This study aims to review the impact of the interactive story reading method on 48-72 month children’s vocabulary based on receptive and expressive language. The study group is 52 children in the 48-72 months age group at the nurseries of primary schools at Ankara province. The research employed a combined pattern analyzing both quantitative and qualitative data. The data were collected via "General Information Form" ,"Expressive and Receptive Language Test in Turkish (TIFALDI)" developed under the leadership of Gul Guven and Berument The "Teacher Observation Form", the "Teacher Interview Form" and the "Family Interview Form". In conclusion of the study, a significant difference in favor of the experiment group in the posttest was observed with respect to average posttest scores of experiment and control groups, following the implementation of the Interactive Story Reading Program. The comparison of the follow-up test and pretest score averages revealed a significantly high value in favor of the total for the follow-up test for the children in the experiment group. The agreement among the forms filled out by two observers with reference to the results of the observation and video analysis regarding the implementation of the "Interactive Story Reading Method" by the teachers, was assessed to be good/very good agreement. In the light of these results it can be said that the interactive story reading method have a fundamental impact on receptive and expressive vocabulary knowledge of 48-72 months old children.

Cognitive is an essential developmental aspect for children. The cognitive barrier is one of the learning barriers experienced by children with autism. From educational perspective, teacher language input can appropriately develop cognitive abilities of autistic students. This study aims to describe (1) teacher’s language input for recognizing the cognitive abilities of autistic students in classroom interactions and (2) cognitive abilities of autistic students based on teacher language input in classroom interactions. The approach of the study was conducted qualitatively with case study, while source of data was oral texts from the teacher language input toward autistic students in classroom. The results shows that the cognitive abilities of autistic students can be recognized through teacher's language input in classroom learning by engaging interrogative speech acts, such as representative, directive, expressive, and commissive. The cognitive level is used to see the variants of the teacher's language input. Meanwhile, the acquisition of students' cognitive abilities based on teacher language’s input is developed through memorizing, understanding, applying, and analyzing skills with criteria student A and B in the medium category, and G in low category.

Speech therapy uses a combination of approaches to assess speech and language, including analysis of spontaneous speech, use of standardized scales and assessment by the child’s parents and/or preschool teachers. In this paper, we present the Teddy Talk Test. Using a sample of sixteen children aged 4 to 5 years, we examined whether the test provided representative data on child language development. The parent questionnaire included information on the parents’ education, the parents’ native language, the child’s gender and the language the parents speak with their child. It was found that the Teddy Talk Test has the characteristics of screening tests for speech and language: it is time-efficient, it covers receptive and expressive language tasks, and it allows for rapid assessment of speech and language in large numbers of children. However, since the Teddy Talk Test has not yet been evaluated, we do not know its value regarding sensitivity, specificity and predictive validity.

This preliminary study examines how three generative AI tools, ChatGPT-4, Google Gemini, and Microsoft Copilot, support B+ level English as a Foreign Language (EFL) students in opinion essay writing. Conducted at a preparatory school in Türkiye, the study explored student use of the tools for brainstorming, outlining, and feedback across three essay tasks. A mixed methods design combined rubric-based evaluations, surveys, and reflections. Quantitative results showed no significant differences between tools for most criteria, indicating comparable performance in idea generation, essay structuring, and feedback. The only significant effect was in the feedback stage, where ChatGPT-4 scored higher than both Gemini and Copilot for actionability. In the brainstorming stage, a difference in argument relevance was observed across tools, but this was not statistically significant after post-hoc analysis. Qualitative findings revealed task-specific preferences: Gemini was favored for clarity and variety in brainstorming and outlining, ChatGPT-4 for detailed, clear, and actionable feedback, and Copilot for certain organizational strengths. While the tools performed similarly overall, perceptions varied by task and tool, highlighting the value of allowing flexible tool choice in EFL writing instruction.