internationale Schiedsgerichtsbarkeit behauptet, der ein Bedeutungsverlust der staatlichen Gerichte gegenüberstehe ('The Vanishing Trial'). Im Folgenden soll der These von der Entstaatlichung der Justiz im internationalen Handel auf empirischer Grundlage nachgegangen werden. Zu diesem Zweck werden bereits vorhandene sowie eigene empirische Studien ausgewertet. Im Ergebnis kann eine Tendenz des Bedeutungsverlusts staatlicher Gerichte in internationalen Wirtschaftsstreitigkeiten plausibel nachgewiesen werden. -- Given the fact that global trade has massively increased during the last decades one would expect an increase in trade law cases before courts accordingly. In fact, however, empirical research shows that the numbers of trade law cases brought before state courts is continuously decreasing. Some legal scholars try to correlate the decreasing importance of state courts for international trade law cases with an ever increasing importance of alternative dispute resolution measures, especially arbitration ('The Vanishing Trial'). We will try to explore this thesis on an empirical basis. For this purpose we have evaluated already existing empirical data but have also carried out empirical studies ourselves. As a result of our research we can plausibly verify a decreasing importance of state courts in trade law cases.

Problems and solutions for using computer (networks) for education

Purpose - The idea to use computers for teaching and learning is over 50 years old. Numerous attempts to use computers for knowledge dissemination under a variety of names have failed in many cases, and have become successful in others. The essence of this paper can be summarized in two sentences. One, in some niches, applications tend to be successful. Second, attempts to fully eliminate humans from the educational process are bound to fail, yet if a large number of aspects is handled well, the role of teachers can indeed be much reduced. The paper aims to discuss these issues. Design/methodology/approach - Report on experimental results. Findings - In some niches, applications of e-Learning technology tend to be successful. However, attempts to fully eliminate humans from the educational process are bound to fail, yet if a large number of aspects is handled well, the role of teachers can indeed be much reduced. Research limitations/implications - A number of features that seemed essential in earlier e-Learning systems turn out to be superfluous. Practical implications - New e-Learning systems have to concentrate on quality of content, not complex technology. Social implications - E-Learning the right way helps learners, teachers and institutions. Originality/value - Experiments reported verify or do the opposite of often loosely stated opinions

Data Mining is becoming Extremely Powerful, but Dangerous

Data Mining describes a technology that discovers non-trivial hidden patterns in a large collection of data. Although, this technology has a tremendous impact on our lives, the invaluable contribution of this invisible technology often goes unnoticed. This paper addresses the various forms of data mining shedding light on its expanding role in enriching our life. Emerging forms of data mining are able to perform multidimensional mining on a wide variety of heterogeneous data sources, to provide solutions to many problems. This paper highlights the advantages and disadvantages that arise from the ever-expanding scope of the data mining. Data Mining augments human intelligence by equipping us with the wealth of knowledge, empowering us to perform our daily task more effectively and efficiently. As the mining scope and capacity increases, users and organisations are now more willing (acceptable) to compromise privacy as a trade-off for gaining peace of mind and additional comforts. The huge data stores of the master miners allow them to gain deep insights about individual lifestyles, social and behavioural patterns and business and financial trends resulting in a disproportionate power distributions. Is it then possible to constrain the scope of mining while delivering the promise of better life

Semi-Automatic Story Generation for a Geographic Server

Većina postojećih poslužitelja koji nude geografske podatke sadrže brojčane podatke o različitim aspektima. Na rad na novom tipu geografskog poslužitelja potaknula su nas četiri glavna problema: (i) Kako se služiti brojkama kad različite baze podataka predstavljaju različite vrijednosti; (ii) Kako izgraditi velike zbirke slika s detaljnim opisima; (iii) Kako ažurirati informacije koje se brzo mijenjaju kao što su osobe na nekim važnim funkcijama te (iv) Kako opisati zemlje ne samo trivijalnim činjenicama, već tipičnim pričama za te zemlje. U prethodnim smo radovima raspravili i djelomično riješili probleme (i) i (ii). Odlučili smo riješiti (iii), regionalna ažuriranja, povezivanjem s međunarodnim konzorcijem čiji će članovi pomoći ili naći pojedince koji će to učiniti. Problemu (iv), kako stvoriti netrivijalne priče tipične za neku zemlju, pristupili smo ručno (konzorcij je do sada stvorio oko 200 priča) te razvijanjem tehnika za poluautomatsko stvaranje priča, što je tema ovoga rada. Osnovna je ideja bila prvo odrediti skupove pouzdanih poslužitelja koji se mogu razlikovati od regije do regije, izvući „zanimljive činjenice“ iz njih i spojiti ih u sirovu verziju izvještaja koja će se obraditi ručno (zato ga nazivamo poluautomatskim). Izdvajanje „zanimljivih činjenica“ s internetskih stranica može zvučati teško, no itekako je moguće odrediti heuristike koji će to učiniti, što nikad ne prelazi nekoliko redova za svrhu citiranja. Spomenimo kao primjer jedno vrlo jednostavno pravilo: Traži rečenice sa superlativima! Ako rečenica sadrži riječ kao što je „najveći“, „najviši“, „najimpresivniji“ i sl., ona vjerojatno sadrži neku zanimljivu činjenicu. S pomoću mašte uspjeli smo odrediti skup takvih pravila. Pokazat ćemo da priče mogu biti potpuno različite: u nekim zemljama dominiraju povijesne činjenice, u drugima ljepota krajolika, u trećima kulturna i ekonomska postignuća, u nekima neobične činjenice koje se odnose na dobitnike Nobelove nagrade, hranu, sport, druge aktivnosti, državne simbole, posebne zakone i sl. Dobiveni rezultati mogu se provjeriti traženjem bilo koje zemlje u kategoriji „Posebne informacije“ (Special Information) i „Iznenađujuće činjenice“ (Surprising Facts). Svi primjeri opisani u ovom radu uzeti su arbitrarno iz skupine od 190 primjera kako bi se prikazalo kako sustav radi. Važno je spomenuti još dvije stvari: (a) riječ je o radnoj verziji koja je već prilično upotrebljiva; (b) osnovne ideje mogu se primijeniti na bilo koje područje. Geografija je izabrana s obzirom na velik broj podataka i interesa za to područje. Ako su naši algoritmi previdjeli neku važu činjenicu, to je manje važno nego da smo primijenili metode na vrste liječenja ili slično tome.Most existing servers providing geographic data tend to offer various numeric data. We started to work on a new type of geographic server, motivated by four major issues: (i) How to handle figures when different databases present different values; (ii) How to build up sizeable collections of pictures with detailed descriptions; (iii) How to update rapidly changing information, such as personnel holding important functions, and (iv) how to describe countries not just by using trivial facts, but stories typical of the country involved. We have discussed and partially resolved issues (i) and (ii) in previous papers; we have decided to deal with (iii), regional updates, by tying in an international consortium whose members would either help themselves or find individuals to do so. It is issue (iv), how to generate non-trivial stories typical of a country, that we decided to tackle both manually (the consortium has by now generated around 200 stories), and by developing techniques for semi-automatic story generation, which is the topic of this paper. The basic idea was first to define sets of reasonably reliable servers that may differ from region to region, to extract “interesting facts” from the servers, and combine them in a raw version of a report that would require some manual cleaning-up (hence: semi-automatic). It may sound difficult to extract “interesting facts” from Web pages, but it is quite possible to define heuristics to do so, never exceeding the few lines allowed for quotation purposes. One very simple rule we adopted was this: ‘Look for sentences with superlatives!’ If a sentence contains words like “biggest”, “highest”, “most impressive” etc. it is likely to contain an interesting fact. With a little imagination, we have been able to establish a set of such rules. We will show that the stories can be completely different. For some countries, historical facts may dominate; for others, the beauty of landscapes; for others, cultural or economic achievements, and for yet others, unusual facts concerning Nobel Prize winners, food, entertainment, sports, other activities, national symbols, special laws, and so on. The results can be checked on by clicking on any country in the category “Special Information” under “Surprising Facts”. All examples shown in this paper were chosen fairly arbitrarily from over 190 examples, to show that the system is indeed working. There are two points to mention here: (a) it is a work in progress, yet has reached a very useable size; (b) the basic ideas can be applied to any area. The choice of geography was due to the wealth of data and interest in this area, but if our algorithms overlook some important facts, this is less critical than applied to types of medical treatment, etc

Coping with the copy-paste-syndrome

The Copy-Paste Syndrome describes a situation whereby students at all levels are becoming more and more reliant on wide-range of easily-available digital content. This is a universal problem that has to be addressed effectively, especially with the revolutionary development of the Web. Weber (Weber, 2006) refers to it as the Google-Copy-Paste-Syndrome, which according to him will drastically affect the quality of scientific publications, leading to a degradation of the quality of life. The expansion of digital content together with an emerging participative social learning (and E-learning) ecosystem could result in even more devastating implications. As opportunities for the proliferation of such infringements becomes widespread, a holistic solution is required combining an institutional approach together with the application of viable technologies. This paper describes an E-learning ecosystem combined with a copy-paste detection suite to comprehensively address the emerging phenomenon

Learning Ecosystems for Dealing with the Copy-Paste Syndrome

The fact that people of all walks of life are becoming more and more reliant on a wide-range of easily-available digital content is often called the Copy-Paste Syndrome. It implies the indiscriminate usage of material, ie without checking for reliability or a concern for violations of intellectual property rights or plagiarism, a kind of cheating that has become uncomfortably widespread. A holistic approach is required to address this universal problem combining an institutional approach together with the application of viable technologies, ..

Poluautomatsko stvaranje priča/sadržaja za geografski poslužitelj

Most existing servers providing geographic data tend to offer various numeric data. We started to work on a new type of geographic server, motivated by four major issues: (i) How to handle figures when different databases present different values; (ii) How to build up sizeable collections of pictures with detailed descriptions; (iii) How to update rapidly changing information, such as personnel holding important functions, and (iv) how to describe countries not just by using trivial facts, but stories typical of the country involved. We have discussed and partially resolved issues (i) and (ii) in previous papers; we have decided to deal with (iii), regional updates, by tying in an international consortium whose members would either help themselves or find individuals to do so. It is issue (iv), how to generate non-trivial stories typical of a country, that we decided to tackle both manually (the consortium has by now generated around 200 stories), and by developing techniques for semi-automatic story generation, which is the topic of this paper. The basic idea was first to define sets of reasonably reliable servers that may differ from region to region, to extract “interesting facts” from the servers, and combine them in a raw version of a report that would require some manual cleaning-up (hence: semi-automatic). It may sound difficult to extract “interesting facts” from Web pages, but it is quite possible to define heuristics to do so, never exceeding the few lines allowed for quotation purposes. One very simple rule we adopted was this: ‘Look for sentences with superlatives!’ If a sentence contains words like “biggest”, “highest”, “most impressive” etc. it is likely to contain an interesting fact. With a little imagination, we have been able to establish a set of such rules. We will show that the stories can be completely different. For some countries, historical facts may dominate; for others, the beauty of landscapes; for others, cultural or economic achievements, and for yet others, unusual facts concerning Nobel Prize winners, food, entertainment, sports, other activities, national symbols, special laws, and so on. The results can be checked on by clicking on any country in the category “Special Information” under “Surprising Facts”. All examples shown in this paper were chosen fairly arbitrarily from over 190 examples, to show that the system is indeed working. There are two points to mention here: (a) it is a work in progress, yet has reached a very useable size; (b) the basic ideas can be applied to any area. The choice of geography was due to the wealth of data and interest in this area, but if our algorithms overlook some important facts, this is less critical than applied to types of medical treatment, etc.Većina postojećih poslužitelja koji nude geografske podatke sadrže brojčane podatke o različitim aspektima. Na rad na novom tipu geografskog poslužitelja potaknula su nas četiri glavna problema: (i) Kako se služiti brojkama kad različite baze podataka predstavljaju različite vrijednosti; (ii) Kako izgraditi velike zbirke slika s detaljnim opisima; (iii) Kako ažurirati informacije koje se brzo mijenjaju kao što su osobe na nekim važnim funkcijama te (iv) Kako opisati zemlje ne samo trivijalnim činjenicama, već tipičnim pričama za te zemlje. U prethodnim smo radovima raspravili i djelomično riješili probleme (i) i (ii). Odlučili smo riješiti (iii), regionalna ažuriranja, povezivanjem s međunarodnim konzorcijem čiji će članovi pomoći ili naći pojedince koji će to učiniti. Problemu (iv), kako stvoriti netrivijalne priče tipične za neku zemlju, pristupili smo ručno (konzorcij je do sada stvorio oko 200 priča) te razvijanjem tehnika za poluautomatsko stvaranje priča, što je tema ovoga rada. Osnovna je ideja bila prvo odrediti skupove pouzdanih poslužitelja koji se mogu razlikovati od regije do regije, izvući „zanimljive činjenice“ iz njih i spojiti ih u sirovu verziju izvještaja koja će se obraditi ručno (zato ga nazivamo poluautomatskim). Izdvajanje „zanimljivih činjenica“ s internetskih stranica može zvučati teško, no itekako je moguće odrediti heuristike koji će to učiniti, što nikad ne prelazi nekoliko redova za svrhu citiranja. Spomenimo kao primjer jedno vrlo jednostavno pravilo: Traži rečenice sa superlativima! Ako rečenica sadrži riječ kao što je „najveći“, „najviši“, „najimpresivniji“ i sl., ona vjerojatno sadrži neku zanimljivu činjenicu. S pomoću mašte uspjeli smo odrediti skup takvih pravila. Pokazat ćemo da priče mogu biti potpuno različite: u nekim zemljama dominiraju povijesne činjenice, u drugima ljepota krajolika, u trećima kulturna i ekonomska postignuća, u nekima neobične činjenice koje se odnose na dobitnike Nobelove nagrade, hranu, sport, druge aktivnosti, državne simbole, posebne zakone i sl. Dobiveni rezultati mogu se provjeriti traženjem bilo koje zemlje u kategoriji „Posebne informacije“ (Special Information) i „Iznenađujuće činjenice“ (Surprising Facts). Svi primjeri opisani u ovom radu uzeti su arbitrarno iz skupine od 190 primjera kako bi se prikazalo kako sustav radi. Važno je spomenuti još dvije stvari: (a) riječ je o radnoj verziji koja je već prilično upotrebljiva; (b) osnovne ideje mogu se primijeniti na bilo koje područje. Geografija je izabrana s obzirom na velik broj podataka i interesa za to područje. Ako su naši algoritmi previdjeli neku važu činjenicu, to je manje važno nego da smo primijenili metode na vrste liječenja ili slično tome