Artificial Intelligence Literacy Competencies for Teachers Through Self-Assessment Tools DOI Open Access
Ieva Tenberga, Linda Daniela

Sustainability, Год журнала: 2024, Номер 16(23), С. 10386 - 10386

Опубликована: Ноя. 27, 2024

This study investigates the key components of teachers’ self-assessed artificial intelligence (AI) literacy competencies and how they align with existing digital frameworks. The rapid development AI technologies has highlighted need for educators to develop AI-related skills in order meaningfully integrate these into their professional practice. A pilot was conducted using a self-assessment questionnaire developed from frameworks such as DigiCompEdu Selfie Teachers tool. aimed explore relationships between competence already defined through principal component analysis (PCA). results revealed distinct competencies, highlighting overlaps some areas, example, resource management, while also confirming that form separate essential category. findings show although aligns other focused attention is required professionally AI-specific competencies. These insights are elements future research refine expand tools educators, providing targeted programs ensure teachers ready opportunities challenges education.

Язык: Английский

Building Proficiency in GAI: Key Competencies for Success DOI Creative Commons
Einat Grimberg, Claire Mason

Опубликована: Янв. 17, 2025

The rapid proliferation and adoption of generative Artificial Intelligence (GAI) underscores its ease use. However, there has been limited research exploring what constitutes proficient use GAI competencies underpin it. In this study, we adopt a grounded approach semi-structured interviews to explore how twenty-five expert users (all knowledge workers) define, exemplify, explain proficiency. A purposive sampling was adopted with the aim capturing input from experts range occupations sectors towards answering three questions. First, can identify characteristics that differentiate (more effective) GAI? Second, are seen underlie Third, benefits associated more tools? Analysis descriptions shared by revealed four aspects proficiency: effective prompting, informed responsible choices, diversity use, complexity frequency addition, following themes emerged analysis supporting GAI: literacy, domain expertise, communication skills, metacognition curiosity inquisitiveness, flexibility adaptability, diligence, (in some contexts) information technology skills. More have ranging improved productivity, higher quality output, original work. By offering comprehensive framework for GAI, in real-world experience, study guides further substantiates continuing relevance human knowledge, mindsets when working tools.

Язык: Английский

Процитировано

0

From Gretel to Strudelcity: Empowering Teachers Regarding Generative AI for Enhanced AI Literacy with CollectiveGPT DOI Creative Commons
Benedikt Brünner, Sandra Schön, Martin Ebner

и другие.

Education Sciences, Год журнала: 2025, Номер 15(2), С. 206 - 206

Опубликована: Фев. 8, 2025

In the era of transformative technologies, generative artificial intelligence (genAI) offers profound opportunities and challenges for education. This study explores development execution an interactive workshop designed to equip educators with foundational genAI literacy. Using a design-based research (DBR) framework, leverages interactivity contextual relevance introduce concepts, prompting strategies ethical considerations. Participants engaged in scripted learning design, comparing human AI responses, exploring genAI’s probabilistic foundations, context dependency, vulnerability manipulation. Conducted across 12 workshops 191 participants Austria, this revealed significant improvements self-perceived understanding, 70% reporting better grades post-assessment evaluations. Feedback emphasized workshop’s strengths relevance, alongside recommendations deeper school-specific applications. Scalability analysis showed that duration remained consistent regardless group size, suggesting potential broader implementation. The findings highlight effectiveness design fostering critical literacy, preparing critically evaluate ethically integrate into pedagogical practices. adaptable model contributes discourse on professional AI-enhanced

Язык: Английский

Процитировано

0

Building Proficiency in Generative AI: Key Competencies for Success DOI Creative Commons
Einat Grimberg, Claire Mason

Опубликована: Фев. 20, 2025

The rapid adoption of generative Artificial Intelligence (GenAI) underscores its ease use, yet research on GenAI proficiency and competencies is limited. This study uses semi-structured interviews with twenty-five expert users from various sectors to explore proficiency. aims answer three questions: What differentiates proficient use? support benefits does use provide? Three aspects emerged: effective prompting, informed responsible choices, diverse, complex use. following were seen GenAI: literacy, domain expertise, communication skills, metacognition, curiosity, flexibility, adaptability, diligence, IT skills. outcomes improved productivity, higher quality output, greater originality. framework, grounded in real-world experience, the importance human knowledge, mindsets for tools.

Язык: Английский

Процитировано

0

Unlocking Proficiency: Experts’ Views on the Use of Generative AI DOI Creative Commons
Einat Grimberg, Claire Mason

Опубликована: Март 25, 2025

The rapid proliferation and adoption of generative Artificial Intelligence (GenAI) underscore its ease use. However, there has been limited research exploring what constitutes proficient use GenAI competencies underpin it. In this study, we used semi-structured interviews to explore how twenty-five expert users (all knowledge workers) define, exemplify explain proficiency. A purposive sampling approach was adopted with the aim capturing input from experts a range occupations sectors towards answering three questions. First, can identify characteristics that differentiate (more effective) GenAI? Second, are seen underlie Third, benefits associated more tools? Analysis descriptions shared by revealed four aspects proficiency: effective prompting, informed responsible choices, diversity complexity use, frequency addition, following themes emerged analysis supporting GenAI: literacy, domain expertise, communication skills, metacognition curiosity inquisitiveness, flexibility adaptability, diligence (in some contexts) information technology skills. More have ranging improved productivity, higher quality output original work. By offering comprehensive framework for GenAI, grounded in real world experience, study guides further substantiates continuing relevance human mindsets when working tools.

Язык: Английский

Процитировано

0

Empowering Preservice Teachers’ AI Literacy: Current Understanding, Influential Factors, and Strategies for Improvement DOI Creative Commons
Bo Pei, Jie Lü, Xiping Jing

и другие.

Computers and Education Artificial Intelligence, Год журнала: 2025, Номер unknown, С. 100406 - 100406

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Examining teachers’ competencies in generative AI-enabled higher education: scale development and validation for empirical research DOI
Sayantan Mandal,

Avantika Bakshi,

Sheriya Sareen

и другие.

SN Social Sciences, Год журнала: 2025, Номер 5(4)

Опубликована: Март 24, 2025

Язык: Английский

Процитировано

0

EQUAL AI: A Framework for Enhancing Equity, Quality, Understanding and Accessibility in Liberal Arts through AI for Multilingual Learners DOI
Amin Davoodi

Language, Technology, and Social Media., Год журнала: 2024, Номер 2(2), С. 178 - 203

Опубликована: Ноя. 25, 2024

The integration of artificial intelligence (AI) into liberal arts education offers a transformative opportunity to address the diverse needs multilingual and multicultural learners. Consequently, this study introduces EQUAL AI framework (Enhancing Equity, Quality, Understanding, Accessibility in Liberal Arts through AI), structured approach utilizing foster inclusion innovation pedagogy. identifies five key domains: linguistic support, cultural representation, creative expression, critical thinking, collaborative learning. Additionally, underscores necessity systemic particularly professional development programs that equip educators with technical proficiency, ethical awareness, ability critically assess tools. By tackling challenges such as algorithmic bias, data privacy, digital divide, advocates for culturally responsive policies inclusive practices. envisions space equitable participation understanding, positioning tool enhance rather than replace humanistic pedagogy, ensuring its relevance technology-driven, interconnected world.

Язык: Английский

Процитировано

3

Restructuring the Landscape of Generative AI Research DOI
Salaheldin Edam

Advances in educational technologies and instructional design book series, Год журнала: 2024, Номер unknown, С. 287 - 334

Опубликована: Сен. 20, 2024

This Chapter delves into the impact of generative AI on academic research and publishing, discussing various architectures such as Mixture Experts (MoE), Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Pre-trained Transformers (GPT). The explores increase AI-centered preprints, their effects peer review, ethical considerations linked to them. peer-review system's integrity is under examination, focusing challenges related AI, misuse, redefining plagiarism. chapter potential tools improve review processes stresses importance institutions creating frameworks for utilization. article concludes by evaluating advantages drawbacks in research, with goal presenting a fair viewpoint its revolutionary capabilities while upholding principles.

Язык: Английский

Процитировано

1

The Construction of a Network Alliance of Foreign Language Teacher Development Communities in the Age of Artificial Intelligence DOI Creative Commons

J. Lu

Applied Mathematics and Nonlinear Sciences, Год журнала: 2024, Номер 9(1)

Опубликована: Янв. 1, 2024

Abstract The construction of a professional learning development community for foreign language teachers is related to the personal and group college guarantee improvement quality teaching in colleges universities. Starting from model networks network communities, this paper establishes teacher using mean drift clustering algorithm optimized by Gaussian kernel function. scale-free BA utilized construct alliance teachers’ establish indicators metrics. data communication platforms used as an example analyze structure alliance, comparison experiment designed application effect alliance. When cluster defined 5, sum squares 79.45%, greatest. average interaction degree number members was only 1.853, six had mediated centrality above 0.5. abilities ordinary excellent improved between 0.36 0.66 points after implementing community. Making full use intelligent technology carry out establishment helps improve ability realize quality.

Язык: Английский

Процитировано

0

Artificial Intelligence Literacy Competencies for Teachers Through Self-Assessment Tools DOI Open Access
Ieva Tenberga, Linda Daniela

Sustainability, Год журнала: 2024, Номер 16(23), С. 10386 - 10386

Опубликована: Ноя. 27, 2024

This study investigates the key components of teachers’ self-assessed artificial intelligence (AI) literacy competencies and how they align with existing digital frameworks. The rapid development AI technologies has highlighted need for educators to develop AI-related skills in order meaningfully integrate these into their professional practice. A pilot was conducted using a self-assessment questionnaire developed from frameworks such as DigiCompEdu Selfie Teachers tool. aimed explore relationships between competence already defined through principal component analysis (PCA). results revealed distinct competencies, highlighting overlaps some areas, example, resource management, while also confirming that form separate essential category. findings show although aligns other focused attention is required professionally AI-specific competencies. These insights are elements future research refine expand tools educators, providing targeted programs ensure teachers ready opportunities challenges education.

Язык: Английский

Процитировано

0