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Blind students exclusively use braille materials for teaching math. Teaching tools that assist blind students' motor and hearing nerves are essential for learning. This study was to describe learning mathematics outcomes for blind students after using teaching material for Android devices based on Newman's theory. This research was a case study of blind students. Blind junior high school students from special schools for visual impairment-- extraordinary schools in Bandar Lampung, extraordinary schools in Cimahi, and Madrasah Tsanawiyah with special education in Yogyakarta-- contributed to the study's subjects. The study employed questionnaires and test questions as research instruments for both teachers and students. The results of this study demonstrate that learning mathematics outcame blind students' after using teaching material with Android apps based on Newman's theory, specifically: i) reading errors: students can understand the information in the questions; ii) comprehension errors: students do not write down things that are known and asked; and iii) transformation errors: students write down the mathematical model (formula) used; iv) skill errors: students can do calculations correctly; and v) coding errors: students do not write conclusions. The average score of the blind students' results using braille was higher than that of the Android application.

Academic writing is a salient skill for medical students all over the world. Academic writing starts with composing effective paragraphs, laying the foundation for students' advancement in writing during college. This study investigated common mistakes in English paragraph writing committed by the first-year medical students of the Medicine Faculty at Kabul University of Medical Sciences. Additionally, it measured the challenges that Medicine Faculty students tackled in paragraph writing. This quantitative study was conducted through an action research design. The data were collected from 52 medical students, and their work was analyzed using the developed rubrics. The data were analyzed in the SPPS 26 version, and the descriptive statistics were reported. The findings revealed that participants obtained the highest means in the mechanics of paragraph writing (22 out of 25), and they received the lowest means (12 out of 25) in the contents of a paragraph. In English for Medical Purposes (EMP), students should improve their content finding, paragraphing, summarizing, and referencing skills for their assignments and research writings. Medical students should give detailed attention to every characteristic of academic paragraph writing because they give readers a full grasp of the contents of their written works.

Many countries do not include the normal distribution concept in their middle school mathematics curriculum, but on the grounds that middle school mathematics teachers need to know more than just mathematics, researchers argue that preservice teachers (PTs) ought to have knowledge and skills in this area. This study was aimed to investigate PTs' subject matter knowledge (SMK) about the normal distribution. Data was collected from 120 PTs attending a state university through a questionnaire. PTs were asked to evaluate a variety of examples of the normal distribution. The data were analyzed using descriptive statistics and item-based analysis. It was found that the PTs were more knowledgeable about the features of the normal distribution than about standard deviation. Real-life situations made it difficult for them to interpret the concepts associated with normal distributions. Normal distribution curves were more easily interpreted by the PTs. It was determined that their mistakes were the result of their not establishing connections between statistical concepts, and their operational evaluation of concepts. Additionally, PT errors were caused by failure to establish a relationship between probability values and the area covered by the curve and making errors in operation.

This study investigates the performance of GPT-4, an advanced AI model developed by OpenAI, on the force concept inventory (FCI) to evaluate its accuracy, reasoning patterns, and the occurrence of false positives and false negatives. GPT-4 was tasked with answering the FCI questions across multiple sessions. Key findings include GPT-4's proficiency in several FCI items, particularly those related to Newton's third law, achieving perfect scores on many items. However, it struggled significantly with questions involving the interpretation of figures and spatial reasoning, resulting in a higher occurrence of false negatives where the reasoning was correct, but the answers were incorrect. Additionally, GPT-4 displayed several conceptual errors, such as misunderstanding the effect of friction and retaining the outdated impetus theory of motion. The study's findings emphasize the importance of refining AI-driven tools to make them more effective in educational settings. Addressing both AI limitations and common misconceptions in physics can lead to improved educational outcomes.

This article examines the use of prompt-based lexical collocations in opinion essays by Vietnamese English as a foreign language (EFL) students. Fifty second-year English majors at a Vietnamese university wrote 100 opinion essays on two topics as progress tests. The AntConc programme (Anthony, 2020) was employed to identify the frequencies of use of the prompt-based lexical collocations in the essays. Paraphrases of the target lexical collocations were further identified and calculated for their occurrences. The AntConc concordance lines that target the prompt-based collocations or paraphrases were analysed for errors, with the consultation of the Oxford Collocations Dictionary (OCD), the British National Corpus (BNC), and the Corpus of Contemporary American English (COCA). The results revealed that students repeated the source lexical collocations and replaced them with various word combinations, though recycling occurred to a greater extent. Erroneous use involved use of i) incorrect word combinations, mainly through wrong choice of verbs, adjectives, or nouns that do not collocate with adjacent words and ii) incorrect grammatical forms of the individual lexical words of the target collocations (i.e., omission of plural marker --s, misuse of parts of speech). Pedagogical implications are discussed to assist students in using lexical collocations appropriately in L2 writing.

We conducted a descriptive study among first-year engineering students at the Anton de Kom University of Suriname. We analyzed students' errors regarding necessary prior knowledge in a calculus A exam. We found that the stage of the solution in which prior knowledge is required impacts the importance of prior knowledge. We also found that many errors concerned basic algebra and trigonometry concepts and skills. We concluded that even though the required prior knowledge concerns basic algebra and trigonometry, the stage of the solution in which prior knowledge is needed is of great importance.

Mathematics proficiency in the Philippines is a persistent concern, seen by many as a sign of an educational crisis. Teachers are responsible for improving learning outcomes in any discipline, including math. Thus, the study intended to conduct an error analysis of verbal problems among pre-service mathematics teachers. The researcher employed descriptive research and Newman's Error Analysis to suffice the research objectives. The findings revealed low levels of error in reading stage, but moderate levels of error in comprehension, transformation, process skills, and encoding stages. In addition, underlying factors contributing to these errors were incomplete solutions and answers, incorrect or incomplete processes, grammatical errors, conversion errors, and failure to indicate an answer. The researchers concluded that pre-service teachers are proficient in the early stage of problem solving, but challenged in properly constructing equations, the utility of operations, and interpreting their results.

The issue of students' difficulties in solving context-based mathematics problems has been extensively investigated by numerous studies. However, limited study focus on how pre-service primary school teacher (PSPSTs) encounter difficulties in solving context-based fundamental mathematics problems. To fill this gap, this study aims to investigate PSPSTs' difficulties encountered while solving context-based mathematics tasks by identifying the error type they made based on the error classification proposed in Newman Error Analysis (NEA). This is an error analysis study with a summative qualitative content analysis approach involving 87 PSPSTs in an Indonesian Islamic University. Data were collected through a test, in-depth interviews and document analysis of the PSPSTs' responses. Data were analyzed qualitatively and quantitatively. Qualitative content analysis was performed using Atlas.ti software. The findings revealed that many PSPSTs encounter difficulties in solving context-based problems. Approximately 22.1% of PSPSTs committed errors in comprehension, 17.5% each in reading and encoding, 14.7% in transformation, and 8.7% in process skill. Furthermore, the findings indicated a hierarchical structure in the occurrence of errors. Errors in the early stages have a high potential to cause errors in subsequent problem-solving stages. All the results are discussed, along with their implications for practice and suggestions for future research.

Students' understanding of negative integers is an important aspect of learning mathematics as it is a requirement for learning broader mathematical concepts. The purpose of this research is to explore students' initial perceptions in understanding negative integers on a number line. This descriptive exploratory qualitative research was conducted on fifth grade elementary school students. The subjects were selected based on students' initial perceptions of writing negative integers on a number line before the teacher presented the material. Students' initial perceptions can be seen from the exploration results of their thinking abilities. The data of this research was collected through written tests and interviews. From the exploration results of research subjects, it was found that there were three characteristics of students' thinking perceptions in understanding the concept of negative integers. These three characteristics are: assume there are no negative numbers; unary understanding; and pseudo understanding. From these findings, it is necessary to design learning which provide scaffolding for students to avoid errors in understanding whole numbers.

Across many language backgrounds, a consistent hurdle to accessing United States higher education is understanding the basic information necessary to apply for admission and financial aid and complete the many enrollment management processes necessary to begin one's college career (apply for housing, receive and submit vaccinations, register for classes, etc.). However, to date, no studies have explored how this type of higher education information can be simplified and translated into Arabic, one of the most widely spoken languages in the world and a linguistic background shared by tens of thousands of prospective international students (and their families) seeking higher education in the United States. This case study reports on research-to-practice work conducted with the University of Iowa, specifically how the university simplified their enrollment management information and how that information was translated into Arabic for native Arabic speakers seeking access to the University of Iowa. Findings reveal that the institution simplified text to speak more directly to prospective student audiences by using second person pronouns and simpler sentence structure and diction to engage this audience. Moreover, analyses of machine and human translations of English to Arabic suggest that human translation should be the preferred mechanism of translating higher education information, as Google Translate and ChatGPT provided adequate but not perfect translations of Iowa's information. Implications for practice and college access are addressed.

Amid the abundance of studies on translation errors in Thailand, a scarcity remains especially within the multi-linguacultural context of Thailand's Deep South. To address this gap, this study aims to examine Thai-English and English-Thai translation errors encountered by 232 Thai EFL university students studying English in three universities located in Pattani, Yala, and Narathiwat, primarily Pattani-Malay speakers with Thai and English as second and third languages, and some proficient in Arabic. The study employed two sets of 20-sentence translation tests and analyzed via qualitative content analysis. The findings reveal that semantic errors (65.02%), miscellaneous errors (20.73%), and syntactic errors (14.25%) were found in English-Thai translations, whereas syntactic errors (46.88%), semantic errors (40.76%), and miscellaneous errors (12.36%) were found in Thai-English translations respectively. The results suggest that linguistic proficiency, cultural familiarity in both the source and target languages and cultures, and L1 interference were considered as possible core factors influencing students' translation abilities. The study suggests integrating cultural experiences into translation teaching to better prepare learners for real-world challenges in multilingual educational settings.

The study examined the types of language errors made by learners in the English narrative essays. It also assessed the feedback techniques employed by teachers of English in the handling of language errors in the English narrative essays. A descriptive research design was employed to examine errors of English narrative essays of 181 form two learners obtained through stratified random sampling and simple random sampling techniques. The eight teachers of English selected through purposive and simple random sampling completed interview schedules. Qualitative data generated from the essays of the learners was analyzed using Error Analysis and Content Analysis. The findings reveal that a total of seven categories of language errors which include: word order, verb tense and form, subject -- verb agreement, spelling, plurality, word choice, and capital letter errors were made by the learners in their English narrative essays. The most preferred corrective technique was to involve the learners actively by encouraging them to read extensively and write severally on various narratives in the target language. The findings will provide reliable feedback to teachers of English because it will guide on the development of teaching methods and evaluative measures to narrative essays. The study will also be useful to curriculum developers in designing materials for teaching English language in secondary schools. It will also be of invaluable benefit to learners of English as it will guide on the way narrative essays need to be written.

The study on "Educators' Academic Insights on Artificial Intelligence -- Challenges and Opportunities" was conducted to gain a deeper understanding of the rapidly evolving phenomenon of AI in education. This research serves multiple objectives. Firstly, it aims to foster awareness regarding the integration of AI into teaching and learning practices by providing clear definitions of AI and explaining key AI-related terms. It also seeks to illustrate AI's diverse applications within a broader context, with a special focus on AI-supported research and learning platforms. Additionally, the study delves into the current discourse surrounding chatbots, contributing to address the central research question. Lastly, this initiative aims to provide valuable recommendations for effectively harnessing AI in education, enhancing the teaching and learning experience. The researchers conducted a review of literature concerning artificial intelligence. They adopted a qualitative method, using open-ended questions to collect feedback from educators globally, including those from the University of Technology and Applied Sciences, Al Musannah, and participants in the online discussion forum at Oxford English Learning Exchange.com. The qualitative data was analysed, leading to the identification of key themes and subthemes derived from the responses of research participants. The study's findings incorporated a wide range of concerns expressed by educators, comprising ten key subthemes. These concerns ranged from doubts about AI's ability to replace human educators and fears of its potential to hinder student development to worries about its hyped popularity and its perceived futuristic nature. Educators stressed the importance of effective AI training while emphasizing the need to prioritize human expertise over excessive reliance on AI. They were also acutely aware of both the advantages and disadvantages of AI, viewing it as both a potential boon and a looming threat. Furthermore, educators recognized the potential for enjoyable experiences with AI and acknowledged the pivotal role of users in determining the extent of AI adoption. Content analysis revealed additional apprehensions, such as concerns about job displacement, AI's impact on critical thinking, teacher frustration in assessing AIassisted student writing, the use of AI-generated content for assessments, potential erosion of human services, stifling of user and learner creativity by AI, the risk of errors in AI-generated information, opportunities for cheating in exams, and concerns about the overreliance on and overrating of AI platforms. Positively, the findings included an array of opportunities that AI platforms offer. Study participants highlighted various aspects of these opportunities that surpassed their concerns and associated risks. The opportunities are categorized into twenty subthemes: enhancing learner motivation, facilitating template creation, utilizing AI as an educational aid, promoting proper training and fostering positive AI usage, harnessing AI for teaching challenging subjects, enabling personalized learning experiences, offering an interactive tutoring experience, supporting remote learning, facilitating self-study, providing comprehensive educational content overviews, giving instantaneous feedback and evaluation, functioning as search engines and chatbots, enabling content validation, efficiency in terms of cost and time, streamlining material preparation, facilitating skill and language enhancement, promoting familiarity with topics and vocabulary, enabling text-to-speech and speech-to-text conversions, editing multimedia elements, and facilitating content generation.

This study focused on investigating common writing errors made by a group of Thai students who participated in online collaborative writing using Google Docs, and understanding their satisfaction and attitudes on this writing approach. The participants consisted 32 Thai first-year English major students who were purposively selected from their Writing I course. The researcher collected and analyzed eight argumentative pieces of writing, identifying a total of 484 errors. The most frequently occurring error areas were incomplete sentences (15.75%), spelling mistakes (13.50%), and word choice issues (12.25%), with grammatical errors being the most prevalent (72%). Following grammatical errors were lexical (12%) and mechanical errors (4%). To gauge students' satisfactions and attitudes, a questionnaire and semi-structured interviews were employed. The findings revealed that the students were highly satisfied with online collaborative writing with an average satisfaction score of 3.50. Overall, the students exhibited a positive attitude towards online collaborative writing, finding it useful due to its flexibility in terms of allowing them to work from anywhere at any time and for its ability to boost their motivation. The study's findings provide valuable insights for English teaching professionals in Thailand to consider when instructing students in writing.

The aim of the research is to investigate the academic achievement of ChatGPT, an artificial intelligence based chatbot, in a national mathematics exam. For this purpose, 3.5 and 4 versions of ChatGPT were asked mathematics questions in a national exam. The method of the research is a case study. In the research, 3.5 and 4 versions of ChatGPT were used as data collection tools. The answers given by both versions of ChatGPT were analyzed separately by three researchers. As a result of the analysis of the data, it was found that ChatGPT-4 was more successful in the exam compared to ChatGPT-3,5 version, was better at understanding the questions asked, understood the instructions better and included more details in the question solution, and at the same time, both versions made common and different mistakes. According to the findings of the study, it was concluded that ChatGPT sometimes worked very well, sometimes only worked well and sometimes failed. In the light of the findings of the study, it can be suggested to use ChatGPT versions in mathematics education to obtain basic information and to get supervised help.

This study aimed to analyze common syntactic errors found in the argumentative essays of third-year English major students at the Faculty of Foreign Languages, Van Lang University, Vietnam. Quantitative and qualitative methods were used to obtain data in this study. The quantitative approach involved counting and calculating the frequency, percentage, and ranking of syntactic errors, while the qualitative method was adopted to explain these errors. The instrument for collecting data was argumentative essays written by 37 third-year English majors enrolling in Writing-5 at Van Lang University. Microsoft Word was used to collect and analyze syntactic errors and sentence structures, while Microsoft Excel was employed to calculate the frequency and rank of these errors and structures. The results found that the five most frequent errors in their essays were at the noun phrase and sentence levels. These errors included run-on sentences, preposition errors, article errors, sentence fragments, and pronoun errors. Through error analysis, it was indicated that the majority of errors made by students were due to the negative transfer from their first language and the literal translation. Based on the findings, language teachers and syllabus designers could use these results as guidance to design appropriate teaching methods and materials.

Developing effective oral business English (OBE) curricula requires clearly understanding student needs. This study evaluated the speaking needs of Chinese English as a Foreign Language (EFL) undergraduates majoring in business English for specific purposes (ESP), aiming to inform the design of a teaching module that bridges the gap between current speaking abilities and the escalating demand for advanced communication skills in business contexts. A needs analysis questionnaire, reflecting the first phase of the ADDIE model (analysis, design, development, implementation, evaluation), was administered to 398 randomly selected participants using a quantitative, cross-sectional survey design. Results revealed that while students struggle with speaking errors and lack communication confidence, they favor interactive activities such as presentations, discussions, and role-plays. Concerns about current OBE pedagogy and materials highlight a need for more collaborative learning and teacher support. Statistical analysis using independent-samples t-test and one-way ANOVA showed no significant differences in speaking needs based on gender, age, years of English study, or English proficiency. However, a significant difference was reported between fourth-year and third-year students. This study offers some insights for developing more effective interventions to address the specific needs of Chinese business English undergraduates in Chinese ESP education.

This study seeks to clarify whether teachers are able to distinguish between essays written by English L2 students or generated by ChatGPT. 47 instructors who hold experience teaching English to native speakers of Japanese in universities or other higher education institutions were tested on whether they could identify between human written essays and ChatGPT generated essays. The ICNALE written corpus (Ishikawa, 2013) was used to find and randomly select the essays of four Japanese university students' written work who studied English at roughly CEFR A2 level. The AI chatbot, ChatGPT, was used to generate four essays utilizing prompts which directed the chatbot to mimic grammar mistakes common to nonnative speakers of English. Teachers were requested to identify which of the eight essays they believed to be human written or ChatGPT generated. On average, the teachers were able to identify 54.25% of items accurately. This result is slightly better than random chance, and implies that most teachers cannot make an accurate assessment on a ChatGPT generated essay when ChatGPT is prompted to make grammar mistakes.

The understanding mathematical concept is an error that often occurs in classroom learning among students when solving mathematical problems. The most difficult part for students is solving problems, because it requires numeracy skills, high concept mastery, as well as the ability to use good language, and so on so that students don't make any more mistakes when working on math problems. Student errors in solving mathematics problems are (1) errors in connecting concepts, (2) errors in operations and (3) errors in constructing concepts. The problem is what is the structure of students' mathematical misconceptions in solving mathematical problems based on cognitive style. The method in this research, namely an exploratory descriptive approach, aims to determine the structure of students' errors based on cognitive style in solving mathematical problems. Analysis of research data, namely: (1) Data reduction, (2) Data exposure, (3) data triangulation and (4) drawing conclusions. The cognitive styles referred to are field dependent and independent. The conclusions are (1) the structure of conceptual errors with an applied field dependent cognitive style begins with disequilibrating, then solving by linking applicable concepts, and (2) the structure of conceptual errors with a field independent cognitive style begins with disequilibrating, then solving using analyse.

Design patterns for learning are about articulating, testing and sharing the principles of problem solving in the educational context. In this way, multiple patterns are developed to solve common problems, described in various pattern language formats. Therefore, this work is about characterizing and establishing functional relationships between the components involved in the construction of a learning design pattern. The research was carried out in a Delphi study of double round individual non-contact between experts (n = 14), from different areas (educational technology, e-learning, distance education, higher education), selected through the coefficient of expert competence. The main result is a pattern language composed of attributes, components, and groups of processes. It is concluded that the language obtained allows externalizing knowledge from its consistent and shareable structure, which makes it suitable for use in different scenarios that require a formal pattern language and facilitates its implementation in online learning contexts.

While acquiring a second language, learners may encounter challenges and difficulties in effectively carrying out verbal communication in the second language. Mastering the apology speech act is a challenge for L2 learners. The objective of this study is to identify the apology strategies utilized by individuals learning the Japanese language, as well as the specific types and underlying causes of errors produced during the execution of apologetic speech acts. The results of this study were gathered via the Discourse Completion Test (DCT), which encompassed a sample of 150 Japanese language learners. The gathered data were further classified using eight semantic formulas based on the research conducted by Haristiani and Sopiyanti (2019), while the various types and sources of error categorization were conducted based on the theories proposed by Corder (1981) and Richards (1975). The results of this study suggest that Japanese learners utilize the same primary strategies in apology speech acts. Furthermore, the study findings indicated that learners at the intermediate level displayed a higher frequency of errors in their speech compared to learners at the beginner levels and pre-intermediate levels, particularly in the strategy of taking responsibility. The main reason for this was primarily a lack of familiarity with the conventions of sentence structures, the proper use of language, and the appropriate use of expressions. The other sources of errors in language learning are likely to be ignoring language rule restrictions, incomplete application of rules, the learner's false hypothesis, overgeneralization, and language transfer. This study is anticipated to function as a point of reference for research in interlanguage pragmatics, second-language acquisition, and error analysis. Gaining comprehension of the various problems and difficulties encountered when performing the speech act of apology in Japanese can assist both learners and educators in reducing these errors.

Developing structure sense is an important part of learning algebra. We investigated learners' structure sense of algebraic expressions involving brackets. This led us to propose the constructs "surface structure" sense and "systemic structure" sense. Using a random sample of 58 Grade 10 learners scoring above 40% in a test, we coded incorrect responses for surface and systemic structure errors. The initial analysis revealed that the presence of more brackets supports surface structure sense. However, learners overgeneralised the presence of brackets to represent multiplication in situations involving subtraction. The arrangement of brackets also led to errors in the order of operations. Further analysis suggested that regular application of procedures on familiar algebraic structures may give the illusion of systemic structure sense. We recommend that the teaching of algebraic expressions must emphasise what the arrangement of an expression means before focusing on how to operate on the expression

This mixed-methods study aims to investigate the bias in peer feedback. Thirty-two English as an additional language learners gave each other anonymous feedback on their texts. Half of the participants received feedback from their teacher disguised as peer feedback, while the other half received actual peer feedback. Data were collected through drafts of two essays, feedback, and a questionnaire. Results indicate that although participants reported trusting teacher feedback more, the quantitative uptake of feedback was similar regardless of the source. Data analysis suggests that the teacher's and peers' social representation plays a more significant role in uptake than the feedback itself.

Studying towards a postgraduate qualification is viewed as a booster that may usher employees towards management positions. We have found common mistakes in research proposals for master's degree students in a department at the University of Namibia. Our presentation shows the shortcomings in the research proposals of postgraduate students and proposes interventions to address the challenges. We collected qualitative data through the observations of nine (9) Master of Education research proposals, which were conveniently selected. Our analysis showed shortcomings in research proposals submitted to the Department of Education at the University of Namibia. Moreover, there is a need for the introduction of a writing unit at the university to supply writing services such as academic writing, proof reading and editing. We recommend that regular practical training is offered on effective academic writing to postgraduate students. We also show the need for postgraduate students to be oriented towards the plagiarism policy and referencing style of the university. This calls for the re-thinking of ways that enable effective postgraduate student supervision, which may address the quality of student research output.

This research investigates errors and misconceptions among learners in algebraic education by utilizing Koch's error analysis method alongside the Structure of the Observed Learning Outcome (SOLO) taxonomy. The primary aim of the investigation is to discern the kinds of errors and cognitive stages demonstrated by Grade 9 students when engaged in algebraic problem-solving tasks. The studies' outcomes uncover several prevalent error categories, including conjoining, cancellation, and problem-solving errors, indicating deficiencies in conceptual comprehension and procedural execution. Moreover, applying the SOLO taxonomy elucidates learners' diverse levels of understanding, with a majority position within the uni-structural or multi-structural stages. Theoretical implications underscore the necessity for tailored instructional approaches to mitigate learners' obstacles and foster a deeper grasp of algebraic principles. Consequently, this research contributes significantly to the advancement of algebraic pedagogy and provides valuable insights for curriculum enhancement, thereby facilitating improved mathematics learning outcomes.

Python programming is widely employed in educational institutions worldwide. Within the "Merdeka Belajar" curriculum context, this programming is recognized as a suitable vehicle for mathematics instruction, significantly influencing students' motivation and learning outcomes, particularly following periods of educational hiatus. This study examines the effectiveness of Python programming in promoting heightened learning outcomes by examining the intricate relationship between student motivation and learning. The study uses quantitative research methodologies to evaluate student learning facilitated through Python programming, encompassing problem-solving assessments and the administration of motivation questionnaires. By engaging in coding practices, students understand the symbols they manipulate, facilitating their ability to juxtapose data derived from mathematical modeling with the resultant programming output. When disparities arise, students are empowered to reassess their work, fostering a more profound comprehension of the subject matter. These exercises serve to augment students' capacity to retain and process information within memory. Furthermore, students demonstrate a favorable disposition, exhibiting persistence in resolving programming challenges by meticulously analyzing error outputs, particularly those pertaining to TypeErrors. Encouraging students to confront errors through thoroughly examining error output manifestations engenders an efficacious learning paradigm. This research proffers invaluable insights for educational institutions contemplating the integration of Python programming as an instructional adjunct.

The present study falls into the efforts to improve practices for addressing errors produced by learners in various situations involving the calculation of integrals. We attempt to clarify as precisely as possible the types of errors that secondary school students produce when using integrals in algebraic and graphical frames. Based on the synthesis of several works dealing with errors specific to integral calculus, we have been able to outline a typology of possible errors that can be produced by students in secondary school. We determine some subcategories for the three known categories of errors: conceptual, procedural, and technical. After administering a test to a random sample of secondary school students and conducting a principal component analysis, we were able to deduce that in the algebraic frame, certain conceptual and procedural subcategories dominate, with a notable advance for errors due to failure to recognize the integrand function. In the graphical frame, errors related to technical subcategories represent a major source of the erroneous productions of the students tested.

Solving systems of linear equations is a core concept in linear algebra and a wide variety of problems found in the sciences and engineering can be formulated as linear equations. This study sought to explore undergraduate students' development of the schema for solving systems of linear equations. The triad framework was used to describe the schema development in general and the system of linear equations was used as an example. A case study of an undergraduate class doing a linear algebra course in 2020 was considered in this study, where fifteen students participated in the study whereby they responded to a task with three question on solving a system of linear equations. The findings revealed that albeit minor manipulation errors, students were able to solve given systems of linear equations using the Cramer's rule and Gaussian elimination. However, students could not adequately go beyond the algorithmic computations to attain appropriate mathematical reasoning and establish underlying relations required to solve systems of linear equations, as no-one attained the trans-stage of conceptualization. It follows from this study that the identifications of the challenges that students encounter when solving systems of linear equations empowers course instructors on how to overcome the challenges.

Students' difficulties in differentiating the direct proportion and inverse proportion problems cause interference. Proactive interference is the error that occurs when old information (concept of direct proportion) interferes with new information (concept of inverse proportion). In solving the problem of inverse proportion, students often use the concept of direct proportion. The student's mental structure regarding the concept of proportion as a result of previous learning is referred to as met-before. Therefore, this study aims to describe the met-before of students who experience proactive interference. This research is a case study involving 32 8th-grade students in Malang, Indonesia. These subjects were students who experienced proactive interference with specific fluency of communication and willingness. Data was collected through proportion problems and interviews. Students' work was analyzed based on the description of the met-before. The results showed that students who experienced proactive interference with the non-flexible type had suppressed problematic, while students with the flexible type have focus supportive met-before in solving direct proportion problems. Both students with non-flexible type and flexible type have focus problematic met-before when solving inverse proportion problems. This is because met-before about cross multiplication strategy interferes with students' problem-solving.

This research explored students' perception vis-à-vis of the (dis)advantages of face-to-face and online learning of foreign languages in a tertiary education institution in Thailand. The research took a mixed methods approach utilizing a pre-set questionnaire and a multiple-choice question. Data were collected from 433 students using an online platform and then analyzed using simple statistics. Findings showed that the main advantages of studying online are easy access to the Internet, the self determined pace of learning, while the main advantage of face-to-face instruction is better social interaction. Conversely, the main disadvantage of studying online is the difficulty of interacting with classmates and the instructor; the main disadvantage of face-to-face learning is students feeling more self-conscious of mistakes made. The findings also indicate the participants prefer learning either in the traditional classroom environment or via the hybrid mode.

This study investigated college Chinese a second language learners' word segmentation error patterns in reading instructional-level Chinese sentences, the relationship between word segmentation errors and reading comprehension, and learners' perspectives on the role of word segmentation in reading comprehension. The results showed that the learners made five types of word segmentation errors. Four of these types moderately correlated with reading comprehension. The survey data showed that most learners considered word segmentation skills important in reading comprehension. This perception became stronger as the learning level advanced. The learners suggested that three factors hindered them from performing accurate word segmentations.

We evaluated two procedures to teach auditory-visual conditional discriminations (receptive labeling) to children with autism. The procedures evaluated a modified Structured Mix (SM) procedure and a modified Counterbalanced Random Rotation (RR) procedure. The modified SM procedure was based on the logic of simplifying the task by breaking it down into smaller, successive steps and by requiring mastery of each step before introducing the next. Compared to previous studies, the modified SM procedure contained fewer steps, less prompting, and a less stringent mastery criterion. The modified RR procedure targeted all three stimuli simultaneously by presenting them across consecutive trials, both during training and error correction. Sample stimuli were presented in a counterbalanced random order and the comparison stimuli were presented in counterbalanced random positions. Participants were nine children with autism. An adapted alternating treatments design was used. Results showed that the modified SM procedure was more efficient for four of the nine participants, the modified RR procedure was more efficient for one of the nine participants, both procedures were equally efficient for two participants, and neither procedure was effective for two of the nine participants. The modified SM procedure appeared more efficient than the SM procedure employed in previous studies. Despite results, further research is warranted to examine within subject comparisons between original discrimination training procedures and modified procedures.

This study aims to investigate Vietnamese students' perceptions of portfolio assessment and how it affects their writing performance. Furthermore, the study explores problems encountered during the assessment process, which could offer professional support for teachers, particularly novice teachers, when applying this formative assessment to teaching writing. Data was collected through students' written papers, observations, and semi-structured interviews with a total of thirteen low- and intermediate-level undergraduate students. The findings demonstrate the aspects of the assessment usefulness, namely validity, authenticity, interactive-ness, and impact. Accordingly, the assessment provides students with a comprehensive understanding of academic writing that enhances their writing abilities. In particular, students recognize their common grammatical errors, pay more attention to organizing ideas logically, and develop writing habits throughout the writing process, which have not been carefully addressed in prior education. Nevertheless, there are a number of issues that need to be carefully considered, including idea development, plagiarism knowledge, self- and peer-assessment, and the order of writing steps. In order to improve the reliability and practicality of the assessment, solutions to those concerns are provided.

The aim of the study is the development of methodology for accurate estimation of electric vehicle demand; which is paramount regarding various aspects of the firms decision-making such as optimal price, production level, and corresponding amounts of capital and labor; as well as supply chain, inventory control, capital financing, and operational expenses management. The forecasting methods utilized include statistical techniques ("autoregressive integrated moving average" [ARIMA], and "polynomial regression"), machine learning ("nonlinear autoregressive neural network" [NAR]), "deep learning (long short-term memory [LSTM])", "hybrid and combination forecasting." With regard to the latter method, our study experiments with four different combining model approaches, including the introduction of an original, novel combining method with the employment of a transcendental LASSO function, which is used to form combinations of forecasts generated by the NAR, ARIMA, and polynomial regression models. The LASSO-based combining model proved superior to all other models, for the majority of forecast error statistics; where the root mean square error (RMSE) and mean absolute percentage error (MAPE) values are 4.5% and 8% respectively lower than the average level of the component model forecasts. The major implications of our empirical findings are that greater accuracy in demand forecasting can be achieved with a combining model approach, rather than reliance on any particular, singular model. Furthermore, given its superior performance, the employment of the studys LASSO-based combining model to forecast electric vehicle demand may lead to optimal firm decision-making over a range of organizational facets, which is predicated on accurate demand function estimation.

A word often expresses many different morphological functions. Which part of a word contributes to which part of the overall meaning is not always clear, which raises the question as to how such functions are learned. While linguistic studies tacitly assume the co-occurrence of cues and outcomes to suffice in learning these functions (Baer-Henney, Kügler, & van de Vijver, 2015; Baer-Henney & van de Vijver, 2012), error-driven learning suggests that contingency rather than contiguity is crucial (Nixon, 2020; Ramscar, Yarlett, Dye, Denny, & Thorpe, 2010). In error-driven learning, cues gain association strength if they predict a certain outcome, and they lose strength if the outcome is absent. This reduction of association strength is called unlearning. So far, it is unclear if such unlearning has consequences for cue--outcome associations beyond the ones that get reduced. To test for such consequences of unlearning, we taught participants morphophonological patterns in an artificial language learning experiment. In one block, the cues to two morphological outcomes--plural and diminutive--co-occurred within the same word forms. In another block, a single cue to only one of these two outcomes was presented in a different set of word forms. We wanted to find out, if participants unlearn this cue's association with the outcome that is not predicted by the cue alone, and if this allows the absent cue to be associated with the absent outcome. Our results show that if unlearning was possible, participants learned that the absent cue predicts the absent outcome better than if no unlearning was possible. This effect was stronger if the unlearned cue was more salient. This shows that unlearning takes place even if no alternative cues to an absent outcome are provided, which highlights that learners take both positive and negative evidence into account--as predicted by domain general error-driven learning.

Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) showed how, consistent with the predictions of error-driven learning models, the order in which stimuli are presented in training can affect category learning. Specifically, learners exposed to artificial language input where objects preceded their labels learned the discriminating features of categories better than learners exposed to input where labels preceded objects. We sought to replicate this finding in two online experiments employing the same tests used originally: A four pictures test (match a label to one of four pictures) and a four labels test (match a picture to one of four labels). In our study, only findings from the four pictures test were consistent with the original result. Additionally, the effect sizes observed were smaller, and participants over-generalized high-frequency category labels more than in the original study. We suggest that although Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) feature-label order predictions were derived from error-driven learning, they failed to consider that this mechanism also predicts that performance in any training paradigm must inevitably be influenced by participant prior experience. We consider our findings in light of these factors, and discuss implications for the generalizability and replication of training studies.

Functions and formulas in spreadsheets provide an instructional opportunity to help students build their skills in identifying errors in their own work and identifying a path to go about correcting the errors. This paper provides examples of functions and equations used to create two approaches to calculating the solution to one problem, such as a weighted average calculation or a loan payment calculation. Solving the problem two ways gives students the opportunity to see why both approaches work and to reconcile them if errors cause the results to differ. Using a guided errors pedagogy, instructors can also create an error in one computational approach so that students then work to reconcile the two. This method helps build problem-solving skills and confidence in a process for persisting to resolve errors. Learning from failure and correcting errors in one's work can contribute to perceptions of self-efficacy.

Presenters' pedagogical choices are strongly affected by whether they view knowledge as coherent or fragmented. This mixed-methods survey study seeks to contribute to epistemological discussions and associated pedagogical suggestions in the context of mole ratio related mistakes evident in stoichiometry calculations performed by in-service teachers in a developing world country. Physical sciences teachers in South Africa were asked to solve four stoichiometry calculation questions, and their written solutions (361 sets) were analyzed for consistency of various types of mole ratio related mistakes. The study found high levels of inconsistencies in each observed mistake, supporting the view that most participants' knowledge lay closer to the fragmented end of the coherent-fragmented epistemological continuum. Evidence is presented for differential cognitive load, overgeneralization, and intuitive heuristics as possible explanations for these mistakes. Pedagogical suggestions are made for addressing such errors in in-service chemistry teacher workshops about stoichiometry calculations, although these may only be applicable where teacher subject matter knowledge tends to be low, such as within the developing world.

Proof facilitates conceptual and meaningful learning in mathematics education rather than rote memorization. In this study, incorrect theorems and proofs are used to assess secondary school pre-service mathematics teachers' proof assessing skills. Using the case study method, the study is conducted on preservice mathematics teachers studying at the Department of Mathematics Education. There were eight preservice mathematics teachers selected from each grade, resulting in 32 participants in total. A semistructured proof form containing 13 questions was used to collect data, which was analyzed using content analysis. As the analysis reveals, pre-service mathematics teachers are highly likely to make incorrect decisions regarding theorems and proofs, and the margin of error is unaffected by grade level. Moreover, pre-service mathematics teachers tend to use proving terms incorrectly and, at times, are unable to differentiate between terms that are commonly used in proving. The pre-service mathematics teachers are believed to have learned proofs by rote rather than understanding how proofs work. With the help of interviews and tests created for different proof methods, it has been suggested that pre-service mathematics teachers should be tested on their proof evaluation skills in more detail.

Recent developments in AI technologies and the increasing accessibility of AI tools, such as ChatGPT, have raised concerns about academic integrity in higher education. Thus, this research aims to shed light on the challenges faced by English as a Second Language (ESL) lecturers in identifying AI-generated texts, and highlighting the skills and resources needed to enhance their detection capabilities. In this qualitative study, data were collected from six ESL lecturers working in a higher educational institution in Cyprus. Participants evaluated four academic essays at C1 level to determine which, if any, of the sample had been fully or partially AI-generated, and these results were then compared to results from four AI detectors. Findings reveal that participants tended to exploit a deficit model of assessment that focuses on error as an indicator of L2 writing output, with high levels of technical and grammatical accuracy and sophisticated language use as indicators of AI-generated text. Moreover, findings suggest that limited awareness of the characteristics and metrics used by ChatGPT, as well as lack of attention to the veracity of facts and references generated by ChatGPT, were features of participants' evaluations. This study identifies the growing challenges encountered by ESL lecturers and underlines the need for digital literacy training, targeted professional development, the use of advanced detection tools and a review of assessment policies and practices in relation to AI. Additionally, this study highlights the importance of reviewing and reinforcing institutional policies and practices that safeguard academic integrity and ensure quality higher education.

In second language learning research, L1-L2 congruency refers to the similarity in form and meaning of the way a word or phrase is said between two languages. If there is low L1-L2 congruency, the learning burden of a word or phrase can be higher, and thus, such items should be focused on more in teaching to help learners avoid errors. For example, an unacceptable structure could be produced when second language learners use direct or literal translation to formulate multiword units (MWUs) in the target language. This study used L1-L2 congruency as a criterion to identify English MWUs with low congruency with their Persian equivalents to create a resource for Persian-speaking English learners. An L1-L2 contrastive analysis was conducted on a list of approximately 11,000 high-frequency MWUs. This list was translated, and the items were given ratings regarding their congruency in Persian. The results revealed that more than 65% of the items examined were incongruent with their word-for-word translations, demonstrating that L1-L2 congruency is a significant factor in selecting MWUs for Persian-speaking English learners. Since focusing on incongruent items may help learners avoid errors, the results of this study can help improve the efficacy of English acquisition by Persian-speaking learners through its identification of particular MWUs that have low congruency between the two languages.

English is a compulsory foreign language in all public and private primary and secondary schools and universities in the Republic of Kosovo. English language is a separate subject in the "Curricular Framework of Pre-University Education in the Republic of Kosovo", where it is ranked after the mother tongue. Thus, English occupies a particular place compared to other foreign languages, especially in the secondary and university education system. In the study, survey method was adopted and the participants were composed of randomly selected 300 gymnasium students. The data were collected using a questionnaire developed by the researcher, an interview form and an observation form. The obtained data were analyzed using descriptive statistics, such as frequency and percentage. The results have revealed that the quality of English language education in the gymnasiums in the Republic of Kosovo needs improvement since students fail to use conjunctions' grammatical functions and meanings properly, they can only understand simple and familiar words, and complex and unknown words hinder students from understanding the concept.

Whether or not to teach grammar explicitly is an issue that has long been debated in the field of SLA. There seems to be a growing consensus among many researchers now in support of embedding some element of explicit instruction within a communicative curriculum. The main arguments in support of explicit instruction are threefold: two widely cited meta-analyses, the fossilization hypothesis, and meeting student expectations. However, none of these arguments are as compelling as they are sometimes made out to be. The studies included in the meta-analyses mostly evaluate explicit knowledge rather than communicative ability; forms that are candidates for fossilization tend to be communicatively redundant anyway; and student expectations stem from common practices, but should not drive them. Furthermore, this article suggests there is a critical element that has been missing from the debate on explicit instruction, namely individual differences between students. The question of whether, which, and how much grammar to teach likely depends on the interests and goals of the particular students being taught. Therefore, arguments for or against explicit instruction should always consider the context rather than seeking a one-size-fits-all best practice.

Dynamic assessment is a dialectic procedure requiring teachers to assess learners' progress by paying attention to students' errors while providing graduated prompts to help them fix them. Although previous studies have focused on the teachers' competence in carrying out the dynamic assessment, this case study explores the dynamic assessment conceptualization of two English language teachers. Data were gathered through video-recorded sessions, reflective reports, semi-structured interviews, and classroom observations. Results showed that while one of the teachers reconceptualized her role as a graduated prompt provider, the other teacher resisted adopting any roles that dynamic assessment requires. The study implies careful consideration of personal and contextual factors shaping teachers' assumptions to make a change in teacher practice.

To ensure the validity of the tests is to check that all items have similar results across different groups of individuals. However, differential item functioning (DIF) occurs when the results of individuals with equal ability levels from different groups differ from each other on the same test item. Based on Item Response Theory and Classic Test Theory, there are some methods, with different advantages and limitations to identify items that show DIF. This study aims to compare the performances of five methods for detecting DIF. The efficacies of Mantel-Haenszel (MH), Logistic Regression (LR), Crossing simultaneous item bias test (CSIBTEST), Lord's chi-square (LORD), and Raju's area measure (RAJU) methods are examined considering conditions of the sample size, DIF ratio, and test length. In this study, to compare the detection methods, power and Type I error rates are evaluated using a simulation study with 100 replications conducted for each condition. Results show that LR and MH have the lowest Type I error and the highest power rate in detecting uniform DIF. In addition, CSIBTEST has a similar power rate to MH and LR. Under DIF conditions, sample size, DIF ratio, test length and their interactions affect Type I error and power rates.

This article explores how teachers respond to student mistakes in one educational setting--an elite private high school. This qualitative study is a thematic analysis of in-depth, semi-structured interviews with teachers at one such school. The results reveal that in their responses to student mistakes, the teachers work to build trust and emotional safety, give students agency throughout the learning and feedback processes, and ask probing questions that rigorously challenge their thinking. By considering teacher accounts of their instructional approaches and past experiences, the study adds a context-specific, real-world perspective on how teachers in an elite school frame student mistakes.

One of the reasons why students fail in mathematics courses is that the problems used in the lessons are abstract. In this context, it is important to embody the problems used in the lessons. Fermi problems are open-ended problems, a type of problem that reflects real-life situations that are solved by making a series of predictions. In the future, with these problems involving real-life situations, it is today's pre-service mathematics teachers who are primarily responsible for carrying out an effective teaching process in school mathematics. This research was carried out within the scope of the case study design, which is one of the qualitative research designs, which aims to determine the errors made by primary school mathematics teacher candidates in their performance and solutions to solve the Fermi problem. The study group of the study consisted of 44 pre-service teachers studying in the 4th grade in the department of primary school mathematics teaching in a province located in the southern region of Turkey in the 2022-2023 academic year. As a result of the research, it was concluded that the scores obtained by the pre-service mathematics teachers from the solutions of Fermi problems were not at the desired level, and the performance of the teacher candidates was at a medium level. From the error detection, it was find that the source of this situation is mostly due to the weakness in the dimensional estimation process.

This study examined effects of pronunciation training using automatic speech recognition technology on common pronunciation errors of Korean English learners. Participants were divided into two groups. One group was given instruction and training about the use of automatic speech recognition for pronunciation practice. The other group was not given such instruction or training as a control group. A pre- and post-test experimental design was used. The treatment period was four weeks. Participants who were taught about using automatic speech recognition for pronunciation practice showed small but significant improvements in pronunciation accuracy than those who did not. In addition, automatic speech recognition was found to assist in the diagnostic evaluation of common pronunciation errors, although it did not produce statistically significant improvements. Participants responded positively to the use of automatic speech recognition for pronunciation practice and testing, although there remain some concerns over technical aspects of the test.