Inclusive Foreign Language Assessment in Trying Times: Pre-service Teachers’ Attribution Mechanisms and Their Implications for Inclusive Emergency Remote Teaching

Abstract

The main goal of foreign language education (FLE) to foster intercultural communicative competence implies the need to include and connect diverse learners (e.g. Council of Europe, 2001) and thereby aligns itself with key principles of inclusive education. Yet, the pursuit of communicative competence (CC) is a task that often divides rather than includes. In the German context FLE was long regarded not worth pursuing among students with special educational needs (cf. Kleinert et al. 2007; Morse 2008; Dose 2019). As a construct, CC is also multifaceted enough to display considerable individual differences between learners. In research, “good learners” have been linked with higher levels of FL success compared than to “low-achieving” or “poor” learners (e.g. Ganschow & Sparks 1995; Nunan, 1995).
Such categorizations can hardly be considered inclusive (Clough & Corbett 2000). In fact, attributing “poor” observable behavior (e.g. "does not keep a conversation going") to dispositional traits (e.g. "is a poor learner"), rather than to external factors (e.g. "does not like the task") is one of the most commonly documented biases in social perception research, called the fundamental attribution error (Ross, 1977). Errors of this sort are likely to happen when assessment takes place under uncertainty or is based on limited contact with learners, e.g. in emergency remote teaching settings. This contribution presents the results of a quantitative questionnaire study which confirms that (pre-service) FL teachers are indeed prone to the fundamental attribution error in their evaluation of FL learners and discusses implications for remote emergency assessment.



Author Information
Joanna Pfingsthorn, University of Bremen, Germany
Julia Weltgen, University of Bremen, Germany

Paper Information
Conference: ECE2021
Stream: Assessment Theories & Methodologies

This paper is part of the ECE2021 Conference Proceedings (View)
Full Paper
View / Download the full paper in a new tab/window


Comments & Feedback

Place a comment using your LinkedIn profile

Comments

Share on activity feed

Powered by WP LinkPress


Share this Research

Posted by amp21