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Mo Zhang; Paul Deane; Andrew Hoang; Hongwen Guo; Chen Li – Educational Measurement: Issues and Practice, 2025
In this paper, we describe two empirical studies that demonstrate the application and modeling of keystroke logs in writing assessments. We illustrate two different approaches of modeling differences in writing processes: analysis of mean differences in handcrafted theory-driven features and use of large language models to identify stable personal…
Descriptors: Writing Tests, Computer Assisted Testing, Keyboarding (Data Entry), Writing Processes
Matthew D. Coss – Language Learning & Technology, 2025
The extent to which writing modality (i.e., hand-writing vs. keyboarding) impacts second-language (L2) writing assessment scores remains unclear. For alphabetic languages like English, research shows mixed results, documenting both equivalent and divergent scores between typed and handwritten tests (e.g., Barkaoui & Knouzi, 2018). However, for…
Descriptors: Computer Assisted Testing, Paper and Pencil Tests, Second Language Learning, Chinese
Jessie S. Barrot – Education and Information Technologies, 2024
This bibliometric analysis attempts to map out the scientific literature on automated writing evaluation (AWE) systems for teaching, learning, and assessment. A total of 170 documents published between 2002 and 2021 in Social Sciences Citation Index journals were reviewed from four dimensions, namely size (productivity and citations), time…
Descriptors: Educational Trends, Automation, Computer Assisted Testing, Writing Tests
Yue Huang; Joshua Wilson – Journal of Computer Assisted Learning, 2025
Background: Automated writing evaluation (AWE) systems, used as formative assessment tools in writing classrooms, are promising for enhancing instruction and improving student performance. Although meta-analytic evidence supports AWE's effectiveness in various contexts, research on its effectiveness in the U.S. K-12 setting has lagged behind its…
Descriptors: Writing Evaluation, Writing Skills, Writing Tests, Writing Instruction
Dan Song; Alexander F. Tang – Language Learning & Technology, 2025
While many studies have addressed the benefits of technology-assisted L2 writing, limited research has delved into how generative artificial intelligence (GAI) supports students in completing their writing tasks in Mandarin Chinese. In this study, 26 university-level Mandarin Chinese foreign language students completed two writing tasks on two…
Descriptors: Artificial Intelligence, Second Language Learning, Standardized Tests, Writing Tests
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
Neha Biju; Nasser Said Gomaa Abdelrasheed; Khilola Bakiyeva; K. D. V. Prasad; Biruk Jember – Language Testing in Asia, 2024
In recent years, language practitioners have paid increasing attention to artificial intelligence (AI)'s role in language programs. This study investigated the impact of AI-assisted language assessment on L2 learners' foreign language anxiety (FLA), attitudes, motivation, and writing skills. The study adopted a sequential exploratory mixed-methods…
Descriptors: Artificial Intelligence, Computer Software, Computer Assisted Testing, Second Language Instruction
Shoeb Saleh; Abdullah Ibrahim Alsubhi – Language Testing in Asia, 2025
This study inspected how techno-competence in artificial intelligence (AI)-driven evaluations affected EFL learners' boredom, self-esteem, and writing skills. To do so, 66 Saudi Arabian male students from Saudi Arabia participated in the study. They were then split into the experimental group (EG) and the control group (CG). While the CG was…
Descriptors: Self Esteem, Writing Skills, Artificial Intelligence, English (Second Language)
Omid S. Kalantar – International Journal of Language Testing, 2024
This study sought to identify the challenges and needs of TOEFL iBT candidates in achieving C1 level scores in the speaking and writing sections of the exam. To this end, the researcher employed a mixed-method approach to collect data from a population of 46 students, both male and female, between the ages of 22 and 30. The participants were…
Descriptors: Language Tests, Scores, Native Language, Grammar