Question

PRZETŁUMACZ PODANY TEKST: The question of whether predictive inferences should be considered part of the propositional representation of a text or the situation-model level cannot at this time be resolved. To assign predictive inferences to a situation-model level would require that there be a clear definition of what kinds of information are included in a situation model and what kinds are not, something that we do not have. Whether propositional or situation-model information, the older adults in our study appear to have encoded and remembered predictive inferences as well as the young adults. In other words, they do appear to understand that something bad happened to the actress. We can draw this conclusion because the diffusion model gives a way to separate the strength with which information is represented in memory from speed/accuracy criteria and nondecision components of processing. The model can be applied to examine encoding and memory for particular kinds of information such as predictive inferences without any commitment to where they fall in or between propositional and situation-model levels. The model solves a scaling problem: The older readers’ responses to test words were much slower than the young adults’, roughly 200–400 ms slower, and the difference between their RTs to ‘‘dead’’ in the predicting and control conditions was larger. For the young adults, the difference was 53 ms, whereas for the two older groups, the difference averaged 99 ms. Applying the model, we found that RTs were longer and differences between conditions larger because the older adults set their criteria farther apart: they were less willing than the young adults to go so fast that they made errors that they could have avoided by going slower. The model also handles another problem: at the same time that the difference in RTs between the predicting and control conditions was considerably larger for the older adults than the younger, the difference in accuracy was almost nonexistent (a .23 difference between predicting and control for the older groups, a .22 difference for the young group). The model resolved this seeming contradiction in the same way it resolved the scaling issue: the older adults’ difference in memory strength (drift rate) for the target test word between the predicting and control conditions was almost identical to the young adults’, even though they set their criteria further apart. To our knowledge, the experiment reported here is the first application of a sequential sampling model to investigations of language comprehension and memory for older adults. It is our hope that, in the near future, such models will allow investigations of the degree to which older adults understand and remember many other kinds of inferences, as well as other sorts of textual information.

Answer 1

The question is whether predictive applications should be considered as part of the representation of sentences of text and situation-model level can not at this time be resolved. To assign a prophetic conclusions to the situation-model level required to be a clear definition of what types of information are included in the model of the situation and what is not, something that is not there. Is the situation or sentences model information, the elderly in our study seems to be encoded and remembered predictive applications, as well as young adults. In other words, they do not seem to understand that something bad happened to the actress. This conclusion can be drawn because the diffusion model gives a way to separate the force with which the information is represented in the memory of the speed / accuracy criteria and components nondecision processing. The model can be used to study the encoding and memory for specific types of information, such as the predictive inferences without the involvement of where they fall within or between levels of sentence and the situation model. Model solves the problem of scale: the older readers reactions to the words of the study were significantly slower than young adults ", about 200-400 ms slower, and the difference between the RTS to'' dead'' in forecasting and control conditions was greater. For young adults, the difference was 53 ms, while for the two older groups, the difference on average 99 ms. Applying the model, we found that RT was longer and larger differences between the conditions, because the elderly set your criteria further apart: they were less likely than young adults to go so fast that it made mistakes that can be avoided by going slower. model also supports another problem at the same time that the difference in RTS between forecasting and control conditions was significantly higher for older people than younger ones, the difference in accuracy was nearly does not exist (0.23 difference between the prediction and control for the older group, 0.22 difference for the young group.) model to resolve this apparent contradiction in the same way that the problem is solved scaling: The elderly "difference in the strength of memory (indicator fluctuations) for a test target words between the prediction and the control was nearly identical to that of young adults, "but they define their criteria further apart. According to our knowledge, the experience reported here is the first application of sequential sampling model for studies of language comprehension and memory for the elderly. We hope that in the near future, such models allow investigations of the extent to which older people understand and remember many other types of inference, as well as other types of text information.

 

Answer 2

Na pytanie, czy wnioski prognostyczne należy rozważyć część zdań reprezentacji tekstu i sytuacji-modelu poziomu nie mogą w tym czasie być rozwiązany. Aby przypisać proroczych wnioski do sytuacji-modelu poziomie wymaga, aby było jasne określenie, jakie rodzaje informacji są zawarte w modelu sytuacji i jakie nie są, coś, czego nie ma. Czy sytuacja lub zdań model informacji, osoby starsze w naszym badaniu wydaje się zakodowane i pamiętać predykcyjne wnioski, jak również młodych dorosłych. Innymi słowy, oni zdają się nie rozumieć, że coś złego stało się z aktorką. Można wyciągnąć taki wniosek, ponieważ model dyfuzyjny daje sposób, aby oddzielić siły, z jaką informacje są reprezentowane w pamięci od szybkości / dokładności kryteriów i komponentów nondecision przetwarzania. Model może być stosowana do badania kodowanie i pamięci dla poszczególnych rodzajów informacji, takich jak predykcyjne wnioskowań bez zaangażowania, w którym wchodzą one w lub pomiędzy poziomami zdaniowych i sytuacja model. Model rozwiązuje problem skalowania: starszej czytelników reakcje na słowa badań były znacznie wolniejsze od młodych dorosłych ", około 200-400 ms wolniej, a różnica między ich RTS do'' martwy'' w prognozowania i warunków kontroli było większe. W przypadku młodych dorosłych, różnica była 53 ms, natomiast dla dwóch grup starszych, różnica średnio 99 ms. Stosowania modelu, okazało się, że RT były dłuższe i różnice między warunkami większe, ponieważ osoby starsze ustawić swoje kryteria dalej od siebie: byli mniej skłonni niż młodych dorosłych, aby przejść tak szybko, że popełnił błędy, które mogą ich uniknąć, przechodząc wolniej. Model obsługuje również inny problem: w tym samym czasie, że różnica w RTS między prognozowania i warunków kontroli była znacznie większa dla osób starszych niż młodszych, różnica w dokładności był prawie nie istnieje (0,23 różnica między przewidywania i kontroli dla starsze grupy, 0,22 różnica dla młodej grupy). Model rozwiązać tę pozorną sprzeczność w ten sam sposób, że problem został rozwiązany skalowania: The osób starszych "różnica w sile pamięci (wskaźnik wahań) dla słowa testowego docelowej między prognozowania i warunków kontroli był niemal identyczny do młodych dorosłych", choć Określają one ich kryteria dalej od siebie. Według naszej wiedzy, doświadczenia poinformował o to pierwsze zastosowanie sekwencyjnego modelu pobierania próbek do badań rozumienia języka i pamięci dla osób starszych. Mamy nadzieję, że w najbliższej przyszłości takie modele pozwolą dochodzenia względem stopnia, w jakim osoby starsze zrozumieć i zapamiętać wiele innych rodzajów wnioskowania, jak również inne rodzaje informacji tekstowych.