Attitude Towards AI DOI
Soumya Thankam Varghese,

Angel Selvaraj

Advances in educational marketing, administration, and leadership book series, Год журнала: 2024, Номер unknown, С. 293 - 308

Опубликована: Ноя. 15, 2024

Understanding the attitude towards AI among teachers and students is meaningful as it will enhance adaptive transformative process in a collaborative manner. This research adopted survey method by distributing questionnaires to understand attitudes. The participation was voluntary after expressing consent. sampling convenient, size of participants 25. questions were mostly open-ended attitude. greater majority (91%) responded that they rely on sometimes only rest them (9%) never used their teaching or learning processes. factors led explore induced choices four different categories like, advance knowledge gain, Support for academic assignments, support time management. Among these category predominant factor with weightage 33% followed management (29%), assignments gain (9%).

Язык: Английский

Reshaping curriculum adaptation in the age of artificial intelligence: Mapping teachers' AI‐driven curriculum adaptation patterns DOI Creative Commons
Fatih Karataş, Barış Eriçok, Lokman TANRIKULU

и другие.

British Educational Research Journal, Год журнала: 2024, Номер unknown

Опубликована: Сен. 14, 2024

Abstract A national curriculum cannot be uniformly applied in all classrooms. Educators frequently adapt the official to suit their particular circumstances. In exploring interplay between artificial intelligence (AI) technologies and adaptation education, this study bridges a significant gap literature by how AI tools influence teachers' strategies for adapting curricula. Employing an explanatory sequential design, research analyses both qualitative quantitative data from 440 teachers, using Curriculum Adaptation Patterns Scale focus group semi‐structured interviews. Results indicate balanced approach among teachers towards extending revising curriculum, with less emphasis on omission. Notably, practices evolve positively increased professional experience, differ across disciplines, but remain constant school levels educational levels. Qualitatively, reported positive experiences AI, particularly ChatGPT, make lessons better fit students' needs. They've used it omit parts that aren't needed, add more relevant personalised content, revise or replace content. The findings highlight AI's transformative potential adaptation, making education engaging, personalised. contributes understanding can support effective implementation enhance learning digital age.

Язык: Английский

Процитировано

6

Effect of Online Learning on Mental Health and Academic Outcomes of Students with Intellectual Disabilities in Higher Education DOI Open Access

M.K. Shreeharsha,

P. Nagesh, Sridevi Kulenur

и другие.

Journal of Intellectual Disability - Diagnosis and Treatment, Год журнала: 2025, Номер 13(1), С. 34 - 43

Опубликована: Март 22, 2025

The COVID-19 pandemic shift to online learning has raised concerns regarding students’ mental health and academic performance, particularly for students with intellectual disabilities. Objective: This paper examines the effects of on stress, anxiety, social isolation those factors Grade Point Average (GPA), participation in engagement, disabilities (IDs). Methods: current study employed a quasi-experimental research design targeted 500 participants, comprising both undergraduate postgraduate students. Of these, 50 participants were identified as having (IDs) through self-reporting institutional records. remaining 450 typically developing selected stratified random sampling ensure proportional representation across levels disciplines. Perceived Stress Scale (PSS), Generalized Anxiety Disorder-7 (GAD-7), UCLA Loneliness adopted from validated widely used psychometric tools research. These instruments have been previously reliability applicability diverse populations. Multiple linear regression Pearson correlation coefficients (PPMC), which help identify associations control confounding factors, examine relationships potential predictive between variables outcomes. utilized analyze (stress, isolation) performance (GPA). Additionally, multiple analysis was conducted predict impact these while controlling such age, gender, degree level. Results: Participants IDs reported significantly higher stress (PSS, M = 25.8), anxiety (GAD-7, 12.5), (UCLA, 48.6) compared group. Mental had significant negative relationship GPA, coefficient -0.51 -0.48. In analysis, found largest effect outcome seconded by then isolation. Conclusion: A direct is observed, IDs, implying necessity an individual promotion program ways creating more effective that alleviate

Язык: Английский

Процитировано

0

Inteligencia artificial (IA) en las escuelas: una revisión sistemática (2019-2023) DOI Creative Commons

R. Bula,

Aureliano Camacho Bonilla

Enunciación, Год журнала: 2024, Номер 29(1), С. 62 - 82

Опубликована: Авг. 12, 2024

La inteligencia artificial (IA) ha surgido como una herramienta innovadora, con programas ChatGPT, Gemini, entre otros, un gran potencial para transformar la educación, y adaptarse a plataformas digitales existentes revolucionando los procesos de enseñanza. Este artículo tiene el objetivo proporcionar visión amplia equilibrada del panorama actual IA en las escuelas, lo cual se realizó revisión sistemática, mediante metodología Prisma (preferred reporting items for systematic reviews and meta-analyses), partir encontraron 52 artículos indexados base datos Scopus durante periodo 2019 2023, que abordaban temática escuelas. Según resultados, hay cuatro áreas temáticas clave destacan impacto IA: (a) enseñanza; (b) pedagogía, currículo formación docente; (c) gestión educativa, (d) implicaciones éticas. Se concluyó esta tecnología presenta por medio herramientas innovadoras; mejorar calidad aprendizaje; optimizar abordar desafíos personalización enseñanza evaluación rendimiento. No obstante, su implementación debe ser planificada meticulosamente, enmarcada principios éticos sólidos acompañada proceso docente adecuado garantizar uso responsable efectivo ámbito educativo.

Процитировано

2

Artificial Intelligence in the Education of Teachers: A Qualitative Synthesis of the Cutting-Edge Research Literature DOI Open Access
Ruşen Meylani

Journal of Computer and Education Research, Год журнала: 2024, Номер 12(24), С. 600 - 637

Опубликована: Сен. 23, 2024

The integration of Artificial Intelligence (AI) into teacher education has been transformative, offering personalized learning experiences, enhanced professional development, and improved teaching methodologies. AI technologies such as Intelligent Tutoring Systems (ITS), AI-driven analytics, automated assessment tools have become central to modern educational practices, significantly improving engagement, adaptability, effectiveness. This study employs a qualitative thematic analysis current literature on in education, examining peer-reviewed articles reports using coding identify key patterns, opportunities, challenges. findings reveal that enhances by providing pathways, fostering critical thinking, supporting ongoing growth. Technologies like ITS, Virtual Reality (VR), analytics proven effective promoting motivation engagement among teachers. However, ethical challenges biases systems concerns regarding data privacy require continuous attention. Furthermore, gap preparedness, particularly developing literacy integrating classroom is evident. Despite these challenges, offers substantial benefits, transforming practices enabling personalized, adaptive instruction supports both teachers students. emphasizes the need for comprehensive training programs focusing digital use, ensuring educators can navigate an AI-enhanced environment effectively. research contributes discourse highlighting guidelines robust programs, actionable insights educators, policymakers, institutions aiming integrate

Язык: Английский

Процитировано

2

Threats and Opportunities of Students’ Use Of AI-Integrated Technology (ChatGPT) in Online Higher Education: Saudi Arabian Educational Technologists’ Perspectives DOI Creative Commons

Mesfer Mihmas Mesfer Aldawsari,

Nouf Rashed Ibrahim Almohish

The International Review of Research in Open and Distributed Learning, Год журнала: 2024, Номер 25(3), С. 19 - 36

Опубликована: Авг. 26, 2024

This research study explored the perspectives of 20 educational technologists from four Saudi Arabian universities regarding integration AI-powered technology, particularly ChatGPT, into online higher education. The used a qualitative method that relied on principles theoretical sampling to select participants and conducted in-depth interviews collect their insights. approach taken for data analysis was thematic analysis, which uncovered rich range insights both challenges opportunities associated with students’ use AI-integrated technology in context Ten significant emerged shed light complexities intricacies integrating environments. These included issues related technological infrastructure, pedagogical adaptation, need comprehensive training programs empower teachers learners. Additionally, eight threats were examined highlighted concerns about security, privacy, potential risks AI institutions. not only provided overview current landscape education, but also valuable education stakeholders, technologists, policy makers. It underscored necessity proactive measures mitigate while harnessing presented by enhance quality effectiveness

Язык: Английский

Процитировано

1

Attitude Towards AI DOI
Soumya Thankam Varghese,

Angel Selvaraj

Advances in educational marketing, administration, and leadership book series, Год журнала: 2024, Номер unknown, С. 293 - 308

Опубликована: Ноя. 15, 2024

Understanding the attitude towards AI among teachers and students is meaningful as it will enhance adaptive transformative process in a collaborative manner. This research adopted survey method by distributing questionnaires to understand attitudes. The participation was voluntary after expressing consent. sampling convenient, size of participants 25. questions were mostly open-ended attitude. greater majority (91%) responded that they rely on sometimes only rest them (9%) never used their teaching or learning processes. factors led explore induced choices four different categories like, advance knowledge gain, Support for academic assignments, support time management. Among these category predominant factor with weightage 33% followed management (29%), assignments gain (9%).

Язык: Английский

Процитировано

0