Опубликована: Фев. 24, 2012
Язык: Английский
Advances in educational marketing, administration, and leadership book series, Год журнала: 2024, Номер unknown, С. 179 - 206
Опубликована: Дек. 24, 2024
This chapter explores the transformative impact of generative artificial intelligence on inquiry-based learning in educational assessment. Generative AI technologies have revolutionized traditional assessment methods, enabling dynamic, individualized experiences that meet individual student needs. By harnessing power intelligence, teachers can create assessments promote critical thinking, conceptual understanding, and deeper engagement with content. The begins an overview theoretical foundations its integration into frameworks such as constructivism technology-enhanced learning. It discusses practical applications creating dynamic environments. Examples include tools like Knewton MATH from Carnegie Learning, which adapt methods based performance.
Язык: Английский
Процитировано
5
Journal of Research in Innovative Teaching & Learning, Год журнала: 2024, Номер 17(2), С. 414 - 416
Опубликована: Авг. 20, 2024
ChatGPT-supported student assessmentcan we rely on it?The advent of generative AI, particularly ChatGPT, in the educational sector is sparking a multifaceted debate its reliability for assessment.Recent literature focuses potential ChatGPT to revolutionize assessment methods, raising both enthusiastic endorsements capabilities and serious concerns about integrity effectiveness AI-driven evaluations (Klyshbekova Abbott, 2024).ChatGPT's advanced natural language processing (NLP) can mimic humanlike text generation, suggesting shift from traditional, linear models learning toward more dynamic personalized approaches (Dama sevi cius, 2023).This transition could enhance outcomes by tailoring experiences individual needs providing immediate feedback.The such AI assessments under scrutiny, concerning depth academic rigor responses.The integration grading has presented various challenges, juxtaposing traditional methods against emerging (Jukiewicz, 2024).ChatGPT when used handle large volumes quickly, feedback that consistent as long input remains within model's training data scope (Kooli Yusuf, grade assignments across different subjects, demonstrating moderate correlation with human graders, which highlights supportive tool 2024).However, ChatGPT's performance lack depth, missing nuanced insights experienced educators might offer (Ghapanchi Purarjomandlangrudi, 2023).The complexity subtlety responses be underappreciated may struggle interpretations require deep understanding contextual awareness.The standardization not address specific developmental students, are critical learning.The adoption similar technologies heralds significant broader implications field education (Yang et al., 2023).One most transformative impacts role educators.With handling routine administrative tasks, 1 2 redirect their focus towards in-depth, interactive teaching methods.This lead an enhancement pedagogical process, where emphasis shifts test fostering deeper thinking skills (Damasevicius Sidekerskiene, 2024).The into processes challenges reshape paradigms.AI's capability analyze vast amounts development sophisticated adaptive environments, JRIT 17,
Язык: Английский
Процитировано
2
Advances in educational marketing, administration, and leadership book series, Год журнала: 2024, Номер unknown, С. 173 - 193
Опубликована: Июнь 28, 2024
The educational landscape is undergoing a seismic shift, moving away from traditional paradigms that prioritize rote learning and static answers. This chapter introduces novel approach leverages AI-driven inquiry scenarios prompt engineering, emphasizing the development of critical questioning skills over mere provision aligns with demands rapidly evolving knowledge landscape, often referred to as “knowledge multiverse.” integrates generative AI, like ChatGPT, tool for fostering inquiry-based learning. methodology focuses on teaching students how formulate refine questions, skill authors term “prompt engineering.” method involves interactive sessions, workshops, project-based modules where learn interact AI effectively, guiding their journey through skillful questioning. posits future education lies in empowering navigate multiverse effective use AI.
Язык: Английский
Процитировано
1
Applied Sciences, Год журнала: 2024, Номер 14(18), С. 8344 - 8344
Опубликована: Сен. 16, 2024
Skilled programmers are in high demand, and a critical obstacle to satisfying this demand is the difficulty of acquiring programming skills. This issue can be addressed with automated assessment, which gives fast feedback students trying code, gamification, motivates them intensify their learning efforts. Although some collections gamified exercises available, producing new ones very demanding. paper presents GAMAI, an AI-powered exercise gamifier, enriching Framework for Gamified Programming Education (FGPE) ecosystem. Leveraging large language models, GAMAI enables teachers effortlessly apply storytelling describe scenario, as decorates natural text sentences needed by OpenAI APIs contextualize prompt. Once scenario has been generated, automatically produces files FGPE-compatible format. According presented evaluation results, most generated AI support were ready used, no or minimum human effort, positively assessed students. The usability software was also users. Our research paves way more efficient interactive approach education, leveraging capabilities advanced models conjunction gamification principles.
Язык: Английский
Процитировано
0
Опубликована: Фев. 24, 2012
Язык: Английский
Процитировано
0