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Download full textOsama Koraishi – Language Teaching Research Quarterly, 2024
This study conducts a comprehensive quantitative evaluation of OpenAI's language model, ChatGPT 4, for grading Task 2 writing of the IELTS exam. The objective is to assess the alignment between ChatGPT's grading and that of official human raters. The analysis encompassed a multifaceted approach, including a comparison of means and reliability…
Descriptors: Second Language Learning, English (Second Language), Language Tests, Artificial Intelligence
Ahmet Can Uyar; Dilek Büyükahiska – International Journal of Assessment Tools in Education, 2025
This study explores the effectiveness of using ChatGPT, an Artificial Intelligence (AI) language model, as an Automated Essay Scoring (AES) tool for grading English as a Foreign Language (EFL) learners' essays. The corpus consists of 50 essays representing various types including analysis, compare and contrast, descriptive, narrative, and opinion…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Teaching Methods
Direct linkHeidari, Nasim; Ghanbari, Nasim; Abbasi, Abbas – Language Testing in Asia, 2022
It is widely believed that human rating performance is influenced by an array of different factors. Among these, rater-related variables such as experience, language background, perceptions, and attitudes have been mentioned. One of the important rater-related factors is the way the raters interact with the rating scales. In particular, how raters…
Descriptors: Evaluators, Rating Scales, Language Tests, English (Second Language)
Investigating the Impact of Rater Training on Rater Errors in the Process of Assessing Writing Skill
Sata, Mehmet; Karakaya, Ismail – International Journal of Assessment Tools in Education, 2022
In the process of measuring and assessing high-level cognitive skills, interference of rater errors in measurements brings about a constant concern and low objectivity. The main purpose of this study was to investigate the impact of rater training on rater errors in the process of assessing individual performance. The study was conducted with a…
Descriptors: Evaluators, Training, Comparative Analysis, Academic Language
Pearson, William S. – Language Testing in Asia, 2019
It is becoming increasingly important for individuals for whom English is a second language to demonstrate their linguistic credentials for academic, work and employment purposes. One option is to undertake International English Language Testing System (IELTS), which involves attempting to meet the linguistic entrance criteria set by a gatekeeping…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Cutting Scores
Ahmadi Shirazi, Masoumeh – SAGE Open, 2019
Threats to construct validity should be reduced to a minimum. If true, sources of bias, namely raters, items, tests as well as gender, age, race, language background, culture, and socio-economic status need to be spotted and removed. This study investigates raters' experience, language background, and the choice of essay prompt as potential…
Descriptors: Foreign Countries, Language Tests, Test Bias, Essay Tests
Müller, Amanda – Higher Education Research and Development, 2015
This paper attempts to demonstrate the differences in writing between International English Language Testing System (IELTS) bands 6.0, 6.5 and 7.0. An analysis of exemplars provided from the IELTS test makers reveals that IELTS 6.0, 6.5 and 7.0 writers can make a minimum of 206 errors, 96 errors and 35 errors per 1000 words. The following section…
Descriptors: English (Second Language), Second Language Learning, Language Tests, Scores
