Redesigning Assessments for AI-Enhanced Learning: A Framework for Educators in the Generative AI Era

Education Sciences, Journal Year: 2025, Volume and Issue: 15(2), P. 174 - 174

Published: Feb. 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.

Language: Английский

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The Impact of Prompt Engineering and a Generative AI-Driven Tool on Autonomous Learning: A Case Study

Education Sciences, Journal Year: 2025, Volume and Issue: 15(2), P. 199 - 199

Published: Feb. 7, 2025

This study evaluates “I Learn with Prompt Engineering”, a self-paced, self-regulated elective course designed to equip university students skills in prompt engineering effectively utilize large language models (LLMs), foster self-directed learning, and enhance academic English proficiency through generative AI applications. By integrating concepts tools, the supports autonomous learning addresses critical skill gaps market-ready capabilities. The also examines EnSmart, an AI-driven tool powered by GPT-4 integrated into Canvas LMS, which automates test content generation grading delivers real-time, human-like feedback. Performance evaluation, structured questionnaires, surveys were used evaluate course’s impact on prompting skills, proficiency, overall experiences. Results demonstrated significant improvements accessible patterns like “Persona” proving highly effective, while advanced such as “Flipped Interaction” posed challenges. Gains most notable among lower initial though engagement practice time varied. Students valued EnSmart’s intuitive integration accuracy but identified limitations question diversity adaptability. high final success rate that proper design (taking consideration Panadero’s four dimensions of learning) can facilitate successful learning. findings highlight AI’s potential task automation, emphasizing necessity human oversight for ethical effective implementation education.

Language: Английский

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Global Guidance on the Use of GenAI in Educational Research

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 53 - 66

Published: March 13, 2025

Generative AI (GenAI) tools have rapidly emerged and their use in educational research has been debated. There absence of national international regulations related to how it is used research. This chapter outlines policies that the GenAI It also reflects through revision literature on policies/regulations which impact state privacy, copyright, intellectual property. The utilizes a qualitative review GenAI. When considering guidelines policy designs, makers should ensure promote cultural diversity, equity inclusion, preservation human development agency, validate supervise education, cultivate competencies ethical GenAI, develop frameworks training programmes build capacity appropriate pluralism ideas expressions opinions, analyze long-term implications interdisciplinary intersectoral matters.

Language: Английский

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Potential of Artificial Intelligence Tools for Text Evaluation and Feedback Provision

Professional Discourse & Communication, Journal Year: 2025, Volume and Issue: 7(1), P. 70 - 88

Published: March 17, 2025

The article aims to explore the potential of generative artificial intelligence (AI) for assessing written work and providing feedback on it. goal this research is determine possibilities limitations AI when used evaluating students’ production feedback. To accomplish aim, a systematic review twenty-two original studies was conducted. selected were carried out in both Russian international contexts, with results published between 2022 2025. It found that criteria-based assessments made by models align those instructors, surpasses human evaluators its ability assess language argumentation. However, reliability evaluation negatively affected instability sequential assessments, hallucinations models, their limited account contextual nuances. Despite detailisation constructive nature from AI, it often insufficiently specific overly verbose, which can hinder student comprehension. Feedback primarily targets local deficiencies, while pay attention global issues, such as incomplete alignment content assigned topic. Unlike provides template-based feedback, avoiding indirect phrasing leading questions contributing development self-regulation skills. Nevertheless, these shortcomings be addressed through subsequent queries model. also students are open receiving AI; however, they prefer receive instructors peers. discussed context using formulating foreign instructors. conclusion emphasises necessity critical approach assessment importance training effective interaction technologies.

Language: Английский

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From Automation to Cognition: Redefining the Roles of Educators and Generative AI in Computing Education

Published: Feb. 12, 2025

Language: Английский

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Challenges in the automation of Education 4.0 using Industry 4.0 Technologies - A Systematic Review

Published: Aug. 28, 2024

Embracing Fourth Industrial Revolution(4IR) techniques is a need for long-term sustainability and to do automation in the processes of education sector. Rapid advancement information technology other engineering technologies demand more proactive steps institutes. In post pandemic world, there an increasing changes teaching learning methodologies with support modern digital technologies. So, all institutes have significant step change areas teaching. The impact 4 IR on sectors compared previous generation’s industrial revolution. Keeping track key can be quite challenge as they keep evolving at very fast pace. revolution current technological which major focus cyber physical biological systems such Artificial Intelligence, Robotics, Internet Things, Virtual Reality etc., educators institutions should establish pedagogies aid Industry 4.0 evolve 4.0. it important understand challenges competencies required about implementation 4IR by faculty members students who are currently studying Higher Education Institutes (HEIs). This paper aim systematic review industry its application relate online teaching, pedagogies, enhancement data management HEIs, virtual laboratories etc.

Language: Английский

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Integration of Generative Artificial Intelligence in Higher Education: Best Practices

Education Sciences, Journal Year: 2024, Volume and Issue: 15(1), P. 32 - 32

Published: Dec. 31, 2024

Generative artificial intelligence (GenAI) is transforming various sectors, including education. This study investigates the integration of GenAI in higher education, focusing on its potential to enhance teaching and learning. Through a series workshops courses delivered university professors, it examines opportunities such as improved resource creation challenges like ethical AI usage, proposing best practices for sustainable implementation classroom. The main objective analyze how use tools ChatGPT, Gemini, Claude can improve teachers’ professional skills overall educational experience while ensuring responsible use. methodology comprised literature review practical experimentation with professors. Data collection involved observations, surveys, discussion forums, cooperative activities, exercises focused evaluating AI-generated resources analyzing forum insights identify practices. results highlight several around improving writing, creating resources, supporting lesson planning, increasing teacher productivity. In addition, significant were identified, strategies detecting text. For instance, demonstrated 30% increase confidence highlighting effectiveness these technologies development. To address challenges, education are presented, primarily ongoing training, establishment institutional policies, encouragement use, evaluation impact setting. Best include clear guidelines, prompt development techniques, continuous training ensure teachers effectively responsibly integrate into their instructional These effective aim maximize benefits mitigating risks. prompts activities guidance balanced approach

Language: Английский

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Innovations in Introductory Programming Education: The Role of AI with Google Colab and Gemini

Education Sciences, Journal Year: 2024, Volume and Issue: 14(12), P. 1330 - 1330

Published: Dec. 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.

Language: Английский

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Capítulo 12: Aproximación a categorías de análisis de la Inteligencia Artificial en la educación

Published: Dec. 31, 2024

En la era actual, los contextos sociales, económicos, culturales, académicos y científicos están influenciados por evolución de las tecnologías digitales. Estas inciden en formas expresión, comunicación, pensamiento, comportamiento general interacción personas con su entorno. Así mismo, son evidentes retos, resistencias, interrogantes tensiones que han acompañado formación ciudadanos a nuevas alfabetización, entre cuales se destaca inteligencia artificial (IA), es considerada un área conocimiento emergente el escenario educativo. La IA contexto educación usa aspectos relacionados mejora experiencia aprendizaje, asistencia para escritura, enseñanza conceptos, desarrollo habilidades investigación evaluación del aprendizaje. El presente trabajo tiene como objetivo identificar categorías análisis emergen estudio artículos secundarios abordan educación. metodología fundamentó protocolo documental síntesis revisión provenientes bases datos Scopus Science Direct. Se incluyeron solamente revisiones analizaban uso superior. Los hallazgos muestran relevancia relacionadas (1) (2) alfabetización IA, (3) desafíos mitos, (4) (5) aplicaciones herramientas IA. Cada una estas pueden dar pautas sobre posibles líneas

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