'It’s hard to define good writing, but i recognise it when i see it’: can consensus-based assessment evaluate the teaching of writing?

In a Higher Education environment where evidence-based practice and accountability are highly valued, most writing practitioners will be familiar with direct requests or less tangible pressures to demonstrate that their teaching has a positive impact on students’ writing skills. Although such evaluations are not devoid of risk and the need for them is contested, it can be argued that it is better to engage with them, as this can avoid the danger of overly simplistic forms of measurements being imposed. The current paper engages with this question by proposing the conceptual basis for a new measurement tool. Based on Amabile’s Consensual Assessment Technique (CAT), developed to assess creativity, the tool develops the idea of consensual assessment of writing as a methodology that can provide robust data through systematic measurement. At the same time, I argue consensual assessment reflects the evaluation of writing in real life situations more closely than many of the methodologies for writing assessment used in other contexts, primarily large scale tests. As such, it would allow writing practitioners to go beyond ethnographic methods, or self- reporting, in order to obtain greater insight into the ways in which their teaching helps change students’ actual writing, without sacrificing the complexity of writing as social interaction, which is fundamental to an academic literacies approach

Measuring Syntactic Complexity in Spoken and Written Learner Language: Comparing the Incomparable?

Spoken and written language are two modes of language. When learners aim at higher skill levels, the expected outcome of successful second language learning is usually to become a fluent speaker and writer who can produce accurate and complex language in the target language. There is an axiomatic difference between speech and writing, but together they form the essential parts of learners’ L2 skills. The two modes have their own characteristics, and there are differences between native and nonnative language use. For instance, hesitations and pauses are not visible in the end result of the writing process, but they are characteristic of nonnative spoken language use. The present study is based on the analysis of L2 English spoken and written productions of 18 L1 Finnish learners with focus on syntactic complexity. As earlier spoken language segmentation units mostly come from fluency studies, we conducted an experiment with a new unit, the U-unit, and examined how using this unit as the basis of spoken language segmentation affects the results. According to the analysis, written language was more complex than spoken language. However, the difference in the level of complexity was greatest when the traditional units, T-units and AS-units, were used in segmenting the data. Using the U-unit revealed that spoken language may, in fact, be closer to written language in its syntactic complexity than earlier studies had suggested. Therefore, further research is needed to discover whether the differences in spoken and written learner language are primarily due to the nature of these modes or, rather, to the units and measures used in the analysis

Predicting language learners' grades in the L1, L2, L3 and L4: the effect of some psychological and sociocognitive variables

This study of 89 Flemish high-school students' grades for L1 (Dutch), L2 (French), L3 (English) and L4 (German) investigates the effects of three higher-level personality dimensions (psychoticism, extraversion, neuroticism), one lower-level personality dimension (foreign language anxiety) and sociobiographical variables (gender, social class) on the participants' language grades. Analyses of variance revealed no significant effects of the higher-level personality dimensions on grades. Participants with high levels of foreign language anxiety obtained significantly lower grades in the L2 and L3. Gender and social class had no effect. Strong positive correlations between grades in the different languages could point to an underlying sociocognitive dimension. The implications of these findings are discussed

Quantum Interaction Approach in Cognition, Artificial Intelligence and Robotics

The mathematical formalism of quantum mechanics has been successfully employed in the last years to model situations in which the use of classical structures gives rise to problematical situations, and where typically quantum effects, such as 'contextuality' and 'entanglement', have been recognized. This 'Quantum Interaction Approach' is briefly reviewed in this paper focusing, in particular, on the quantum models that have been elaborated to describe how concepts combine in cognitive science, and on the ensuing identification of a quantum structure in human thought. We point out that these results provide interesting insights toward the development of a unified theory for meaning and knowledge formalization and representation. Then, we analyze the technological aspects and implications of our approach, and a particular attention is devoted to the connections with symbolic artificial intelligence, quantum computation and robotics.Comment: 10 page

On the cross-linguistic equivalence of sentir(e) in Romance languages: a contrastive study in semantics

Recent linguistic studies on perception have focused mainly on verbs referring to the dominant visual and auditory modalities, (e.g. English see/look and hear/listen) and have largely ignored the minor verbs. The present paper seeks to fill this gap by comparing the complex semantics of the cognate verbs sentir(e) in three Romance languages, namely Spanish, French and Italian. Because the objective study of semantics is a problematic issue, we pay special attention to methodological problems and opt for a combined corpus approach involving both a translation corpus and comparable data. Evidence from both corpora indicates that, notwithstanding the fact that the rich polysemy of the three verbs partly coincides, each individual verb has undergone semantic specializations differentiating the morphological cognates

Examining Scientific Writing Styles from the Perspective of Linguistic Complexity

Publishing articles in high-impact English journals is difficult for scholars around the world, especially for non-native English-speaking scholars (NNESs), most of whom struggle with proficiency in English. In order to uncover the differences in English scientific writing between native English-speaking scholars (NESs) and NNESs, we collected a large-scale data set containing more than 150,000 full-text articles published in PLoS between 2006 and 2015. We divided these articles into three groups according to the ethnic backgrounds of the first and corresponding authors, obtained by Ethnea, and examined the scientific writing styles in English from a two-fold perspective of linguistic complexity: (1) syntactic complexity, including measurements of sentence length and sentence complexity; and (2) lexical complexity, including measurements of lexical diversity, lexical density, and lexical sophistication. The observations suggest marginal differences between groups in syntactical and lexical complexity.Comment: 6 figure

Evaluation of uncertainty in the measurement of sense of natural language constructions

The task of evaluating uncertainty in the measurement of sense in natural language constructions (NLCs) was researched through formalization of the notions of the language image, formalization of artificial cognitive systems (ACSs) and the formalization of units of meaning. The method for measuring the sense of natural language constructions incorporated fuzzy relations of meaning, which ensures that information about the links between lemmas of the text is taken into account, permitting the evaluation of two types of measurement uncertainty of sense characteristics. Using developed applications programs, experiments were conducted to investigate the proposed method to tackle the identification of informative characteristics of text. The experiments resulted in dependencies of parameters being obtained in order to utilise the Pareto distribution law to define relations between lemmas, analysis of which permits the identification of exponents of an average number of connections of the language image as the most informative characteristics of text

Algorithmic complexity for psychology: A user-friendly implementation of the coding theorem method

Kolmogorov-Chaitin complexity has long been believed to be impossible to approximate when it comes to short sequences (e.g. of length 5-50). However, with the newly developed \emph{coding theorem method} the complexity of strings of length 2-11 can now be numerically estimated. We present the theoretical basis of algorithmic complexity for short strings (ACSS) and describe an R-package providing functions based on ACSS that will cover psychologists' needs and improve upon previous methods in three ways: (1) ACSS is now available not only for binary strings, but for strings based on up to 9 different symbols, (2) ACSS no longer requires time-consuming computing, and (3) a new approach based on ACSS gives access to an estimation of the complexity of strings of any length. Finally, three illustrative examples show how these tools can be applied to psychology.Comment: to appear in "Behavioral Research Methods", 14 pages in journal format, R package at http://cran.r-project.org/web/packages/acss/index.htm