Agreement Errors in Learner Corpora across CEFR: A Computer-Aided Error Analysis of Greek and Turkish EFL Learners Written Productions

This paper illustrates the use of learner corpus data (extracted from Cambridge Learner Corpus – CLC) to carry out an error analysis to investigate authentic learner errors and their respective frequencies in terms of types and tokens as well as contexts in which they regularly occur across four distinct proficiency levels, B1-B2; C1-C2, as defined by Common European Framework of Reference for Languages (henceforth CEFR) (Council of Europe, 2001). As a variety of learner corpora compiled by researchers become relatively accessible, it is possible to explore interlanguage errors and conduct error analysis (EA) on learner-generated texts. The necessity to cogitate over these authentic learner errors in designing foreign language learning programs and remedial teaching materials has been widely emphasized by many researchers (see e.g., Juozulynas, 1994; Mitton, 1996; Cowan, Choi, & Kim, 2003; Ndiaye & Vandeventer Faltin, 2003; Allerton et al., 2004). This study aims at conducting a corpus-based error analysis of agreement errors to reveal the related error categories between Greek and Turkish EFL learners, the distribution of agreement errors along the B1 - C2 proficiency range according to CEFR, and the distribution of agreement error types in respect of the L1 of the learners. The data analyzed in this study is extracted from the Cambridge Learner Corpus (CLC), the largest annotated test performance corpus which enables the investigation of the linguistic and rhetorical features of the learner performances in the above stated proficiency bands. The findings from this study reveal that, across B1-C2 proficiency levels and across different registers and genres, the most common agreement error categories by the frequency in which they occur are Verb Agreement (AGV), Noun Agreement (AGN), Anaphor Agreement (AGA), Determiner Agreement (AGD), Agreement Error (AG), and Quantifier Agreement (AGQ) errors. This study’s approach uses the techniques of computer corpus linguistics and follows the steps of the Error Analysis framework proposed by Corder (1971): identification, description, classification and explanation of errors

Integración de la consulta de alfabetización de corpus en la formación de profesores de idiomas: Diseño, implementación y evaluación del curso

This qualitative study presents a corpus literacy course designed and implemented at an undergraduate language teacher education program in Turkey, and its evaluation by pre-service ELT teachers. The course introduces the main concepts of corpus linguistics, raises future teachers’ linguistic and pedagogical awareness through corpus applications, and introduces them to corpus-informed practices to improve their pedagogical skills. In the first phase of the study, students’ corpus literacy levels were determined through a pre-course survey revealing that most of the participants did not know about corpora and their uses. The second and third phases were devoted to evaluating the course. Initially, student teachers were asked to write minute papers and reflection papers during the semester to evaluate the process. In the final phase, semi-structured interviews and focus group discussions were conducted after the course to explore their overall evaluations. Findings implied that corpus literacy integration into teacher education programs clearly yields positive outcomes, yet only one course is not enough to popularize it among EFL teachers.  Hence, extensive exposure to corpus literacy and curriculum-wide integration in the TEFL programs could contribute to its popularization among future practitioners.Este estudio presenta un curso de alfabetización de corpus diseñado e implementado en un programa de formación de profesores de idiomas de pregrado y su evaluación por profesores de inglés en formación. En la primera fase del estudio, los niveles de alfabetización del corpus de los estudiantes se determinaron a través de una encuesta previa al curso que reveló que la mayoría de los participantes no sabían sobre los corpus y sus usos. La segunda y tercera fase se dedicaron a la evaluación del curso. Inicialmente, se pidió a los estudiantes de magisterio que escribieran actas y un documento de reflexión durante el semestre para evaluar el proceso. En la fase final, se realizaron entrevistas semiestructuradas y discusiones de grupos focales después del curso para explorar sus evaluaciones generales. Los hallazgos implicaron que la integración de la alfabetización del corpus en los programas de formación docente claramente produce resultados positivos, pero solo un curso no es suficiente para popularizarlo entre los docentes de inglés como lengua extranjera. Por lo tanto, una amplia exposición a la alfabetización del corpus y la integración amplia del plan de estudios en los programas TEFL podría contribuir a su popularización entre los futuros profesionales

Body Lift and Drag for a Legged Millirobot in Compliant Beam Environment

Much current study of legged locomotion has rightly focused on foot traction forces, including on granular media. Future legged millirobots will need to go through terrain, such as brush or other vegetation, where the body contact forces significantly affect locomotion. In this work, a (previously developed) low-cost 6-axis force/torque sensing shell is used to measure the interaction forces between a hexapedal millirobot and a set of compliant beams, which act as a surrogate for a densely cluttered environment. Experiments with a VelociRoACH robotic platform are used to measure lift and drag forces on the tactile shell, where negative lift forces can increase traction, even while drag forces increase. The drag energy and specific resistance required to pass through dense terrains can be measured. Furthermore, some contact between the robot and the compliant beams can lower specific resistance of locomotion. For small, light-weight legged robots in the beam environment, the body motion depends on both leg-ground and body-beam forces. A shell-shape which reduces drag but increases negative lift, such as the half-ellipsoid used, is suggested to be advantageous for robot locomotion in this type of environment.Comment: First three authors contributed equally. Accepted to ICRA 201

A Learner Corpus-Based Study on Verb Errors of Turkish EFL Learners

As learner corpora have presently become readily accessible, it is practicable to examine interlanguage errors and carry out error analysis (EA) on learner-generated texts. The data available in a learner corpus enable researchers to investigate authentic learner errors and their respective frequencies in terms of types and tokens as well as contexts in which they regularly occur. The need to consider these authentic learner errors in the design of useful language learning programs and remedial teaching materials has been widely emphasized by many researchers (see e.g., Juozulynas, 1994; Mitton, 1996; Cowan, Choi, & Kim, 2003; Ndiaye & Vandeventer Faltin, 2003; Allerton et al., 2004). This study aims at analyzing inflectional, derivational and word form errors for verbs produced by Turkish EFL learners across six distinct proficiency levels, A1-A2; B1-B2; C1-C2, as defined by Common European Framework of Reference for Languages (henceforth CEFR) (Council of Europe, 2001). The corpus used in this study is the Cambridge Learner Corpus (CLC), the largest annotated test performance corpora which enables the investigation of the linguistic and rhetorical features of the learner performances in the above stated proficiency bands. The findings from this study seem to indicate that, across different proficiency levels and across different registers and genres, the most common verb error categories are incorrect tense of verb (TV), wrong verb choice (RV), wrong verb form (FV), missing verb (MV), and verb agreement (AGV) errors. This study’s approach uses the techniques of computer corpus linguistics and has its roots in the Error Analysis framework as proposed by Corder (1971): identification, description, classification and explanation of errors

“When a foreign language learner becomes a foreign language teacher…” – A cross-cultural study into the affective domain of teaching

The aim of this paper is to characterize early experiences of future teachers of English in Polish and Turkish contexts; describe their emotions and attitudes as well as analyze their evaluations of the past situations. When a foreign language learner becomes a foreign language teacher…, firstly s/he has to transform from a FL student to a FL teacher, develop the ability to talk about one’s early experiences and relate them to future growth. In this sense, narrative inquiry largely helps in contextualizing and transforming one’s experience. The data collected for the study involve narratives produced by Turkish and Polish teacher trainees

BRANCHING NEURAL NETWORKS

A conditional deep learning model that learns specialized representations on a decision tree is described. Unlike similar methods taking a probabilistic mixture of experts (MoE) approach, a feature augmentation based method is used to jointly train all network and decision parameters using back–propagation, which allows for deterministic binary decisions at both training and test time, specializing subtrees exclusively to clusters of data. Feature augmentation involves combining intermediate representations with scores or confidences assigned to branches. Each representation is augmented with all of the scores assigned to the active branch on the computational path to encode the entire path information, which is essential for efficient training of decision functions. These networks are referred to as Branching Neural Networks (BNNs). As this is an approach that is orthogonal to many other neural network compression methods, such algorithms can be combined to achieve much higher compression rates and further speedups