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The purpose of this paper is to illuminate for social studies teachers and teacher educators the ways in which students' disciplinary writing is scaffolded within the context of the inquiry design model; trends in such scaffolding are called “the learner's pathway,” since it leads students to more abstract levels of historical argumentation. The author argues that engaging historical writing genres is a necessary component of historical thinking and that understanding the ways that teachers support students' historical writing capacities can help them to make more intentional choices when building inquiries.

To study genre-related scaffolding across inquiries, this study draws on systemic functional linguistics (SFL)-based genre theory as an analytical structure and seventy-four history-focused secondary social studies inquiries to determine any patterns in the ways that teachers scaffold students' writing genres through an inquiry.

Findings suggest that there is a learner's pathway that teachers use to develop students' argumentative writing capacities; however, there is also evidence to suggest that notetaking and source synthesis are not valued instructional products, limiting the potential impact of historical thinking work within the inquiry process.

The existence of this learner's pathway has implications for the ways that teachers and preservice teachers can be professionally developed to leverage this pathway. Rather than the often-used methods of support students' generic writing capacities, professional development should focus on the ways social studies teachers can guide students to more abstract reasoning through their writing. This study's findings also have implications for the ways that social studies teachers assess students' summative arguments. Assessment practices should focus on the genre-features of “argument” rather than just the stages of the argumentative essay.

This piece is original because genre-based research is missing from much of the social studies education research. This study's findings present an additional paradigm through which social studies teachers and teacher leaders can explore the purposes of historical writing tasks and assessment.

The lesson study aims to examine college English teachers' growth in technological pedagogical content knowledge (TPACK) and the improvement of students' learning outcomes in the context of MOOC-based and AI-powered flipped teaching and assessment of EFL writing (MAFTA).

Three college EFL teachers and their students (66 in total) participated in three cycles of MAFTA instruction. Triangulated analysis was conducted by considering all relevant data sources, including the teachers' discussions and reflections, the argumentative essays produced by the students before and after the MAFTA instruction, as well as the data gathered through questionnaires and interviews.

The three teachers demonstrated varying degrees of growth in TPACK, as evidenced by their increased knowledge of the technology tools and skills in utilizing the tools to realize their pedagogical beliefs on teaching EFL writing. Substantial improvements were detected in students' essays. The students generally have affirmative perceptions on the MAFTA model and the questionnaire and interviews specified the benefits they gained from each stage of the model.

Firstly, the lesson study is grounded in an innovative approach to teaching EFL writing that incorporates multiple technological affordances. Secondly, it closely scrutinizes the dynamics of both teachers' and students' growths during the innovative practice. The findings could offer insights into teachers' TPACK development and effective integration of technological advancements in EFL education at the tertiary level.

This paper investigated the possibilities of implementing inclusive education in the tertiary-level language classrooms and suggests new teaching methodologies adhering to the guidelines of multicultural education (MCE) framework. It explored how Indian teachers fostered social inclusivity in ESP (English for Specific Purposes) classrooms and documented the methods used by the language teachers to sustain a socially inclusive environment in the classroom.

This qualitative study undertaken with 17 faculty members using online interviews and surveys as tools revealed the challenges faced by the teachers.

The results have implications towards teacher training as there is a clear dearth of teacher strategies to foster an equitable and inclusive learning environment inside the classroom.

Classrooms are the sources of values and perspectives, and teachers are responsible for providing equal opportunities to students who are otherwise marginalised in society.

Inclusive education aims at providing equal opportunities to people despite the differences in terms of race, class, caste, region, religion, gender, sexuality, ethnicity and disabilities. India being a multilingual and multicultural country, inculcating values in students to enable them to reflect beyond these differences becomes important.

The global prominence of languages and Saudi Arabia’s Vision 2030, which supports the necessity of German proficiency for the nation’s socioeconomic evolution, necessitate a deeper understanding of German teaching in Saudi international schools. This study delves into the influence of various teaching strategies on students' German writing skills. The research particularly focuses on traditional and innovative methods and considers the factors that drive these teaching approaches.

Data were collected from 304 students in Riyadh, Saudi Arabia, through a questionnaire. The relationships between teaching strategies and students' German writing abilities were analyzed using regression techniques.

The results indicate that both traditional and innovative teaching strategies positively influence students' writing skills. The regression analysis shows that the independent variables (traditional teaching strategies, innovative teaching strategies and factors influencing teaching strategies) collectively account for 68.9% of the variation in students' German writing skills. Even though a variety of techniques influence students' academic performance, the study’s findings indicate that several strategies – such as self-evaluation, pair work, oral feedback, grammar instruction and translation – have a major impact on students' German writing abilities.

This research brings unique insights into the German teaching realm of Saudi international schools, emphasizing the harmony between Vision 2030 goals and effective teaching methodologies. It elucidates the considerable influence of both traditional and innovative strategies on student writing outcomes. For educators in Saudi Arabia’s international educational environment, the study’s findings underline the importance of adopting student-centric approaches in the writing process, ensuring students evolve as proficient writers. Additionally, the research underscores the significant role of variables affecting teaching strategies, spotlighting their pivotal role in shaping student outcomes.

With 43.2 million coronavirus cases and 525,000 deaths in 2022, India ranked second worldwide, after the United States (84.6 million cases and 1 million deaths), according to the latest available June 2022 COVID-19 impact data.

Amid people’s growing mistrust in the government, India’s news media enhanced the nation’s distinguished designation as the world’s largest and most populous democracy. India’s news media inform, educate, empower, and entertain a surging population of 1.4 billion people, which is roughly one-sixth of the world’s people.

Drawing upon the media agendamelding theoretical framework, we conducted a case study research into interplay between two prominent democratic institutions, the media and the government, to analyze the role of the COVID-19 pandemic in redefining India’s networked society.

India’s COVID-19 pandemic aggravated internecine tensions between media and government relating to four key freedom issues: (1) world’s largest COVID-19 lockdown affecting 1.3 billion Indians from March 25, 2020 to August 2020 with extensions and five-phased re-openings, to restrict the spread of COVID-19; (2) Internet shutdowns; (3) media censorship during the 1975–1977 “Emergency”; and (4) unabated murders of journalists in India.

Although the COVID-19 pandemic caused deleterious problems debilitating the tensions between the media and the government, India’s journalists thrived by speaking truth to power. This study delineates key aspects of India’s media agendamelding that explicates how the people of India form their media agendas. India’s news audiences meld media messages from newspapers, television, and social media to form a picture of the issues, insights, and ideas that define their lives and times in the 21st century digital age.

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

Self-regulation is the level of learning where the learner becomes an active agent in their learning process in terms of activity and aspects of motivation and metacognition. The current paper mostly deals with the metacognitive aspect. The purpose of this study is to gain insight into self-regulation of learning in the context of modern technology in higher education. This study also aims to highlight the direction, tendencies and trends toward which self-regulation of learning is moving in relation to modern technologies.

The review study was compiled via searches in three databases: Scopus, Web of Science and ERIC. A filter was used to search for empirical studies solely in English, published over the past decade on the topics of self-regulation of learning and technology in higher education.

The findings clearly show a correlation between self-regulation of learning and modern technology, especially after a significant event such as the Covid-19 pandemic. However, in the wake of this change, the field of education has seen the emergence of methods and new platforms that can provide support for the development of self-regulated learning strategies.

The originality of the study lies in the fact that it focuses on the link between self-regulation of learning and modern technologies in higher education, including some predictions of the future direction of self-regulation of learning in this context.

Preservice teachers (PSTs) typically have few opportunities to observe social studies instruction in PSTs' elementary field placements. To practice effective integration as a pathway to include more social studies instruction, PSTs developed a unit plan based on inquiry during an undergraduate methods course. The purpose of this study was to explore what scaffolds were effective in PSTs' development of social studies inquiry projects.

The author used a multiple case study approach, examining initial submissions, feedback and resubmissions as PSTs developed PSTs' inquiry projects. The data were analyzed with an eye on PSTs' ability to plan a unit according to the four dimensions of the C3 Framework's inquiry arc (National Council for the Social Studies [NCSS], 2013).

The author analyzed data related to PSTs’ area of highest need from PSTs' initial submissions: staging the task, formative tasks and resources. PSTs were able to develop inquiry projects after being supported in their (1) organization, (2) clarity, (3) alignment and (4) developmental appropriateness.

This study shows that novice teachers can create high-quality social studies learning experiences in elementary school when provided appropriate supports (in this case, feedback about organization, clarity, alignment and developmental appropriateness). With the tools to develop such projects, new teachers may be able to increase the amount of social studies taught in elementary classrooms.

This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.

This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.

Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.

This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.

This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.

This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.