Hasil untuk "History of education"

M. Bond, Hassan Khosravi, Maarten de Laat et al.

Although the field of Artificial Intelligence in Education (AIEd) has a substantial history as a research domain, never before has the rapid evolution of AI applications in education sparked such prominent public discourse. Given the already rapidly growing AIEd literature base in higher education, now is the time to ensure that the field has a solid research and conceptual grounding. This review of reviews is the first comprehensive meta review to explore the scope and nature of AIEd in higher education (AIHEd) research, by synthesising secondary research (e.g., systematic reviews), indexed in the Web of Science, Scopus, ERIC, EBSCOHost, IEEE Xplore, ScienceDirect and ACM Digital Library, or captured through snowballing in OpenAlex, ResearchGate and Google Scholar. Reviews were included if they synthesised applications of AI solely in formal higher or continuing education, were published in English between 2018 and July 2023, were journal articles or full conference papers, and if they had a method section 66 publications were included for data extraction and synthesis in EPPI Reviewer, which were predominantly systematic reviews (66.7%), published by authors from North America (27.3%), conducted in teams (89.4%) in mostly domestic-only collaborations (71.2%). Findings show that these reviews mostly focused on AIHEd generally (47.0%) or Profiling and Prediction (28.8%) as thematic foci, however key findings indicated a predominance of the use of Adaptive Systems and Personalisation in higher education. Research gaps identified suggest a need for greater ethical, methodological, and contextual considerations within future research, alongside interdisciplinary approaches to AIHEd application. Suggestions are provided to guide future primary and secondary research.

Paul C. Helmreich

W. Wilder

Suharno, N. A. Pambudi, B. Harjanto

Abstract This study aims at comprehensively describing the ups and downs of vocational education in Indonesia, which includes its history, development, opportunities, and challenges. Researches in this field are rarely conducted, but necessary to be revealed in the midst of the incessant criticism. This study uses a qualitative approach with a cross-sectional design. However, due to the complexity of the variables and the difficulty in accessing sources in their original form (primary sources), this study utilizes policy documents and relevant research work. Data analysis has been added, including: inductive, deductive, and meta-analysis. Data were obtained from principals, students and teachers of vocational high schools (SMK). Furthermore, purposive sampling was selected to obtain data, giving a sample population consisting of 44 principals, 152 teachers, and 202 students. Purposive sampling was chosen due to its in-depth understanding on vocational education. However, not all principals and teachers in Indonesia are vocational based. Data were obtained from experts in the field of vocational education through interview, observation, documentation, and questionnaire guidelines compiled and validation. The results showed that vocational education in Indonesia has been in existence before the country gained independence, and after reform. However, before independence, the Netherlands organized Vocational Education, known as the Bandung Institute of Technology (ITB), which is still developing. Vocational education before independence was divided into 4 areas of expertise, namely feminine, engineering, agriculture and trade schools. After reform in 1998, the different schools were merged into one, namely vocational school (SMK) having 142 spectrums of skills. Furthermore, the development of vocational education was changed in 2008. The Indonesian government changed the ratio of senior high schools: vocational schools from 70%: 30% to 30%: 70%. The establishment of a new school was not balanced with a feasibility study, and this resulted in graduates finding it difficult to get a job. They learned approaches which tended to be theoretical and less relevant in the labour market. In addition, 74% of students were bored during learning due to the numerous social lessons. Some of the challenges faced were the inadequate facilities, teachers and industry support. However, the clear regulation on the industry's role is one of the important solutions. Strong industry support can be applied and vocational graduates have the competence in accordance with the needs of the labour market.

Eun-Byul Cho, Jae-Chang Lee, Eun-Jung Kim et al.

Objectives: The present study aimed to analyze the status and needs of Korean Medicine doctors’ (KMDs) continuing professional development (CPD) and establish future improvement directions. Methods : A cross-sectional survey targeting all KMDs was conducted between October 23 to November 5, 2024, obtaining 624 responses. The questionnaire was developed to assess satisfaction with continuing education and residency training, perceived efficacy on competency development, and improvement needs. Results : While current CPD programs effectively enhanced optimal patient care competencies (highest-rated domain), approximately 40% of respondents indicated minimal improvement in social accountability and clinical management competencies. The most requested improvements were the expansion of practical training opportunities (63.0%) and curriculum improvement (37.0%). For residency training, respondents prioritized developing competency-centered curricula (65.0%) and standardized educational programs across training hospitals (63.3%). Conclusion : Findings indicate that KMDs desire increased practical training opportunities, competency-based standardized curricula, and expanded scope of practice through institutional support. Establishing competency frameworks across clinical departments and strengthening competencies required in modern healthcare environments are essential for advancing Korean Medicine practice.

Lisa Bornscheuer, Evelina Landstedt, Karl Gauffin et al.

Abstract Background Childhood adversity places individuals in a vulnerable position, resulting in potentially enduring disadvantage across life domains like health and work. Studying the manifestation of this disadvantage is crucial for understanding which resources society can provide to mitigate or prevent it, which makes this subject a fundamental public health concern. This study investigated whether disadvantage patterns after childhood adversity differ by gender and educational level, using out-of-home care as proxy for early adversity. Methods We used register data from a 1953 Swedish birth cohort. Distinct profiles of socioeconomic and health disadvantage in individuals with out-of-home care experience were identified using group-based multi-trajectory modelling. Multinomial logistic regression was then used to determine whether gender and education, individually or in interaction with each other, predict group membership. Results In the population without history of out-of-home care, adulthood disadvantage was highly gendered, with women being more likely to experience disadvantage related to unemployment and poor health, while criminality and substance misuse was more common among men. History of out-of-home care was associated with a general increase in adulthood disadvantage, but the gender differences were largely absent. Women in this group were however less likely than men to experience disadvantage across multiple life domains (complex disadvantage OR = 0.56, p = 0.046; unemployment-related disadvantage OR = 0.51, p = 0.005). Higher level of education was associated with reduced likelihood of membership in the group marked by disabling health disadvantage (OR = 0.55, p = 0.002) and complex disadvantage (OR = 0.37, p = 0.001). An interaction term between gender and education was not significant. Conclusions Adulthood disadvantage was more common in the group with history of out-of-home care. The gender differences in disadvantage present in the full cohort were largely attenuated among individuals with out-of-home care history. We showed that using administrative data on outcomes across multiple life domains can provide rich descriptions of adult experiences after childhood adversity. Future research could examine gender differences in mechanisms translating into resilient or vulnerable trajectories, including the protective potential of education in relation to specific disadvantage patterns.

Tinsae Seyoum, Selamnesh Tesfaye, Yohannes Shiferaw et al.

<h4>Background</h4>Type 2 diabetes accounts for over 90% of all diabetes cases and is caused by a combination of behavioral risk factors. It is currently a serious health issue, particularly among women of reproductive age, as it is associated with reproductive disorders. Preventing it requires knowledge, but there is limited data on behavioral risk factors in Ethiopia.<h4>Objective</h4>To assess knowledge of the behavioral risks of type 2 diabetes mellitus and its associated factors among women of reproductive age.<h4>Methods</h4>A community-based cross-sectional study was conducted, with all women in the town serving as the source population. A multistage sampling method was utilized to recruit kebeles, and a systematic random technique was employed to select households at every 13th interval. We completed interview questionnaires for 623 samples. The crude odds ratio was calculated using a bivariate logistic model, and multivariate analysis was performed to control for confounding and identify associated factors among model-fitting variables using an adjusted odds ratio (AOR).<h4>Result</h4>The knowledge of behavioral risk factors (BRF) among women of reproductive age (WRA) is 47.0% [95% CI, 43.5-50.9], and significant associations were found with the following factors: average family income of between 3000 and 5000 Ethiopian Birr(ETH) 1.81 [95% CI, 1.03-3.18], > = 5001 ETH 1.93 [95% CI, 1.02-3.68], diabetes mellitus (DM) in the friend or relatives 4.03 [95% CI, 1.56-10.46], family history of DM 9.47 [95% CI, 4.74-18.90], source of information: health workers 1.87 [95% CI, 1.04-3.34] and friend or relatives 1.65 [95% CI, 1.04-2.62].<h4>Conclusion</h4>Knowledge of behavioral risk factors for type 2 diabetes was poor among study participants. Factors such as family income, diabetes mellitus (DM) in friends or relatives, family history of DM, and sources of information were strongly associated with good knowledge. It is essential to emphasize health education about behavioral risk factors for women.

Kiwhan Song, Boyuan Chen, Max Simchowitz et al.

Classifier-free guidance (CFG) is a key technique for improving conditional generation in diffusion models, enabling more accurate control while enhancing sample quality. It is natural to extend this technique to video diffusion, which generates video conditioned on a variable number of context frames, collectively referred to as history. However, we find two key challenges to guiding with variable-length history: architectures that only support fixed-size conditioning, and the empirical observation that CFG-style history dropout performs poorly. To address this, we propose the Diffusion Forcing Transformer (DFoT), a video diffusion architecture and theoretically grounded training objective that jointly enable conditioning on a flexible number of history frames. We then introduce History Guidance, a family of guidance methods uniquely enabled by DFoT. We show that its simplest form, vanilla history guidance, already significantly improves video generation quality and temporal consistency. A more advanced method, history guidance across time and frequency further enhances motion dynamics, enables compositional generalization to out-of-distribution history, and can stably roll out extremely long videos. Project website: https://boyuan.space/history-guidance

Nikolaos Avouris

This paper discusses key challenges of Artificial Intelligence in Education, with main focus on higher education institutions. We start with reviewing normative actions of international organizations and concerns expressed about the current technical landscape. Then we proceed with proposing a framework that comprises five key dimensions relating to the main challenges relating to AI in higher education institutions, followed by five key strategic actions that the main stakeholders need to take in order to address the current developments. We map these actions to the main stakeholders of higher education and propose a deployment plan. This defines a framework along the dimensions: Challenges, Actions, Stakeholders, Deployment CASD. Examples of AI specific actions at the institutional and individual course level are also provided and discussed.

Noah Q. Cowit, Sri Yash Tadimalla, Stephanie T. Jones et al.

Many institutions are currently grappling with teaching artificial intelligence (AI) in the face of growing demand and relevance in our world. The Computing Research Association (CRA) has conducted 32 moderated virtual roundtable discussions of 202 experts committed to improving AI education. These discussions slot into four focus areas: AI Knowledge Areas and Pedagogy, Infrastructure Challenges in AI Education, Strategies to Increase Capacity in AI Education, and AI Education for All. Roundtables were organized around institution type to consider the particular goals and resources of different AI education environments. We identified the following high-level community needs to increase capacity in AI education. A significant digital divide creates major infrastructure hurdles, especially for smaller and under-resourced institutions. These challenges manifest as a shortage of faculty with AI expertise, who also face limited time for reskilling; a lack of computational infrastructure for students and faculty to develop and test AI models; and insufficient institutional technical support. Compounding these issues is the large burden associated with updating curricula and creating new programs. To address the faculty gap, accessible and continuous professional development is crucial for faculty to learn about AI and its ethical dimensions. This support is particularly needed for under-resourced institutions and must extend to faculty both within and outside of computing programs to ensure all students have access to AI education. We have compiled and organized a list of resources that our participant experts mentioned throughout this study. These resources contribute to a frequent request heard during the roundtables: a central repository of AI education resources for institutions to freely use across higher education.

Maria Eleni Koutsiaki, Marina Delianidi, Chaido Mizeli et al.

The integration of AI chatbots into educational settings has opened new pathways for transforming teaching and learning, offering enhanced support to both educators and learners. This study investigates the design and application of an AI chatbot as an educational tool in higher education. Designed to operate in the Greek language, the chatbot addresses linguistic challenges unique to Greek while delivering accurate, context grounded support aligned with the curriculum. The AI chatbot is built on the Retrieval Augmented Generation (RAG) framework by grounding its responses in specific course content. RAG architecture significantly enhances the chatbots reliability by providing accurate, context-aware responses while mitigating common challenges associated with large language models (LLMs), such as hallucinations and misinformation. The AI chatbot serves a dual purpose: it enables students to access accurate, ondemand academic support and assists educators in the rapid creation of relevant educational materials. This dual functionality promotes learner autonomy and streamlines the instructional design process. The study aims to evaluate the effectiveness, reliability, and perceived usability of RAG based chatbots in higher education, exploring their potential to enhance educational practices and outcomes as well as supporting the broader adoption of AI technologies in language specific educational contexts. Findings from this research are expected to contribute to the emerging field of AI driven education by demonstrating how intelligent systems can be effectively aligned with pedagogical goals.

周愚文 Yu-Wen Chou

以往教育研究多注意國家太平時期的發展，較少關注政局動盪下的教育變革。1912年1月中華民國建立，但因民初政局未穩，為因應開學所需，新設教育部只得儘速修改前清癸卯學制後發布命令施行；之後再新頒教育宗旨、學校系統、各級教育令及課程標準。最初教育部曾想另訂新制，但後迫於復學時間緊湊，只能修改舊制。再者，新訂學校系統仍是以前清學 制為基礎而稍修訂。本研究旨在探討民初辛亥革命後至袁氏稱帝前（1912-1916年）教育制度的再造，採史學方法，根據政府檔案、法規、公報、教育報刊及時人文集等一手資料，經內、外部考證後，探討教育制度調整的原因、經過、實施狀況及影響因素。研究發現，當時地方未能完全落實新制，其原因除政局不穩、戰事迭起外，原仿日學制持續發揮影響力、中央及地方經費支絀、地方教育行政體制殘破及中央地方爭權，均影響新制改革與落實。最後，研究指出政治革命後，舊有教育制度不必然也遭推翻，政府往往仍沿用後再修改，策略上是「穿衣改衣」，而無法另起爐灶。此段國家動盪時期的教育變革經驗，值得今後欲採革命式教育改革策略決策者關注。 The state of education during tumultuous times has often been overlooked by educational historians. However, such periods warrant attention because educational opportunities can be severely limited during these times. The fall of the Ch’ing dynasty in October 1911 led to the establishment of the Republic of China. Although a provisional Republican government was inaugurated in Nanking on January 1, 1912, the new democracy remained divided. A new Ministry of Education was established, and Dr. Yuan-Pei Tsai became its first minister. Tsai endeavored to replace the Ch’ing dynasty’s existing K’uei Mao School System, instituted in 1904, with a new educational framework for the Republic. Because the government urgently wished to resume academic sessions by March of that year, a provisional general education regulation was promulgated through telegrams by the new ministry. The Republic was forced to adapt the Chi’ing dynasty’s educational system, implementing emergency modifications such as renaming schools and principals, implementing a two-semester academic year, permitting coeducation in primary schools, removing the distinction between general and vocational secondary schools, revising primary and secondary school textbooks, and shortening the duration of secondary and normal school to 4 years. The effectiveness of the new regulations remained unclear because of ongoing conflicts between China’s southern and northern governments. Reconciliation between the two factions led to superficial national unity in April. Subsequently, the Ministry of Education convened the Provisional Education Meeting in Peking, the new capital, in July 1912. President Shih-Kai Yuan announced new educational objectives and a reformed school system in early September, 2 months after the meeting. The revised educational goals emphasized moral, military and national, and aesthetic education. The new system comprised five educational stages: 4-year junior elementary school, 3-year senior elementary school, 4-year secondary school, 3-year prep-school, and 4-year university. This structure, although similar to the Ch’ing dynasty 4-5-4-3-3-4 model, had been streamlined to a 4-3-4-3-4 model; completing one’s education from elementary school through university required a minimum of 18 years. A series of educational codes, regulations, and curricula were systematically introduced between 1912 and 1913, culminating in the establishment of the Jen Tzu K’uei Ch’ou School System. Regarding the historical narrative of educational reforms in early Republican China, the literature provides only a cursory overview of the new system; it does not delve into the complexities of the reform process or offer critical commentary. Employing a historical method, this study used first-hand sources, including documents from government archives, statutes, regulations, official gazettes, journals, and newspapers. This study employed both internal and external criticism to explore how the new central government sought to reconstruct China’s educational system between 1912 and 1916; to analyze the causes, process, practices, and factors influencing these educational reforms; and to draw conclusions and implications. The major findings are as follows. The primary motivations for reforming the Ch’ing dynasty’s educational system included its inefficiency, shortcomings, excessively long duration, improper curricula, and inconsistencies or redundancies across educational levels. Empirical evidence indicates that only 6 out of 18 provincial governments adopted the new statutes and regulations to implement the new educational system; the status of the remaining provinces remains unknown. Four major factors influenced these reforms. First, the Ch’ing school system, which was modeled after the Japanese system, continued to exert a considerable influence. Although the number of students who had graduated from Western countries increased after 1912, most had not focused on educational studies and consequently had limited understanding of Western educational systems. Second, ongoing political turmoil from 1913 to 1916, involving the rapid failure of the Second Revolution, the dissolution of China’s parliament, the abolition of the constitution, the ascent and rapid descent of President Yuan as Emperor, the fleeting restoration of the Ch’ing dynasty, and the outbreak of civil wars among various warlords, severely hampered reform efforts. Third, the financial resources allocated to education by local governments were consistently inadequate, primarily due to the diversion of educational funds to military activities. In addition, the limited educational funds were often squandered by local educational agencies and schools. Finally, administrative disorganization and power struggles among provincial, local, and central governments negatively affected the implementation of the new system. The lessons from China’s modern history indicate that completely abolishing an existing educational system is not strategically necessary for a new regime. In China, some revisions were made, and the old system continued to function. In understanding these reforms, consideration must be given to the fact that numerous provincial and central government officials visited Japan to gain educational insights after 1894. Additionally, a substantial number of Chinese students were studying in Japan at that time. These factors may have influenced the subsequent introduction of the Japanese education model into China. In the development of comparative education, modern China transitioned from what can be termed the “traveler’s tale” stage to a stage of “educational borrowing.” A comparison of the number of Chinese students studying in Japan and the US between 1906 and 1912 revealed that more students were in Japan. Moreover, these students displayed a deeper understanding of the educational system they were immersed in. During the Provisional Education Meeting of 1912, the participants who had received Japanese education outnumbered those of US and therefore likely had a greater influence on the final decisions. Notably, Hsi-Kuang Yau and Yi Chen, who were sent by Hu-Kuang Governor-General Chih-Tung Chang to inspect Japanese education in the late Ch’ing dynasty, played influential roles. Chen had even translated Japanese educational laws and drafted a framework for the K’uei Mao School System. Both individuals were official delegates, and therefore, their influence was substantial. Since 1922, the educational system established between 1912 and 1913 has been replaced by what is known as the New School System, which was modeled after the US 6-3-3-4 educational structure. In conclusion, the educational reforms of early Republican China offer valuable lessons for modern educational reformers. Adopting an evolutionary strategy rather than a revolutionary one, China reformed its education system during a period of political instability. Modern China’s experience serves as an insightful case study for those considering revolutionary strategies for educational reform in the future.

Zoe Karanikola, Georgios Panagiotopoulos

Globalization provides access to people, services, goods, ideas, beliefs and values in a new way and poses fundamental challenges for all areas of education in every country. Education on global issues is a process of individual and collective growth which allows for transformation and self-transformation. In this vein, this quantitative study seeks to investigate the perspectives of 310 adult educators on global education training. The accessible population of the study was adult educators working in the public and private vocational training institutes in the region of Western Greece during the academic year 2021–2022. The random sampling technique was applied. Research findings show that teachers recognize the necessity and importance of training on global competence and most of them have attended one or more courses mostly during their undergraduate or postgraduate studies or during their participation in training programs. They also regard the University as the most appropriate training actor, and they are in favor of optional training programs and of mixed type. Regarding training topics, they proposed interculturalism, diversity, current events, religion, history, immigrants, environment, geography, human rights and culture. Finally, participants’ aspects do not seem to be affected by their employment relationship and years of service. On the contrary, gender, ICT knowledge and additional studies seem to affect the results of the research.

Christine G. Parks, Darya Leyzarovich, Shelly-Ann Love et al.

Objectives: Self-reported shingles was associated with history of high pesticide exposure events (HPEE) in licensed pesticide applicators aged >60 years in the Agricultural Health Study (AHS). In the current study, using AHS-linked Medicare claims data, we examined incident shingles in relation to pesticide-related illness and pesticide poisoning, as well as HPEE. Methods: We studied 22,753 licensed private pesticide applicators (97% white males, enrolled in the AHS 1993–97), aged ≥66 years with >12 consecutive months of Medicare fee-for-service hospital and outpatient coverage between 1999 and 2016. Incident shingles was identified based on having ≥1 shingles claim(s) after 12 months without claims. At AHS enrollment, participants were asked if they ever sought medical care or were hospitalized for pesticide-related illness, and a supplemental questionnaire (completed by 51%) asked about HPEE and poisoning. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox proportional hazards regression, adjusted for age, sex, race, state, and education. Results: Over 192,053 person-years (PY), 2396 applicators were diagnosed with shingles (10.5%; age-standardized rate, 13.6 cases per 1,000PY), with higher rates among those reporting hospitalization for pesticide-related illness, pesticide poisoning, and HPEE (23.2, 22.5, and 16.6 per 1,000PY, respectively). In adjusted models, shingles was associated with hospitalization for pesticide-related illness (HR 1.69; 1.18, 2.39), poisoning (1.49; 1.08, 1.46), and HPEE (1.23; 95% CI = 1.03, 1.46), especially HPEE plus medical care/poisoning (1.78; 1.30, 2.43). Conclusion: These novel findings suggest that acute, high-level, and clinically impactful pesticide exposures may increase risk of shingles in subsequent years to decades following exposure.

Dara Cassidy, Yann-Aël Le Borgne, Francisco Bellas et al.

This report presents a set of use scenarios based on existing resources that teachers can use as inspiration to create their own, with the aim of introducing artificial intelligence (AI) at different pre-university levels, and with different goals. The Artificial Intelligence Education field (AIEd) is very active, with new resources and tools arising continuously. Those included in this document have already been tested with students and selected by experts in the field, but they must be taken just as practical examples to guide and inspire teachers creativity.

Yangqiuting Li, Chandralekha Singh

Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying the proposed model, as there are statistically equivalent models with distinct causal structures that equally well fit the data. Therefore, it is crucial for researchers using SEM to consider statistically equivalent models and to clarify why the proposed model is more accurate than the equivalent ones. However, many SEM studies did not explicitly address this important step, and no prior study in physics education research has delved into potential methods for distinguishing statistically equivalent models with differing causal structures. In this study, we use physics identity model as an example to discuss the importance of considering statistically equivalent models and how other data can help to distinguish them. Previous research has identified three dimensions of physics identity: perceived recognition, self-efficacy, and interest. However, the relationships between these dimensions have not been thoroughly understood. In this paper, we specify a model with perceived recognition predicting self-efficacy and interest, which is inspired by individual interviews with students in physics courses to make physics learning environments equitable and inclusive. We test our model with fit indices and discuss its statistically equivalent models with different causal inferences among perceived recognition, self-efficacy, and interest. We then discuss potential experiments that could further empirically test the causal inferences underlying the models, aiding the refinement to a more accurate causal model for guiding educational improvements.

Kevin Wang, Jason Ramos, Ramon Lawrence

With the rapid evolution of Natural Language Processing (NLP), Large Language Models (LLMs) like ChatGPT have emerged as powerful tools capable of transforming various sectors. Their vast knowledge base and dynamic interaction capabilities represent significant potential in improving education by operating as a personalized assistant. However, the possibility of generating incorrect, biased, or unhelpful answers are a key challenge to resolve when deploying LLMs in an education context. This work introduces an innovative architecture that combines the strengths of ChatGPT with a traditional information retrieval based chatbot framework to offer enhanced student support in higher education. Our empirical evaluations underscore the high promise of this approach.

Doreen Fraser, Maria Papageorgiou

The formulation of a measurement theory for relativistic quantum field theory (QFT) has recently been an active area of research. In contrast to the asymptotic measurement framework that was enshrined in QED, the new proposals aim to supply a measurement framework for measurements in local spacetime regions. This paper surveys episodes in the history of quantum theory that contemporary researchers have identified as precursors to their own work and discusses how they laid the groundwork for current approaches to local measurement theory for QFT.

Sahan Bulathwela, Hamze Muse, Emine Yilmaz

The automatic generation of educational questions will play a key role in scaling online education, enabling self-assessment at scale when a global population is manoeuvring their personalised learning journeys. We develop \textit{EduQG}, a novel educational question generation model built by adapting a large language model. Our extensive experiments demonstrate that \textit{EduQG} can produce superior educational questions by further pre-training and fine-tuning a pre-trained language model on the scientific text and science question data.

Ming Li, Ariunaa Enkhtur, Fei Cheng et al.

This scoping review explores the ethical challenges of using ChatGPT in higher education. By reviewing recent academic articles in English, Chinese, and Japanese, we aimed to provide a deep dive review and identify gaps in the literature. Drawing on Arksey and O'Malley's (2005) scoping review framework, we defined search terms and identified relevant publications from four databases in the three target languages. The research results showed that the majority of the papers were discussion papers, but there was some early empirical work. The ethical issues highlighted in these works mainly concern academic integrity, assessment issues, and data protection. Given the rapid deployment of generative artificial intelligence, it is imperative for educators to conduct more empirical studies to develop sound ethical policies for its use.