Linking text readability and learner proficiency using linguistic complexity feature vector distance

Abstract

How can we identify authentic reading material that matches the learner's proficiency and fosters their language development? Traditionally, this involves assigning a one-dimensional label to the text that identifies the grade or proficiency level of the learners that the text is intended for. Such an approach is inadequate given that both the text complexity and proficiency constructs are multi-dimensional in nature. We propose to instead link readers and texts through multidimensional vectors characterizing the linguistic complexity of the reading material and that of texts written by the learners as proxy of their proficiency level. We first validate the approach using a leveled reading corpus by showing that vector distances computed on the complexity representations can serve the function of the traditional labels. We then highlight the advantage of the multi-dimensional approach using data from a continuation writing task, showing that it makes it possible to study individual complexity dimensions and to explore different degrees of challenge for different dimensions. Our approach essentially makes it possible to empirically investigate the +1 of Krashen's i+1, the challenge that best fosters development given the learner's interlanguage. On the practical side, we discuss an ICALL system demonstrating the viabilityof the approach in real-life..

Keywords:

• Linguistic complexity
• readability assessment
• learner proficiency
• intelligent computer-assisted language learning

Acknowledgments

The authors would like to thank Prof. Chuming Wang and Prof. Min Wang, the authors of Wang and Wang (2015), for their generosity in sharing the continuation writing corpus with us.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 http://www.corestandards.org/other-resources/key-shifts-in-english-language-arts

2 In mathematics, a vector is defined as an object that has both a magnitude and a direction. It can be represented in a coordinate system as a set of coordinates. For example, a two-dimensional vector can be represented as a pair of coordinates (x, y) in a Cartesian coordinate system. The same vector can also be visualized as an arrow pointing from the origin (0, 0) to the point at (x, y) in the Cartesian coordinate system. The magnitude of this vector is then the length of the arrow and the direction the direction the arrow points to. A vector is not limited to two dimensions; it can be multidimensional, but the basic principles are the same.

Additional information

Funding

This research was funded by the LEAD Graduate School & Research Network [GSC1028], a project of the Excellence Initiative of the German federal and state governments. Xiaobin Chen is a doctoral student at the LEAD Graduate School & Research Network.

Notes on contributors

Xiaobin Chen

Xiaobin Chen is a PhD Candidate of the LEAD Graduate School & Research Network at the University of Tübingen. His research interests include intelligent computer-assisted language learning, NLP, and complexity analysis of language production.

Detmar Meurers

Detmar Meurers is a Professor of Computational Linguistics and a steering board member of the LEAD Graduate School & Research Network at the University of Tübingen. His work focuses on linguistic modeling for intelligent computer-assisted language learning, learner corpora, second language acquisition, language teaching and testing, and the use of computational linguistic methods in empirical educational science.