The incorporation of Computer Science teaching in educational systems has increased in recent years. Given international interest, Chile has promoted projects to promote the development of students' digital skills. Focusing on this new educational context, this research reports the results regarding the identification of computational concepts and practices that can be articulated with the contents and skills of the curriculum. of Chilean mathematics. for first grade of primary school based on the use of the Bee-Bot robot. For this, the study followed a qualitative approach, developing a case study of the Chilean study program with the content analysis technique and using, as analysis categories, computational concepts and practices from the field of educational computing. In total, 30 learning objectives of the study program were analyzed. The results indicate that, although there is little articulation between computational concepts and first grade content proposed in the curriculum, there is greater articulation between computational practices and mathematical skills suggested in the Chilean curriculum. It is concluded that Computational Thinking can be developed from the earliest school levels using the Bee-Bot robot (or similar), and this is demonstrated by the structure of the Chilean primary mathematics curricular program.

The role of artificial intelligence (AI) in education remains incompletely understood, demanding further evaluation and the creation of robust assessment tools. Despite previous attempts to measure AI's impact in education, existing studies have limitations. This research aimed to develop and validate an assessment instrument for gauging AI effects in higher education. Employing various analytical methods, including Exploratory Factor Analysis, Confirmatory Factor Analysis, and Rasch Analysis, the initial 70-item instrument covered seven constructs. Administered to 635 students at Nueva Ecija University of Science and Technology – Gabaldon campus, content validity was assessed using the Lawshe method. After eliminating 19 items through EFA and CFA, Rasch analysis confirmed the construct validity and led to the removal of three more items. The final 48-item instrument, categorized into learning experiences, academic performance, career guidance, motivation, self-reliance, social interactions, and AI dependency, emerged as a valid and reliable tool for assessing AI's impact on higher education, especially among college students.

The field of English as a Foreign Language (EFL) instruction has gained recognition worldwide, particularly in non-native English-speaking countries. However, traditional teaching methods fall short of meeting the needs of today's EFL learners. In response, the Production-Oriented Approach (POA) has emerged as a new pedagogical approach to address these challenges. Despite its significant impact on EFL education, there is a lack of reviews on the POA. This study conducted a systematic review to explore the POA's effectiveness, challenges, and future trends. Using the PRISMA framework, 31 articles from reputable databases (Web of Science, Education Resources Information Center, Scopus, and Google Scholar) were analyzed, covering the years 2018 to 2023. The study's comprehensive analysis, employing Nvivo, revealed that the POA has immense potential for enhancing English learners' language skills, particularly in reading, speaking, writing, and translating. Moreover, the study highlighted the POA's positive influence on learners' affective factors, including motivation, confidence, critical thinking, and self-directed learning abilities. Nonetheless, the POA faces challenges for both teachers and learners, particularly during the transition from traditional methods and the associated increase in workload. Despite these challenges, this study unequivocally establishes the POA as an effective pedagogical approach for teaching EFL. Additionally, it identifies research gaps that must be addressed to sustain and improve EFL education in the future through further development of the POA.

Information and Communication Technology (ICT) brings modern learning approaches, forms and methods to education, and with them new opportunities for learning and teaching. The use of ICT in the classroom motivates students, enables them to participate, provides individualisation and differentiation, interactivity, and encourages creativity and critical thinking. Teachers play a very important role in this, as they are the ones who can provide students with a stimulating learning environment, including through the use of ICT. As Slovene (first language) is the subject with the most teaching hours in public primary schools in the Republic of Slovenia, we conducted an empirical study on the views of general and subject teachers of Slovene (N = 190) on the integration of information and communication technology in teaching. Teachers’ opinions were investigated through quantitative research. We found that teachers frequently use ICT in Slovene lessons, namely for repeating and consolidating learning material and for presenting new learning material, and that ICT is used most often in frontal forms of learning. Teachers mostly use LCD projectors, computers, interactive whiteboards, e-workbooks, audio recordings and videos. We also found that teachers are moderately satisfied with the available ICT equipment and e-materials, and that they feel moderately competent when it comes to using ICT in Slovene lessons. Teachers also used ICT during the COVID-19 epidemic. We also found that there are no statistically significant differences in the use of ICT between teachers teaching Slovene according to their teaching level, age and years of service.

This paper explores information related to misconceptions and conceptual change during the last thirty years 1992-2022 to be used as a preliminary study in science education. This study used bibliometric analysis with the help of the Scopus database. This paper used a bibliometric analysis study with the Scopus database and the help of MS Excel, VosViewer, and Rpackage software to visualize the data obtained. The results of this research found that Indonesian researchers have contributed the most in terms of the number of documents published in Australia and the United States. Additionally, research on these two topics has decreased since 2019 due to the Covid-19 pandemic. In addition, these findings present trends in the areas of misconceptions and conceptual change that can be used as baseline data for future research. Studies related to misconceptions will continue to develop because they cannot be separated from the inside of education, whether at any level of elementary school, middle school, or college. This is an opportunity that must be taken advantage of by institutions and policies in an effort to improve and create quality of education, teacher resources, and students.

The computing and creative skills of students in Indonesia are still low since the government has not focused on student creativity and computational empowerment programs. This research aims to develop a science, technology, engineering, art, mathematics, and reflection (STEAMER) hybrid learning project model for teachers' creative and computational thinking abilities, as well as analyze elementary school teacher candidates' perceptions of the use of STEAMER hybrid learning model to improve teachers' creative and computational thinking abilities. This research is development research with an analysis, design, development, implementation, and evaluation (ADDIE) model. The instruments used in this study were questionnaires and interviews with experts, lecturers, and elementary school teacher candidates. The research was conducted at eight universities in Indonesia with a total sample of 100 elementary school teacher candidates. Through quantitative and qualitative data analysis, the research results have developed the STEAMER hybrid learning project model based on learning theory, syntax, social systems, support systems, and the instructional impact of learning models. The results of the validation show that the developed learning model is feasible in terms of model, material, media, and language experts. The model is suitable for elementary school teacher education. Furthermore, based on the perceptions of the teacher candidates, it is stated that the STEAMER hybrid learning project can develop the ability of the teacher candidates to think creatively and computationally.

The research on the pedagogical knowledge of teachers in technological education arises from the need to address the problem of pedagogical practices, which are traditional. The classes are at the graduate level, focusing on lecturing the student while the student remains with a passive attitude. It is believed that making explicit that teachers' pedagogical knowledge will allow reflection and awareness, thereby transforming pedagogical practices. Therefore, the objective is to understand the teachers’ constructions on pedagogical knowledge in technology programs in Plant Operations and Industrial Instrumentation of the Faculty of Engineering in order to reconstruct it theoretically, as well as identify its characteristics and trace action routes for teacher training. In this way, it allows education to be accessible to low-income and resource-poor populations, whose purpose is to strengthen the productivity and competitiveness of the economy through the training of human talent according to the needs of the working sector in a unique context. This research uses grounded theory as a methodological tool for data processing. In this sense, data collection procedures such as in-depth interviews were conducted with 16 teachers and seven of them were related to the industry. Whereas, 9 were linked to the teaching(educational) sector including elementary, high school and college level. The results showed differentiated, and socially constructed pedagogical knowledge that responds to teachers’ nature in a particular context. These results contribute to consolidate a broad vision about the pedagogical knowledge’s characteristics that the teacher builds.

The main thrust of the study was to explore the third-year English student’s sentiments on the application of the artificial intelligence (AI)-integrated paraphrasing tools. Specifically, it aimed to investigate the benefits and drawbacks brought by AI paraphrasing tools towards the writing skills of the students. The investigation utilized a semi-structured interviews with an open-ended questionnaire using an audio-video recorder. The data gathered were interpreted using the Thematic Analysis of Braun and Clarke. The study was carried out at one of the campuses of a state university located at Candijay, Bohol, Philippines. Using the Purposive sampling technique, twelve (12) respondents provided information on the research endeavor. The findings revealed that students had a positive opinion of AI-integrated paraphrase tools: they saw them as helpful resources that significantly improve their academic writing process; it includes plagiarism reduction, efficiency, and timesaving, and aids in rephrasing text. The findings also revealed the risks and issues of using AI-integrated paraphrasing tools, such as Prone to plagiarism, automated suggestions dependency, and loss of original meaning and context. With that, the students showed how they deal with those risks and issues, including as responsible users and thorough editing and reviewing. In accordance with the study, students are encouraged not to rely excessively on AI-integrated paraphrase tools, even though they can improve their writing abilities. This research emphasizes that students play a pivotal role in ensuring the appropriateness of texts generated by AI-integrated paraphrasing tools by mastering the art of proper paraphrasing.

Teachers’ access to technology in this day and age could have a positive effect on the teaching and learning of English first additional language (EFAL). This qualitative interpretive case study explored how limited access to technology resources affects the teaching practices of Intermediate Phase EFAL teachers in rural schools in Limpopo, South Africa. This study, underpinned by the Technology Acceptance Model (TAM), conducted semi-structured interviews to collect data from ten EFAL teachers who were purposively sampled. Thematic analysis was used to analyse the data. The study revealed that three of the ten EFAL teachers sampled integrated technology into their teaching despite challenges such as insufficient projectors, lack of learners’ smartphones and data bundles, and Internet connectivity. However, the other seven sampled participants did not use technology, citing a lack of digital tools and knowledge as a contributing factor. The study concludes that the lack of resources contributed to limited or no use of technology and the motivation to integrate technology into their lessons. Based on these findings, it is recommended that technological resources that can help EFAL teachers with digital teaching be made available so that they can integrate them to assist learners in developing language skills. Furthermore, in-service training and ongoing support should be provided to EFAL teachers to give them knowledge and skill to use available technology resources effectively.

The study investigated the effects of utilising English as the primary teaching language on the academic development of Grade 4 (Gr4) learners, specifically focusing on the Life and Living (L&L) component of Natural Sciences (NS). Gr4 learners commonly transition to English as the Language of Learning and Teaching (LoLT), relegating native languages such as Sesotho to mere study subjects. This shift often results in comprehension and retention challenges, hindering students' academic achievements. By employing a quasi-experimental research design, the study used a purposefully selected sample of 80 Gr4 students from two primary schools. The control group (45 learners) received English instruction from Grade R to Grade 7, while the experimental group (35 learners) switched from Sesotho to English in Gr4. Both groups underwent pre-tests and post-tests, revealing statistically significant differences favouring the experimental group. These findings support the research hypothesis that introducing English as the LoLT as early as Grade R has a significant impact on learners' performance, particularly in NS. It is recommended that English be adopted as a medium of instruction for NS, as this better prepares students for future academic challenges.

This pilot study is part of a larger “Decolonization of Digital Learning Spaces” project, which aims to develop research tools for communities that are remote and/or excluded geographically, politically, economically, socially, culturally, and linguistically. The project’s ultimate goal is to work alongside these communities to design their own digital learning tools, networks, and online educational environments by accessing and leveraging their knowledge and skills. Testing the single-criterion card sorting method is the first step toward this goal. Card sorting is an easy, enjoyable, and cost-effective method for data collection and analysis, particularly for researchers working in remote areas with limited access to electricity or the Internet. The pilot explored single-criterion card sorting as a method to elicit knowledge from two diverse cultural and linguistic groups engaged in learning activities within their communities. These groups were from a Deaf and Hard of Hearing (DHH) community in Canada (engaged in a bow-making workshop) and a rural Kabyle community in Algeria (engaged in a traditional cooking lesson). Despite low participant numbers, distinct patterns emerged, indicating the method's effectiveness. The results, though anticipated, were non-random, demonstrating the potential of card sorting in producing patterns indicative of how individuals and/or communities categorize their world(s). Kabyle sortings focused on ingredients, highlighting older individuals as teachers passing along knowledge, while the DHH sortings emphasized face-to-face contact and hand movements in communication. The findings, though modest, established relationships, provided insights into the research context and offered logistical understanding, paving the way for further work with DHH and Kabyle communities towards the design of digital learning spaces.

This study explores the relationship between language competence and intercultural communicative competence (ICC) among English as a Foreign Language (EFL) learners through a mixed-methods approach. A sample of 196 Chinese EFL learners was divided into three proficiency groups (low, intermediate, and high), with data collected through Likert-scale questionnaires and semi-structured interviews involving 16 participants. Quantitative analysis revealed that higher language proficiency is linked to improved overall ICC scores and its specific dimensions. The Kruskal-Wallis H test confirmed significant differences in overall ICC, attitude, and skill across proficiency levels, with attitude showing the strongest effect. Spearman's correlation analysis demonstrated small but significant positive correlations between English proficiency and overall ICC, attitude, and skill. Qualitative findings further enriched the quantitative results, emphasizing the foundational and catalytic role of language competence in enhancing ICC and its dimensions. However, participants acknowledged that language competence alone is insufficient for fully successful intercultural interactions. This study expands Byram’s model by offering detailed insights into the intricate relationship between language competence and various ICC dimensions. The study recommends that to fully cultivate ICC, it is essential to integrate the development of language competence into instructional practices.

In primary and middle schools in China, banzhuren is the teacher responsible for managing and overseeing a specific class of students. The lower job satisfaction of banzhurens has been a longstanding issue. This study employs a quantitative method to investigate the impact of banzhurens' self-efficacy and burnout on their job satisfaction. A total of 624 primary school banzhurens from G City (in Henan province, China) participated in an online survey assessing their perceived job satisfaction, self-efficacy, and burnout. The data were analysed using structural equation modelling analysis. The results revealed that (a) banzhurens' burnout negatively influenced their self-efficacy and job satisfaction; (b) banzhurens' job satisfaction was positively influenced by self-efficacy; (c) banzhurens' self-efficacy could mediate the adverse effects of burnout on job satisfaction. Therefore, we suggest that banzhurens' job satisfaction can be enhanced by increasing their self-efficacy, particularly in terms of communication with leaders, and by reducing their burnout.

This study examines the transition challenges faced by students with learning disabilities (LD) from primary to secondary school, focusing on emotional, behavioral, and social aspects. Using a sample of 168 special education teachers, the study employs the Strengths and Difficulties Questionnaire (SDQ-Hel) to assess emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship difficulties, and prosocial behavior before and after the COVID-19 pandemic. Statistical analyses, including t-tests and repeated measures ANOVA, reveal significant increases in emotional and behavioral challenges post-pandemic. Effect sizes (Cohen’s d) indicate moderate to strong impacts in key areas, with emotional symptoms (η² = .06) and hyperactivity/inattention (η² = .05) exhibiting notable changes. The findings highlight the necessity for targeted interventions, such as teacher training on emotional regulation strategies and structured transition programs. Implications for educators and policymakers include the implementation of inclusive practices and specialized transition support structures to mitigate these challenges and enhance the overall well-being of students with LD.

This PRISMA-based systematic review analyzes how artificial intelligence (AI) and Machine Learning (ML) are integrated into educational institutions, examining the challenges and opportunities associated with their adoption. Through a structured selection process, 27 relevant studies published between 2019 and 2023 were analyzed. The results indicate that AI adoption in education remains uneven, with significant barriers such as limited teacher training, technological accessibility gaps, and ethical concerns. However, findings also highlight promising applications, including AI-driven adaptive learning systems, intelligent tutoring, and automated assessment tools that enhance personalized education. The geographical analysis reveals that most research on AI in education originates from North America, Europe, and East Asia, while developing regions remain underrepresented. Without strategic integration, the uneven implementation of AI in education may widen social inequalities, limiting access to innovative learning opportunities for disadvantaged populations. Consequently, this study underscores the urgent need for policies and teacher training programs to ensure equitable AI adoption in education, fostering an inclusive and technologically prepared learning environment.

This paper explores the potential of Eye Movement Miscue Analysis (EMMA) as a method to evaluate the complexity of picturebooks as reading material for primary school children. While EMMA has been applied to examine reading processes and strategies, this paper reports on the first study using EMMA to examine classroom picturebook complexity and its implications for developing readers. This research found EMMA method revealed specific nuances for understanding children’s reading practices in response to the complexity of the text at hand. Drawing together an internationally established reading teaching resource, the text complexity guide (Pinnell & Fountas, 2007) with miscue analysis reading assessment and eye movement technology, this research sought to gain insights into potential areas of complexity or challenge in picturebooks commonly available in Australian school libraries and classrooms. The method shared here examines text complexity ratings, children’s reading performance, and eye movements, as they read in natural classroom settings. Analysis of children’s reading miscues revealed that readers encountered challenges not anticipated through the use of the text complexity guide. Argued in this paper is that EMMA methodologies could extend understandings about text complexity beyond established frameworks and hence guide future assessments.

This qualitative study explored the implementation of Differentiated Instruction (DI) in Philippine multigrade classrooms with the aim of understanding teachers’ experiences, strategies, and challenges, as well as developing a performance appraisal tool. Guided by its specific objectives, the research examined how teachers plan, deliver, and manage differentiated lessons while addressing the diverse learning needs of students across multiple grade levels. Findings revealed that effective DI is rooted in intentional instructional planning, including learner profiling, curriculum mapping, and flexible pacing. Instructional delivery was enriched through the use of thematic and multimodal strategies, ability-based groupings, and contextually relevant teaching aids, although technological access and training remained persistent barriers. Classroom management practices emphasized inclusive routines, peer collaboration, and adaptive learning spaces. Teachers also highlighted the importance of assessment tools and reflective teaching practices in continuously improving instruction. In response to these findings, the study developed the Multigrade Differentiated Instruction Performance Appraisal Tool (MDI-PAT), which synthesizes theoretical frameworks with authentic classroom practices. The MDI-PAT serves as both a self-assessment and professional development guide for multigrade educators, promoting ongoing improvement in DI competencies. The study concludes that enhancing teacher capacities in planning, delivery, assessment, classroom management, and reflective practice is essential for fostering inclusive and effective learning environments in multigrade contexts. The insights and tools presented provide a practical framework for educational stakeholders seeking to enhance multigrade instruction in resource-constrained settings.

Educational researchers, as well as researchers in other disciplines, often work with ordinal data, such as Likert item responses and test item scores. Critical questions arise when researchers attempt to implement statistical models to analyse ordinal data, given that many statistical techniques assume the data analysed to be continuous. Could ordinal data be treated as continuous data, that is, assuming the ordinal data to be continuous and then applying statistical techniques as if analysing continuous data? Why and why not? Focusing on structural equation models (SEMs), particularly confirmatory factor analysis (CFA), this article discusses an ongoing debate on the treatment of ordinal data and reports a short review on the practices of conducting and reporting SEMs, in the context of mathematics education research. The author reviewed 70 publications in mathematics education research that reported a study involving SEMs to analyse ordinal data, but less than half discussed how data were treated or guided readers through the analysis; it is therefore harder to repeat such an analysis and evaluate the results. This article invites methodological discussions on SEMs with ordinal variables in the practices of educational research. Subsequently, a standard for reporting SEMs with ordinal data is proposed, followed by an example. This standard contributes to educational research by enabling researchers (self and others) to evaluate SEMs reported. The example demonstrates, using real-life research data, how two different approaches for analysing ordinal data (as continuous or as a product of discretisation from some continuous distributions) can lead to results that disagree.

This study applies explainable machine learning to identify which vocal attributes in a lecturer’s speech influence students’ views of a lecturer’s charisma, a key contributor to teaching quality. It further explores whether vocal qualities differ between male and female lecturers and how students of different genders respond to these differences, offering insights into voice-related factors that influence the impact of educators. Speech segments from YouTube videos featuring 200 native-English lecturers were evaluated by 900 students using charisma rating scales. A set of attributes related to three primary prosodic dimensions of voice - pitch, rhythm, and loudness - was computed. A random forest classifier was employed to predict the charisma level based on the speech attributes and to list and rank the attributes that contributed most to the prediction. The findings revealed prominent vocal attributes that achieved higher charisma scores in the students' ratings. Same-gender evaluations of charisma were mainly based on pitch, while cross-gender evaluations rely mostly on loudness or rhythm. The automated, interpretable method provides a reliable and efficient way to measure vocal charisma in academic lecturers. It can be adapted to examine additional individual factors that influence the perception of a lecturer’s charismatic presence. It may also be integrated into practice-based tools, designed to support instructors in improving their presentation skills. Our research bridges the fields of applied psychology and computer science to contribute to the development of educational technology.

Within the context of investigating belief systems, this work exemplifies a mixed-method approach. Two approaches are utilized to explore the philosophical, ontological, and epistemological assumptions that university students foster regarding the relationships between knowledge and reality. In the first step, written materials that elaborated on the matter at hand were subjected to content analysis with the assistance of Leximancer, a software that recognizes themes and concepts and turns textual data into concept maps that express networks of meaning. The second step involved conducting a cluster analysis on the data obtained from the questionnaire to identify distinct groups of participants who shared consistent epistemological viewpoints. The results obtained from the two approaches are in agreement and shed light on the prevalent epistemic inclination that favors a constructivist viewpoint. Discussion on the ramifications of the findings, as well as the methodological issues that are pertinent to the present illustration, is provided.