The AEREST Reading Database
Authors: Marcello Ferro, Sara Giulivi, Claudia Cappa (CNR-ILC, Scuola Professionale della Svizzera Italiana SUPSI, CNR-IFC, 2020)
Topic: Text Simplification

Abstract
Aerest is a reading assessment protocol for the concurrent evaluation of a child's decoding and comprehension skills. Reading data complying with the Aerest protocol were automatically collected and structured with the ReadLet web-based platform in a pilot study, to form the Aerest Reading Database. The content, structure and potential of the database are described here, together with the main directions of current and future developments.

Introduction
In the PISA 2000 report (OECD, 2003), a distinction is introduced between the concept of “reading literacy” as opposed to “reading”, the latter being restricted to the ability of decoding or reading aloud, the former including a much wider and more complex range of cognitive and meta-cognitive competencies: decoding, vocabulary, grammar, mastery of larger linguistic and textual structures and features, knowledge about the world, but also use of appropriate strategies necessary to process a text (p. 23). In the PISA 2019 report (OECD, 2019) ”reading literacy” is defined as ”an individual’s capacity to understand, use, evaluate, reflect on and engage with texts in order to achieve one’s goals, develop one’s knowledge and potential, and participate in society”, and as the ”range of cognitive and linguistic competencies, from basic decoding to knowledge of words, grammar and the larger linguistic and textual structures needed for comprehension, as well as integration of meaning with one’s knowledge about the world” (p.28). Achieving reading literacy is crucial for an individuals’ participation in society and ultimately for their realization in academic context, in workplace or, more generally, in life. To achieve reading literacy, pupils need first and foremost to be able to read accurately, understand what they read, and do this in a reasonably small amount of time. This multifaceted ability is defined here as “reading efficiency”. Efficient reading implies on its turn, in the subject, the development of deep comprehension skills. As a matter of fact, comprehension is a complex construct that requires coordination and processing of several cognitive abilities at word, sentence, and text level (Perfetti et al., 2005; Padovani, 2006), including, but not limited to, building coherent semantic representations of what is being read (Nation and Snowling, 2000), making lexical and semantic inferences, using reading strategies, activating metacognitive control (Carretti et al., 2002). When it comes to assessment, the above described complexity is not given due consideration and is, among other aspects, at the basis of the inadequacy of most protocols currently available. The latter often measure comprehension performance (in a way the ”product” of reading comprehension) without considering the underlying processes, or treat those processes as if they were independent, not in interaction with one another. In addition, reading comprehension tests often tend to be used interchangeably, while they actually measure different skills or processes and are not really comparable to one another (Colenbrander et al., 2017; Keenan et al., 2008; Cutting and Scarborough, 2006; Calet et al., 2020; Joshi, 2019). Finally, most currently available reading assessment tools fail to focus on reading efficiency, as they normally measure decoding and reading comprehension separately. This leads to failure in the identification of kids having difficulties in integrating the above mentioned abilities. The AEREST protocol for reading assessment was designed and developed to fill this gap, by testing student skills in three tasks: reading aloud, silent reading, and listening comprehension. In the last two conditions, the student’s comprehension of the text being read is assessed through a questionnaire. Only in the reading aloud condition, the text can also contain non-words. In 2019, AEREST was tested in schools located in Southern Tuscany (Italy) and in the Canton of Ticino (Switzerland), involving a total of 433 children, from the 3rd grade of the Italian primary school through to the first grade of the Italian middle school (6th grade). The protocol was automatically administered using a prototype version of ReadLet (Ferro et al., 2018a; Ferro et al., 2018b), a web-based platform that records large streams of time-aligned, multimodal reading data.

Conclusion
The AEREST protocol was shown to be effective in characterizing the decoding and comprehension performance of children of late primary school and early middle school in text reading tasks. Results are clear and encouraging, opening the way to further, more detailed, dynamic, and multimodal analysis. Completion of the current AEREST protocol with a second battery of tests is foreseen in the near future. This will provide schools with two different test batteries, to be used for assessment at the beginning and end of school year, for adequate monitoring of pupils’ reading and reading comprehension skills. A version of the protocol conceived for clinical context is also foreseen, as well as translation and adaptation of the protocol to languages other than Italian. The collected data will be assembled in a multimodal linguistic resource and made freely available to the scientific community.