Challenges Facing EFL Teachers in Conducting Summative Speaking Tests: Insights from the University of El Oued English Department

Abstract

The assessment of learners’ speaking abilities is a difficult and complex undertaking for teachers in English as a Foreign Language (EFL) context like Algeria. The purpose of this study is twofold: First, to explore the primary challenges experienced by EFL teachers at the University of El Oued English Department in conducting summative tests of speaking. Second, to identify the potential solutions that can help in addressing the highlighted challenges and improving the quality of summative speaking assessment. To this end, the researchers opted for a qualitative approach depending on semi-structured interviews as tools for data collection. Through purposive sampling technique, ten EFL teachers were selected to participate in this study. Data were analyzed thematically so as to uncover recurrent themes and trends related to the research questions. The findings revealed that the multi-componential nature of speaking, ambiguity of assessment criteria, time limitations and subjective scoring were the most prominent problems. In addition, test anxiety, unauthentic tasks and scoring inconsistencies were also noted among the challenges that further complicate the assessment process. These problems can adversely undermine and impact the validity, reliability and practicality of summative speaking tests. In response, teachers suggested some solutions, such as the use of formative speaking assessment, provision of clear assessment criteria, rater training and technology integration to enhance the accuracy, objectivity and feasibility of speaking assessment. Moreover, this study underscores the need for reforms in designing speaking tests, institutional support, and adopting globally recognized assessment standards, along with leveraging artificial intelligence applications for more valid, consistent and fair summative speaking assessment. Future researchers should examine the effectiveness of technology-assisted speaking assessment in minimizing rater bias, ensuring scoring accuracy and enhancing assessment consistency.