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Misconceptions on the topic of waves are a systemic problem in high school physics learning that requires a comprehensive diagnostic instrument. Conventional diagnostic instruments up to the four-tier generation have limitations in revealing the conceptual structure behind students' thinking errors. This study aims to develop a five-tier multi-representation diagnostic instrument on the topic of waves using the 4D model (Define, Design, Develop, Disseminate). The main innovation of this instrument lies in the integration of multi-representations (verbal, pictures, graphics, mathematical) in Tier 1 and the addition of a paraphrase tier (Tier 5) that asks students to rewrite their understanding in their own words. The development process includes needs analysis, designing a grid of 16 questions, validation by two experts, and a limited trial on 34 grade XI students of SMAN 13 Kota Jambi. The results of expert validation showed an average percentage of 91.25% (Very Good) from both validators. Content validity was met with a percentage of False Positive (FP) of 6.80% and False Negative (FN) of 4.41%, both below the 10% threshold. Construct validity was confirmed through a significant Product Moment correlation (r = 0.342–0.348; sig. < 0.05) and factor analysis with six significant factors (eigenvalue > 1). The instrument's reliability was high, with a Cronbach's Alpha of 0.726. This instrument is expected to help physics teachers diagnose students' misconceptions more precisely and thoroughly on the topic of waves.

This study aims to analyze the influence of social support and soft skills on the work readiness of the 2022 cohort students in Tasikmalaya City. Work readiness is an essential aspect that students must possess to face increasingly competitive labor market demands. This research employed a quantitative approach using a survey method. Data were collected through an online questionnaire distributed to 110 respondents selected from a population of 150 students using the Slovin formula with a 5% margin of error and a simple random sampling technique. Data analysis was conducted using multiple linear regression with the assistance of IBM SPSS Statistics 25. Prior to hypothesis testing, validity and reliability tests were performed to ensure the quality of the research instruments. In addition, classical assumption tests, including normality, multicollinearity, heteroscedasticity, autocorrelation, and linearity tests, were conducted to verify the suitability of the regression model. The findings indicate that both social support and soft skills have a positive and significant effect on students’ work readiness. Support from family, peers, and the academic environment enhances students’ confidence in preparing for employment. Furthermore, communication skills, teamwork, problem-solving abilities, and responsibility as components of soft skills strengthen students’ readiness to enter the professional workforce. These findings highlight the importance of developing soft skills and strengthening social support to improve students’ work readiness.

The quick advancement of digital technology has drastically changed the social and religious life of Indonesian teenagers. The purpose of this study is to investigate how pupils at Al Muslim Junior High School's daily worship practices, self-control, and fear of missing out (FoMO) affect the principles of Islamic Religious Education (PAI). The study used a quantitative methodology with a causal and correlational design. All students in grades VII, VIII, and IX made up the study population for the 2025–2026 school year. Using the Slovin formula, a proportionate stratified sample of 171 students with a 5% margin of error was chosen. A five-point Likert scale questionnaire was used to gather data. The Pearson Product-Moment correlation (r > 0.30) was used to evaluate validity, while Cronbach's Alpha (α > 0.70) was used to test reliability. Multiple linear regression using SPSS version 26 was used for quantitative analysis, beginning with traditional assumption tests for heteroscedasticity (Glejser), multicollinearity (VIF), and normality (Kolmogorov-Smirnov). According to the analysis results, self-control had a substantial, favorable impact on the practice of PAI values, but FoMO had no significant influence (β = -0.034, p = 0.530).

Scientific writing is one of the essential skills that college students need to support research activities and the development of knowledge. However, students still encounter various challenges during the writing process. This study aimed to identify students’ responses toward scientific activities at FMIPA Universitas Negeri Surabaya and to examine the difficulties experienced by students in preparing scientific papers. The study employed a qualitative descriptive method using a purposive sampling technique. The research subjects consisted of 36 students from various study programs at FMIPA Universitas Negeri Surabaya who had been involved in research activities and scientific proposal writing. Data were collected through student response questionnaires consisting of closed-ended and open-ended questions. The data were analyzed descriptively and presented in tables and narrative descriptions. The results showed that most students had understood the existing student research programs and were familiar with the use of research guidelines. However, students still faced difficulties in systematically organizing research ideas, determining research variables and methods, finding relevant literature reviews, and connecting theories from various references. In addition, time management and the use of citation management applications were also obstacles for some students. Therefore, more structured assistance is needed through scientific writing training, reference searching training, and the use of citation management applications to improve the quality of students’ scientific writing.

The ability to describe graphs accurately in English is an essential academic skill for EFL learners, particularly in higher education contexts where students are required to interpret and communicate visual data. However, many learners still experience difficulties in producing grammatically accurate graph descriptions. This study aims to investigate the level of grammatical accuracy demonstrated by EFL learners in graph description tasks and identify the grammatical aspects that require further improvement. Employing a descriptive qualitative approach, the research analyzed 30 samples of students’ written graph descriptions produced by undergraduate learners. The analysis focused on several grammatical aspects, including subject–verb agreement, tense consistency, article usage, sentence structure, prepositions, and punctuation. The findings reveal that students frequently struggle with subject–verb agreement and article usage, while punctuation errors occurred less frequently. The study highlights that grammatical accuracy remains an important challenge for EFL learners in academic writing tasks involving data interpretation. Therefore, it is recommended that grammar instruction be integrated more intensively into graph description activities in English classes. The findings are expected to contribute to the development of more effective teaching strategies in academic writing instruction for EFL learners.

Nahwu (Arabic grammar) is a fundamental discipline in learning the Arabic language, helping to prevent errors in speech and serving as a primary key to clearly understanding Islamic legal texts. However, in practice, the teaching of Nahwu often faces complex challenges, particularly the lack of active participation among female students and their uneven mastery of the subject. Therefore, this study aims to explore the problems in teaching Nahwu at Al-Madani Islamic Boarding School in Cikalong and to identify the factors causing these issues. This study aims to: (1) reveal the problems faced by second-grade female students of KMI in learning Nahwu at Al-Madani Islamic Boarding School in Cikalong, and (2) identify the contributing factors influencing the emergence of these problems. This research employs a descriptive qualitative approach. The researcher used three data collection techniques: classroom observation, in-depth interviews with the Nahwu teacher, and questionnaires distributed to the students. For data analysis, the researcher applied the Miles and Huberman model, which consists of data reduction, data display, and conclusion drawing. To ensure data validity, data triangulation techniques were used. The results of the study indicate that the problems are divided into two main aspects: (1) learning-related problems, including the gap between memorization of grammatical rules and their application (i‘rab), high levels of academic anxiety, and decreased classroom concentration; and (2) contributing factors, including methodological factors, linguistic-psychological factors, and classroom management factors. The researcher suggests that teachers adopt more interactive teaching methods and media, as well as innovative visual tools to reduce the abstract nature of Nahwu materials and enhance students’ functional understanding. Additionally, activating “Halaqah Nahwiyyah” (grammar study circles) in dormitories is recommended to overcome psychological barriers and improve students’ linguistic confidence.

This study aims to identify and explain language errors in a scientific journal article entitled "Analysis of Language Errors in Expository Texts on the Digital Platform 'Ruangguru', August 2024 Edition as a Reading Resource for High School Students," published in the Semantik Journal, Issue 3, Number 4. The method applied in this study is descriptive qualitative using a literature study approach. For data collection, observation and recording techniques were used, while data analysis was carried out using the content analysis method. The findings of this study revealed 27 language errors divided into five categories, including 12 spelling errors (typos) (44.4%), 5 word choice errors (18.5%), 4 punctuation errors (14.8%), as well as ineffective sentence structure errors and errors in the bibliography (3 each) (11.1%). The causes of these errors include minimal editing process, inadequate understanding of PUEBI (Indonesian Standards for Ethics and Education), and inaccuracies from the author. This study shows that articles analyzing language errors still contain errors, so there is a need for improvements in the quality of editing by the author and the journal's editorial team.

This study aims to identify the learning needs of deaf students in internship programs, examine the challenges they face, develop appropriate solutions, and design as well as evaluate a visual module-based learning model to improve their work skills. The study used a Research and Development (R&D) approach with a 4D model: Define, Design, Develop, and Disseminate. The participants included deaf students from special needs high schools (SMALB) involved in vocational internships, mentor teachers, and industry supervisors. Data were collected through observation, interviews, questionnaires, documentation, and focus group discussions, and analyzed using qualitative techniques supported by descriptive analysis. The findings indicate that deaf students require visual, structured, and easily understandable work instructions supported by symbols, color codes, and guidance materials. Major challenges include limited verbal communication, difficulty understanding instructions, and risks of procedural errors. To address these issues, a systematic and communicative visual module-based learning model was developed, incorporating collaborative support from schools and industry. The resulting model integrates planning, implementation, mentoring, and evaluation stages, and has proven feasible and effective in enhancing students’ independence, technical competence, and overall work readiness.

This study analyzes junior high school students' errors in solving mathematics problems involving integers. This study was conducted through a systematic literature review of 12 related research articles published between 2021 and 2026. The analysis shows that students' errors in integers include contextual, procedural, and technical (calculation) errors. The most common conceptualization errors were found in the understanding of positive and negative signs and the rules for mixed operations. The main causes of errors are a lack of in-depth conceptual understanding, the habit of memorizing without understanding, and a lack of practice using concrete media. Internal factors such as learning motivation and external factors such as learning methods and media also contribute. This study recommends that the mathematics learning process emphasize meaningful conceptual understanding, the use of concrete media, and learning strategies that engage students' mathematical connection skills. Thus, difficulties in learning integers can be minimized sustainably.

This research aims to analyze the structure and identify various forms of linguistic errors found in students’ research reports. A qualitative approach with a descriptive method was employed, using documentation studies on three different students’ research reports as the primary data. The findings indicate discrepancies in the text structure, such as unsystematic composition of the introduction, methodology, results, discussion, and conclusion sections. Furthermore, various linguistic errors were identified, including spelling, punctuation, diction, ineffective sentence construction, and inconsistencies in citations and references. Other identified issues include content duplication, technical errors in word processing features, and lack of relevance in the theoretical review. The implications of this research emphasize the necessity of improving the quality of research report writing through strengthened academic writing curricula, structured mentoring, the use of reference management technology, and a disciplined scientific literacy culture. This study is expected to serve as an evaluation tool for students, lecturers, and study programs to enhance the standards of scientific writing in higher education.

This study aims to compare the performance of Multiple Linear Regression (MLR) and Random Forest Regression (RFR) in predicting student performance based on academic scores. Student performance is defined as the average of math scores, Reading Scores, and writing scores. This study uses a quantitative approach with a comparative design based on predictive modeling. The data used is secondary data from the Student Prediction dataset obtained through the Kaggle platform, which was processed using the Python programming language through the Google Colab platform. The analysis stages included the formation of performance variables, the separation of training and test data with a ratio of 80:20, model training, and evaluation using the Mean Squared Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R²) metrics. The results show that the Multiple Linear Regression model produced an MSE value of 2.74 × 10⁻²⁸, an MAE of 1.51 × 10⁻¹⁴, and an R² of 1.000. Meanwhile, Random Forest Regression produced an MSE of 0.296, an MAE of 0.375, and an R² of 0.998. These findings indicate that both models have a very high level of accuracy, but Multiple Linear Regression provides the best performance. This is due to the strong linear relationship between the input variables and the target variables formed directly from the combination of academic values. Thus, the linear regression model is proven to be more suitable for use in data structures that have simple linear relationships compared to ensemble-based models.

International student enrollment is a critical driver of financial sustainability for Higher Education Institutions (HEIs). While advanced forecasting is standard in the corporate sector, its application in educational planning remains limited. This study addresses this gap by comparing the predictive performance of ARIMA, Facebook Prophet, and Long Short-Term Memory (LSTM) models. Using a publicly available annual dataset from a US-based institution (2000–2022), the analysis employed a strategic partition training on 2000–2017 and testing on 2018–2019 to validate models on stable, pre-pandemic data. Empirical results revealed that the statistical ARIMA (2,1,0) model demonstrated superior accuracy, achieving a Mean Absolute Percentage Error (MAPE) of 1.26%. Conversely, Prophet (11.81%) and LSTM (13.84%) struggled with the limited sample size, failing to generalize effectively compared to the linear approach. The findings suggest that for annual enrollment trends, parsimonious statistical models outperform complex deep learning architectures, providing administrators with a robust, accessible framework for data-driven strategic decision-making.

English is an international language that plays an important role for students in the era of globalization; however, speaking anxiety or fear of speaking remains a major obstacle in academic practice within higher education institutions. This anxiety emerges as a complex psychological phenomenon involving cognitive, affective, and social aspects, rather than merely an issue of language proficiency. This study examines the problems faced by students, particularly those majoring in non English disciplines, in overcoming speaking anxiety in English academic settings. A descriptive qualitative approach was employed, with data collected through semi-structured interviews involving students of PASIM National University who exhibited varying levels of speaking anxiety. The data were analyzed using qualitative analysis techniques to identify emerging patterns and themes.The findings indicate that speaking anxiety is caused by fear of making pronunciation and grammatical errors, concern about receiving negative evaluations, limited vocabulary, and a lack of experience in communicating in English. These conditions are further exacerbated by limited opportunities for speaking practice, non-interactive learning methods, and insufficient support from teachers and peers. Students developed adaptive strategies such as relaxation techniques, thorough preparation, positive self-talk, and consistent language practice. To create a safe learning environment in which students can speak English effectively, this study proposes learning strategies that are more inclusive, supportive, and grounded in psychological principles.  

Students of vocational high schools are required to write an internship report as a form of accountability for completing their industrial training. However, various language errors are still found in students’ PKL reports. This study aims to describe and analyze morphological errors in the PKL reports of vocational high school students majoring in Electronics Engineering. The study employed a descriptive qualitative approach using document analysis. A total of 223 PKL reports were written by all students of SMK Negeri 3 Yogyakarta in 2025. The research data consisted of 25 PKL reports from students of the Electronics Engineering major selected through purposive sampling. Data analysis was carried out through the stages of identification, classification, description, quantification, and interpretation of morphological errors, with data validity ensured through theoretical triangulation. The results show that 286 morphological errors were identified, consisting of prefix errors (96), suffix errors (52), confix errors (41), reduplication errors (28), compound word errors (34), and base-form errors (35). Prefix errors were the most dominant type, accounting for 33.6% of all errors. These findings indicate that students still experience difficulties in applying affixation rules and forming standard words in formal written language. Such errors are influenced by interference from spoken language and the technical language used in the workplace. This study highlights the importance of structured and contextual morphology instruction to improve the quality of vocational students’ PKL report writing.