The present study aims at investigating some English speaking problems found by the students of English language education department at State Islamic Institute of Kudus and exploring some implications for speaking curriculum development of English language education department. This study used a descriptive qualitative approach and the data were taken from semi-structured interviews, observation and focus group discussion (FGD). The results of the analysis reveal that the problems encountered by the students in English language education department in speaking English cover the lack of appropriate vocabulary, the lack of grammar mastery, the lack of correct pronunciation, the lack of input of English outside the class, the lack of confidence and the lack of English speaking curriculum development. There have been some implications for developing English speaking curriculum. First, the curriculum of speaking should be well designed. Second, lecturers should design English speaking curriculum integrated by technology and social media that makes students to enrich some culture, knowledge and experience around the world. Third, lecturers should facilitate the English speaking curriculum with the English speaking community so that the students will have more chance to speak English inside and outside the class.

Successfully solving reality-based tasks requires both mathematical and text comprehension skills. Previous research has shown that mathematical tasks requiring language proficiency have lower solution rates than those that do not, indicating increased difficulty through textual input. Therefore, it is plausible to assume that a lack of text comprehension skills leads to performance problems. Given that different sociodemographic characteristics and cognitive factors can influence task performance, this study aims to determine whether text comprehension mediates the relationship between these factors and competence in solving reality-based tasks. Additionally, it examines the impact of systematic linguistic variation in texts. Using an experimental design, 428 students completed three reality-based tasks (word count: M = 212.4, SD = 19.7) with different linguistic complexities as part of a paper-pencil test. First, students answered questions about the situation-related text comprehension of each text, followed by a mathematical question to measure their competence in solving reality-based tasks. The results indicate that: a) Tasks with texts of lower linguistic complexity have a significantly higher solution rate for both text comprehension (d = 0.189) and mathematical tasks (d = 0.119). b) Cognitive factors are significant predictors of mathematical solutions. c) Text comprehension mediates the relationship between the impact of students’ cultural resources and cognitive factors and their competence to solve reality-based tasks. These findings highlight the importance of linguistic complexity for mathematical outcomes and underscore the need to reinforce text comprehension practice in mathematical education owing to its mediating role.

Children today encounter English in various contexts, with cartoons serving as a particularly influential medium. Beyond their entertainment value, cartoons also promote incidental foreign language acquisition. This article presents the findings of a study involving 240 sixth-grade pupils from Slovenian primary schools. Employing a quantitative approach, the study utilised both a questionnaire and a knowledge test to explore the relationship between English cartoon viewing and incidental vocabulary acquisition. It examined the frequency of cartoon viewing, pupils’ attitudes towards English-language cartoons, and the impact of subtitles on vocabulary test performance. The results indicate that a higher frequency of cartoon viewing, positive attitudes towards English cartoons, and the use of English subtitles are significantly associated with enhanced English vocabulary knowledge. The findings underscore the educational value of English cartoons in supporting vocabulary development and highlight the potential of engaging multimedia content in fostering incidental vocabulary acquisition in both classroom settings and out-of-school contexts. Consequently, educators should incorporate cartoon-based materials to enhance vocabulary learning, introduce authentic language exposure, and provide multi-sensory experiences tailored to varying learner preferences and proficiency levels.

Text readability assessment stands as a fundamental component of foreign language education because it directly determines students' ability to understand their course materials. The ability of current tools, including ChatGPT, to precisely measure text readability remains uncertain. Readability describes the ease with which readers can understand written material, while vocabulary complexity and sentence structure, along with syllable numbers and sentence length, determine its level. The traditional readability formulas rely on data from native speakers yet fail to address the specific requirements of language learners. The absence of appropriate readability assessment methods for foreign language instruction demonstrates the need for specialized approaches in this field. This research investigates the potential use of ChatGPT to evaluate text readability for foreign language students. The examination included selected textbooks through text analysis with ChatGPT to determine their readability level. The obtained results were evaluated against traditional readability assessment approaches and established formulas. The research aims to establish whether ChatGPT provides an effective method to evaluate educational texts for foreign language instruction. The research evaluates ChatGPT's capabilities beyond technical aspects. The study examines how this technology may influence students' learning experiences and outcomes. The text clarity evaluation capabilities of ChatGPT might lead to innovative approaches for developing educational tools. The implementation of this approach would generate lasting benefits for educational practices in schools. For example, ChatGPT’s readability classifications correlated strongly with Flesch-Kincaid scores (r = .75, p < .01), and its mean readability rating (M = 2.17, SD = 1.00) confirmed its sensitivity to text complexity.