Innovations in Introductory Programming Education: The Role of AI with Google Colab and Gemini DOI Creative Commons
Joe Llerena-Izquierdo, Johan Méndez Reyes, Raquel Ayala Carabajo

и другие.

Education Sciences, Год журнала: 2024, Номер 14(12), С. 1330 - 1330

Опубликована: Дек. 4, 2024

This study explores the impact of artificial intelligence on teaching programming, focusing GenAI Gemini tool in Google Colab. It evaluates how this technology influences comprehension fundamental concepts, processes, and effective practices. In research, students’ motivation, interest, satisfaction are determined, as well fulfillment surpassing their learning expectations. With a quantitative approach quasi-experimental design, an investigation was carried out seven programming groups polytechnic university Guayaquil, Ecuador. The results reveal that use significantly increases interest with 91% respondents expressing increased enthusiasm. addition, 90% feel integration meets expectations, it has exceeded those expectations terms educational support. evidences value integrating advanced technologies into education, suggesting can transform programming. However, successful implementation depends timely training educators, ethics for students, ongoing technology, curriculum design maximizes capabilities GenAI.

Язык: Английский

Redesigning Assessments for AI-Enhanced Learning: A Framework for Educators in the Generative AI Era DOI Creative Commons
Zuheir N. Khlaif,

Wejdan Awadallah Alkouk,

Nisreen Salama

и другие.

Education Sciences, Год журнала: 2025, Номер 15(2), С. 174 - 174

Опубликована: Фев. 2, 2025

The emergence of generative artificial intelligence (Gen AI) in education offers both opportunities and challenges, particularly the context student assessment. This study examines faculty members’ motivations to redesign assessments for their courses Gen AI era introduces a framework this purpose. A qualitative methodology was employed, gathering data through semi-structured interviews focus groups, along with examples redesigned assessments. Sixty-one members participated study, were analyzed using deductive inductive thematic approaches. Key redesigning included maintaining academic integrity, preparing learners future careers, adapting technological advancements, aligning institutional policies. However, also highlighted significant such as need professional development addressing equity accessibility concerns. findings identified various innovative assessment approaches tailored requirements era. Based on these insights, developed conceptual titled “Against, Avoid, Adopt, Explore”. Future research is needed validate further refine its application educational contexts.

Язык: Английский

Процитировано

1

It Is Not the Huge Enemy: Preservice Teachers’ Evolving Perspectives on AI DOI Creative Commons
Ese Emmanuel Uwosomah, Melinda Dooly

Education Sciences, Год журнала: 2025, Номер 15(2), С. 152 - 152

Опубликована: Янв. 26, 2025

The application of Artificial Intelligence (AI) to teacher training is a rather recent phenomenon and there need for more research on its use in education. This paper examines the interpretation AI by student language teachers during 10-week telecollaborative course between students from two universities, one USA other Spain (n = 46). focused Technology-Enhanced Project-Based Language Learning (TePBLL) was divided into different ‘technological blocks’. article centered around technology block. analysis based three exit tickets (reflection prompts) that demonstrate participants’ thoughts changing perspectives towards AI. Through thematic open-ended responses, this study shows participants initially appeared skeptical before moving tentative optimism after first studying theory examples AI, followed creation AI-based lessons activities. identify as means personalize make learning efficient while expressing concerns related overuse, ethical issues potential undermining critical thinking creativity. small looks at evolution teachers’ concepts about AI-enhanced teaching before, they engage findings suggest hands-on includes lesson design helps view complementary tool many aspects their teaching, although can only be achieved through an adequate pedagogical application.

Язык: Английский

Процитировано

0

GenAI in Indian Higher Education: Faculty at the Crossroads of Adoption DOI
Mohammad Razi-ur-Rahim,

Jahangir Chauhan,

Furquan Uddin

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Фев. 10, 2025

Abstract While global institutions embrace GenAI to enhance education, many faculty members in India remain hesitant adopt it. Earlier research found that only a few studies have examined the adoption of at university level, especially developing countries. Sparsely explores how teachers accept and use GenAI, they failed provide complete picture its adoption. It highlights significant gap. This study provides what influences GenAI. Being, part an information system, novel construct 'Output Quality' TAM is added. The employed quantitative, single cross-sectional design. A total 455 from higher education participated, their responses were analyzed using CB-SEM. reveals perceived ease drives most, followed by usefulness social norms. Output quality has most decisive impact on use. Institutions can inspire through incentives recognition. findings will guide educators, administrators, policymakers who want integrate into education.

Язык: Английский

Процитировано

0

Bridging expectations and reality: Addressing the price-value paradox in teachers' AI integration DOI
Nitzan Elyakim

Education and Information Technologies, Год журнала: 2025, Номер unknown

Опубликована: Март 4, 2025

Язык: Английский

Процитировано

0

What percentage of secondary school students do their homework with the help of artificial intelligence? - A survey of attitudes towards artificial intelligence DOI Creative Commons
Mátyás Turós

Computers and Education Artificial Intelligence, Год журнала: 2025, Номер unknown, С. 100394 - 100394

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Exploring the Determinants of the Sustainable Use of Artificial Intelligence in Peruvian University Teachers: A Structural Equation Modeling Analysis DOI Open Access
Benicio Gonzalo Acosta Enríquez, Moisés David Reyes Pérez, Olger Huamaní Jordan

и другие.

Sustainability, Год журнала: 2025, Номер 17(7), С. 2834 - 2834

Опубликована: Март 22, 2025

This study examines the determinants of sustainable use artificial intelligence (AI) among university professors in Peru. research adopted a quantitative approach through cross-sectional empirical–explanatory study, employing structural equation model. Data were collected from 368 eight Peruvian universities using structured questionnaire that assessed six main constructs: attitude toward AI, prejudice against facilitating conditions, teaching concerns, and ethical perception. While results reveal significant correlational relationships—with AI showing association with its use, relationship professors’ perceptions—the nature this precludes causal inferences. No was found between concerns. Additionally, demographic variables such as gender age did not exhibit moderating effects. These findings contribute to understanding factors related adoption higher education provide valuable insights for development effective institutional strategies Latin American context.

Язык: Английский

Процитировано

0

Inteligencia artificial generativa en la educación superior: usos y opiniones de los profesores DOI Creative Commons
José Eduardo Perezchica Vega, Jesuán Adalberto Sepúlveda Rodríguez, Alan David Román-Méndez

и другие.

European Public & Social Innovation Review, Год журнала: 2024, Номер 9, С. 1 - 20

Опубликована: Авг. 29, 2024

Introducción: La inteligencia artificial generativa (IAG) ha suscitado gran interés en el ámbito educativo, así como preocupaciones sobre su mal uso. Este estudio exploró las inquietudes de los docentes uso, cómo la han utilizado ellos, medidas preventivas que adoptan y formación tema. Metodología: Se realizó una investigación tipo cuantitativa, no experimental, transversal, con alcance exploratorio descriptivo. Incluyó elaboración aplicación un instrumento cuestionario, análisis Resultados: encontró docentes: a) están preocupados por riesgo exámenes tareas sean resueltos apoyo IAG, b) reconocen beneficios IAG para datos, generación ideas, redacción actividades aprendizaje creación materiales didácticos, destacando ahorro tiempo mejora calidad educativa, c) formándose y, general, se perciben capaces integrar sus clases. Conclusiones: Los muestran ávidos uso lo personal académico, pero clases sienten preocupación riesgos, aunque aún realizan ajustes a mecanismos evaluación.

Процитировано

3

The impact of pedagogical beliefs on the adoption of generative AI in higher education: predictive model from UTAUT2 DOI Creative Commons
Julio Cabero Almenara, Antonio Palacios‐Rodríguez, María Isabel Loaiza Aguirre

и другие.

Frontiers in Artificial Intelligence, Год журнала: 2024, Номер 7

Опубликована: Окт. 17, 2024

Artificial Intelligence in Education (AIEd) offers advanced tools that can personalize learning experiences and enhance teachers' research capabilities. This paper explores the beliefs of 425 university teachers regarding integration generative AI educational settings, utilizing UTAUT2 model to predict their acceptance usage patterns through Partial Least Squares (PLS) method. The findings indicate performance expectations, effort expectancy, social influence, facilitating conditions, hedonic motivation all positively impact intention behavior related use AIEd. Notably, study reveals with constructivist pedagogical are more inclined adopt AIEd, underscoring significance considering attitudes motivations for effective technology education. provides valuable insights into factors influencing decisions embrace thereby contributing a deeper understanding contexts. Moreover, study's results emphasize critical role orientations utilization technologies. Constructivist educators, who student-centered active engagement, shown be receptive incorporating AIEd compared transmissive counterparts, focus on direct instruction information dissemination. distinction highlights need tailored professional development programs address specific needs different teaching philosophies. Furthermore, comprehensive approach, various dimensions model, robust framework analyzing

Язык: Английский

Процитировано

2

Adoption of artificial intelligence in higher education: an empirical study of the UTAUT model in Indian universities DOI
Silky Sharma, Gurinder Singh

International Journal of Systems Assurance Engineering and Management, Год журнала: 2024, Номер unknown

Опубликована: Дек. 2, 2024

Язык: Английский

Процитировано

0

Innovations in Introductory Programming Education: The Role of AI with Google Colab and Gemini DOI Creative Commons
Joe Llerena-Izquierdo, Johan Méndez Reyes, Raquel Ayala Carabajo

и другие.

Education Sciences, Год журнала: 2024, Номер 14(12), С. 1330 - 1330

Опубликована: Дек. 4, 2024

This study explores the impact of artificial intelligence on teaching programming, focusing GenAI Gemini tool in Google Colab. It evaluates how this technology influences comprehension fundamental concepts, processes, and effective practices. In research, students’ motivation, interest, satisfaction are determined, as well fulfillment surpassing their learning expectations. With a quantitative approach quasi-experimental design, an investigation was carried out seven programming groups polytechnic university Guayaquil, Ecuador. The results reveal that use significantly increases interest with 91% respondents expressing increased enthusiasm. addition, 90% feel integration meets expectations, it has exceeded those expectations terms educational support. evidences value integrating advanced technologies into education, suggesting can transform programming. However, successful implementation depends timely training educators, ethics for students, ongoing technology, curriculum design maximizes capabilities GenAI.

Язык: Английский

Процитировано

0