RESUMEN

We provide the first openly-available German QUestion-Answer Congruence Corpus (QUACC), designed for the task of sentence-based question generation with question-answer congruence. Based on this corpus, we establish suitable baselines for question generation, comparing systems of very different nature. Question generation is an interesting challenge in particular for current neural network architectures given that it combines aspects of language meaning and forms in complex ways. The systems have to generate question phrases appropriately linking to the meaning of the envisaged answer phrases, and they have to learn to generate well-formed questions using the source. We show that our QUACC corpus is well-suited to investigate the performance of various neural models and gain insights about the specific error sources.

RESUMEN

Performance on word problems is influenced by linguistic and arithmetic factors, and by their interaction. To study these factors and interactions, we manipulated linguistic and arithmetic factors independently in a within-participant design that included complexity parameters (a) in the domain of arithmetic: carry/borrow (no-carry/borrow vs. carry/borrow), operation (addition vs. subtraction), (b) in the domain of linguistics: nominalization (nominalized vs. verbalized form), and (c) linking the two domains: lexical consistency (linguistic predicate locally consistent vs. inconsistent with mathematical operation). Response times of 25 students solving 320 one-step word problems were measured. All four factors showed a main effect on response times, and interactions between linguistic and arithmetic factors affected response times. These interactions were observed when the linguistic and arithmetic factors were conceptually linked. Our results highlight that not only the linguistic and arithmetic complexities of an item contribute to the difficulty of a word problem, but linguistic and arithmetic factors interact. We discuss the theoretical implications for the numerical and the linguistic domain as well as the possible impact of domain-general characteristics, such as working memory limitations as a potential reason for the observed interactions between numerical and linguistic attributes.

Asunto(s)

RESUMEN

The present study compared lab-based and web-based versions of cognitive individual difference measures widely used in second language research (working memory and declarative memory). Our objective was to validate web-based versions of these tests for future research and to make these measures available for the wider second language research community, thus contributing to the study of individual differences in language learning. The establishment of measurement equivalence of the two administration modes is important because web-based testing allows researchers to address methodological challenges such as restricted population sampling, low statistical power, and small sample sizes. Our results indicate that the lab-based and web-based versions of the tests were equivalent, i.e., scores of the two test modes correlated. The strength of the relationships, however, varied as a function of the kind of measure, with equivalence appearing to be stronger in both the working memory and the verbal declarative memory tests, and less so in the nonverbal declarative memory test. Overall, the study provides evidence that web-based testing of cognitive abilities can produce similar performance scores as in the lab.

Asunto(s)

RESUMEN

This study examined predictors of the development of Wikipedia articles that deal with controversial issues. We chose a corpus of articles in the German-language version of Wikipedia about alternative medicine as a representative controversial issue. We extracted edits made until March 2013 and categorized them using a supervised machine learning setup as either being pro conventional medicine, pro alternative medicine, or neutral. Based on these categories, we established relevant variables, such as the perspectives of articles and of authors at certain points in time, the (im)balance of an article's perspective, the number of non-neutral edits per article, the number of authors per article, authors' heterogeneity per article, and incongruity between authors' and articles' perspectives. The underlying objective was to predict the development of articles' perspectives with regard to the controversial topic. The empirical part of the study is embedded in theoretical considerations about editorial biases and the effectiveness of norms and rules in Wikipedia, such as the neutral point of view policy. Our findings revealed a selection bias where authors edited mainly articles with perspectives similar to their own viewpoint. Regression analyses showed that an author's perspective as well as the article's previous perspectives predicted the perspective of the resulting edits, albeit both predictors interact with each other. Further analyses indicated that articles with more non-neutral edits were altogether more balanced. We also found a positive effect of the number of authors and of the authors' heterogeneity on articles' balance. However, while the effect of the number of authors was reserved to pro-conventional medicine articles, the authors' heterogenity effect was restricted to pro-alternative medicine articles. Finally, we found a negative effect of incongruity between authors' and articles' perspectives that was pronounced for the pro-alternative medicine articles.

Asunto(s)